The impact of sea level rise on nesting sea turtles: a global meta-analysis to highlight current understanding and knowledge gaps - Staines, Melissa N.; Booth, David T.; Laloë, Jacques-Olivier; Hays, Graeme C. (Marine Biology, 2025)
Abstract Sea turtles face a number of threats from climate change. One pertinent threat is the impact of sea level rise (SLR), which can lead to a loss of nesting habitat and reduced survival of embryos due to inundation and erosion. Here we review the impacts of SLR on sea turtles. We examined 34 studies (66 assessments) on SLR impacts across six species and 40 sites globally, with 62.1% of assessments located in the Americas. Overall, 78.8% of the assessments showed declining trends in historical and projected estimates of nesting habitat area and or nest survival from inundation. Assessments with projected nesting habitat area showed appreciable loss across all site types (coral island, elevated island, barrier island and mainland), regardless of the SLR scenario. The projected percentage of habitat loss and nest flooding was greatest in island sites compared to the mainland sites, highlighting that SLR is likely to be most acute for low-lying islands with no nearby alternative nesting areas. We reviewed the predicted extent of nesting beach loss and examined how natural processes and conservation interventions might mitigate this threat. However, we require more empirical data on the extent of historical nesting habitat loss. There is also little known about a population’s ability to colonise new nesting areas once a site becomes unsuitable. By tracking their routes towards the breeding sites, there is potential to show how resilient sea turtles are to environmental change, as females may be exposed to other suitable nesting sites on their migration route.
Keywords: Scopus_Alert_26_Octobre_2025

Prediction of Flood Level Using LSTM and Watershed Hydrological Data - Kim, Hyun‐il; Jang, Se‐Dong; Choi, Hehun; Kim, Tae‐Hyung; Kim, Byunghyun (Journal of Flood Risk Management, 2025)
ABSTRACT Accurate flood level prediction is crucial for mitigating flood damage caused by typhoons or localized heavy rainfall. However, predicting flood levels is challenging due to changes in river environments and external factors, such as dam or weir operations. To address these challenges, this study proposes a methodology for constructing an optimal combination of input data using basic hydrological information and predicting flood levels in real time through a deep learning model. The study focuses on identifying the best input data combination tailored to each river basin's characteristics, considering both natural runoff rivers and those influenced by dam discharges. The Long Short‐Term Memory (LSTM) model, known for its superior performance in time‐series forecasting, was employed. The results demonstrate high accuracy in flood level prediction, particularly within a 3‐h lead time.
Keywords: Scopus_Alert_26_Octobre_2025

Improved XGBoost model for predicting minimum miscibility pressure in CO2 flooding - Yang, Yuxin; Zhang, Yizhong; Qin, Bowen; Guo, Jianhong; Zhang, Maolin (Scientific Reports, 2025)
Keywords: Scopus_Alert_26_Octobre_2025

Assessment of Flood Damage Costs for Different Storm Surge, Climate Change, and Drainage Scenarios in Busan, South Korea - Shin, Seoyoung; Kim, Jieun; Park, Daeryong; Kang, Taesoon; Jung, Kichul (JAWRA Journal of the American Water Resources Association, 2025)
ABSTRACT Sea level rise and storm surges resulting from climate change are expected to increase the frequency and intensity of floods. Aging and/or inefficient drainage systems can significantly exacerbate flood damage. Effective flood defense policies must categorize flood damage and provide a detailed assessment of each contributing factor. In this study, we evaluated the cost of flood damage in Busan—the second most populous city on the coast of South Korea. Flood damage costs were analyzed based on an object‐based approach across 10 scenarios, which accounted for variations in storm surge frequency, climate change impacts, and drainage efficiency. Flood damage costs for four categories, namely buildings, agriculture, human casualties, and vehicles, were examined across different administrative regions. Results reveal that flood damage costs increase with higher storm surge frequencies and climate change effects, while reduced drainage efficiency further amplifies these costs. Given that damage costs are predominantly concentrated in coastal areas, future data‐based flood defense policies should be developed to reflect the specific vulnerabilities and damage patterns of each administrative region.
Keywords: Scopus_Alert_26_Octobre_2025

Leveraging geospatial technology for flood inundation mapping and assessing vulnerability and risk in Agartala City, India - Jaman, Toushif; Nongkynrih, Jenita Mary; Sumanth, B. C.; Kurbah, Hunlinshisha; Gogoi, Rekha Bharali; Sarma, K. K.; Aggarwal, S. P. (GeoJournal, 2025)
Keywords: Scopus_Alert_26_Octobre_2025

Integrated morphometric and machine learning-based flood risk assessment in the Rangit river sub-watersheds, Eastern Himalayas - Das, Pintu; Sarkar, Debabrata; Saha, Sunil; Saikh, Nur Islam; Mondal, Prolay (Discover Applied Sciences, 2025)
Keywords: Scopus_Alert_26_Octobre_2025

The spatiotemporal movement ecology of shortfin eels and entrainment risk of yellow eels at a flood relief pump station with gravity bypass - Mahlum, Shad; Baker, Cindy; Lake, Mike; White, Emily; Williams, Alicia; Williams, Peter; Franklin, Paul (Ecological Solutions and Evidence, 2025)
Abstract Land drainage and flood protection infrastructure such as pump stations, tide/flood gates and levees are used to mitigate flood hazards and maintain productive land. However, such infrastructure fragments aquatic ecosystems, often altering the hydrological, geomorphic and physico‐chemical characteristics of waterways. To better understand the risks to eels in the vicinity of flood relief pump stations, we undertook a passive integrated transponder tag study evaluating the movements of 332 shortfin eels ( Anguilla australis ) across 2.5 years at a pump station with a gravity bypass in New Zealand. We observed clear diel and seasonal patterns in eel movements, with increased eel activity at dusk and during late spring and summer. In addition, we observed a unimodal relationship between daily eel activity and water temperature with peak activity occurring between 14°C and 15°C. The gravity bypass was the primary route used by eels for both downstream (45%) and upstream (20%) movements, while direct passage through the pump was uncommon, occurring in only 28 individuals. Among more than 12,000 recorded encounters with the flood pump and gravity bypass, the most frequent outcomes were avoidance of the bypass and obstruction at the pump (42% and 58% of the encounters across individuals, respectively), whereas direct or delayed entrainment through the flood pump occurred rarely (13.5% and 15.2% of the encounters across individuals, respectively). No eels were entrained in the flood pumps during the autumn downstream migration due to low flows throughout this period that precluded the need for active pump operations. In contrast, we observed eel entrainment during winter and spring, when the pumps were most frequently operating, suggesting that non‐migratory (yellow) eels may have been affected. Practical implications . These results highlight that the risk to eels of pump entrainment and mortality extend beyond the main period of downstream migration that has been the focus of most studies. Pump station design and operational management must allow for bidirectional movements of eels to provide effective functional connectivity.
Keywords: Scopus_Alert_26_Octobre_2025

Forecasting extreme events and storms and prediction of coastal flooding along microtidal Coast of El Djamila Bay, Algeria - Berkani, Moussaab; Otmani, Housseyn; Mezouar, Khoudir; Saf, Brahim (Journal of Coastal Conservation, 2025)

Evolution and prediction of drought-flood abrupt alternation in mainland China using an improved index - Tong, Yiming; Chen, Yu; Qu, Yanping; Bento, Virgílio A.; Song, Hongquan; Qiu, Han; Shui, Wei; Zeng, Jingyu; Wang, Qianfeng (Climate Dynamics, 2025)
Keywords: Scopus_Alert_26_Octobre_2025

Autonomous Decision-Making Enhancing Natural Disaster Management through Open World Machine Learning: A Systematic Review - Gerolimos, Nikitas; Alevizos, Vasileios; Edralin, Sabrina; Xu, Clark; Priniotakis, Georgios; Papakostas, George A.; Yue, Zongliang (Human-Centric Intelligent Systems, 2025)
Abstract Natural disasters can be fatal and necessitate critical thinking in decision-making processes; thus, simulations of multiple scenarios must be evaluated to prepare for such imminent events. An Open World Machine Learning (OWML) framework has been proposed as a focal tool to improve decision-making in natural disaster management. To better understand and formulate a comprehensive foundation, a systematic review of different cases was conducted. In this study, four types of natural disasters-earthquakes, floods, wildfires, and hurricanes-were analyzed using machine learning techniques within the OWML framework. The essence of this approach lies in its ability to accumulate knowledge from various sources and adapt to new, unknown event types. Moreover, by explicitly incorporating both qualitative and quantitative characteristics, the framework enhances predictive accuracy and adaptability. The results demonstrate that OWML models can effectively process large geospatial datasets and respond to looming threats with greater precision. Albeit some limitations, such as data quality and model complexity, the findings suggest that OWML can serve as a foundational tool for governments to reduce expenditure and improve evacuation strategies. The evolutionary nature of the OWML framework allows for continuous learning and adaptation, which is crucial as natural disasters escalate in frequency and intensity due to climate change. In essence, this study provides a significant contribution to natural disaster management by explicitly demonstrating the potential of OWML frameworks in enhancing decision-making processes.
Keywords: Scopus_Alert_26_Octobre_2025

Artificial intelligence in wastewater treatment plants: a review of current trends and adaptation strategies in the face of climate-driven rainfall fluctuations - Hocaoglu, Selda Murat; Roghani, Bardia; Gulcan, Hande; Magna, Débora Jareta; Aydöner, Cihangir; Barros, Virginia Grace; Koyunluoglu Aynur, Sebnem; Ratnaweera, Harsha; Fatone, Francesco; Eusebi, Anna Laura; Maletskyi, Zakhar (Journal of Water and Climate Change, 2025)
ABSTRACT Wastewater treatment plants (WWTPs) are encountering challenges related to sustainability, efficiency, and economic viability due to stricter discharge standards and the impact of climate change, including heavy rainfall. Enhancing the resilience and performance of WWTPs is therefore crucial. This paper reviews the application of artificial intelligence (AI) models that can improve WWTP resilience in response to extreme rainfall events. It provides an overview of publications on digitalization of WWTPs over the past 33 years, proposes a new classification approach for AI models, and reviews existing AI applications aimed at improving the performance of WWTPs in response to extreme rainfall events. These applications highlight the importance of developing hybrid models that integrate AI with knowledge-driven models to improve accuracy. Furthermore, future AI research in WWTPs should incorporate hydrological forecasting to enable advance estimation of flow rates, and facilitate effective management.
Keywords: Scopus_Alert_26_Octobre_2025

Nexus between climate change and maternal mortality: a review of literature - Haq, Shah Md Atiqul; Mawa, Jannatul; Tasneem, Nishat; Saha, Bijoya; Ahmed, Mufti Nadimul Quamar; Ahmed, Khandaker Jafor (SN Social Sciences, 2025)
Abstract Climate change presents a significant threat to global health, with both immediate and long-term consequences, especially in low-income countries with limited adaptive capacity. Pregnant women, developing fetuses, and youth are among the most vulnerable populations, yet the specific risks they face remain underexplored. This literature review examines the impact of climate change on maternal mortality, focusing on both direct and indirect pathways. We analyzed peer-reviewed studies that address how climate-related events, such as severe droughts, water scarcity, wildfires, rising sea levels, frequent floods, melting polar ice caps, catastrophic storms, and biodiversity loss contribute to complications during pregnancy and childbirth. The evidence suggests that climate change can indirectly increase maternal health risks and mortality through social, economic, and psychological pathways, including inadequate sanitation, population shifts, disrupted healthcare access, malnutrition, and disease transmission. Our findings reveal a consistent pattern of heightened risk for maternal complications and mortality linked to climate-related events. We recommend conducting more country-specific and comprehensive studies to better understand these relationships and inform effective interventions. Policymakers should prioritize efforts to reduce maternal mortality and improve the health of expectant mothers and their newborns in the context of a changing climate.
Keywords: Scopus_Alert_26_Octobre_2025

Meteorological Tsunamis: From Local Hazard to Global Relevance - Vilibić, Ivica; Zemunik Selak, Petra; Šepić, Jadranka (Reviews of Geophysics, 2025)
Abstract Research on meteorological tsunamis or meteotsunamis—long ocean waves in the tsunami frequency band generated by propagating atmospheric disturbances which resonantly enhance ocean waves—has grown significantly in recent decades. This expansion is due to progress in (a) ocean and atmospheric measurements, including advanced instrumentation with higher precision and smaller sampling time steps, as well as installation of meteotsunami tracking measurement networks, (b) ocean and atmospheric data products, including those related to the upper atmosphere and ionosphere, and (c) supercomputing capabilities and sophisticated atmosphere‐ocean models that successfully simulate both atmospheric planetary processes and mesoscale systems capable of generating meteotsunamis, as well as sea level response to these. Meteotsunamis can induce multi‐meter sea level oscillations in harbors and low‐lying areas, leading to severe flooding, infrastructure damage, injuries, and sometimes fatalities. Traditionally, meteotsunami research focused on individual event analyses using available sea level and lower‐layer atmospheric observations. Recently, efforts have shifted toward global hazard mapping, the development of forecast and early‐warning systems, and toward quantifying projected meteotsunamis intensity and frequency, using climate models. The January 2022 eruption of the Hunga Tonga‐Hunga Ha'apai volcano, which generated acoustic‐gravity waves that circled the globe, has spurred research of planetary meteotsunami waves and their potential to pose coastal hazards worldwide. Additionally, meteotsunamis radiate acoustic‐gravity waves vertically, creating ionospheric oscillations detectable through electron content variations. This review will cover the mentioned developments and conclude with a discussion of research gaps and potential directions for further studies. , Plain Language Summary Sea level extremes are an emerging topic in the era of climate change, as most coastal damage and impacts occur during such events. One of the underrated phenomena contributing to these extremes are meteorological tsunamis or meteotsunamis—long ocean waves in the tsunami frequency band resonantly generated by traveling air pressure/wind disturbances—which are known to substantially impact certain coastlines and locations, causing deaths, injuries, and damage to coastal infrastructure, ships and yachts, buildings, and households, as well as affecting navigational safety. Until about a decade ago, research on meteotsunamis was mostly localized, focusing on specific meteotsunami hotspots. However, in recent years, research has become more global. This was made possible by the development of high‐precision oceanic and atmospheric instruments that collect data at minute or higher resolutions, as well as ultra‐high‐resolution atmosphere‐ocean models capable of reproducing meteotsunamis, supported by high‐performance computing facilities. This review summarizes all aspects of meteotsunamis, from available data, products, and tools that can be used for research, to an in‐depth exploration of the science behind the phenomenon, and its impact on coastal regions. It also discusses the development of forecasting and early‐warning systems. Finally, the review provides recommendations for future research directions on this hazardous phenomenon. , Key Points Minute‐scale sea level oscillations, including meteotsunamis, significantly contribute to extreme sea levels worldwide Generated though atmosphere‐ocean resonances, meteotsunamis can have from local to global impact and be destructive at certain locations Reliable estimates of meteotsunami hazard in present and future climates, along with effective forecasting and warning, remain a challenge
Keywords: Scopus_Alert_26_Octobre_2025

Machine learning-based hydrological models for flash floods: a systematic literature review - Santos, Leonardo B. L.; Escobar-Silva, Elton V.; Satolo, Luiz F.; Oyarzabal, Ricardo S.; Diniz, Michael M.; Negri, Rogério G.; Lima, Glauston R. T.; Stephany, Stephan; Soares, Jaqueline A. J. P.; Duque, Johan S.; Saraiva Filho, Fernando L.; Caseri, Angélica N.; et al. (Smart Construction and Sustainable Cities, 2025)
Abstract Flash floods are critical events for emergency management, yet their modeling remains highly challenging, even in smart cities approaches. Physically based hydrological models are often unsuitable at small spatiotemporal scales due to their computational complexity and dependence on detailed local parameters, which are rarely available during flash floods. With the growing availability of hydrological data, machine learning (ML) has emerged as a promising alternative. This work performs a Systematic Literature Review (SLR) to improve our understanding of the research landscape on ML applications for flash flood forecasting, a significant subset of flash flood modeling. From more than 1,200 papers published until January 2024 in Web of Science, SCOPUS/Elsevier, Springer/Nature, and Wiley, 50 were selected following PRISMA guidelines. The inclusion and exclusion criteria removed reviews, retractions, papers focused on post-flood damage assessment (not forecasting), and those with time resolutions of 6 hours or more, retaining only studies with fine-scale temporal data (<6 hours). For each paper, we extracted information on forecasting horizon, study area size, input data, ML techniques, and outcomes (regression or classification). Results show a sharp rise in ML-based flash flood research, with China leading (38%). Nearly all studies rely on rainfall, discharge, and water level data - often in combination. Long short-term memory (LSTM) networks dominate (60%). Unfortunately, only 10% of the selected studies provide access to their datasets. This lack of transparency poses a major barrier to reproducibility, inhibits fair comparative evaluation of models, and ultimately slows methodological progress in flash flood forecasting. Furthermore, our review highlights that no method consistently outperforms others. This variability in performance is likely influenced by factors such as regional hydrological characteristics (e.g., differences between arid and tropical basins), variations in input data quality, and the length of the forecast horizon (e.g., 1- vs. 6-hour prediction). Lastly, we recommend advancing this field through integration with early warning systems, creation of benchmarks, open data practices, and stronger multidisciplinary collaboration.
Keywords: Scopus_Alert_26_Octobre_2025

A systematic review of climate change adaptation in vegetable farming systems in Africa - Obossou, Esdras; Totin, Edmond; Singh, Chandni; Segnon, Alcade C. (Communications Earth & Environment, 2025)
Keywords: Scopus_Alert_26_Octobre_2025

Do Public and Farmer Preferences for Natural Flood Management Align? - King, Phoebe; Bark, Rosalind H.; Lovett, Andrew (Journal of Flood Risk Management, 2025)
ABSTRACT The demand for catchment‐based flood management to adapt to climate change is growing, with natural flood management (NFM) receiving increasing attention. NFM has implications for the ‘providers’ of land for measures upstream (the farmers) and the ‘beneficiaries’ of flood reduction downstream (the public). The misalignment of interests from these stakeholder groups may pose a challenge for flood risk managers during the delivery of NFM at the catchment scale. Considering this, a rapid evidence assessment (REA) of 60 peer‐reviewed articles was undertaken. This REA provides an overview of catchment perspectives, compares farmer and public preferences for NFM design, and explores key determinants of scheme acceptance. The public expressed positive perceptions and willingness to pay for NFM, with preferences for measures with large water storage capacity that deliver co‐benefits alongside flood management objectives. For farmers, NFM schemes that contributed to on‐farm conditions, for example, soil stability, were seen as positive, but overall, their willingness to adopt measures was limited. Nevertheless, knowledge of NFM among both groups strongly determined its acceptance. This suggests that resolving misaligned values will require policymakers and practitioners to work with these stakeholders on NFM design and farmer incentives to secure the delivery of future schemes.
Keywords: Scopus_Alert_26_Octobre_2025

Flood Impacts on Civil Infrastructure Systems: A Comprehensive Review of Impacts, Modeling Tools, Emerging Technologies, and Mitigation Strategies - Abegaz, Ruth; Xu, Jun; Wang, Fei (Natural Hazards Review, 2026)
Keywords: Scopus_Alert_26_Octobre_2025

Forecasting extreme events and storms and prediction of coastal flooding along microtidal Coast of El Djamila Bay, Algeria - Berkani, Moussaab; Otmani, Housseyn; Mezouar, Khoudir; Saf, Brahim (Journal of Coastal Conservation, 2025)
Keywords: Scopus_Alert_26_Octobre_2025

Mapping of Sea-Level Rise Impacts on the Cultural Heritage of the Apulian Gulf of Manfredonia and Ionian Coast - Lobascio, Arianna; Fioriello, Custode S.; Scardino, Giovanni; Scicchitano, Giovanni; Zingaro, Marina (Geographic Approaches to Climate Change and Mitigation: Urban and Rural Perspectives (Volume 2), 2025)
Series Title: Advances in Science, Technology & Innovation
Keywords: Scopus_Alert_26_Octobre_2025

Morphometric analyses of a deltaic strandplain inferred from LiDAR data and old maps: A contribution to the coastal risk mapping of the Tiber Delta (Italy) - Sarrau, Justine; Salomon, Ferréol (Journal of Geographical Sciences, 2025)
Keywords: Scopus_Alert_26_Octobre_2025

Multi-Hazard Scenarios of Extreme Compounded Events at the Local Scale Under Climate Change - Sfetsos, Athanasios; Politi, Nadia; Vlachogiannis, Diamando (Atmosphere, 2025)
As local risk assessments are fundamental for risk management and mitigation strategies, this work introduces a methodology for assessing multi-hazard scenarios of extreme compounded events and their duration using daily time series of surface variables from high-resolution climate simulations during historical and future periods under RCP8.5. The aim was to investigate the return level extremes of 20- and 50-year periods of hazards occurring within specific durations and concurrent extreme values of other surface variables, for selected locations in Greece. In addition, future changes in the temporal occurrence of compounded hazards involving precipitation and wind with temperature extremes were performed based on temperature extreme percentiles. The assessment revealed the geographical dependence in the projected occurrence, intensity, and duration of compounded multi-hazard extremes, emphasising the need for high spatial resolution climate data for their investigation. The highlights of the findings include a significant increasing trend of compounded multi-hazard extremes, e.g., hot days and tropical nights, milder winter minimum temperatures with lower rainfall extremes, hotter and windier events of shorter duration, and longer precipitation extremes with increased extreme temperatures. The projections showcased the impact of climate change on extreme compounds with a multitude of interesting findings associated with significant changes in their duration, intensity, and temporal occurrence.
Keywords: Scopus_Alert_17_Octobre_2025

Increasing compound heat and precipitation extremes and population exposure in a warming Vietnam - Nguyen-Duy, Tung; Ngo-Duc, Thanh; Nguyen-Le, Dzung; Nguyen-Xuan, Thanh; Tran-Anh, Quan (Natural Hazards, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Flood insurance purchasing behavior in two Gulf Coast cities - Cass, Evan; Shao, Wanyun; Hao, Feng (Cities, 2026)
Keywords: Scopus_Alert_17_Octobre_2025

Assessing subway station flood risks with a resilience Framework: Combining weighting methods and two-dimensional cloud model - Guo, De-Sai; Yang, Xin-Xin; Yang, Jin-Chen; Wu, Huai-Na; Meng, Fan-Yan; Chen, Ren-Peng (Tunnelling and Underground Space Technology, 2026)
Keywords: Scopus_Alert_17_Octobre_2025

GIS-driven hybrid multicriteria model for flood susceptibility assessment in a coastal metropolis of Ghana - Danso, Samuel Yaw (Geosystems and Geoenvironment, 2026)
Keywords: Scopus_Alert_17_Octobre_2025

Multi-model verification and evaluation of precipitation forecasts and Southwest China Vortex Rainstorms in Eastern Tibetan Plateau - Wu, Zhipeng; Zhang, Yan; Hu, Chunmei; Deng, Chengzhi; Luo, Juan; Wu, Shenggang; Zhou, Yingying; Zhang, Hong; Liao, Zhiyi; Wang, Huan; Pang, Yue (Atmospheric Research, 2026)
Keywords: Scopus_Alert_17_Octobre_2025

Serious Game Design for Resilience Enhancement of Transportation Infrastructure to Cyber Threats and/or Flood Hazards - Gordan, Meisam; Ko, Ili; Soroudi, Mona; McCrum, Daniel; König, Sandra; Schauer, Stefan; Connolly, Lorcan; Carroll, Páraic (Transport Transitions: Advancing Sustainable and Inclusive Mobility, 2026)
Abstract It is challenging to predict the precise location and severity of flood events, which can cause major disturbance to different public services, such as disruption to and the closure of critical transportation infrastructure. Therefore, approaches to enhance the resilience of these infrastructures are required. Serious games are new computing tools that have been applied in various fields with a combination of gameplay, learning and training. However, the application of serious games in intelligent transportation systems remains underutilized. As a result, the concept of a serious game is developed in this study to significantly improve transportation infrastructure resilience in an example of a flooding event. The serious game concept presented in this paper is being developed as part of the H2020-funded PRECINCT project ( www.precinct.info ).
Series Title: Lecture Notes in Mobility
Keywords: Scopus_Alert_17_Octobre_2025

The impact of risk control options in reducing/preventing risk in case of a flooding event - Mauro, Francesco; Paterson, Donald; Vassalos, Dracos (Ocean Engineering, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Design storm estimation for flood risk assessment in the temperate Himalayan basin using hydrological modelling - Attar, Mohmmad Idrees; Khan, Junaid Nazir; Altaf, Yasir; Alsubih, Majed; Naseer, Sameena; Kumar, Rohitashw; Bhat, Owais Ahmad; Bangroo, Shabir Ahmad; Sharma, M. K. (Scientific Reports, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Conceptual model of spatial level structure for developing multi-functional parks to reduce urban flood risk: A case study in Ho Chi Minh city - Duy, Phan Nhut; Tuan, Pham Anh; Nguyen, Nguyen Phuong Thao (City and Environment Interactions, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Accumulating climate change influences on extreme coastal, fluvial, and compound flooding in the upper transition zone - Mita, Kazi Samsunnahar; Orton, Philip; Montalto, Franco; Anbessie, Tsega (Journal of Hydrology, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Exploring characteristics and drivers of flood hazard under different urban development patterns - Zhong, Ming; Chen, Tailin; Zhuo, Lu; Wang, Zeqiang; Ling, Feng; Han, Dawei (Environmental and Sustainability Indicators, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Assessing blue-green infrastructures for urban flood and drought mitigation under changing climate scenarios - Wu, Xuan; Willems, Patrick (Journal of Hydrology: Regional Studies, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

City-scale digital twin framework for flood impact analysis: Integrating urban infrastructure and real-time data analytics - Kaynak, Sümeyye; Kaynak, Baran; Mermer, Omer; Demir, Ibrahim (Urban Climate, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Interception reduction from deforestation and forest fire increases large-scale fluvial flooding risk - Kang, Tae-Ho; Sharma, Ashish; Marshall, Lucy; Kim, Young-Oh (Communications Earth & Environment, 2025)
Abstract Catastrophic flooding has been noted to occur with greater frequency following deforestation, but limited observations have been available to test this connection over large spatial scales. Here we used the data of mega forest fires impacting a region of 25,000 km 2 in Australia exhibiting rapid loss in forest canopy, where the runoff generation has been carefully observed with minimum anthropogenic influences for more than half a century. This provides a unique opportunity to assess the impact of the forest canopy loss on large-scale fluvial flooding. A state-controlled hypothesis test, with the climate and watershed states controlled to enhance robustness, shows a statistically significant increase in annual maximum flows resulting from the forest loss treatment. The reasoning for this natural experiment is that the forest loss impact on the interception potential of forest canopy, fallen leaves, and root-zone soils in wide region could have a recognizable impact on the fluvial flood.
Keywords: Scopus_Alert_17_Octobre_2025

Land tenure (in) security in the context of urban flood risk in Ghana - Ibrahim, Abdul-Salam; Isaac, Marney E.; Kepe, Thembela (Land Use Policy, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Optimizing the allocation of flood control investments for effective disaster risk reduction - Chang, Kuo-Hao; Hsu, Yueh-Ning; Li, Hsin-Chi (Computers & Industrial Engineering, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

An integrated methodology for flood risk assessment of road networks: a case study of Ordu, Türkiye - Yılmaz, Muhammet; Alemdar, Kadir Diler (Modeling Earth Systems and Environment, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Adaptive flood risk management: A decision support system integrating deep learning, digital twins, and economic risk assessment - Chabot, Miia; Bertrand, Jean-Louis (Global Environmental Change, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Flood risk from small mountain lakes - Sattar, Ashim; Emmer, Adam; Lhazom, Tashi; Rai, Shashi Kant; Azam, Mohd. Farooq (Communications Earth & Environment, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Flood evacuation shelter location-allocation considering vulnerability identification in the context of pre-requisition - Gong, Zaiwu; Guo, Xinrui; Wei, Guo; Luo, Xinxin; Xu, Xiaoxia (Climate Services, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Leveraging Coupled Hydrodynamic with Data-Driven GeoAI Models for Advancing Systemic Compound Flood Risk Evaluation in Coastal Urban Areas - Atmaja, Tri; Fukushi, Kensuke; Lee, Duu-Jong (Archives of Computational Methods in Engineering, 2025)
Abstract Compound flood (CF) represents a complex hazard that often leads to severe impacts. CF propagates across interconnected systems, generating systemic societal and environmental risks, particularly in coastal cities. Despite progress in data science and remote sensing, a comprehensive review of coupled hydrodynamics with the data-driven GeoAI—an integration of geospatial analysis and artificial intelligence (AI)—for systemic CF risk remains scarce. This review summarizes foundational data-driven and numerical approaches in CF modeling. It then synthesizes emergence, utilization modes, and advancements of coupled hydrodynamic-GeoAI frameworks for CF prediction and systemic impact quantification. A systematic review follows the PRISMA protocol, examining 403 articles from the Web of Science and Scopus databases. The concept of the coupled hydrodynamics-GeoAI model synergizes physics-based simulations with data-driven computational learning, enhancing predictive accuracy and spatially detailed flood risk while explicitly embedding geographic features into the framework. The model offers three utilization modes: (i) direct coupling, (ii) surrogate modeling, and (iii) stochastic statistical-hydrodynamic-ML framework. To enhance comprehensive and robust risk assessment, the review proposes four key model advancements: (1) implementing an active learning framework, (2) integration with physics-guided data-driven, (3) dynamically coupling CF drivers with external factors, and (4) incorporating spatiotemporal analysis under changing climate and socioeconomic conditions. We further advocate for integrating the quantification of both tangible and intangible cascading impacts into systemic CF risk assessments. This review synthesizes computational strategies integrating physics-based hydrodynamics with GeoAI, providing a foundation for systemic CF risk evaluation and guiding future advances in computational hydrology and resilient urban flood management. Graphical Abstract This graphical abstract visually encapsulates the core concept of leveraging coupled hydrodynamic with data-driven GeoAI models for systemic compound flood (CF) risk evaluation in coastal urban areas. The abstract integrates the three main flood drivers—coastal, pluvial, and fluvial—interacting to form the CF. The diagram flows from left to right, where the first section depicts the urban coastal zone, followed by a combination of flood drivers that illustrate the complexity and interconnectedness of factors leading to CF. On the right panel, the graphical focus shifts to the “Coupled Hydrodynamic with Data-Driven GeoAI Model” as the proposed approach for predicting the CF event, encompassing probabilistic analysis, flood propagation, risk assessment, real-time forecasting, and emergency response. The approach integrates physics-based simulations with data-driven geographic data analysis, known as GeoAI. On the bottom left panel, the illustration emphasizes the utilization of the approach through three key strategies: (i) direct coupling through ML-derived boundary conditions, (ii) surrogate modeling to emulate hydrodynamic outputs, and (iii) stochastic statistical-hydrodynamic-ML framework. These strategies demonstrate how GeoAI enhances hydrodynamic simulations to produce more accurate, timely, and spatially detailed flood predictions in various ways. The model’s advancements are also highlighted, addressing the critical need for the utilization of an active learning framework, integration with physics-guided data-driven, dynamically coupling CF drivers with external factors, and the importance of considering spatiotemporal analysis under climate and socioeconomic change. The graphic in the bottom right panel displays the CF output results from the model, which can be further utilized to assess the cascading impact on various aspects. Together, the elements of this graphical abstract convey a sophisticated, interdisciplinary approach to CF risk evaluation, focusing on integrating hydrodynamic with data-driven GeoAI models to better manage the complex challenges of systemic CF risks in urban coastal zones.

Anammox in nature-based systems for urban water management: A review and Bayesian assessment of environmental drivers - Tang, Yinghui; Prodanovic, Veljko; O'Carroll, Denis M.; Zheng, Min; Zhang, Kefeng (Journal of Environmental Management, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Roles and nature of public participation in climate change adaptation in coastal South Asia - Siddiqui, Md Rezwan; Ishtiaque, Asif (Discover Environment, 2025)
Abstract This paper presents a systematic review of the roles and nature of public participation in climate change adaptation in coastal South Asia. In this region, coastal communities face significant climate-related risks due to their inherent vulnerability from population density, rapid changes in landuse, and extensive shoreline. They are particularly vulnerable to hazards such as sea-level rise, tropical cyclones, and storm surges. Governments in the region have initiated adaptation strategies, emphasizing the inclusion of local stakeholders. However, the extent and impact of public participation in these strategies vary across case studies. Drawing on 42 published peer review articles, this review synthesizes participatory approaches in coastal adaptation strategies. We found that public participation strengthens community cohesion, improves adaptation outcomes, and is a mandatory tool for identifying local vulnerabilities and capacities. Participation through grassroots organizations may result in wider sustainability for the vulnerable coastal communities. Additionally, the review identifies several barriers, including the prevalence of elite capture and token participation, externally driven participation processes, and unclear task definitions. We also found that to enhance the effectiveness of public participation in climate change adaptation, it is crucial to adopt inclusive, bottom-up approaches, empower marginalized groups, and ensure that participation is contextually grounded and representative. This study’s insights are applicable not only to South Asia but also to other vulnerable coastal regions in the Global South.
Keywords: Scopus_Alert_17_Octobre_2025

Advances in artificial intelligence to model the impact of El Niño–Southern Oscillation on crop yield variability - Wannasingha, Usa Humphries; Waqas, Muhammad; Wangwongchai, Angkool; Hlaing, Phyo Thandar; Dechpichai, Porntip; Ahmad, Shakeel (MethodsX, 2025)
Keywords: Scopus_Alert_17_Octobre_2025

Risks to the future health and productivity of tropical estuaries under climate change and increasing human development - Burford, M.A.; Brooks, A.; Cartwright, P.; Faggotter, S.J.; Irvine, D.J.; Waltham, N.J. (Marine Pollution Bulletin, 2026)
Keywords: Scopus_Alert_17_Octobre_2025

Leveraging Coupled Hydrodynamic with Data-Driven GeoAI Models for Advancing Systemic Compound Flood Risk Evaluation in Coastal Urban Areas - Atmaja, Tri; Fukushi, Kensuke; Lee, Duu-Jong (Archives of Computational Methods in Engineering, 2025)
Abstract Compound flood (CF) represents a complex hazard that often leads to severe impacts. CF propagates across interconnected systems, generating systemic societal and environmental risks, particularly in coastal cities. Despite progress in data science and remote sensing, a comprehensive review of coupled hydrodynamics with the data-driven GeoAI—an integration of geospatial analysis and artificial intelligence (AI)—for systemic CF risk remains scarce. This review summarizes foundational data-driven and numerical approaches in CF modeling. It then synthesizes emergence, utilization modes, and advancements of coupled hydrodynamic-GeoAI frameworks for CF prediction and systemic impact quantification. A systematic review follows the PRISMA protocol, examining 403 articles from the Web of Science and Scopus databases. The concept of the coupled hydrodynamics-GeoAI model synergizes physics-based simulations with data-driven computational learning, enhancing predictive accuracy and spatially detailed flood risk while explicitly embedding geographic features into the framework. The model offers three utilization modes: (i) direct coupling, (ii) surrogate modeling, and (iii) stochastic statistical-hydrodynamic-ML framework. To enhance comprehensive and robust risk assessment, the review proposes four key model advancements: (1) implementing an active learning framework, (2) integration with physics-guided data-driven, (3) dynamically coupling CF drivers with external factors, and (4) incorporating spatiotemporal analysis under changing climate and socioeconomic conditions. We further advocate for integrating the quantification of both tangible and intangible cascading impacts into systemic CF risk assessments. This review synthesizes computational strategies integrating physics-based hydrodynamics with GeoAI, providing a foundation for systemic CF risk evaluation and guiding future advances in computational hydrology and resilient urban flood management. Graphical Abstract This graphical abstract visually encapsulates the core concept of leveraging coupled hydrodynamic with data-driven GeoAI models for systemic compound flood (CF) risk evaluation in coastal urban areas. The abstract integrates the three main flood drivers—coastal, pluvial, and fluvial—interacting to form the CF. The diagram flows from left to right, where the first section depicts the urban coastal zone, followed by a combination of flood drivers that illustrate the complexity and interconnectedness of factors leading to CF. On the right panel, the graphical focus shifts to the “Coupled Hydrodynamic with Data-Driven GeoAI Model” as the proposed approach for predicting the CF event, encompassing probabilistic analysis, flood propagation, risk assessment, real-time forecasting, and emergency response. The approach integrates physics-based simulations with data-driven geographic data analysis, known as GeoAI. On the bottom left panel, the illustration emphasizes the utilization of the approach through three key strategies: (i) direct coupling through ML-derived boundary conditions, (ii) surrogate modeling to emulate hydrodynamic outputs, and (iii) stochastic statistical-hydrodynamic-ML framework. These strategies demonstrate how GeoAI enhances hydrodynamic simulations to produce more accurate, timely, and spatially detailed flood predictions in various ways. The model’s advancements are also highlighted, addressing the critical need for the utilization of an active learning framework, integration with physics-guided data-driven, dynamically coupling CF drivers with external factors, and the importance of considering spatiotemporal analysis under climate and socioeconomic change. The graphic in the bottom right panel displays the CF output results from the model, which can be further utilized to assess the cascading impact on various aspects. Together, the elements of this graphical abstract convey a sophisticated, interdisciplinary approach to CF risk evaluation, focusing on integrating hydrodynamic with data-driven GeoAI models to better manage the complex challenges of systemic CF risks in urban coastal zones.
Keywords: Scopus_Alert_17_Octobre_2025

Flood relief logistics planning for coastal cities: a case study in Shanghai, China - Liang, Pujun; Yin, Jie; Wang, Dandan; Lu, Yi; Yang, Yuhan; Gao, Dan; Mai, Jianfeng (Natural Hazards and Earth System Sciences, 2025)
Abstract. Coastal cities are becoming more vulnerable to flood risks due to climate change, rising sea levels, intense storm surges, population growth and land subsidence. Developing emergency preparedness and response strategies can reduce the impact of coastal flooding and improve a city's resilience. This article presents a flood relief logistics planning approach aimed at providing decision-makers with a feasible framework. The framework integrates geographic information system (GIS) network analysis and resource allocation optimisation models. Considering the equity of resource allocation, a bi-objective allocation model that minimises the total transportation cost and maximum unsatisfied rate is developed. This flood relief logistics planning approach is applied to Shanghai, China, to present feasible distribution strategies. The case study indicates that the current spatial distribution of emergency reserve warehouses (ERWs) and emergency flood shelters (EFSs) in Shanghai may be vulnerable to extreme flood events. Under a 1000-year coastal flood scenario, the existing emergency resources are insufficient to meet the needs of the affected elderly population. In situations of resource scarcity, reducing the maximum unsatisfied rate can help to improve the equity of resource allocation. Furthermore, incorporating private warehouse clubs (WHCs) into government emergency logistics through public–private collaboration could reduce the governmental burden and improve system efficiency and resilience. This study provides a scientific reference for developing flood relief logistics plans in Shanghai, and it presents a transferable framework that is applicable to other coastal cities.
Keywords: Scopus_Alert_10_Octobre_2025

Machine Learning-Based Flood Risk Assessment in Urban Watershed: Mapping Flood Susceptibility in Charlotte, North Carolina - Shrestha, Sujan; Dahal, Dewasis; Bhattarai, Nishan; Regmi, Sunil; Sewa, Roshan; Kalra, Ajay (Geographies, 2025)
Flood impacts are intensifying due to the increasing frequency and severity of factors such as severe weather events, climate change, and unplanned urbanization. This study focuses on Briar Creek in Charlotte, North Carolina, an area historically affected by flooding. Three machine learning algorithms —bagging (random forest), extreme gradient boosting (XGBoost), and logistic regression—were used to develop a flood susceptibility model that incorporates topographical, hydrological, and meteorological variables. Key predictors included slope, aspect, curvature, flow velocity, flow concentration, discharge, and 8 years of rainfall data. A flood inventory of 750 data points was compiled from historic flood records. The dataset was divided into training (70%) and testing (30%) subsets, and model performance was evaluated using accuracy metrics, confusion matrices, and classification reports. The results indicate that logistic regression outperformed both XGBoost and bagging in terms of predictive accuracy. According to the logistic regression model, the study area was classified into five flood risk zones: 5.55% as very high risk, 8.66% as high risk, 12.04% as moderate risk, 21.56% as low risk, and 52.20% as very low risk. The resulting flood susceptibility map constitutes a valuable tool for emergency preparedness and infrastructure planning in high-risk zones.
Keywords: Scopus_Alert_10_Octobre_2025

Analysis of Risk Factors for Tunnel Flooding Disasters Based on DEMATEL - Fang, Yongxiang; Zhang, Yanmei; Zhu, Yanchang; Tao, Yingying; Zhang, Rui; Wang, Qikai (Water, 2025)
The growing frequency of extreme rainstorms has increasingly exposed tunnels to flooding risks, underscoring the urgent need for effective flood prevention and drainage measures. In this context, an evaluation framework for tunnel flood hazards was developed based on three criteria—hazard-inducing factors, hazard-formative environment, and disaster-bearing body—encompassing nine specific indicators. This study employs the Decision Making Trial and Evaluation Laboratory (DEMATEL) method to construct a causal analysis model and assess the interrelationships and influence levels of risk factors associated with tunnel flooding disasters. Rainfall intensity (C1), rainfall duration (C2), ground elevation (C4), road slope (C5), and impervious surface area (C6) exhibit high causal values, acting as external input factors that drive the occurrence of tunnel flooding incidents. Conversely, water depth (C3), tunnel drainage capacity (C7), emergency flood control measures (C8), and infrastructure aging (C9) display high centrality values, serving as internal factors that reflect the tunnel’s flood prevention capability and determine the extent of disaster losses. Simply enhancing tunnel drainage capacity from the perspective of internal factors alone is insufficient; optimizing the tunnel’s flood resilience requires a combined consideration of both internal and external factors.
Keywords: Scopus_Alert_10_Octobre_2025

Impact of Grated Inlet Clogging on Urban Pluvial Flooding - Russo, Beniamino; Beiró, Viviane; Lopez-Julian, Pedro Luis; Acero, Alejandro (Hydrology, 2025)
This study aims to analyse the effect of partially clogged inlets on the behaviour of urban drainage systems at the city scale, particularly regarding intercepted volumes and flood depths. The main challenges were to represent the inlet network in detail at a rather large scale and to avoid the effect of sewer network surcharging on the draining capacity of inlets. This goal has been achieved through a 1D/2D coupled hydraulic model of the whole urban drainage system in La Almunia de Doña Godina (Zaragoza, Spain). The model focuses on the interaction between grated drain inlets and the sewer network under partial clogging conditions. The model is fed with data obtained on field surveys. These surveys identified 948 inlets, classified into 43 types based on geometry and grouped into 7 categories for modelling purposes. Clogging patterns were derived from field observations or estimated using progressive clogging trends. The hydrological model combines a semi-distributed approach for micro-catchments (buildings and courtyards) and a distributed “rain-on-grid” approach for public spaces (streets, squares). The model assesses the impact of inlet clogging on network performance and surface flooding during four rainfall scenarios. Results include inlet interception volumes, flooded surface areas, and flow hydrographs intercepted by single inlets. Specifically, the reduction in intercepted volume ranged from approximately 7% under a mild inlet clogging condition to nearly 50% under severe clogging conditions. Also, the model results show the significant influence of the 2D mesh detail on flood depths. For instance, a mesh with high resolution and break lines representing streets curbs showed a 38% increase in urban areas with flood depths above 1 cm compared to a scenario with a lower-resolution 2D mesh and no curbs. The findings highlight how inlet clogging significantly affects the efficiency of urban drainage systems and increases the surface flood hazard. Further novelties of this work are the extent of the analysis (city scale) and the approach to improve the 2D mesh to assess flood depth.
Keywords: Scopus_Alert_10_Octobre_2025

Generalized Methodology for Two-Dimensional Flood Depth Prediction Using ML-Based Models - Soliman, Mohamed; Morsy, Mohamed M.; Radwan, Hany G. (Hydrology, 2025)
Floods are among the most devastating natural disasters; predicting their depth and extent remains a global challenge. Machine Learning (ML) models have demonstrated improved accuracy over traditional probabilistic flood mapping approaches. While previous studies have developed ML-based models for specific local regions, this study aims to establish a methodology for estimating flood depth on a global scale using ML algorithms and freely available datasets—a challenging yet critical task. To support model generalization, 45 catchments from diverse geographic regions were selected based on elevation, land use, land cover, and soil type variations. The datasets were meticulously preprocessed, ensuring normality, eliminating outliers, and scaling. These preprocessed data were then split into subgroups: 75% for training and 25% for testing, with six additional unseen catchments from the USA reserved for validation. A sensitivity analysis was performed across several ML models (ANN, CNN, RNN, LSTM, Random Forest, XGBoost), leading to the selection of the Random Forest (RF) algorithm for both flood inundation classification and flood depth regression models. Three regression models were assessed for flood depth prediction. The pixel-based regression model achieved an R2 of 91% for training and 69% for testing. Introducing a pixel clustering regression model improved the testing R2 to 75%, with an overall validation (for unseen catchments) R2 of 64%. The catchment-based clustering regression model yielded the most robust performance, with an R2 of 83% for testing and 82% for validation. The developed ML model demonstrates breakthrough computational efficiency, generating complete flood depth predictions in just 6 min—a 225× speed improvement (90–95% time reduction) over conventional HEC-RAS 6.3 simulations. This rapid processing enables the practical implementation of flood early warning systems. Despite the dramatic speed gains, the solution maintains high predictive accuracy, evidenced by statistically robust 95% confidence intervals and strong spatial agreement with HEC-RAS benchmark maps. These findings highlight the critical role of the spatial variability of dependencies in enhancing model accuracy, representing a meaningful approach forward in scalable modeling frameworks with potential for global generalization of flood depth.
Keywords: Scopus_Alert_10_Octobre_2025

A Novel Multimodal Large Language Model-Based Approach for Urban Flood Detection Using Open-Access Closed Circuit Television in Bandung, Indonesia - Yang, Tsun-Hua; Wijaya, Obaja Triputera; Ardianto, Sandy; Christian, Albert Budi (Water, 2025)
Monitoring urban pluvial floods remains a challenge, particularly in dense city environments where drainage overflows are localized, and sensor-based systems are often impractical. Physical sensors can be costly, prone to theft, and difficult to maintain in areas with high human activity. To address this, we developed an innovative flood detection framework that utilizes publicly accessible CCTV imagery and large language models (LLMs) to classify flooding conditions directly from images using natural language prompts. The system was tested in Bandung, Indonesia, across 340 CCTV locations over a one-year period. Four multimodal LLMs, ChatGPT-4.1, Gemini 2.5 Pro, Mistral Pixtral, and DeepSeek-VL Janus, were evaluated based on classification accuracy and operational cost. ChatGPT-4.1 achieved the highest overall accuracy at 85%, with higher performance during the daytime (89%) and lower accuracy at night (78%). A cost analysis showed that deploying GPT-4.1 every 15 min across all locations would require approximately USD 59,568 per year. However, using compact models like GPT-4 nano could reduce costs by up to seven times, with minimal loss of accuracy. These results highlight the trade-off between performance and affordability, especially in developing regions. This approach offers a scalable, passive flood monitoring solution that can be integrated into early warning systems. Future improvements may include multi-frame image analysis, automated confidence filtering, and multi-level flood classification for enhanced situational awareness.
Keywords: Scopus_Alert_10_Octobre_2025

Evaluating Infiltration Methods for the Assessment of Flooding in Urban Areas - Bianucci, Paola; Fernández-Fidalgo, Javier; Kyaw, Kay Khaing; Soriano, Enrique; Mediero, Luis (Water, 2025)
Urban flooding caused by short and high-intensity rainfall events presents increasing challenges for cities, threatening infrastructure, public safety and economic activity. Accurately representing infiltration processes in hydrodynamic models is critical, as oversimplifying infiltration can lead to significant errors in predicted flood extents and water depths. This study systematically compares two widely used infiltration models—Green-Ampt and Curve Number—implemented within two leading 2D hydraulic models, HEC-RAS and IBER, to assess their influence on urban flood predictions. Simulations were conducted for 26 rainfall events, including both observed and synthetic hyetographs, across two urban neighbourhoods in Pamplona metropolitan area, Spain. Model performance was evaluated using root mean square error, mean absolute error and confusion matrix-derived metrics such as precision, accuracy, specificity, sensitivity and negative predictive value. Results indicate that the choice of infiltration method significantly affects both water depths and inundation extents: while Green-Ampt yields more conservative water depth estimates, Curve Number tends to underestimate flood extents. The comparison between the two hydraulic models has shown that IBER simulates broader flood extents and lower water depth errors compared to HEC-RAS. The findings highlight the importance of selecting appropriate infiltration methods and hydraulic models for reliable urban flood risk assessment, as well as providing guidance for model selection in urban inundation studies.
Keywords: Scopus_Alert_10_Octobre_2025

Learning predictable and informative dynamical drivers of extreme precipitation using variational autoencoders - Spuler, Fiona R.; Kretschmer, Marlene; Balmaseda, Magdalena Alonso; Kovalchuk, Yevgeniya; Shepherd, Theodore G. (Weather and Climate Dynamics, 2025)
Abstract. Large-scale atmospheric dynamics modulate the occurrence of extreme precipitation events and provide sources of predictability of these events on timescales ranging from days to decades. In the midlatitudes, regional dynamical drivers are frequently represented as discrete, persistent and recurrent circulation regimes. However, available methods identify circulation regimes which are either predictable but not necessarily informative of the relevant local-scale impact studied, or targeted to a local-scale impact but no longer as predictable. In this paper, we introduce a generative machine learning method based on variational autoencoders for identifying probabilistic circulation regimes targeted to spatial patterns of precipitation. The method, CMM-VAE, combines targeted dimensionality reduction and probabilistic clustering in a coherent statistical model and extends a previous architecture published by the authors to allow for categorical target variables. We investigate the trade-off between regime informativeness of local precipitation extremes and predictability of the regimes at subseasonal lead times. In an application to study drivers of extreme precipitation over Morocco, we find that the targeted CMM-VAE regimes are more informative of the impact variable of interest, compared to two well-established linear approaches, while maintaining the predictability of conventional non-targeted circulation regimes in subseasonal hindcasts, hence resolving the trade-off identified in previous studies. Furthermore, the targeted regimes and their predictability are physically interpretable in terms of known subseasonal teleconnections relevant to the region, the Madden-Julian Oscillation and variability of the stratospheric polar vortex. The proposed method therefore allows to identify predictable, interpretable and locally relevant representations of regional dynamical drivers given a target variable of interest. These results highlight the potential of the method for a variety of applications, ranging from subseasonal forecasting to attribution and statistical downscaling.
Keywords: Scopus_Alert_10_Octobre_2025

Future forest conditions under alternative management and hydrological scenarios in the Upper Mississippi River floodplain - Trumper, Matthew L.; De Jager, Nathan R.; Van Appledorn, Molly; Meier, Andrew R. (Landscape Ecology, 2025)
Abstract Context Floodplain forests are being transformed by multiple pressures, prompting widespread management and restoration efforts. It is uncertain how disturbances, including hydrologic change, and management actions will interact to influence the ecology of these threatened forests. Objectives This study examined the effects of alternative management and hydrologic regimes on forest succession at an Upper Mississippi River floodplain site with a restoration project in planning. Methods We used the spatially explicit forest landscape model, LANDIS-II, to simulate forest succession for 100 years under four hydrogeomorphic management scenarios, three forest management scenarios, and two scenarios of future hydrologic conditions. We evaluated changes in forest biomass and composition over time and assessed the relative importance of management actions and hydrologic change on succession. Results Forest aboveground biomass decreased in all management-hydrology scenarios, especially in the wetter hydrological scenario. Intensified hydrogeomorphic and forest management scenarios reduced the magnitude and extent of biomass declines; however, they were unable to prevent overall declines in biomass or cause large shifts in tree species composition. Silver maple ( Acer saccharinum ) was projected to decrease in biomass, while increases in biomass were projected for several late-successional species including swamp white oak ( Quercus bicolor ). Among the factors influencing variation in biomass, forest management had the largest influence in the first 50 years of our simulations, but hydrological regime became the most important factor by the end of the century. Conclusions Our simulations indicate that management actions could play an important role in the conservation of floodplain forests, but their effectiveness will likely be limited if recent upward trends in flooding conditions in this system continue in the future. Thus, our results highlight both the potential benefits and limitations of management actions in the face of hydrologic change.
Keywords: Scopus_Alert_10_Octobre_2025

Current Status of Studying on Physiological Mechanisms of Rice Response to Flooding Stress and Flooding-Resistant Cultivation Regulation - Bu, Weicheng; Ahmad, Irshad; Fei, Han; Ibrahim, Muhi Eldeen Hussien; Xu, Yunji; Meng, Tianyao; Zuo, Qingsong; Lei, Tianjie; Zhou, Guisheng; Zhu, Guanglong (Plants, 2025)
Due to climate change, flooding stress has occurred more frequently and intensively than ever before, which has become one of the major abiotic stresses affecting rice production. In tropical regions around the world, southeastern coastal countries, and southern rice production areas of China, frequent flooding disaster usually takes place during the rainy season and heavy summer rainfall, which leads to great yield losses in rice production. Currently, only a few rice genotypes are flooding-tolerant, and the relevant flooding-resistant cultivation and regulation practices are still lacking. Therefore, this review highlighted the latest studies on the physiological mechanisms of rice response to flooding stress and flooding-resistant cultivation, particularly summarizing the effect of flooding stress on rice root system architecture, plant growth, reactive oxygen metabolism, energy metabolism, radiation use efficiency, endogenous hormone metabolism, nitrogen utilization efficiency, and yield formation. In addition, the breeding strategies and cultivation regulation approaches for alleviating the flooding stress of rice were analyzed. Finally, future research directions are outlined. This review comprehensively summarizes the rice growth performance and physiological traits response to flooding stress, and sums up some useful regulation strategies, which might assist in further interpreting the mechanisms of plants’ response to flooding stress and developing stress-resistant cultivation practices for rice production.
Keywords: Scopus_Alert_10_Octobre_2025

Informing Coastal Futures: Sea Level Rise and Ecosystem Service Disruption in Caribbean Biodiversity Hotspots - Hurtado-Valdivieso, Rafael; Mancera-Pineda, Jose Ernesto; Martin, Ariadna; Quintero, Paola; Ruíz, Daniel; Baggio, Jacopo (Current Climate Change Reports, 2025)

Informing Coastal Futures: Sea Level Rise and Ecosystem Service Disruption in Caribbean Biodiversity Hotspots - Hurtado-Valdivieso, Rafael; Mancera-Pineda, Jose Ernesto; Martin, Ariadna; Quintero, Paola; Ruíz, Daniel; Baggio, Jacopo (Current Climate Change Reports, 2025)
Keywords: Scopus_Alert_10_Octobre_2025

A state-of-the-art approach to assessing relative multi-dimensional vulnerabilities for urban flood resilience in the UK - Woods, Arthur C.; Gupta, Vijaya; Campos, Luiza C. (International Journal of Disaster Risk Reduction, 2025)
Keywords: Scopus_Alert_10_Octobre_2025

A risk-informed approach for combined functionality analysis of buildings and road network under flooding: A case study at Silchar, India - Sen, Mrinal Kanti; Kumar, Prem; Laskar, Jahir Iqbal; Dutta, Subhrajit (International Journal of Disaster Risk Reduction, 2025)
Keywords: Scopus_Alert_10_Octobre_2025

Flood vulnerability analysis in the Itang watershed, lower Baro-Akobo basin, Southwestern Ethiopia - Chengu, Shibiru; Assen, Mohammed; Gebeyehu, Elias (Discover Sustainability, 2025)
Keywords: Scopus_Alert_10_Octobre_2025

Practitioner Perspectives of Flood Source Area ( FSA ) Analysis for System‐Based Flood Risk Management - Dawson, David A.; O'Donnell, Emily; Bond, Stephanie; Willis, Thomas; Huck, Jonathan; Sherwood, Matthew; Moxon, Jonathan (Journal of Flood Risk Management, 2025)
ABSTRACT Urban Flood Risk Management (FRM) is a critical aspect of developing resilient environments for future generations to inhabit. It is now interconnected with the requirement to be more environmentally conscious through blue‐green infrastructure and the delivery of wider co‐benefits. The complexity of balancing urban growth with environmental drivers and increasing resilience is a key challenge for strategic urban decision‐making. Through computational modelling developments, new approaches to assess the spatial contribution of area to flood hazard are improving our understanding of the catchment response and our ability to develop multifunctional, multi‐beneficial projects. Yet at present, these approaches remain largely theoretical or are a ‘best intention’. This study uses an adapted ‘Unit Flood Response’ approach to generate Flood Source Area (FSA) maps for an urban catchment in the UK. A user‐focused engagement approach is applied using FSA outputs to generate key insight into its applicability from a practitioner perspective. The FSA modelling identified several hazard sources, from widespread contributions upstream to discrete contributions downstream. Stakeholders concluded that the FSA can support FRM at the pre‐planning stage by providing a clearer strategic vision across the catchment to support traditional ‘receptor‐led’ decision‐making. Improved identification and negotiation of project partners and the potential to support/identify wider scale options that integrate with existing and planned infrastructure in other sectors, for example, housing and transport, were additional benefits of this approach. While the computational aspects of FSA analyses could be improved for model robustness (e.g., calibration, validation), they must do so with a full understanding of the practicalities of applying these techniques on the ground, demonstrating the importance of co‐development of research with practitioners and decision‐makers.
Keywords: Scopus_Alert_10_Octobre_2025

Assessment of urban flood risk of the lower Tapi basin through an integrated approach using GIS based AHP - Jariwala, Aayushi; Agnihotri, Prasit (Journal of Earth System Science, 2025)
Keywords: Scopus_Alert_10_Octobre_2025

A Coupled Hydrological‐Hydrodynamic Modelling Approach for Assessing the Impacts of Multiple Natural Flood Management Interventions on Downstream Flooding - Zhu, Qiuyu; Klaar, Megan; Willis, Thomas; Holden, Joseph (Journal of Flood Risk Management, 2025)
ABSTRACT While natural flood management (NFM) as a flood mitigation strategy is becoming widely used, there remains a lack of evidence regarding the effectiveness of different NFM scenarios under high flow events. To demonstrate how different types and extents of NFM interventions interact to flood peaks at larger catchment scales, combined scenarios of existing NFM interventions and an ideal maximum woodland scenario were modelled in the Upper Aire, northern England, using a coupled model that integrates Spatially Distributed TOPMODEL (SD‐TOPMODEL) with a 2D hydrodynamic model (Flood Modeller 2D) at an 81.4 km 2 catchment. The coupled model exhibited a strong fit with observed data (NSE up to 0.95), effectively capturing flood peaks and peak shapes. Leaky dams were found to be more effective at delaying flood peaks with mean values ranging from 8.6 to 60 min than reducing peak discharge (mean values ranging from 0.53% to 1.84%), though these effects were inversely proportional and influenced by tributary characteristics such as channel gradient. Simulations applying multiple NFM interventions consistently demonstrated positive flood mitigation impacts, including reduced peak discharge up to 2.59% and delayed peaks up to 30 min, while inundation depths reduced by 0.5 m in most areas, with inundation extent reduction at critical points in an urban area. The study demonstrated the utility of the coupled model for evaluating NFM strategies while emphasising the need for further validation and exploration of systematic interventions at larger catchment scales. By providing insights into the interactions between NFM interventions and catchment characteristics, this research contributes to the optimisation of flood risk management strategies and informs future policy development.
Keywords: Scopus_Alert_10_Octobre_2025

Flood disaster experiences of elderly individuals living in the western black sea region of Türkiye: a phenomenological study - Atalay, Ezgi; Gündüz Zeybekoğlu, Fatma; Torpuş, Kemal; Usta, Galip (BMC Geriatrics, 2025)
Keywords: Scopus_Alert_10_Octobre_2025

Analyzing Synthetic Stage‐Discharge Rating Curves and Riverine Flood Inundation Maps Derived From Global‐Scale Hydrologic and Hydraulic Modeling - Gutenson, Joseph L.; Follum, Michael L.; Staebell, Kathleen A.; Ondich, Emily S.; Wahl, Mark D. (Journal of Flood Risk Management, 2025)
ABSTRACT Synthetic rating curves (SRCs) are often used to translate streamflow forecasts into flood inundation maps. Previous studies have investigated the development and errors in SRCs at local, regional, and continental scales. In this analysis, we used the latest global methodology and datasets to develop SRCs for use in flood inundation map forecasting. Using the Yellowstone River Basin and the 2022 floods that affected the region, we analyzed the error in the SRCs assessment of stage and water surface elevation (WSE). We then investigated the error in flood inundation maps produced using the SRCs. Comparing SRCs to locally derived rating curves from 29 U.S. Geological Survey (USGS) stream gages, median error in SRC stage ranged from 0.45 to 0.65 m and SRC error was greatest at higher magnitude streamflows. This error increased to a median of 1.98–2.30 m when converting the stage to a WSE. After using the SRC WSE estimates to create an estimated flood inundation map, the WSE error at observed high‐water marks (1.99 m) was nearly proportional to average WSE error at the stream gage locations along the same river reach. Our results provide the first regional assessment of globally derived SRCs that are used in flood inundation mapping.
Keywords: Scopus_Alert_10_Octobre_2025

Evaluation of climate change impact on future flood in the Bagmati river basin, Nepal using CMIP6 climate projections and HEC-RAS modeling - Malla, Sushmita; Ohgushi, Koichiro (Water Cycle, 2026)
Keywords: Scopus_Alert_10_Octobre_2025

Integrating Hydrodynamic Mechanisms and Deep Learning for Real-Time Flood Inundation Forecasting - Fang, Xin; Li, Heng; Zhang, Sherong; Liu, Kang; Wang, Xiaohua; Wang, Chao (Journal of Computing in Civil Engineering, 2026)
Keywords: Scopus_Alert_10_Octobre_2025

Systematic Review of Multidimensional Assessment of Coastal Infrastructure Resilience to Climate-Induced Flooding: Integrating Structural Vulnerability, System Capacity, and Organizational Preparedness - Mashwama, Nokulunga Xolile; Phesa, Mbulelo (Climate, 2025)
This study investigates the multifaceted factors influencing the success of government-funded construction projects and addresses the challenges posed by climate-induced flooding, proposing integrated solutions encompassing structural vulnerability, system capacity, and organizational preparedness. By examining the challenges faced by coastal infrastructure, such as aging infrastructure, sea-level rise, and extreme weather events, this research seeks to identify strategies that enhance resilience and minimize the impact of flooding on coastal communities. The study presents a systematic review of 80 scholarly articles integrating quantitative and qualitative findings. Utilizing the PRISMA guidelines, the review highlights structural analysis, hydraulic modeling, and organizational surveys, to assess the resilience of coastal infrastructure systems. The results of this study offer actionable insights for policymakers, infrastructure managers, and coastal communities, facilitating informed decision-making and promoting climate-resilient development. Coastal regions around the world are increasingly vulnerable to climate-induced hazards such as sea level rise, storm surges, and intense flooding events. Among the most at-risk assets are transport infrastructure and buildings, which serve as the backbone of urban and regional functionality. This research paper presents a multidimensional assessment framework that integrates structural vulnerability, system capacity, and organizational preparedness to evaluate the resilience of coastal infrastructure. Drawing upon principles of resilience such as robustness, redundancy, safe-to-fail design, and change-readiness, the study critically reviews and synthesizes existing literature, identifies gaps in current assessment models, and proposes a comprehensive methodology for resilience evaluation. By focusing on both transport systems and building infrastructure, the research aims to inform adaptive strategies and policy interventions that enhance infrastructure performance and continuity under future climate stressors.
Keywords: Scopus_Alert_10_Octobre_2025

Enhancing water security through integrated storage mechanisms and rainwater harvesting for sustainable development - Alao, Joseph Omeiza; Eze, Stanley U.; Onyenweife, Geraldine I.; Ibe, Amarachukwu A.; Otorkpa, Oche J.; Ayejoto, Daniel A.; Abubakar, Fahad; Abdulsalami, Momohjimoh; Abdulmalik, Danga Onimisi (Discover Sustainability, 2025)
Keywords: Scopus_Alert_10_Octobre_2025

Unlocking Financial Potential for Urban Nature‐Based Solutions: A PRISMA ‐Based Systematic Review - Ahmad, Maruf; Du, Jinfeng (Sustainable Development, 2025)
ABSTRACT Contemporary urbanization has intensified environmental, social, and economic challenges, underscoring the need for Nature‐Based Solutions (NBS) to address issues of urban carbon emission, flooding, stormwater management, heatwaves, and biodiversity loss. However, securing funding for NBS implementation and maintenance remains a critical barrier. This study systematically reviews 121 financial‐related scholarly literature on urban NBS, applying the PESTLE (political, economic, social, technological, legal, and environmental) method to identify barriers to financial innovation and implementation. To ensure reliability, countermeasures cited in at least three independent sources were included. Key financial barriers for urban NBS include unstandardized valuation metrics (19%), insufficient financing mechanisms (15%), and regulatory limits (11%). This review also highlights countermeasures such as economic valuation (8%), innovative finance modalities (8%), tax benefits, and community workshops (7%) that can address these barriers. The study's uniqueness lies in how financial resource alignment and regulatory support, guided by Resource‐Based View and Institutional Theory , can promote sustainable NBS adoption. It also calls for standardized valuation metrics and adaptive monitoring systems to improve the social, environmental, and economic impact of NBS, making them more attractive to investors and ensuring long‐term sustainability. These findings provide actionable insights for financial restructuring and urban planners to effectively bridge funding gaps and promote sustainable environmental financing.
Keywords: Scopus_Alert_10_Octobre_2025

Dynamic flood risk modeling in urban metro systems considering station configuration - Liang, Chen; Guan, Mingfu; Guo, Kaihua; Yu, Dapeng; Yin, Jie (Reliability Engineering & System Safety, 2026)
Keywords: Scopus_Alert_3_Octobre_2025

Real-time coastal flood risk assessment using IoT-integrated satellite data and machine learning models for predicting flooding events and informing resilient coastal planning for Durban coastal region, South Africa - Vadivel, M.; Vijaya Saraswathi, R.; Sree Lakshmi, P.; Merugu, R Rajaramesh; T., Subbulakshmi; Vivek, S. (Journal of African Earth Sciences, 2026)
Keywords: Scopus_Alert_3_Octobre_2025

Does flood risk matter in shaping climate gentrification? Evidence from Brisbane (2006–2021) - Gao, Xiaoyong; Yi, Xianjian; Kwan, Mei-Po; Li, Huan (Cities, 2026)
Keywords: Scopus_Alert_3_Octobre_2025

A data-driven and expert flood knowledge model based on the development of the Huber loss function for flood forecasting - Malik, Haider; Feng, Jun; Shao, Pingping; Abduljabbar, Zaid Ameen (Water Research, 2026)
Keywords: Scopus_Alert_3_Octobre_2025

Flood vulnerability and risk mapping in Arba minch city using remote sensing, GIS and AHP - Kasahun, Melion; Diriba, Dechasa; Lemma, Tesfaye; Karuppannan, Shankar; Kanko, Niguse (Scientific African, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Complementing expertise: Q-visualization method for community-participatory flood loss assessment of Mihe Town, Zhengzhou, China - Feng, Xiao; Zhao, Zhenbin; Zhang, Jian; Li, Yangyang; Zhang, Yuqian (Applied Geography, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Spatial Modeling of Flood Hazard in Addis Ababa Using Geographic Information System ( GIS ) and Information Gain Ratio ( IGR ) Method - Bekalo, Desta Jula; Bojer, Amanuel Kumsa; Debelee, Taye Girma; Fadhil Al‐Quraishi, Ayad M.; Negera, Worku Gachena; Gebissa, Kena Wendimu; Nadarajah, Saralees; Woldesillasie, Firesew Feyiso (Journal of Flood Risk Management, 2025)
ABSTRACT Floods are one of nature's most disturbing catastrophes, resulting in infrastructure damage, property devastation, and mortality. In Addis Ababa, flooding has significantly impacted residents and caused millions' worth of property damage in the last decade alone. It is continuously threatening and affecting city residents. This study focused on the spatial modeling of floods and the identification of areas susceptible to flood hazards in the city. Geographic information system (GIS) techniques combined with the information gain ratio (IGR) method were employed in this study. Five major flood hazard factors were identified: elevation, slope, rainfall, drainage density, and distance from drainage channels. The results show that 1.3% (7.1 km 2 ) of the area is highly susceptible to floods, 29.4% (159 km 2 ) is highly susceptible to heavy rains, 56% (302 km 2 ) of the area is moderately susceptible, 12.5% (67.3 km 2 ) of the area has low susceptibility, and less than 1% (4.2 km 2 ) has very low susceptibility. Slope is the most influential factor (42.74%), followed by drainage density (28.21%), distance from drainage channels (18.8%), rainfall (7.69%), and elevation (2.56%). The sub‐cities of Nifas Silk Lafto and Akaki Kality are the most susceptible to flood hazards; areas with steep slopes trigger high runoff during heavy rainy periods and cause flood hazards on gentle slope surfaces. It is recommended that to improve the accuracy of identifying susceptible flood‐hazard locations, flooding simulation should be performed in conjunction with other variables and rainfall data (such as rainfall duration and intensity). Nevertheless, this research provides recommendations to municipal administration decision‐makers regarding strategic management in the prioritization of flood‐hazard zones.
Keywords: Scopus_Alert_3_Octobre_2025

Reduction of the uncertainty of flood projection under a future climate by focusing on similarities among multiple SSP-RCP scenarios - Kimura, Y.; Hirabayashi, Y.; Yamazaki, D. (Scientific Reports, 2025)
Abstract Climate projections contain the uncertainty due to the internal variability of the climate system, including its chaotic nature. While the uncertainty due to the internal variability can be theoretically mitigated by executing large ensemble simulations with perturbed initial conditions, only a limited number of large-ensemble experiments are available in CMIP6 future scenario dataset. Here we propose a method that increases the effective ensemble sampling size in evaluations of future projection by integrating multiple SSP-RCPs for a period corresponding to a specific increase in temperature from the preindustrial level (i.e., X°C warming). The success of the method was assessed by investigating whether the uncertainty due to small number of ensemble members could be reasonably reduced. First, we confirmed that the spatial distributions of the future flood magnitude change were similar under a 2 °C warming in all SSP-RCP scenarios. Additionally, the uncertainty due to the different SSP-RCPs (5–10%) was smaller than the differences between different warming levels such as between 2 and 3 °C (around 20–50%), suggesting differences among SSP-RCPs as to future flood discharge change are relatively small. These results suggested that integrating SSP-RCPs to increase the effective ensemble size was a reasonable approach, reducing unbiased variance among GCMs in about 70% of land grid points comparing to the result using SSP5-RCP8.5 alone.
Keywords: Scopus_Alert_3_Octobre_2025

Human health risk assessment of heavy metals in fish and shellfishes from heavy monsoon flood affected coastal zones of Tuticorin, Southeastern India - Yogeshwaran, Arumugam; Anandhan, Krishnan; Sanjeev, Chandrasekar; Rajaram, Rajendran; Muralisankar, Thirunavukkarasu (Food and Humanity, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Towards measuring community resilience to flood risk: A baseline analysis - Awah, Lum Sonita; Belle, Johanes Amate; Orimoloye, Israel Ropo; Nyam, Yong Sebastian (Scientific African, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Ferric sulfate-modified biochar as a dual-function amendment for methane mitigation and heavy metal risk control in flooded rice systems - Zhang, Zhiwei; Bo, Xiaomeng; Lu, Mingwang; Mai, Xiaofeng; Li, Zhutao; Guo, Shumin; Shen, Mengxue; Han, Zhaoqiang; Wu, Shuang; Wang, Jinyang; Zou, Jianwen (Environmental Technology & Innovation, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Multi-decade analysis of flood risks to community infrastructure in Philadelphia - Son, Youngjun; Sun, Ning; Reesman, Cade; Judi, David; Li, Xue (International Journal of Disaster Risk Reduction, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Between flood vulnerability and watery pedagogies: A critical review of children and young people’s voices and experiences - Verlie, Blanche; Rousell, David; De Kleyn, Lisa; Hartup, Michael; Rickards, Lauren; St Clair, Jeanti; Bayes, Chantelle; Widdop Quinton, Helen; Blom, Simone; Hotko, Katie; Cutter-Mackenzie-Knowles, Amy; De Rivera, Liberty; et al. (Geoforum, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Dynamic urban flood risk assessment based on human activity patterns: An IFAHP-EWM-TOPSIS approach - He, Weijie; Zeng, Jian; Zhang, Jiahao; Namaiti, Aihemaiti; Shi, Weihao; Song, Yuanzhen; Tian, Jian (Sustainable Cities and Society, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Key Drivers in Flood and Drought Risk Assessment: Unveiling Risk Factors through a Multi-Metric Network Approach - Fasihi, Siavash; Lim, Wen Zyn; Wu, Wenyan; Proverbs, David (Water Resources, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Flood risk analysis of strategically important structures to river coasts: case study of wastewater disposal facility - Akpınar, Özkan; Anıl, Özgür (Environmental Earth Sciences, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

The effects of flood disasters on urban farmers in Ghana: a case-based perspective - Owusu, Doreen; Mensah, Henry; Simpeh, Eric Kwame; Guodaar, Lawrence; Asare-Baafi, Louisa (SN Social Sciences, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Climate Change and Population Aging Exacerbate Flood Risk to the Elderly in European Regions - Yang, Wenyu; Zhao, Ziyong; Wang, Zhenyu; Wang, Xuan; Li, Ruifei; Hua, Pei; Cheng, Xiangju; Liu, Yungang; Wang, Haijun; Krebs, Peter; Zhang, Jin (Earth's Future, 2025)
Abstract Floods threaten human lives globally, yet the flood risk to the elderly (above 65) remains uncertain within warming climates and population aging. Hence, this study incorporated the General Circulation Model and Shared Socioeconomic Pathway projections into the hydraulic modeling framework, to analyze the flood risk to the elderly in Europe under climatic and socioeconomic changes. Results demonstrated that central Europe has experienced an increase in both surface runoff and streamflow (exceeding 50%), which have jointly contributed to intensified flooding in the major basins (Loire, Rhine, Elbe, and Danube) within the region. Among them, the Elbe basin exhibited a significant increase in 100‐year flood peak (∼107%) and elderly population (∼15%), resulting in 51,300 (CI: 45,300–60,500) of the elderly population being exposed to high‐hazard floods under a high greenhouse gas scenario (SSP5‐8.5), with at most 58% (29,800, CI: 25,100–33,700) of them being densely settled or in low‐& middle‐income groups. Among aging cities, Prague was severely affected by floods, with 40%–54% of the exposed elderly in high‐risk areas. Followed by Dresden and Hamburg, where up to 18% of the exposed elderly were threatened by high‐risk floods. This study revealed regional inequalities induced by flood exposure within the context of warming climates and population aging. The methods and findings are expected to provide additional insights into sustainable flood risk management under global change. , Plain Language Summary Floods are threatening people around the world. As the climate gets warmer and the population gets older, it's important to understand how floods might affect the elderly (older than 65). In this study, we investigated how floods could impact the elderly in Europe by 2100. We coupled climate and socioeconomic projections with numerical simulations to analyze the flood risk in different future scenarios. We found that the flood risk could spatiotemporally vary across European basins and cities. In the Elbe River basin, flood peaks could increase by more than 100%, and the elderly population could grow by 15%, resulting in a maximum of 51,300 elderly population being exposed to floods, and up to 29,800 of them are highly vulnerable because of densely settled or in low‐& middle‐income groups. In aging cities like Prague, Dresden, and Hamburg, at most 54% of the exposed elderly can be in high‐risk areas. This research revealed that the vulnerable groups (elderly, low‐income) are disproportionately threatened by high‐risk floods. Here, we advocate for incorporating social vulnerability into flood risk evaluation and management, thereby helping mitigate regional inequalities and contribute to the United Nations Sustainable Development Goals. , Key Points Flood risk to the elderly across European regions was analyzed by coupling climatic and socioeconomic projections with hydraulic modeling Flood risk spatiotemporally varied in Europe, with Elbe basin showing an increase in floods (∼107%) and elderly population (∼15%) in future Over 51,300 of the elderly were exposed to floods in Elbe basin, with 58% of them being densely settled or in low‐& middle‐income groups
Keywords: Scopus_Alert_3_Octobre_2025

Testing the durability of hydraulic lime-based renders against extreme weather: Experimental aging tests for compound events in a changing climate - Romero-Gómez, M.I.; Flores-Colen, I.; Hooper, F.; Cardoso, R.; Pereira, M.F.C.; Bravo, M.; Mendes, M.P. (Journal of Building Engineering, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Impact of spatial resolution on multi-scenario WRF-ARW simulations driven by the CMIP6 MPI-ESM1-2-HR global model: a focus on precipitation distribution over Italy - Struglia, Maria Vittoria; Anav, Alessandro; Antonelli, Marta; Calmanti, Sandro; Catalano, Franco; Dell'Aquila, Alessandro; Pichelli, Emanuela; Pisacane, Giovanna (Geoscientific Model Development, 2025)
Abstract. We present the results of downscaling CMIP6 global climate projections to local scales for the Mediterranean and Italian regions, aiming to produce high-resolution climate information for the assessment of climate change signals, with a focus on precipitation extreme events. We performed hindcast (i.e., ERA5-driven) and historical simulations (driven by the MPI-ESM1-2-HR model) to simulate the present (1980–2014) and future (2015–2100) climate under three different emission scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5). For each experiment, a double-nesting approach is adopted to dynamically downscale global data to the regional domain of interest, firstly over the Europe (EURO) COordinated Regional climate Downscaling Experiment (CORDEX) domain, at a spatial resolution of 15 km, and then further refined (second nesting) over Italy and the northwestern Mediterranean at a resolution of 5 km, i.e., in the so-called gray zone (5–10 km), close to the convection-permitting (CP) limit. Besides validating the experimental protocol, this work potentially questions the need for climate simulations to always resort to deep convection parameterizations when spatial refinement is increased up to the limit of the CP scale, yet convective processes are still not explicitly resolved. Analyses of air temperature and precipitation are presented, with a focus on the spatial distribution of precipitation, its probability density function, and the statistics of extreme events for both current climate and far-end scenarios. By the end of the century for all the scenarios and seasons there is a projected general warming along with an intensification of the hydrological cycle over most of continental Europe and mean precipitation reduction over the Mediterranean region accompanied, over the Italian Peninsula, by a strong increase in the intensity of extreme precipitation events, particularly relevant for the SSP5-8.5 scenario during autumn.
Keywords: Scopus_Alert_3_Octobre_2025

Have river flow droughts become more severe? A review of the evidence from the UK – a data-rich, temperate environment - Hannaford, Jamie; Turner, Stephen; Chevuturi, Amulya; Chan, Wilson; Barker, Lucy J.; Tanguy, Maliko; Parry, Simon; Allen, Stuart (Hydrology and Earth System Sciences, 2025)
Abstract. When extreme hydrological events (floods and droughts) occur, there is inevitably speculation that such events are a manifestation of anthropogenic global warming. The UK is generally held to be a wet country, but recent drought events in the UK have led to growing concerns around droughts becoming more severe – for sound scientific reasons, given physical reasoning and projections for the future. In this extended review, we ask whether such claims are reasonable for hydrological droughts in the UK using a combination of literature review and extended analysis. The UK has a well-established monitoring programme and a very dense body of research to call on and, hence, provides the basis for a good international case study for addressing this question. We firstly assess the evidence for changes in the well-gauged post-1960 period before considering centennial-scale changes using published reconstructions. We then seek to provide a synthesis of the state of the art in our understanding of the drivers of change, both climatic and in terms of direct human disturbances to river catchments (e.g. changing patterns of water withdrawals, impoundments, land use changes). These latter impacts confound the identification of climate-driven changes, and yet, human influences are themselves being increasingly recognised as potential agents of changing drought regimes. We find little evidence of compelling changes towards worsening drought, apparently at odds with climate projections for the relatively near future and with widely held assumptions regarding the role of human disturbances in intensifying droughts. Scientifically, this is perhaps unsurprising (given uncertainties in future projections; the challenge of identifying signals in short, noisy records; and a lack of datasets to quantify human impacts), but it presents challenges to water managers and policymakers. We dissect some of the reasons for this apparent discrepancy and set out recommendations for guiding research and policy alike. While our focus is the UK, we envisage that the themes within this study will resonate with the international community, and we conclude with ways in which our findings are relevant more broadly, as well as how the UK can learn from the global community.
Keywords: Scopus_Alert_3_Octobre_2025

A systematic investigation of flood resilience measures in the Mekong River Basin - Ho, Thanh Phuoc; Garschagen, Matthias; Tri, Van Pham Dang; Yang, Liang Emlyn (Environmental Science & Policy, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

A systematic review on climate change-induced flood susceptibility, vulnerability and risk: future research perspective - Ali, Rayees; Sajjad, Haroon; Rahaman, Md Hibjur; Saha, Tamal Kanti; Masroor, Md; Roshani; Sharma, Aastha (Environmental Monitoring and Assessment, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

A review of the evolution of satellite radar altimetry for hydrological Monitoring: Water level and discharge estimation - Kumar, Barun; Bhattacharjee, Rajarshi; Dwivedi, Shyam Bihari; Gaur, Shishir; Chander, Shard; Ohri, Anurag (Physics and Chemistry of the Earth, Parts A/B/C, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Lessons from the catastrophic floods in southern Brazil: geographic and environmental factors, vulnerabilities, and the resilience of nephrology services during natural disasters - Silva, Dirceu Reis; Luz, Lucas Gobetti Da; Moura-Neto, José A. (Current Opinion in Nephrology & Hypertension, 2025)
Purpose of review In April and May of 2024, the state of Rio Grande do Sul in southern Brazil faced one of the most devastating natural disasters in its history. Torrential rains caused catastrophic flooding, affecting over 2.4 million people and damaging critical infrastructure. Among the most vulnerable were individuals with chronic kidney disease, particularly those dependent on dialysis or immunosuppressive therapy following kidney transplantation. This narrative report describes the impact of the floods on nephrology services, highlights systemic vulnerabilities, and outlines the responses by the Brazilian Society of Nephrology, healthcare providers, government authorities and other stakeholders. Recent findings Drawing on field reports and institutional data, the article details breakdowns in transportation, communication, water and power supply, and the cascading challenges affecting dialysis provision. It also documents mitigation efforts, including patient relocation, resource reallocation, inter-institutional collaboration, and telemedicine deployment. Although no deaths due to lack of dialysis were reported, the crisis exposed the fragility of health service continuity in extreme events. Summary This event underscores the urgent need to incorporate disaster preparedness into nephrology service planning. Strategies must be tailored to the specific geographic and infrastructural contexts of each region and integrated into broader public health emergency frameworks. The lessons learned offer valuable insights for strengthening healthcare system resilience in the face of climate-related disasters.
Keywords: Scopus_Alert_3_Octobre_2025

Artificial Intelligence in Sustainable Drainage Water Reuse: A Comprehensive Review - Abdulameer, Layth Saeed; Abdalrahem, Mushtaq K.; Al Maimuri, Najah M. L.; Al-Dujaili, Ahmed N.; Al-Shammari, Musa (Water Conservation Science and Engineering, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Extreme weather events and early childhood growth in low- and middle-income regions: A systematic review and meta-analysis - Wang, Xuechun; Lan, Lu; Xing, Xing; Yang, Wenyu; Zhu, He; Ding, Ruoxi (Environmental Research, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Use of Internet of Things in water resources applications: challenges and future directions: a critical review - Ansari, Sajad Ali; Vidyarthi, Vikas Kumar (Discover Internet of Things, 2025)
Keywords: Scopus_Alert_3_Octobre_2025

Concurrent modes of climate variability linked to spatially compounding wind and precipitation extremes in the Northern Hemisphere - François, Bastien; Teber, Khalil; Brett, Lou; Leeding, Richard; Gimeno-Sotelo, Luis; Domeisen, Daniela I. V.; Suarez-Gutierrez, Laura; Bevacqua, Emanuele (Earth System Dynamics, 2025)
Abstract. Compound wind and precipitation (CWP) extremes often cause severe impacts on human society and ecosystems, such as damage to crops and infrastructure. Spatially compounding events with multiple regions affected by CWP extremes in the same winter can impact the global economy and reinsurance industry; however, our understanding of these events is limited. While climate variability modes such as El Niño Southern Oscillation (ENSO) can influence the frequency of precipitation and wind extremes, their individual and combined effects on spatial co-occurrences of CWP extremes across the Northern Hemisphere have not been systematically examined. Here, by combining reanalysis data and climate model simulations, we investigate how two oceanic and two atmospheric variability modes – ENSO, the Atlantic Multidecadal Variability (AMV), the North Atlantic Oscillation (NAO), and the Pacific North American (PNA) – amplify the wintertime (December–February) frequency of daily CWP extremes and associated spatial co-occurrences across the Northern Hemisphere. We find many hotspot regions where concurrent variability mode anomalies significantly amplify wintertime CWP extreme event frequencies compared to single variability modes. By examining the relationships between frequencies of wintertime CWP extremes across regions, we identify dependencies enabling extreme spatially compounding events, that is winters with many regions experiencing CWP extremes. While ENSO is the most influential variability mode for such extreme spatially compounding events, the occurrence of these events increases further when multiple modes of variability are in anomalous phases. In particular, combinations of modes increase both the number of regions and the population exposed to daily CWP extremes in the same winter. For example, combined ENSO- and NAO+ nearly doubles the number of affected regions compared to neutral conditions on average. Our analysis highlights the importance of considering the interplay between variability modes to improve risk management and adapt to the impacts of spatially compounding CWP extremes.
Keywords: Scopus_Alert_3_Octobre_2025

Keyword Analysis and Systematic Review of China’s Sponge City Policy and Flood Management Research - Lu, Yichen; Huang, Muge; Xiao, Haixin; Lu, Zekun; Xie, Mingjing; Chen, Kaida (Atmosphere, 2025)
With the acceleration of climate change and urbanisation, Chinese cities are facing increasingly severe flood risks. To address this challenge, China began implementing its sponge city policy in 2013, leveraging low-impact development, green infrastructure construction, and integrated water resource management to enhance urban resilience to floods and improve water security. This study utilises the Web of Science database as a reference, retrieving 201 relevant literature sources. From these, 61 studies closely related to China’s sponge city policy and urban flood management were selected. CiteSpace was employed to conduct keyword co-occurrence and temporal evolution analyses, comprehensively outlining the research hotspots and developmental trajectory of this field. The results indicate that research content has gradually shifted from early engineering-based flood control models to multi-objective, interdisciplinary comprehensive management, encompassing flood risk assessment, policy implementation mechanisms, integration of green infrastructure, and economic feasibility analysis. Based on this, this paper constructs an analytical framework incorporating technical, environmental, institutional, and social dimensions to integrate existing research findings, while identifying gaps in cross-scale coordination, smart management, and public participation. The research conclusions can provide valuable references for future policy optimisation and urban sustainable development.
Keywords: Scopus_Alert_3_Octobre_2025

Advancing High‐Resolution Precipitation Analysis for Operational Hydrological Applications in Australia: Data Sources, Methodologies, and Recommendations - Zhang, Yuhang; Wang, Quan J.; Frost, Andrew J.; Trewin, Blair; Pudashine, Jayaram; Velasco‐Forero, Carlos; Su, Chun‐Hsu; Villani, Vincent (WIREs Water, 2025)
ABSTRACT High‐resolution precipitation products (e.g., km‐scale and hourly) are essential for capturing extreme rainfall dynamics and improving hydrological models for flood forecasting and related applications. However, single‐source estimates—whether from gauges, radar, or satellites—suffer from inherent limitations such as sparse spatial coverage, limited observational extent, and retrieval uncertainties. Multi‐source precipitation combinations can potentially provide a more accurate estimate by using the strengths of each source. This review presents globally relevant methodologies for constructing high‐resolution precipitation datasets, with a focus on sub‐daily temporal and km‐scale spatial resolutions. Particular emphasis is placed on their applicability to the development of a new multi‐source precipitation dataset for Australia (BRAIN: Blended Rain). We first compile and assess precipitation data sources specific to Australia, particularly those readily available to the Australian Bureau of Meteorology. These include ground‐based gauge observations, radar estimates, satellite‐derived products, reanalysis datasets, and numerical weather prediction outputs. While the primary emphasis is on Australian datasets, many sources provide global coverage, enhancing the broader relevance of this work. We then review globally applicable blending techniques, highlighting methods such as weighted averaging, multifractal blending, data assimilation, and machine learning. Key challenges, including latency, quality control, spatial heterogeneity, and validation, are discussed alongside opportunities for advancing multi‐source precipitation blending. Finally, we recommend specific datasets and blending methods for trial and assessment, considering both current Australian data availability and potential future upgrades. The insights provided aim to support the development of robust high‐resolution precipitation products for hydrological applications in Australia and other regions with similar data integration challenges. This article is categorized under: Science of Water > Methods
Keywords: Scopus_Alert_3_Octobre_2025

Experimental Modeling of Three-Dimensional (3D) Partial Dam-Break Flows: A Review - Meng, Chuke; Zhao, Weiyang; Niu, Zhipan; Lin, Pengzhi (Water, 2025)
The growing threat of dam-break events, fueled by aging infrastructure and climate change, necessitates comprehensive risk management and mitigation strategies. Experimental studies on partial dam-break flows are pivotal for understanding the complex dynamics of these events, particularly in assessing flood risk and refining predictive models. This review synthesizes current experimental investigations on three-dimensional (3D) partial dam-break flows, with an emphasis on breach dynamics, wave impacts, and the role of urban structures. It highlights the challenges in capturing high-resolution 3D flow characteristics and the advancements in measurement techniques such as particle tracking velocimetry and ultrasonic distance meters. The paper discusses the integration of experimental data with numerical models to validate and improve predictive capabilities, stressing the need for continuous refinement of experimental setups and computational approaches. Gaps in the current literature, including the under-representation of irregular breach geometries and complex terrain, are identified, and future research directions are proposed to address these shortcomings. This work underscores the importance of hybrid measurement techniques and interdisciplinary collaboration to enhance dam-break modeling accuracy and flood risk mitigation.
Keywords: Scopus_Alert_3_Octobre_2025

A Systematic Review of Forest Cover for Catchment‐Scale Flood Mitigation: A Nature‐Based Solution - Herath, Prabhasri; Croke, Barry; Prinsley, Roslyn; Vaze, Jai; Pollino, Carmel (Journal of Flood Risk Management, 2025)
ABSTRACT Forest cover within catchments is a widely adopted Nature‐based Solution (NbS) for flood mitigation, offering hydrological benefits such as rainfall interception, enhanced infiltration, and reduced overland flow. Despite its recognized potential, quantitative reviews remain limited, especially at the catchment scale, with effectiveness varying by spatial scale, forest type, and climate. This review synthesizes 50 international case studies involving forest‐based NbS, selected through structured screening based on intervention type, catchment characteristics, and availability of quantitative flood metrics, and presents a detailed bibliometric and content analysis. Forest cover consistently impacts peak flow across catchments of all sizes, with a generalized linear relationship where the effect magnitude is approximately half the forest cover change. For example, a 20% increase in forest cover tends to reduce peak flow by 10% across small, medium, and large catchments. Across a range of catchment sizes, there are only minor differences in the mean peak flow reductions for different event intensities (up to 1% AEP). An asymmetric hydrological response is evident: deforestation consistently increases peak flows, whereas afforestation yields gradual reductions, which are shaped by forest maturity, spatial distribution, and modeling assumptions. Upstream distributed forest placements offer distinct hydrological benefits. These outcomes highlight the importance of conserving mature forests, preventing deforestation, and optimizing forest placement, while acknowledging potential adverse impacts on water availability during dry periods.
Keywords: Scopus_Alert_3_Octobre_2025

Sex and Gender Influences on the Impacts of Disasters: A Rapid Review of Evidence - Muñoz-Nieves, Carol; Greaves, Lorraine; Huber, Ella; Brabete, Andreea C.; Wolfson, Lindsay; Poole, Nancy (International Journal of Environmental Research and Public Health, 2025)
Both sex-related factors and gender-related factors affect the immediate and long term mental and physical health impacts of disasters, including those resulting from public health emergencies, climate-related events, and naturally occurring phenomena. These include sex-specific biological, physiological and genetic processes, mechanisms underlying reproduction, disease outcomes, and stress, immune, and trauma responses. Gendered factors such as roles, relations, identity, and institutional policies that have an impact on caregiving, occupation, gender-based violence, and access to healthcare, also influence the impacts of disasters and emergencies. Sex/gender factors interact with a range of social determinants to affect the equitability of impacts. A rapid review was conducted to examine evidence from Australia, Canada, countries from the European Union, New Zealand, the United Kingdom (UK), and the United States of America (USA) on the influence of sex- and gender-related factors in the context of disasters, such as COVID-19, earthquakes, floods, hurricanes, and wildfires. This article describes and categorizes this evidence with attention to real-world impacts of the interactions between sex, gender, and other equity related factors. Broad considerations for improving research and practices to support more sex and gender research in this area and ultimately, to improve emergency and disaster management, are discussed.
Keywords: Scopus_Alert_3_Octobre_2025

The Bioremediation of Nutrients and Heavy Metals in Watersheds: The Role of Floating Treatment Wetlands - Kumar, Nirmal; Singh, Bhupinder; Chen, Yuanze; Kafle, Abishek; Zhu, Weihang; Ray, Ram L.; Kumar, Sandeep; Shan, Xiaonan; Balan, Venkatesh (Applied Sciences, 2025)
Floating treatment wetlands (FTWs) are engineered systems that utilize floating platforms planted with aquatic vegetation to treat polluted water such as stormwater, agricultural runoff, and wastewater. FTWs have emerged as promising and environmentally sustainable solutions for water purification. This review synthesizes the current knowledge on FTW design, plant selection, and performance evaluation. It highlights key factors influencing nutrient and heavy metal removal, including the hydraulic retention time, mat thickness, and types of plant species. Recent findings on the roles of root architecture, microbial interactions, and seasonal variability in treatment efficiency are also discussed. Additionally, the review explores advanced analytical methods for monitoring water quality and assessing plant growth and contaminant uptake. Case studies from both laboratory- and field-scale experiments illustrate how variation in FTW configurations impacts pollutant removal efficiency. The review concludes by identifying critical research gaps, including the need for standardized monitoring protocols, strategies to enhance long-term performance, and the integration of FTWs with complementary treatment technologies to improve effectiveness across diverse aquatic environments.
Keywords: Scopus_Alert_3_Octobre_2025

Enhancing streamflow ensemble forecasting: evaluating pre- and post-processing strategies for a spatially distributed model - Askarinejad, Alireza; Trudel, Mélanie; Boucher, Marie-Amélie (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2025)
Keywords: Infolettre_Octobre_2025

JAX-WSPM: A GPU-accelerated parallel framework based on the JAX library for modeling water flow and solute transport in unsaturated porous media using an implicit finite element method - Toutlini, Nour-Eddine; Soulaïmani, Azzeddine; Beljadid, Abdelaziz (Computer Physics Communications, 2026)
Keywords: Infolettre_Octobre_2025

Global flood extent monitoring using SAR satellite and hydrological data: A multi-scale and multi-source approach - Zhu, Yuting; Yoshimura, Kei; Liu, Yingying; Fu, Haohuan (Journal of Hydrology, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

An integrated Bayesian hydrodynamic framework for quantifying rating curve uncertainty in design flood estimation and flood hazard mapping in a data-scarce urban area - Das, Tanmoy; Das, Subhasish (Water Research, 2026)
Keywords: Scopus_Alert_26_Septembre_2025

Short-Term Streamflow and Flood Forecasting Based on Graph Convolutional Recurrent Neural Network and Residual Error Learning - Pan, Xiyu; Mohammadi, Neda; Taylor, John E. (Journal of Computing in Civil Engineering, 2026)
Keywords: Scopus_Alert_26_Septembre_2025

Satellite-based monitoring and hazard assessment of multiple flooding types in the Haihe river Basin induced by the July 2023 extreme rainstorm - Xu, Ziteng; Yang, Wentao; Zhang, Xiya; Gu, Changjun; Shen, Lingling; Hu, Haibo (Journal of Hydrology, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

Comprehensive performance assessment of state-of-the-art metaheuristic algorithms for multi-scenario reservoir flood control optimization - Wang, Wen-chuan; Tian, Wei-can; Zang, Hongfei; Zhang, Xu-tong (Results in Engineering, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

Development of probabilistic flood forecast based on ensemble weather forecast and historical flood simulation database for resource-constrained area. Case study: Semarang City, Indonesia - Suwarman, Rusmawan; Farid, Mohammad; Abdillah, Muhammad Rais; Wahid, Ahmad Nur; Hadi, Tri Wahyu; Riawan, Edi; Fajary, Faiz Rohman; Simanjuntak, Yogi; Azizah, Siti; Sirait, Rinaldi; Adityawan, Mohammad Bagus; Roesbianto, Azman Syah Barran; et al. (Environmental Challenges, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

Integrated use of the analytical hierarchy process method for mapping areas susceptible to flooding in the urban area in a city in southwest Bahia, Brazil - Oliveira Lima, Klaus Cardoso; Ferraz, Lorena Lima; Santana, Gregório Matheus; Gomes, Ronaldo Lima; Silva Santos, Carlos Amilton; Pereira, Thais Barros; De Jesus, Raildo Mota (Journal of South American Earth Sciences, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

Critical overflow of the main combined sewer in the city of Lviv: A case study of recent extreme flooding - Matlai, Ivan; Popadiuk, Ihor; Vovk, Lesya; Zhuk, Volodymyr (Case Studies in Chemical and Environmental Engineering, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

Comparative Flood Risk Mapping Using Knowledge-Driven, Data-Driven, and Ensemble Models in a Humid Tropical River Basin in India - Senan, Chandini Padmanabha Panicker Chandr; Ajin, Rajendran Shobha; Devi, B. R. Anaswara; Rajaneesh, A.; Nagar, Jitendra K.; Sajinkumar, K. S. (Water Conservation Science and Engineering, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

Evidence of increasing coastal flood risk along mainland China from 1985 to 2050: Perspectives on climate change and urban expansion - Bian, Wanchao; Fang, Jiayi; Du, Shiqiang; Hu, Tangao (Ocean & Coastal Management, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

Quantifying uncertainties in data and model: a prediction model for extreme rainfall events with application to Beijing subway - Mu, Liang; Kang, Yurui; Yan, Zixu; Yang, Xiaobao; Zhu, Guangyu (Accident Analysis & Prevention, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

How do flood risk–socioeconomic interactions influence household income dynamics in shrinking cities of the Rust Belt in the US? - Kim, Young Eun; Lee, Jaekyung; Kim, Hyungkyoo (International Journal of Disaster Risk Reduction, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

Climate change-driven coastal flooding in the Mid Adriatic Sea and adaptation of coastal defense structures - Baldoni, Agnese; Marini, Francesco; Filomena, Giorgio; Parlani, Stefano; Brocchini, Maurizio (Estuarine, Coastal and Shelf Science, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

Advancing Flood Detection and Mapping: A Review of Earth Observation Services, 3D Data Integration, and AI-Based Techniques - Destefanis, Tommaso; Guliyeva, Sona; Boccardo, Piero; Fissore, Vanina (Remote Sensing, 2025)
Floods are among the most frequent and damaging hazards worldwide, with impacts intensified by climate change and rapid urban growth. This review analyzes how satellite-based Earth Observation (EO) technologies are evolving to meet operational needs in flood detection and water depth estimation, with a focus on the Copernicus Emergency Management Service (CEMS) as a mature and widely adopted European framework. We compare the capabilities of conventional EO datasets—optical and Synthetic Aperture Radar (SAR)—with 3D geospatial datasets such as high-resolution Digital Elevation Models (DEMs) and Light Detection and Ranging (LiDAR). While 2D EO imagery is essential for rapid surface water mapping, 3D datasets add volumetric context, enabling improved flood depth estimation and urban impact assessment. LiDAR, in particular, can capture microtopography between high-rise structures, but its operational use is constrained by cost, data availability, and update frequency. We also review how artificial intelligence (AI), including machine learning and deep learning, is enhancing automation, generalization, and near-real-time processing in flood mapping. Persistent gaps remain in model transferability, uncertainty quantification, and the integration of scarce high-resolution topographic data. We conclude by outlining a roadmap towards hybrid frameworks that combine EO observations, 3D datasets, and physics-informed AI, bridging the gap between current technological capabilities and the demands of real-world emergency management.
Keywords: Scopus_Alert_26_Septembre_2025

Digital Twin Technology for Urban Flood Risk Management: A Systematic Review of Remote Sensing Applications and Early Warning Systems - Hlal, Mohammed; Baraka Munyaka, Jean-Claude; Chenal, Jérôme; Azmi, Rida; Diop, El Bachir; Bounabi, Mariem; Ebnou Abdem, Seyid Abdellahi; Almouctar, Mohamed Adou Sidi; Adraoui, Meriem (Remote Sensing, 2025)
Digital Twin (DT) technology has emerged as a transformative tool in urban flood risk management (UFRM), enabling real-time data integration, predictive modeling, and decision support. This systematic review synthesizes existing literature to evaluate the scientific impact, technological advancements, and practical applications of DTs in UFRM. Using the PRISMA 2020 framework, we retrieved 1085 records (Scopus = 85; Web of Science = 1000), merged and deduplicated them using DOI and fuzzy-matched titles, screened titles/abstracts, and assessed full texts. This process yielded 85 unique peer-reviewed studies published between 2018 and 2025. Key findings highlight the role of remote sensing (e.g., satellite imagery, IoT sensors) in enhancing DT accuracy, the integration of machine learning for predictive analytics, and case studies demonstrating reduced flood response times by up to 40%. Challenges such as data interoperability and computational demands are discussed, alongside future directions for scalable, AI-driven DT frameworks. This review identifies key technical and governance challenges while recommending the development of modular, AI-driven DT frameworks, particularly tailored for resource-constrained regions.
Keywords: Scopus_Alert_26_Septembre_2025

Enhancing Preparedness and Response to Flood Disasters: A Scoping Review of Training Activities for Response Staff - Kokoç, Mehmet; Şimşek, Perihan; Gündüz, Abdülkadir; Akyıldız, Salih (Disaster Medicine and Public Health Preparedness, 2025)
Abstract Objective This study examines the scope and trends of empirical research on training activities for flood disaster response teams. Methods A scoping review, adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines, was conducted in June 2024 across four electronic databases and grey literature. The analysis included experimental and quasi-experimental studies published since 2005. An initial pool of 1193 studies was identified, 18 met the eligibility criteria and were included in the final analysis. Results These studies revealed three key themes: 1) evaluation and improvement of operational procedures, 2) preparation of response teams, and 3) management of health-related issues. Conclusion The results highlight the limited availability of empirical evidence in this area, reflecting the relatively small number of studies focusing specifically on training activities for flood disaster response teams. However, research in this field has shown growth since 2010, with a notable integration of educational technologies in most studies. Key training topics include psychological first aid and the evaluation of operational plans. Given the increasing frequency and severity of flood disasters due to global warming, further research is essential to develop and implement effective training programs, enabling response teams to address such emergencies more efficiently and comprehensively.
Keywords: Scopus_Alert_26_Septembre_2025

Towards wildfire risk reduction goals and targets for Europe – Opportunities and challenges - Berchtold, C.; Petersen, K.; Kaskara, M.; Pettinari, M.L.; Vinders, J.; Schlierkamp, J.; Kalapodis, N.; Sakkas, G.; Brunet, P.; Soldatos, J.; Lazarou, A.; Casciano, D.; et al. (Climate Risk Management, 2025)
Keywords: Scopus_Alert_26_Septembre_2025

Nature-Based Solutions for Urban Drainage: A Systematic Review of Sizing and Monitoring Methods - Cansian, André Ricardo; Guzmán, Diego A.; Rosa, Altair; De Toledo Machado, Juliana (Water, 2025)
Urban areas face escalating hydrological risks due to climate change, urban sprawl, and aging stormwater infrastructures. In this context, Nature-Based Solutions (NbSs), especially Sustainable Urban Drainage Systems (SUDSs), have emerged as viable strategies to enhance water resilience and sustainability. However, the literature still lacks standardized and scalable methodologies for their design and performance monitoring. This study conducts a systematic review following the PRISMA protocol, combined with bibliometric and co-occurrence analyses, to identify prevailing approaches in the sizing and monitoring of NbS-based SUDSs. Based on the peer-reviewed literature indexed in Scopus and Web of Science from 2020 to 2024, the findings reveal an increasing integration of hydrological modeling with artificial intelligence, remote sensing, and IoT-based real-time monitoring. Despite this progress, challenges remain in methodology validation, data availability, and system adaptability. The review underscores the need for hybrid, context-sensitive frameworks that integrate empirical and simulated data to support decision-making in urban drainage planning and management.
Keywords: Scopus_Alert_26_Septembre_2025

Network Governance: What Two Decades of Social and Institutional Network Research Tell Us About Flood Risk Management - Ziga‐Abortta, Fafali R.; Espinosa, Julio César Millán; Ziervogel, Gina; Kruse, Sylvia (WIREs Water, 2025)
ABSTRACT Despite increasing scholarly attention to flood risk management (FRM), there remains limited systematic understanding of how network governance arrangements influence FRM outcomes. This knowledge gap is particularly critical given the frequency and severity of floods, causing significant socio‐economic and environmental damages globally. Through a systematic literature review analyzing 38 peer‐reviewed publications from 2000 to 2023, this paper investigates network governance in FRM using a three‐component analytical framework examining actor constellations, operational activities, and governance outcomes. Our analysis explores the nature of network actor constellations in FRM research, the exchanges characterizing their operational activities, and the resultant governance outcomes that emerge from their interactions. The findings identify distinct network configurations: formal state agencies at different governance scales, informal local networks and bottom‐up initiatives, and hybrid constellations incorporating both state and non‐state actors. Operational activities are shaped by complex interdependencies including altruistic support, resource exchanges, knowledge flows, power dynamics, formal collaborations, and trust‐based sociability. Our results reveal both desired outcomes, such as social learning and innovation, and undesired outcomes stemming from structural weaknesses and pragmatic constraints. For improving FRM practice and governance outcomes, we suggest, where possible, shifting more responsibility to highly effective non‐state actors, managing negative interdependencies, and leveraging network governance throughout FRM phases. Our findings provide practical guidance for policymakers and practitioners for optimizing FRM governance arrangements while contributing theoretically to understanding how different network types influence flood resilience outcomes across developed and developing contexts. This article is categorized under: Human Water > Water Governance
Keywords: Scopus_Alert_26_Septembre_2025

Understanding South Africa’s Flood Vulnerabilities and Resilience Pathways: A Comprehensive Overview - Byaruhanga, Nicholas; Kibirige, Daniel; Mkhonta, Glen (Water, 2025)
This review examines South Africa’s escalating flood vulnerability through a synthesis of over 80 peer-reviewed articles, historical records, policy reports, and case studies. Using a PRISMA-guided analysis, the study identifies key climatic drivers, including extreme rainfall from tropical–temperate interactions, cut-off lows, and La Niña conditions that interact with structural weaknesses such as inadequate drainage, poorly maintained stormwater systems, and rapid urban expansion. Apartheid-era spatial planning has further entrenched risk by locating marginalised communities in floodplains. Governance failures like weak disaster risk reduction (DRR) policies, fragmented institutional coordination, and insufficient early warning systems intensify flood vulnerabilities. Catastrophic events in KwaZulu-Natal (KZN) and the Western Cape (WC) illustrate the consequences exemplified by the April 2022 KZN floods alone, which caused over 450 deaths, displaced more than 40,000 people, and generated damages exceeding ZAR 17 billion. Nationally, more than 1500 flood-related fatalities have been documented in the past two decades. Emerging resilience pathways include ecosystem-based adaptation, green infrastructure, participatory governance, integration of Indigenous knowledge, improved hydrological forecasting, and stricter land-use enforcement. These approaches can simultaneously reduce physical risks and address entrenched socio-economic inequalities. However, significant gaps remain in spatial flood modelling, gender-sensitive responses, urban–rural disparities, and policy implementation. The review concludes that South Africa urgently requires integrated, multi-scalar strategies that combine scientific innovation, policy reform, and community-based action. Embedding these insights into disaster management policy and planning is essential to curb escalating losses and build long-term resilience in the face of climate change.
Keywords: Scopus_Alert_26_Septembre_2025

Impacts of a Reduced AMOC on the South America Mean Climate and Extremes - Meccia, Virna L.; Blázquez, Josefina (Journal of Geophysical Research: Atmospheres, 2025)
Abstract The Atlantic meridional overturning circulation (AMOC) plays a crucial role in regulating global and regional climate by distributing heat meridionally across the planet. Future projections indicate a weakening of the AMOC in response to increased greenhouse gas concentrations. In this study, we investigate the impact of AMOC weakening on South America's mean climate, as well as temperature and precipitation extremes. We analyze targeted sensitivity experiments using the EC‐Earth3 climate model. Our findings reveal that AMOC weakening induces cooling and wetting in the tropics of South America, contrasted by warming and dryness in the extratropics. This pattern weakens the meridional temperature gradient, shifts the intertropical convergence zone and the high‐latitude winter and summer jets southward, and reduces midlatitude storm tracks, particularly in austral winter. We analyze extreme events in two representative regions—La Plata Basin and northeast Brazil—which exhibit contrasting responses. In La Plata Basin, summer heat waves become more frequent, intense, and prolonged, while winter cold spells occur more frequently but with decreased intensity and duration when the AMOC reduces. In contrast, northeast Brazil experiences an increase in the frequency and intensity of heat waves, while cold spells become less frequent but more intense. Extreme precipitation events weaken in the La Plata Basin but intensify in northeast Brazil in both seasons under AMOC weakening. Some of these climate impacts may exacerbate global warming effects, while others may partially offset them. These findings underscore the critical need to refine climate models' representation of AMOC dynamics to improve predictions of future climate scenarios. , Plain Language Summary The Atlantic meridional overturning circulation (AMOC) helps to regulate the Earth's climate by transporting heat around the globe. Scientists expect it to weaken in the future due to global warming. This study looks at how a weaker AMOC could affect South America's climate, including temperature and rainfall extremes. Using a climate model, the researchers found that a weaker AMOC would make tropical South America cooler and wetter, while the extratropical regions would get warmer and drier. This change is associated with modifications in weather patterns like jet streams and storm tracks. They focused on two important regions: the La Plata Basin and northeast Brazil to analyze extreme events. In the La Plata Basin, summers would have more intense and longer‐lasting heat waves, while winters would have more frequent but milder cold spells. Northeast Brazil, on the other hand, would see stronger and more frequent heat waves, and less frequent but harsher cold spells. Rainfall extremes would decrease in the La Plata Basin but increase in northeast Brazil. Some of these changes could make global warming amplificated, while others might ease its effects a bit. The study highlights the importance of improving how climate models simulate AMOC to better predict future climate changes. , Key Points The Atlantic meridional overturning circulation is projected to weaken, and this affects the South America mean climate and extreme events A weaker AMOC would induce cooling and wetting in tropical South America, whereas warming and drying in the extratropics Some climate impacts of a weakened AMOC in South America may amplify the effects of global warming, while others could counteract them
Keywords: Scopus_Alert_26_Septembre_2025

Comparison of Factors of Spatiotemporal Variability of 7-Day Low-Flow Timing in Southern Quebec - Assani, Ali Arkamose (Atmosphere, 2025)
The objective of this article is to analyze the impacts of climatic, physiographic, and land use/cover factors on the spatiotemporal variability of 7-day low-flow occurrence dates for 17 rivers during the period 1950–2023 in winter and summer in southern Quebec. Regarding spatial variability, correlation analysis revealed that these occurrence dates are primarily negatively correlated with agricultural surface area (early occurrence) during both seasons. In winter, they are also negatively correlated with total rainfall and daily mean maximum temperatures, but positively correlated with forest area and mean watershed slopes. Regarding temporal variability, the application of three Mann–Kendall tests showed that in summer, 7-day low flows tend to occur late in the season due to increased rainfall, particularly in the most agricultural watersheds. In contrast, in winter, very few significant changes were observed in the long-term trend of the analyzed hydrological series. Correlation analysis using redundancy analysis between eight climate indices and the occurrence dates of 7-day low flows showed that in summer, these dates are positively correlated with the global warming climate index, while they are not correlated with any climate index in winter. This study demonstrated that the spatiotemporal variability of the occurrence dates and magnitude of 7-day low flows are not influenced by the same factors in southern Quebec, except for the global warming climate index in summer. Finally, this study shows that the timing is much less sensitive to changes in climate change than the magnitude of low flows in southern Quebec.
Keywords: Infolettre_Octobre_2025

Prediction of flood susceptibility in an inter-fluvial region of Northern India using machine learning algorithms - Ghosh, Arijit; Siddiqui, Azizur Rahman (Natural Hazards Research, 2024)
Keywords: Scopus_Alert_19_Septembre_2025

From vulnerability to resilience: Addressing the causes, impacts, and solutions for recurrent flash floods in the Philippines - Rivera, Alice T.; Dela Vega, Jim Boy G. (Tropical Cyclone Research and Review, 2025)
Keywords: Scopus_Alert_19_Septembre_2025

How Responsive Are Mortgage Lending Conditions to Flood Risk? The Case of the Netherlands - Götz, Laura Naomi; Mager, Ferdinand; Zietz, Joachim (European Financial Management, 2025)
ABSTRACT We study the link between flood risk and mortgage lending in the Netherlands, a country where approximately 60% of the population resides in flood‐prone areas. Using over 100,000 securitised mortgages issued from 2013 to 2023, our study concludes that credit terms are indistinguishable between areas with and without flood risk. When we use the 2021 river flood disaster in a diff‐in‐diff setting, our results suggest that lenders temporarily (for about 6 months) raised interest premiums and partially reduced LTVs. It appears that regulatory mandates are needed if central banks want commercial banks to price climate risk into their lending.
Keywords: Scopus_Alert_19_Septembre_2025

NLP-driven crowdsourcing for urban flood monitoring: insights from mumbai - Navalkar, Aniket; Tripathy, Shrabani S.; Gupta, Mayank; Basu, Sanghita; Tripathy, Puja; Banerjee, Archismita; Sekharan, Sheeba; Murtugudde, Raghu; Ghosh, Subimal (Sustainable Cities and Society, 2025)
Keywords: Scopus_Alert_19_Septembre_2025

Assess the impacts of climatic change and human activities on streamflow and floods by using a hybrid-physics-data (HPD) model: A case study in the Lancang-Mekong River Basin - Liu, Binxiao; Yun, Xiaobo; Pan, Baoxiang; Xu, Ximeng; Gaffney, Paul P.J.; Lu, Hui; Luo, Lifeng; Sun, Gaohu; Tang, Qiuhong (Journal of Hydrology: Regional Studies, 2025)
Keywords: Scopus_Alert_19_Septembre_2025

A multi-scenario framework for quantifying flood hazard and exposure accounting for runoff-driven uncertainty in global flood models - Parmar, Jayesh; Karmakar, Subhankar (Science of The Total Environment, 2025)
Keywords: Scopus_Alert_19_Septembre_2025

Assessment of flood risk using integrated GIS and analytic hierarchy process in the Mekerra basin, Northwestern Algeria - Berrezel, Yacine Abdelbaset; Abdelbaki, Cherifa; Megnounif, Abdesselam; Saber, Mohamed; Benabdelkrim, Mohammed El Amin; Kumar, Navneet (Journal of African Earth Sciences, 2026)
Keywords: Scopus_Alert_19_Septembre_2025

Identifying challenges and future directions of flood hazards mitigation strategies in health facilities: a systematic literature review - Arefi, Farhad; Tavan, Asghar; Moradi, Seyed Mobin; Daneshi, Salman; Farahmandnia, Hojjat (BMC Emergency Medicine, 2025)

Climate changes and cancer risk: Key factors and emerging health threats - Sotomayor, Marina Rayciki; Campos, Aline Graciele Henriques; Filho, Altair Rodrigues Pires De Paula; Goulart, Ana Carolina Aredes; Vacario, Beatriz Geovana Leite; Orrutéa, Julia Fernandes Gois; Valentim, Juliana Maria Bitencourt De Morais; Fagundes, Tatiane Renata; Gaboardi, Shaiane Carla; Panis, Carolina (Hygiene and Environmental Health Advances, 2025)

Identifying challenges and future directions of flood hazards mitigation strategies in health facilities: a systematic literature review - Arefi, Farhad; Tavan, Asghar; Moradi, Seyed Mobin; Daneshi, Salman; Farahmandnia, Hojjat (BMC Emergency Medicine, 2025)

Multi-objective optimization of nature-based solutions in urban stormwater management: A scoping review - Bista, A.; Paus, K.A.H.; Seifert-Dähnn, I. (Environmental Modelling & Software, 2025)

Identifying challenges and future directions of flood hazards mitigation strategies in health facilities: a systematic literature review - Arefi, Farhad; Tavan, Asghar; Moradi, Seyed Mobin; Daneshi, Salman; Farahmandnia, Hojjat (BMC Emergency Medicine, 2025)

Climate changes and cancer risk: Key factors and emerging health threats - Sotomayor, Marina Rayciki; Campos, Aline Graciele Henriques; Filho, Altair Rodrigues Pires De Paula; Goulart, Ana Carolina Aredes; Vacario, Beatriz Geovana Leite; Orrutéa, Julia Fernandes Gois; Valentim, Juliana Maria Bitencourt De Morais; Fagundes, Tatiane Renata; Gaboardi, Shaiane Carla; Panis, Carolina (Hygiene and Environmental Health Advances, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

Multi-objective optimization of nature-based solutions in urban stormwater management: A scoping review - Bista, A.; Paus, K.A.H.; Seifert-Dähnn, I. (Environmental Modelling & Software, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

Natural Disasters and Rehabilitation: Post‐Disaster Aid, Corruption, Misallocation, and Mistargeting - Ahmad, Muhammad Irshad; Shen, Qiong; Boota, Muhammad Waseem; Liu, Ruifeng; Ma, Hengyun (Sustainable Development, 2025)
ABSTRACT The increasing frequency of natural disasters, such as floods, droughts, and tsunamis, has made vulnerable communities less resilient, pushing them toward long‐term poverty and food insecurity. Effective post‐disaster rehabilitation is critical to restoring livelihoods, infrastructure, and food security. However, challenges such as corruption, misallocation, and mistargeting undermine post‐disaster aid programs. This study systematically reviews 86 peer‐reviewed articles (1990–2023) using the preferred reporting items for systematic reviews and meta‐analyses (PRISMA) protocol to investigate aid inefficiencies in disaster recovery. The findings reveal that aid often fails to reach the most affected communities, being diverted to unaffected areas due to political influence and local elites, exacerbating inequalities. Corruption further hampers institutional performance and long‐term disaster resilience efforts. The study calls for transparent, accountable, and inclusive strategies for aid distribution, aligning with SDG 10 (reduced inequalities) and SDG 11 (sustainable cities and communities). Future research should focus on gender‐sensitive strategies, local governance, and technological innovations to enhance aid transparency and effectiveness.
Keywords: Scopus_Alert_12_Septembre_2025

Identifying challenges and future directions of flood hazards mitigation strategies in health facilities: a systematic literature review - Arefi, Farhad; Tavan, Asghar; Moradi, Seyed Mobin; Daneshi, Salman; Farahmandnia, Hojjat (BMC Emergency Medicine, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

Flood inundation amplified by large-scale ground subsidence funnel under the ongoing global climate change - He, Liming; Yin, Yanzhuang; Cai, Jiuyang; Wu, Lixin; Tang, Yongliang; He, Ronghua; Qu, Zhenglin; Liu, Yu; Pei, Panke; Wang, Qiao (Communications Earth & Environment, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

The 2021 Henan flood increased citizen demand for government-led climate change adaptation in China - Shen, Shiran Victoria (Communications Earth & Environment, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

Enhancing management of flood forecasting in Southern New Jersey: a HEC-HMS model development for Maurice River and Raccoon Creek Watersheds - Chowdhury, Rumman M.; Ahn, Jeong; Torlapati, Jagadish; Jahan, Kauser (Applied Water Science, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

Quantitative assessment of exacerbating effect on urban inundation when river flood encounters heavy rainfall in an urbanized watershed - Zhang, Haijia; Liu, Jiahong; Zhou, Jinjun; Mei, Chao; Wang, Jia; Song, Tianxu (Science China Technological Sciences, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

Integrating hydrological and economic assessments of soil infiltration enhancement for urban flood resilience - Ren, Xingwei; Guo, Zeyu; Li, Qingli; Zhou, Zhengzheng; Chen, Xin; Liao, Jiajie (Science of The Total Environment, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

Enhanced spatiotemporal prediction of rainfall erosivity through flood season data integration - Qi, Fei; Wang, Yunpeng; Xu, Luyue; Liu, Xia; Zhang, Chunqiang; Fan, Zhaofei; Guo, Jiayu; Yang, Xing (CATENA, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

Predicting current habitat suitability for intermediate snail hosts of urogenital and intestinal schistosomiasis in the Lower Shire Valley floodplain of southern Malawi - Nkolokosa, Clinton; Chirombo, James; Jones, Christopher M.; Mbewe, Rex B.; Kambewa, Eggrey Aisha; Makaula, Peter; Tangena, Julie-Anne Akiko; Stothard, J. Russell (Parasites & Vectors, 2025)
Abstract Background Relating the geographical distribution of intermediate freshwater snail hosts (viz. vectors of schistosomes) to local environmental attributes offers value for understanding the epidemiological landscape of schistosomiasis transmission in a changing aquatic environment. Schistosomiasis—both urogenital and intestinal—causes significant human suffering, affecting approximately 240 million people globally and grouped within the neglected tropical disease (NTD) umbrella. This study addresses the following questions: 1. Where are the most suitable habitats for intermediate host snails in the Lower Shire Valley (LSV) in Malawi? 2. Which environmental factors are strongly associated with the geographical distribution of such snails in the LSV? Methods This paper presents the first species distribution models (SDMs) for intermediate snail hosts for urogenital and intestinal schistosomiasis in Chikwawa and Nsanje Districts, which together form the LSV). The SDMs developed for this study are ensemble machine learning approaches based on Random Forest (RF), Support Vector Machines (SVM), and multilayer perceptron (MLP) and are specific to the Bulinus africanus group and Biomphalaria pfeifferi . The former transmits urogenital schistosomiasis ( Schistosoma haematobium ), while the latter transmits intestinal schistosomiasis ( Schistosoma mansoni ). Results The SDMs reveal the following: 1) currently, Bu. africanus group not only has a wide distribution across central Chikwawa and eastern Nsanje but is also concentrated in floodplains, and the LSV has few habitats that can support Bi. pfeifferi , and 2) vegetation cover is the most important predictor of Bu. africanus group distribution, whereas precipitation variables are most important for Bi. pfeifferi in the LSV. Thus, Bu. africanus group habitat is the most dominant and abundant, while Bi. pfeifferi suitable habitat is patchy and scarce. Conclusion The distribution of suitable habitats for potential urogenital and intestinal schistosomiasis transmission across LSV is not uniform and typically non-overlapping. Understanding the spatial and temporal distributions of these snails is important for controlling and eliminating schistosomiasis. Graphical Abstract
Keywords: Scopus_Alert_12_Septembre_2025

Rapid simulation for real-time flood depth prediction using support vector machine - Kim, Beom-Jin; Kim, Minkyu; Yoo, Jaehwan; Kim, Byunghyun (Scientific Reports, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

Market-based instruments to fund nature-based solutions for flood risk management can disproportionately benefit affluent areas - Hill, Bartholomew; Marjoribanks, Tim; Moore, Harriet; Bosher, Lee; Gussy, Mark (Communications Earth & Environment, 2025)
Abstract Market-based instruments, including competitive tenders, are central to funding global environmental restoration and management projects. Recently, tenders have been utilised to fund Nature-based Solutions schemes for Natural Flood Management, with the explicit purpose of achieving co-benefits; flood management and reducing inequities. While multiple studies consider the efficacy of Nature-based Solutions for tackling inequities, no prior research has quantified whether the resource allocation for these projects has been conducted equitably. We analyse two national natural flood management programmes funded through competitive tenders in England to explore who benefits by considering the characteristics of projects, including socio-economic, geographical (e.g. rurality) and flood risk dynamics. Our results suggest that inequity occurs at both the application and funding stages of Nature-based Solutions projects for flood risk management. This reflects wider international challenges of using market-based instruments for environmental resource allocation. Competitive tenders have the potential to undermine the equitable benefits of Nature-based Solutions.
Keywords: Scopus_Alert_12_Septembre_2025

Urban growth or urban risk? Unraveling the flood paradox in Kumasi (Ghana) through the lens of natural factors and spatial decision modeling - Liwur, Stephen Biliyitorb; Tagnan, Jacob Nchagmado; Asamoah, Pearl Seyram (Journal of African Earth Sciences, 2025)
Keywords: Scopus_Alert_12_Septembre_2025

Research on Extreme Precipitation Risk Considering Physical-social-environmental Attributes - Zhang, Jianlei; Chu, Chenkun; Wang, Peng (Journal of Disaster Prevention and Mitigation Engineering, 2025)
This study aims to conduct a grid-scale extreme precipitation risk assessment in Xuanwu District, Nanjing, so as to fill the gaps in existing indicator systems and improve the precision of risk characterization. By integrating physical, social, and environmental indicators, a risk assessment framework was constructed to comprehensively represent the characteristics of extreme precipitation risk. This study applied the entropy weight method to calculate indicator weights, combined with ArcGIS technology and the K-means clustering algorithm, to analyze the spatial distribution characteristics of risk under a 100-year extreme precipitation scenario and to identify key influencing indicators across different risk levels. The results showed that extreme precipitation risk levels in Xuanwu District exhibited significant spatial heterogeneity, with an overall distribution pattern of low risk in the central area and high risk in the surrounding areas. The influence mechanisms of key indicators showed tiered response characteristics: the low-risk areas were mainly controlled by the submerged areas of urban and rural, industrial and mining, and residential lands, water body area, soil erosion level, and normalized difference vegetation index (NDVI). The medium-risk areas were influenced by the submerged areas of urban and rural, industrial and mining, residential lands, the submerged areas of forest land, emergency service response time to disaster-affected areas, soil erosion level, and NDVI. The high-risk areas were jointly dominated by the submerged areas of urban and rural, industrial and mining, residential lands, the submerged areas of forest land, and NDVI. The extremely high-risk areas were driven by three factors—the submerged areas of forest land, emergency service response time to disaster-affected areas, and the proportion of the largest patch to the landscape area. This study improves the indicator system for extreme precipitation risk assessment and clarifies the tiered response patterns of risk-driving indicators, providing a scientific basis for developing differentiated flood control strategies in Xuanwu District while offering important theoretical support for improving regional flood disaster resilience. © 2025 Editorial Office of Journal of Disaster Prevention and Mitigation Engineering. All rights reserved.
Publisher: Editorial Office of Journal of Disaster Prevention and Mitigation Engineering
Keywords: Scopus_Alert_5_Septembre_2025

Integrated hydrologic-economic modeling for urban flood risk mitigation using SWMM, HEC-RAS, and HAZUS: a case study of the Bronx river watershed, NYC - Javidi Sabbaghian, Reza; Fereshtehpour, Mohammad; Goli Hosseinabad, Mohammad Reza (Sustainable Water Resources Management, 2025)
Rapid urban expansion has significantly altered land use patterns, resulting in a decrease in pervious surface areas and a disruption of hydrologic connectivity between surface water and groundwater systems. Combined with inadequate drainage systems and poorly managed runoff, these changes have intensified urban flooding, leading to fatalities and significant infrastructure damage in many rapidly growing and climate-vulnerable urban areas around the world. This study presents an integrated economic-hydrologic model to assess the effectiveness of Low Impact Development (LID) measures—specifically permeable pavement, infiltration trenches, bio-retention cells, and rain barrels—in mitigating flood damage in the Bronx river watershed, NYC. The Storm Water Management Model (SWMM) was employed to simulate flood events and assess the effectiveness of various LIDs, applied individually and in combination, in reducing peak discharge. Flood inundation maps generated using HEC-GeoRAS were integrated with the HAZUS damage estimation model to quantify potential flood damages. A benefit-to-cost (BC) ratio was then calculated by comparing the monetary savings from reduced flood damage against the implementation costs of LID measures. Results indicate that the combined LID scenario offers the highest peak flow reduction, with permeable pavement alone reducing flow by 57%, outperforming other techniques under equal area coverage. Among all individual options, permeable pavement yields the highest cumulative BC ratio under all scenarios (4.6), whereas rain barrels are the least effective (2.6). The proposed evaluation framework highlights the importance of economic efficiency in flood mitigation planning and provides a structured foundation for informed decision-making to enhance urban resilience through LID implementation. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.
Publisher: Springer Science and Business Media Deutschland GmbH
Keywords: Scopus_Alert_5_Septembre_2025

River basin urban flood resilience: A multi-dimensional framework for risk mitigation to adaptive management and ecosystem protection under changing climate - Soomro, Shan-e-hyder; Wei, Huaibin; Boota, Muhammad Waseem; Soomro, Nishan-E-hyder; Faisal, Muhammad; Nazli, Sana; sarwari, Soraya; Shi, Xiaotao; Hu, Caihong; Guo, Jiali; Li, Yinghai (Ecological Informatics, 2025)
Study region: This study aims at the Kunhar River Basin, Pakistan, that has been facing repeated flood occurrences on a recurring basis. As the flood susceptibility of this area is high, its topographic complexity demands correct predictive modeling for strategic flood planning. Study focus: We developed a system of flood susceptibility mapping based on Geographic Information Systems (GIS), Principal Component Analysis (PCA), and Support Vector Machine (SVM) classification. Four kernel functions were applied, and the highest-performing was the Radial Basis Function (SVM-RBF). The model was validated and trained using historical flood inventories, morphometric parameters, and hydrologic variables, and feature dimensionality was reduced via PCA for increased efficiency. New hydrological insights: The SVM-RBF model recorded an AUC of 0.8341, 88.02% success, 84.97% predictability, 0.89 Kappa value, and F1-score of 0.86, all of which indicated high predictability. Error analysis yielded a PBIAS of +2.14%, indicating negligible overestimation bias but within limits acceptable in hydrological modeling. The results support the superiority of the SVM-RBF approach compared to conventional bivariate methods in modeling flood susceptibility over the complex terrain of mountains. The results can be applied in guiding evidence-based flood mitigation, land-use planning, and adaptive management in the Kunhar River Basin. © 2025 The Author(s)
Publisher: Elsevier B.V.
Keywords: Scopus_Alert_5_Septembre_2025

Integrative strategies for urban flood resilience and risk: A meta-analysis of policy, infrastructural, and ecosystem-based interventions - Wang, Shitao; Bi, Xuehao (Physics and Chemistry of the Earth, 2025)
Urban flooding, intensified by climate change and rapid urbanization, demands robust and operationally effective resilience strategies. However, empirical evidence on the comparative effectiveness of such strategies remains limited. This study presents the first meta-analytic synthesis evaluating urban flood resilience interventions across institutional, infrastructural, and socio-ecological domains. By synthesizing data from 29 peer-reviewed studies (2000–2024), this study applies standardized effect sizes (Cohen's d) and meta-regression models to assess the effectiveness of different strategies. Results reveal a substantial overall effect (pooled d = 2.96, 95 % CI: [1.92, 3.99]) with high heterogeneity (I2 = 93.8 %). Institutional mechanisms, such as policy coordination, regulatory frameworks, and risk governance, consistently show the strongest and most statistically significant impacts (d ≈ 2.96). Low Impact Development (LID) demonstrates limited, non-significant effects (d ≈ 0.08). The study introduces a novel hierarchical resilience framework spanning different dimensions and establishes an evidence-based typology of urban flood resilience strategies. These findings highlight the importance of integrated, multi-level governance and context-specific planning in enhancing urban flood resilience. The study findings provides critical insights for implementing resilience strategies in flood-prone urban areas, and support the formulation of adaptive and sustainable urban policies. © 2025
Publisher: Elsevier Ltd
Keywords: Scopus_Alert_5_Septembre_2025

Increasing tidal inundation does not buffer heat stress effects: Implications for benthic ecosystem responses to climate change - Thomas, Simon D.; Bartl, Ines; Thrush, Simon F. (Journal of Experimental Marine Biology and Ecology, 2025)
Intertidal soft sediments are on the frontline of climate change effects, subject to increasing atmospheric heatwave intensity alongside rising sea levels. Longer inundation periods can keep sediments more saturated with water, potentially providing a thermal buffer against atmospheric heatwaves and creating refugia for resident communities and the ecosystem functions they produce. To assess this effect, we set up a field experiment to simulate a heat stress event along a gradient of inundation time on an intertidal flat using open top heat chambers. We examined how heat stress and inundation interact to influence sediment temperature, and how this in turn affects CO₂ flux, a proxy for ecosystem metabolism, and its relationship to key ecological covariates. We found that in ambient conditions, maximum sediment temperature decreased with increasing inundation. However, under heat stress, this relationship reversed, with maximum sediment temperature increasing with inundation, suggesting that more saturated sediments conduct heat more efficiently and promote higher temperatures under prolonged heat stress. Despite this temperature anomaly, the effect of heat stress on ecosystem metabolism remained consistent across the inundation gradient, indicating that increasing inundation time does not provide refugia from heat stress, nor does the elevated temperature anomaly amplify metabolic responses. Resilience mechanisms such as functional redundancy and compensatory interactions in sediment communities may have buffered against temperature variability, therefore maintaining function under heat stress. Our findings highlight the complex interactions between heat stress and inundation and suggest that sea level rise will not provide straightforward thermal refugia for soft sediment ecosystem function. © 2025 The Authors
Publisher: Elsevier B.V.
Keywords: Scopus_Alert_5_Septembre_2025

Enhancing the hydrological performance of Low Impact Development infrastructure through earthworm activity and vegetation dynamics for mitigating urban flooding - Lhamidi, Khalil; El Khattabi, Jamal (Ecological Engineering, 2025)
Urban soil sealing and anthropogenic activities, combined with the increasing intensity of rainfall due to climate change, is a threat to urban environments, exacerbating flood risks. To assess these challenges, Low Impact Development strategies, based on Nature-based solutions, are a key solution to mitigate urban flooding. To enhance the hydrological performance of LID infrastructure, and to meet the guideline requirements related to emptying time, specifically in low hydraulic conductivity soils, earthworm activity and vegetation dynamics can play a major role. The ETAGEP experimental site was built to study to address those challenges. 12 swales (10 m2 infiltration area for each swale) were monitored to evaluate the impact of earthworm activity (A. caliginosa and L. terrestris) and vegetation dynamics (Rye Grass, Petasites hybridus and Salix alba) to enhance the hydrological performance. The infiltration rate of the swales evolved in a differentiated manner, with an increase of 16.1 % to 310.8 % and draining times decrease of 13.9 % to 75.7, depending on initial soil hydro-physical properties and the impervious areas of the catchment which influence runoff volumes. The simulations on SWMM software showed similar results, with an enhancement of the hydraulic conductivity of N6 swales (60 m2 total catchment area) increasing from 18 mm h−1 to 25 mm h−1, and a reduction of drawdown time by 24.4 % (N6) and 20.8 % (N11–110 m2 active surface). A simulated storm event of 44.8 mm resulted in an overflow of 2.12 m3 for the N11 swale configuration, while no overflow was observed for N6. These results highlight the ecosystem services of earthworms for a sustainable stormwater management in urban environments, enhancing the hydrological performance of LID infrastructures and reducing therefore flood risks and limiting pressure on drainage network. © 2025 The Author(s)
Publisher: Elsevier B.V.
Keywords: Scopus_Alert_5_Septembre_2025

Predictive Modeling and Strategic Planning for Urban Flood Risk Mitigation - Mitali, Patel; Patel, Nishit; Modi, Kshitish; Patel, Samir (Commun. Comput. Info. Sci., 2026)
Urban flooding threatens Indian cities and is made worse by rapid urbanization, climate change and poor infrastructure. Severe flooding occurred in cities such as Mumbai, Chennai and Ahmedabad. This has caused huge economic losses and displacement. This study addresses the limitations of traditional flood forecasting methods. It has to contend with the complex dynamics of urban flooding. We offer a deep learning approach which uses the network Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to improve flood risk prediction. Our CNN-LSTM model combines spatial data (water table, topography) and temporal data (historical model) to classify flood risk as low or high. This method includes collecting data pre-processing (MinMaxScaler, LabelEncoder) Modeling, Training and Evaluation. The results demonstrate the accuracy of flood risk predictions and provide insights into flexible strategies for urban flood management. This research highlights the role of data-driven approaches in improving urban planning to reduce flood risk in high-risk areas. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
Journal Abbreviation: Commun. Comput. Info. Sci.
Keywords: Scopus_Alert_5_Septembre_2025

Analysis of rainfall disaster-causing factors weight and hazard assessment of non-typhoon rainstorms in Fujian Province - Lin, Xin; Yang, Kaijia; Zhang, Rongyan (Torrential Rain and Disasters, 2025)
Conducting an importance analysis of rainfall disaster-causing factors and hazard assessment is crucial for preventing rainstorm disasters. Based on precipitation observation data from 66 national meteorological stations from 1981 to 2020 and 1,038 provincial meteorological stations from 2010 to 2020 in Fujian Province, the correlation coefficient weighting method was used to calculate and compare the weight coefficients of the rainfall disaster-causing factors of non-typhoon rainstorms in 5 seasons (early spring, rainy season, summer, autumn and winter) and typhoon rainstorms in 3 periods (early, common and late). Then, the comprehensive index method was employed to conduct the hazard assessment and validation of non-typhoon rainstorms. The results are as follows: (1) The spatial extent of heavy precipitation is the primary factor in causing disasters for non-typhoon rainstorms in all seasons and for late typhoon rainstorms. Short-duration intense precipitation is the major factor causing disasters in summer non-typhoon rainstorms, early typhoon rainstorms, and common typhoon rainstorms. (2) The results of the disaster risk assessment of non-typhoon rainstorms show that the hazard of the non-typhoon rainstorm event from June 14 to 26, 2010 was the highest. There is an overall spatial distribution indicating a pattern of being high in the east and west while low in the central area, with two contiguous high and very high risk areas in the northwest inland and southeast coastal areas, respectively. (3) The spatial distributions of disaster risk for three historical non-typhoon rainstorm events from 2010 to 2020 obtained from the non-typhoon rainstorm disaster assessment model are basically consistent with the disaster situation. © Editorial Office of Torrential Rain and Disasters. OA under CC BY−NC−ND 4.0.
Publisher: Editorial Office of Torrential Rain and Disasters
Keywords: Scopus_Alert_5_Septembre_2025

Impact of Land Use Patterns on Flood Risk in the Chang-Zhu-Tan Urban Agglomeration, China - Zhang, Ting; Wu, Kai; Wang, Xiulian; Li, Xinai; Li, Long; Chen, Longqian (Remote Sensing, 2025)
Flood risk assessment is an effective tool for disaster prevention and mitigation. As land use is a key factor influencing flood disasters, studying the impact of different land use patterns on flood risk is crucial. This study evaluates flood risk in the Chang-Zhu-Tan (CZT) urban agglomeration by selecting 17 socioeconomic and natural environmental factors within a risk assessment framework encompassing hazard, exposure, vulnerability, and resilience. Additionally, the Patch-Generating Land Use Simulation (PLUS) and multilayer perceptron (MLP)/Bayesian network (BN) models were coupled to predict flood risks under three future land use scenarios: natural development, urban construction, and ecological protection. This integrated modeling framework combines MLP’s high-precision nonlinear fitting with BN’s probabilistic inference, effectively mitigating prediction uncertainty in traditional single-model approaches while preserving predictive accuracy and enhancing causal interpretability. The results indicate that high-risk flood zones are predominantly concentrated along the Xiang River, while medium-high- and medium-risk areas are mainly distributed on the periphery of high-risk zones, exhibiting a gradient decline. Low-risk areas are scattered in mountainous regions far from socioeconomic activities. Simulating future land use using the PLUS model with a Kappa coefficient of 0.78 and an overall accuracy of 0.87. Under all future scenarios, cropland decreases while construction land increases. Forestland decreases in all scenarios except for ecological protection, where it expands. In future risk predictions, the MLP model achieved a high accuracy of 97.83%, while the BN model reached 87.14%. Both models consistently indicated that the flood risk was minimized under the ecological protection scenario and maximized under the urban construction scenario. Therefore, adopting ecological protection measures can effectively mitigate flood risks, offering valuable guidance for future disaster prevention and mitigation strategies. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Significant Attribution of Urbanization to Triggering Extreme Rainfall in the Urban Core—A Case of Dallas–Fort Worth in North Texas - Ahmad, Junaid; Eisma, Jessica A.; Sajjad, Muhammad (Urban Science, 2025)
While rainfall occurs for several reasons, climate change and urbanization influence its frequency and geographical disparities. Although recent research suggests that urbanization may lead to increased rainfall, insights into how urbanization can trigger rainfall remain limited. We selected the Dallas–Fort Worth (DFW) metroplex, which has minimal orographic and coastal influences, to analyze the urban impact on rainfall. DFW was divided into 256 equal grids (10 km × 10 km) and grouped into four clusters using K-means clustering based on the urbanization ratio. Using Multi-Sensor Precipitation Estimator data (with a spatial resolution of 4 km), we examined rainfall exceeding the 95th percentile (i.e., extreme rainfall) on low synoptic days to highlight localized effects. The urban heat island (UHI) effect was estimated based on the average temperature difference between the urban core and the other three non-urban clusters. Multiple rainfall events were monitored on an hourly basis. Potential linkages between urbanization, the UHI, extreme rainfall, wind speed, wind direction, convective inhibition, and convective available potential energy were evaluated. An intense UHI within the DFW area triggered a tornado, resulting in maximum rainfall in the urban core area under high wind speeds and a dominant wind direction. Our findings further clarify the role of urbanization in generating extreme rainfall events, which is essential for developing better policies for urban planning in response to intensifying extreme events due to climate change. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

An Attention-Enhanced Bivariate AI Model for Joint Prediction of Urban Flood Susceptibility and Inundation Depth - Le, Thuan Thanh; Vo, Tuong Quang; Kim, Jongho (Mathematics, 2025)
This study presents a novel bivariate-output deep learning framework based on LeNet-5 for the simultaneous prediction of urban flood susceptibility and inundation depth in Seoul, South Korea. Unlike previous studies that relied on single-output models, the proposed approach jointly learns classification and regression targets through a shared feature extraction structure, enhancing consistency and generalization. Among six tested architectures, the Le5SD_CBAM model—integrating a Convolutional Block Attention Module (CBAM)—achieved the best performance, with 83% accuracy, an Area Under the ROC Curve (AUC) of 0.91 for flood susceptibility classification, and a mean absolute error (MAE) of 0.12 m and root mean squared error (RMSE) of 0.18 m for depth estimation. The model’s spatial predictions aligned well with hydrological principles and past flood records, accurately identifying low-lying flood-prone zones and capturing localized inundation patterns influenced by infrastructure and micro-topography. Importantly, it detected spatial mismatches between susceptibility and depth, demonstrating the benefit of joint modeling. Variable importance analysis highlighted elevation as the dominant predictor, while distances to roads, rivers, and drainage systems were also key contributors. In contrast, secondary terrain attributes had limited influence, indicating that urban infrastructure has significantly altered natural flood flow dynamics. Although the model lacks dynamic forcings such as rainfall and upstream inflows, it remains a valuable tool for flood risk mapping in data-scarce settings. The bivariate-output framework improves computational efficiency and internal coherence compared to separate single-task models, supporting its integration into urban flood management and planning systems. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Enhanced Urban Flood Hazard Assessment by Stochastic Event Catalog - Yan, Haochen; Guo, Kaihua; Guan, Mingfu (Water Resources Research, 2025)
Assessing flood severity in urban areas is a pivotal task for urban resilience and climate adaptation. However, the lack of in situ measurements hinders direct spatial estimation of flood return periods, while conventional assumptions about rainstorm-flood consistency introduce significant uncertainties due to rainstorm spatiotemporal variability (STV). This study proposes a novel framework that utilizes multivariate frequency analysis of flood variables at the street level (50 m) through a stochastic rainstorm-flood event catalog. The rainstorm events in the catalog are generated by a random field generator and resampled to match the joint distribution of STV variables consistent with radar observations. Urban flood processes are then simulated by a hydrodynamic model for flood hazard assessment (FHA). We applied the framework to a rural-urban watershed using 3,000 cases randomly resampled from the catalog. Results reveal that inundation characteristics respond more rapidly to increasing rainfall intensities than downstream flood peaks, particularly during the early stages of rainstorms. The complex joint probability structures of rainstorm severity and STV variables obscure the mechanistic control of individual factors on flood response. A significant underestimation of street-level flood hazards occurs when assuming the same return periods (RPs) as those for watershed-level hazards. The inconsistency between rainstorm and flood severities results in widespread underestimation of street-level flood hazards in upstream regions, while traditional storm designs that neglect STV lead to overestimations in mid- and downstream areas. This study highlights the complex probabilistic behavior of spatially distributed flood hazards across multiple scales, enhancing the insights and methodologies for street-level FHA. © 2025 The Author(s).
Publisher: John Wiley and Sons Inc
Keywords: Scopus_Alert_5_Septembre_2025

Land Subsidence and Coastal Flood Impact Scenarios Based on Remote Sensing in Selangor, Malaysia - Batmanathan, Navakanesh M.; Pereira, Joy Jacqueline; Shah, Afroz Ahmad; Muhamad, Nurfashareena; Sian, Lim Choun (Journal of Marine Science and Engineering, 2025)
This study uses remote sensing data to assess susceptibility to hazards, which are then validated to model impact scenarios for land subsidence and coastal flooding in the Integrated Coastal Zone Management (ICZM) of Selangor, Malaysia, to support decision-making in urban planning and land management. Land subsidence and coastal floods affect a major proportion of the population in the ICZM, with subsidence being significant contributing factors, but information on the extent of susceptible areas, monitoring, and wide-area coverage is limited. Land subsidence distribution is demarcated using Interferometric Synthetic Aperture Radar (InSAR) time-series data (2015–2022), and integrated with coastal flood susceptibility derived from Analytic Hierarchy Process (AHP)-based weights to model impacts on land cover. Results indicate maximum subsidence rates of 46 mm/year (descending orbit) and 61 mm/year (ascending orbit); reflecting a gradual increase in subsidence trends with an average rate of 13 mm/year. In the worst-case scenario, within the ICZM area of 2262 km2, nearly 12% of the total built-up land cover with the highest population density is exposed to land subsidence, while exposure to coastal floods is relatively larger, covering nearly 34% of the built-up area. Almost 27% of the built-up area is exposed to the combined effects of both land subsidence and coastal floods, under present sea level conditions, with increasing risks of coastal floods over 2040, 2050 and 2100, due to both combinations. This research prioritizes areas for further study and provides a scientific foundation for resilience strategies aimed at ensuring sustainable coastal development within the ICZM. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Flood Exposure Assessment of Railway Infrastructure: A Case Study for Iowa - Alabbad, Yazeed; Cikmaz, Atiye Beyza; Yildirim, Enes; Demir, Ibrahim (Applied Sciences (Switzerland), 2025)
Floods pose a substantial risk to human well-being. These risks encompass economic losses, infrastructural damage, disruption of daily life, and potential loss of life. This study presents a state-wide and county-level spatial exposure assessment of the Iowa railway network, emphasizing the resilience and reliability of essential services during such disasters. In the United States, the railway network is vital for the distribution of goods and services. This research specifically targets the railway network in Iowa, a state where the impact of flooding on railways has not been extensively studied. We employ comprehensive GIS analysis to assess the vulnerability of the railway network, bridges, rail crossings, and facilities under 100- and 500-year flood scenarios at the state level. Additionally, we conducted a detailed investigation into the most flood-affected counties, focusing on the susceptibility of railway bridges. Our state-wide analysis reveals that, in a 100-year flood scenario, up to 9% of railroads, 8% of rail crossings, 58% of bridges, and 6% of facilities are impacted. In a 500-year flood scenario, these figures increase to 16%, 14%, 61%, and 13%, respectively. Furthermore, our secondary analysis using flood depth maps indicates that approximately half of the railway bridges in the flood zones of the studied counties could become non-functional in both flood scenarios. These findings are crucial for developing effective disaster risk management plans and strategies, ensuring adequate preparedness for the impacts of flooding on railway infrastructure. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

AI-Enhanced Remote Sensing of Land Transformations for Climate-Related Financial Risk Assessment in Housing Markets: A Review - Zhang, Chuanrong; Li, Xinba (Land, 2025)
Amid accelerating climate change, climate-related hazards—such as floods, wildfires, hurricanes, and sea-level rise—increasingly drive land transformations and pose growing risks to housing markets by affecting property valuations, insurance availability, mortgage performance, and broader financial stability. This review synthesizes recent progress in two distinct domains and their linkage: (1) assessing climate-related financial risks in housing markets, and (2) applying AI-driven remote sensing for hazard detection and land transformation monitoring. While both areas have advanced significantly, important limitations remain. Existing housing finance studies often rely on static models and coarse spatial data, lacking integration with real-time environmental information, thereby reducing their predictive power and policy relevance. In parallel, remote sensing studies using AI primarily focus on detecting physical hazards and land surface changes, yet rarely connect these spatial transformations to financial outcomes. To address these gaps, this review proposes an integrative framework that combines AI-enhanced remote sensing technologies with financial econometric modeling to improve the accuracy, timeliness, and policy relevance of climate-related risk assessment in housing markets. By bridging environmental hazard data—including land-based indicators of exposure and damage—with financial indicators, the framework enables more granular, dynamic, and equitable assessments than conventional approaches. Nonetheless, its implementation faces technical and institutional barriers, including spatial and temporal mismatches between datasets, fragmented regulatory and behavioral inputs, and the limitations of current single-task AI models, which often lack transparency. Overcoming these challenges will require innovation in AI modeling, improved data-sharing infrastructures, and stronger cross-disciplinary collaboration. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Integrating climate change and land use change into storm flood impact analysis in coastal cities - Sun, Qinke; Reyns, Johan; Fang, Jiayi; Wang, Xiaoting; Wang, Zhe; Zhou, Liang; Liu, Min (Journal of Hydrology: Regional Studies, 2025)
Study region: Shanghai, China Study focus: This paper proposes a comprehensive framework for quantifying storm surge floods in coastal cities by incorporating the influences of both climate change and urbanization. The framework achieves a physically process-based numerical simulation of storm surge-induced flood hazards due to tropical cyclones in coastal cities by coupling the fast flood inundation model (SFINCS) and the land use change model (GeoSOS-FLUS), along with the numerical nested model for storm surges (Delft 3D Flow & Wave). Using a 1000-year tropical cyclone simulated by the STORM model as an example, this study analyzes and maps coastal flood impacts under the moderate climate scenario (SSPs245) and high emission scenario (SSPs585), and also evaluates the impact of land use changes on these scenarios. New hydrological insights for the region: Taking Shanghai, China as an example, the results show that by 2100, urban land use changes will lead to an increase in the extent of 1000-year TC flooding areas by 4.91–34.00 %, underestimating the inundation area of storm surges if future urban land use changes are not considered. Additionally, our predictions indicate the vulnerability of Chongming island and Changxing island to the impacts of climate change, despite the protective role of coastal embankments considered in the tropical cyclone storm surge simulation. The results of this study represent an important contribution to a better understanding of how future urban land use changes will affect storm surge flooding risks in and around Shanghai. The proposed methodology can be applied to coastal areas worldwide that are vulnerable to tropical cyclones, aiding in the formulation of hazard mitigation policies to alleviate flood impacts in these regions. © 2025 The Authors
Publisher: Elsevier B.V.
Keywords: Scopus_Alert_5_Septembre_2025

Assessing subseasonal forecast skill for use in predicting US coastal inundation risk - Albers, John R.; Newman, Matthew; Balmaseda, Magdalena A.; Sweet, William; Wang, Yan; Xu, Tongtong (Ocean Science, 2025)
Abstract. Developing predictions of coastal flooding risk on subseasonal timescales (2–6 weeks in advance) is an emerging priority for the National Oceanic and Atmospheric Administration (NOAA). In this study, we assess the ability of two current operational forecast systems, the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS) and the Centre National de Recherches Météorologiques climate model (CNRM), to make subseasonal ensemble predictions of the non-tidal residual component of coastal water levels at United States coastal gauge stations for the period 2000–2019. These models were chosen because they assimilate satellite altimetry at forecast initialization and attempt to predict the mean sea level, including a global mean component whose absence in other forecast systems complicates assessment of tide gauge reforecast skill. Both forecast systems have skill that exceeds damped persistence for forecast leads through 2–3 weeks, with IFS skill exceeding damped persistence for leads up to 6 weeks. Post-processing forecasts to include the inverse barometer effect, derived from mean sea level pressure forecasts, improves skill for relatively short forecast leads (1–3 weeks). Accounting for vertical land motion of each gauge primarily improves skill for longer leads (3–6 weeks), especially for the Alaskan and Gulf coasts; sea-level trends contribute to reforecast skill for both model and persistence forecasts, primarily for the East and Gulf coasts. Overall, we find that current forecast systems have sufficiently high levels of deterministic and probabilistic skill to be used in support of operational coastal flood guidance on subseasonal timescales.
Keywords: Scopus_Alert_5_Septembre_2025

Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble system - Wang, Chung-Chieh; Van Nguyen, Duc; Van Vu, Thang; Nga, Pham Thi Thanh; Chuang, Pi-Yu; Truong, Kien Ba (Natural Hazards and Earth System Sciences, 2025)
This is the second part of a two-part study that investigates an extreme rainfall event that occurred from 8 to 12 December 2018 over central Vietnam (referred to as the D18 event). In this part, the study aims to evaluate the practical predictability of the D18 event using the quantitative precipitation forecasts (QPFs) from a time-lagged cloud-resolving ensemble system. To do this, 29 time-lagged (8 d in forecast range) high-resolution (2.5 km) members were run, with the first member initialized at 12:00 UTC on 3 December and the last one at 12:00 UTC on 10 December 2018. Between the first and the last members are multiple members that were executed every 6 h. The evaluation results reveal that the cloud-resolving model (CReSS) predicted the rainfall fields in the short range (less than 3 d) well for 10 December (the rainiest day). Particularly, the CReSS model shows high skill in heavy-rainfall QPFs for this date with a similarity skill score (SSS) greater than 0.5 for both the last five members and the last nine members. The good results are due to the model having good predictions of relevant meteorological variables such as surface winds. However, the predictive skill is reduced at lead times longer than 3 d, and it is challenging to achieve good QPFs for rainfall thresholds greater than 100 mm at lead times longer than 6 d. These results also confirmed our scientific hypothesis that the cloud-resolving time-lagged ensemble system (using the CReSS model) improved the QPFs of this event in the short range. Furthermore, the results also demonstrated that a decent QPF can be made at a longer lead time (by a member initialized at 18:00 UTC on 4 December). In addition, the ensemble-based sensitivity analysis (ESA) of 24 h rainfall in central Vietnam shows that it is highly sensitive to initial conditions, not only at lower levels but also at upper levels. The rainfall is sensitive to both kinematics and moisture convergence at low levels, and such sensitivities decrease with increasing lead time. The ESA also facilitates a better understanding of the mechanisms in the D18 event, implying that it is meaningful to apply ESA to control initial conditions in the future. © Author(s) 2025.
Publisher: Copernicus Publications
Keywords: Scopus_Alert_5_Septembre_2025

Seismic Performance Assessment of Gravity Dams for Urban Flood Risk Mitigation Using the Scaled Boundary Finite Element Method (SBFEM) - Kim, Min-Koan; Xu, Dai (Hydrology, 2025)
Rapid urbanization and climate change have intensified urban flood risks, necessitating resilient upstream infrastructure to ensure metropolitan water security and effective flood mitigation. Gravity dams, as critical components of urban flood protection systems, regulate discharge to downstream urban areas. Gravity dams are critical for regulating flood discharge, yet their seismic vulnerability poses significant challenges, particularly under compound effects involving concurrent seismic loading and climate-induced elevated reservoir levels. This study introduces a novel seismic analysis framework for gravity dams using the scaled boundary finite element method (SBFEM), which efficiently models dam–water and dam–foundation interactions in infinite domains. A two-dimensional numerical model of a concrete gravity dam, subjected to realistic seismic loading, was developed and validated against analytical solutions and conventional finite element method (FEM) results, achieving discrepancies as low as 0.95% for static displacements and 0.21% for natural frequencies. The SBFEM approach accurately captures hydrodynamic pressures and radiation damping, revealing peak pressures at the dam heel during resonance and demonstrating computational efficiency with significantly reduced nodal requirements compared to FEM. These findings enhance understanding of dam behavior under extreme loading. The proposed framework supports climate-adaptive design standards and integrated hydrological–structural modeling. By addressing the seismic safety of flood-control dams, this research contributes to the development of resilient urban water management systems capable of protecting metropolitan areas from compound climatic and seismic extremes. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Spatial–Temporal Characteristics and Drivers of Summer Extreme Precipitation in the Poyang Lake City Group (PLCG) from 1971 to 2022 - Liu, Hua; Zhang, Ziqing; Liu, Bo (Remote Sensing, 2025)
Global warming has intensified the hydrological cycle, resulting in more frequent extreme precipitation events and altered spatiotemporal precipitation patterns in urban areas, thereby increasing the risk of urban flooding and threatening socio-economic and ecological security. This study investigates the characteristics of summer extreme precipitation in the Poyang Lake City Group (PLCG) from 1971 to 2022, utilizing the China Daily Precipitation Dataset and NCEP/NCAR reanalysis data. Nine extreme precipitation indices were examined through linear trend analysis, Mann–Kendall tests, wavelet transforms, and correlation methods to quantify trends, periodicity, and atmospheric drivers. The key findings include: (1) All indices exhibited increasing trends, with RX1Day and R95p exhibiting significant rises (p < 0.05). PRCPTOT, R20, and SDII also increased, indicating heightened precipitation intensity and frequency. (2) R50, RX1Day, and SDII demonstrated east-high-to-west-low spatial gradients, whereas PRCPTOT and R20 peaked in the eastern and western PLCG. More than over 88% of stations recorded rising trends in PRCPTOT and R95p. (3) Abrupt changes occurred during 1993–2009 for PRCPTOT, R50, and SDII. Wavelet analysis revealed dominant periodicities of 26–39 years, linked to atmospheric oscillations. (4) Strong subtropical highs, moisture convergence, and negative OLR anomalies were closely associated with extreme precipitation. Warmer SSTs in the eastern equatorial Pacific amplified precipitation in preceding seasons. This study provides a scientific basis for flood prevention and climate adaptation in the PLCG and highlighting the region’s vulnerability to monsoonal shifts under global warming. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Flood susceptibility mapping in arid urban areas using SHAP-enhanced stacked ensemble learning: A case study of Jeddah - Zerouali, Bilel; Almaliki, Abdulrazak H.; Santos, Celso Augusto Guimarães (Journal of Environmental Management, 2025)
Flooding is an escalating hazard in arid and rapidly urbanizing environments such as Jeddah, Saudi Arabia, where the lack of historical flood records and sparse monitoring systems challenge effective risk prediction. To address this gap, this study aims to develop an accurate and interpretable flood susceptibility-mapping framework tailored to data-scarce urban settings. The research integrates a stacked ensemble model—comprising machine learning: XGBoost, CatBoost, and Histogram-based Gradient Boosting (HGB)—with SHapley Additive exPlanations (SHAP) to enhance prediction accuracy and model transparency. Random Forest was excluded from the final model stack due to inferior classification performance. A diverse set of geospatial inputs, including digital elevation model, slope, flow direction, Curve Number, topographic indices, and LULC (from ESRI Sentinel-2) were used as predictors. Furthermore, 92 and 198 flooded and non-flooded points were used for model validation. The model achieved strong predictive performance (AUC = 0.92, Accuracy = 0.82) on the validation set. In the absence of official flood records, model outputs were intersected with road network data to identify 395 road points in highly susceptible zones. Although these points do not represent a formal validation dataset—due to the general lack of detailed flood event records in the region, particularly in relation to infrastructure—they provide a valuable proxy for identifying flood-prone road segments. SHAP explainability analysis revealed that TRI, TPI, and distance to rivers were the most globally influential features, while Curve Number and LULC were key drivers of high-risk predictions. The model mapped 139 km2 (8.7 %) of the area as very high flood susceptibility and 325 km2 (20.3 %) as high susceptibility, outperforming individual learners. These results confirm that stacked ensemble learning, paired with explainable AI and creative validation strategies, can produce reliable flood susceptibility maps even in data-constrained contexts. This framework offers a transferable and scalable solution for flood risk assessment in similar arid and urbanizing environments. © 2025 Elsevier Ltd
Publisher: Academic Press
Keywords: Scopus_Alert_5_Septembre_2025

Revolutionizing urban water resilience: Innovative strategies and advancements in sustainable urban drainage systems (SuDS) - Pachouri, Vikrant; Kothari, Prafull; Kathuria, Samta; Gehlot, Anita; Singh, Rajesh; Thakur, Amit Kumar; Gupta, Lovi Raj; Dogra, Sudhanshu; Priyadarshi, Neeraj; Mohamed, Heba G. (Desalination and Water Treatment, 2025)
Climate change and rapid urbanisation are straining urban stormwater management further, with floods and water pollution becoming more intense. SUDS is a nature-based alternative that solves these issues because it replicates natural hydrologic processes to create urban resilience. This systematic review summarises recent trends in SUDS technologies, performance, and policy frameworks, and their potential to mitigate flood risks, improve water quality, and enhance climate resilience. By the PRISMA methodology, 90 peer-reviewed studies published between 2014 and 2025 were considered, dealing with SUDS performance, cost-effectiveness, and overall difficulties with large-scale implementation of these systems. Main results are that bio-retention systems, permeable pavements, and green roofs are effective in controlling surface runoff and enhancing water quality. Moreover, the development of IoT-based monitoring and smart technologies has also considerably increased the scalability and efficiency of a SUDS. The review recommends the standardisation of SUDS performance, the incorporation of smart technologies, and more attractive policy incentives to speed up the uptake of SUDS in urban planning. One of the main contributions that this research is likely to make to the discourse concerning urban water resilience is that it offers evidence-based suggestions to policymakers and urban developers, and these suggestions argue in favour of taking urgent action in the area of climate adaptation by using SUDS extensively. © 2025 The Authors
Publisher: Elsevier B.V.
Keywords: Scopus_Alert_5_Septembre_2025

Producing Hydrological Projections Under Climate Change: A Groundwater-Inclusive Practical Guide - Mourot, Frédérique M.; Irvine, Dylan J.; Remenyi, Tomas A.; Hutley, Lindsay B.; Crosbie, Russell S.; Moore, Catherine R. (Earth's Future, 2025)
With global warming, the hydrological cycle is intensifying with more frequent and severe droughts and floods, placing water resources and their dependent communities under increasing stress. Guidance and insights into the projection of future water conditions are, therefore, increasingly needed to inform climate change adaptation. Hydrological projections can provide such insights when suitably designed for user needs, produced from the best available climate knowledge, and leverage appropriate hydrological models. However, producing such hydrological projections is a complex process that requires skills and knowledge spanning from the often-siloed disciplines of climate, hydrology, communication, and decision-making. Groundwater projections are still underrepresented compared to surface water projections, despite the importance of groundwater to sustain society and the environment. Accordingly, this paper bridges these silos and fills a gap by providing detailed guidance on the important steps and best practices to develop groundwater-inclusive hydrological projections that can effectively support decision-making. Using an extensive literature review and our practical experience as climate scientists, hydro(geo)logists, numerical modelers, uncertainty experts and decision-makers, here we provide: (a) an overview of climate change hydrological impacts as background knowledge; (b) a step-by-step guide to produce groundwater-inclusive hydrological projections under climate change, targeted to both scientists and water practitioners; (c) a summary of important considerations related to hydrological projection uncertainty; and (d) insights to use hydrological projections and their associated uncertainty for impactful communication and decision-making. By providing this practical guide, our paper addresses a critical interdisciplinary knowledge gap and supports enhanced decision-making and resilience to climate change threats. © 2025 Commonwealth of Australia. Earth Science New Zealand. Acclimatised Pty Ltd and The Author(s). Earth's Future published by Wiley Periodicals LLC on behalf of American Geophysical Union.
Publisher: John Wiley and Sons Inc
Keywords: Scopus_Alert_5_Septembre_2025

Interest Flooding Attacks in Named Data Networking and Mitigations: Recent Advances and Challenges - Ogunbunmi, Simeon; Chen, Yu; Zhao, Qi; Nagothu, Deeraj; Wei, Sixiao; Chen, Genshe; Blasch, Erik (Future Internet, 2025)
Named Data Networking (NDN) represents a promising Information-Centric Networking architecture that addresses limitations of traditional host-centric Internet protocols by emphasizing content names rather than host addresses for communication. While NDN offers advantages in content distribution, mobility support, and built-in security features, its stateful forwarding plane introduces significant vulnerabilities, particularly Interest Flooding Attacks (IFAs). These IFA attacks exploit the Pending Interest Table (PIT) by injecting malicious interest packets for non-existent or unsatisfiable content, leading to resource exhaustion and denial-of-service attacks against legitimate users. This survey examines research advances in IFA detection and mitigation from 2013 to 2024, analyzing seven relevant published detection and mitigation strategies to provide current insights into this evolving security challenge. We establish a taxonomy of attack variants, including Fake Interest, Unsatisfiable Interest, Interest Loop, and Collusive models, while examining their operational characteristics and network performance impacts. Our analysis categorizes defense mechanisms into five primary approaches: rate-limiting strategies, PIT management techniques, machine learning and artificial intelligence methods, reputation-based systems, and blockchain-enabled solutions. These approaches are evaluated for their effectiveness, computational requirements, and deployment feasibility. The survey extends to domain-specific implementations in resource-constrained environments, examining adaptations for Internet of Things deployments, wireless sensor networks, and high-mobility vehicular scenarios. Five critical research directions are proposed: adaptive defense mechanisms against sophisticated attackers, privacy-preserving detection techniques, real-time optimization for edge computing environments, standardized evaluation frameworks, and hybrid approaches combining multiple mitigation strategies. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Injectivity, Potential Wettability Alteration, and Mineral Dissolution in Low-Salinity Waterflood Applications: The Role of Salinity, Surfactants, Polymers, Nanomaterials, and Mineral Dissolution - Sarma, Hemanta K.; Awolayo, Adedapo N.; Olayiwola, Saheed O.; Fakir, Shasanowar H.; Belhaj, Ahmed F. (Processes, 2025)
Waterflooding, a key method for secondary hydrocarbon recovery, has been employed since the early 20th century. Over time, the role of water chemistry and ions in recovery has been studied extensively. Low-salinity water (LSW) injection, a common technique since the 1930s, improves oil recovery by altering the wettability of reservoir rocks and reducing residual oil saturation. Recent developments emphasize the integration of LSW with various recovery methods such as CO2 injections, surfactants, alkali, polymers, and nanoparticles (NPs). This article offers a comprehensive perspective on how LSW injection is combined with these enhanced oil recovery (EOR) techniques, with a focus on improving oil displacement and recovery efficiency. Surfactants enhance the effectiveness of LSW by lowering interfacial tension (IFT) and improving wettability, while ASP flooding helps reduce surfactant loss and promotes in situ soap formation. Polymer injections boost oil recovery by increasing fluid viscosity and improving sweep efficiency. Nevertheless, challenges such as fine migration and unstable flow persist, requiring additional optimization. The combination of LSW with nanoparticles has shown potential in modifying wettability, adjusting viscosity, and stabilizing emulsions through careful concentration management to prevent or reduce formation damage. Finally, building on discussions around the underlying mechanisms involved in improved oil recovery and the challenges associated with each approach, this article highlights their prospects for future research and field implementation. By combining LSW with advanced EOR techniques, the oil industry can improve recovery efficiency while addressing both environmental and operational challenges. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Establishing a Sea Level Rise-Adjusted Design Flood Elevation for Buildings: A Comparative Study of Methods - Meguro, Wendy; Briones, Josephine I.; Teeples, Eric; Fletcher, Charles H. (Water (Switzerland), 2025)
Coastal high tide flooding doubled in the U.S. between 2000 and 2022 and sea level rise (SLR) due to climate change will dramatically increase exposure and vulnerability to flooding in the future. However, standards for elevating buildings in flood hazard areas, such as base flood elevations set by the Federal Emergency Management Agency, are based on historical flood data and do not account for future SLR. To increase flood resilience in flood hazard areas, federal, state, regional, and municipal planning initiatives are developing guidance to increase elevation requirements for occupied spaces in buildings. However, methods to establish a flood elevation that specifically accounts for rising sea levels (or sea level rise-adjusted design flood elevation (SLR-DFE)) are not standardized. Many municipalities or designers lack clear guidance on developing or incorporating SLR-DFEs. This study compares guidance documents, policies, and methods for establishing an SLR-DFE. The authors found that the initiatives vary in author, water level measurement starting point, SLR scenario and timeframe, SLR adjustment, freeboard, design flood elevation, application (geography and building type), and whether it is required or recommended. The tables and graph compare the different initiatives, providing a useful summary for policymakers and practitioners to develop SLR-DFE standards. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Machine Learning for Flood Resiliency—Current Status and Unexplored Directions - Uddameri, Venkatesh; Hernandez, E. Annette (Environments - MDPI, 2025)
A systems-oriented review of machine learning (ML) over the entire flood management spectrum, encompassing fluvial flood control, pluvial flood management, and resiliency-risk characterization was undertaken. Deep learners like long short-term memory (LSTM) networks perform well in predicting reservoir inflows and outflows. Convolution neural networks (CNNs) and other object identification algorithms are being explored in assessing levee and flood wall failures. The use of ML methods in pump station operations is limited due to lack of public-domain datasets. Reinforcement learning (RL) has shown promise in controlling low-impact development (LID) systems for pluvial flood management. Resiliency is defined in terms of the vulnerability of a community to floods. Multi-criteria decision making (MCDM) and unsupervised ML methods are used to capture vulnerability. Supervised learning is used to model flooding hazards. Conventional approaches perform better than deep learners and ensemble methods for modeling flood hazards due to paucity of data and large inter-model predictive variability. Advances in satellite-based, drone-facilitated data collection and Internet of Things (IoT)-based low-cost sensors offer new research avenues to explore. Transfer learning at ungauged basins holds promise but is largely unexplored. Explainable artificial intelligence (XAI) is seeing increased use and helps the transition of ML models from black-box forecasters to knowledge-enhancing predictors. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Exploring the potential of coastal cities to address climate change towards an inclusive, equitable and politically engaged orientation - Monckeberg, Elisa; Gómez, Sílvia (Anthropocene Coasts, 2025)
In the context of the global climate crisis, the analysis and strengthening of adaptive capacities in coastal urban environments has become imperative. Nearly 40% of the global population lives within 100 km of the coastline, making them critical research hotspots due to their particular vulnerability. This qualitative literature review takes a transdisciplinary approach and prioritizes research that addresses specific challenges and solutions for these vulnerable environments, with an emphasis on resilience to phenomena such as sea level rise, flooding and extreme weather events. The review analyzes articles that offer a holistic view, encompassing green and blue infrastructures, community needs and governance dynamics. It highlights studies that propose innovative strategies to foster citizen participation and explicitly address aspects such as climate justice. By synthesizing interdisciplinary perspectives and local knowledge, this review aims to provide a comprehensive framework for climate adaptation in coastal urban areas. The findings have the potential to inform public policy and urban planning practices. © The Author(s) 2025.
Publisher: Springer Nature
Keywords: Scopus_Alert_5_Septembre_2025

Copula-based joint distribution modelling of precipitation, temperature and humidity events in the assessments of agricultural risks, with a case study in Morocco - Latif, Shahid; El Ouadi, Ihssan; Ouarda, Taha B. M. J. (Stochastic Environmental Research and Risk Assessment, 2025)
The agriculture sector is profoundly impacted by the abiotic stresses in arid or semi-arid regions that experience extreme weather patterns related to temperature (T), precipitation (P), humidity (H), and other factors. This study adopts a flexible approach that incorporates the D-vine copula density to analyze trivariate (and bivariate) joint and conditional hazard risk. The methodology was applied to a case study in the Ait Ben Yacoub region of Morocco. Monthly series for T, H, and P were modeled using the Weibull-2P and Weibull-3P models, selected based on fitness statistics. The survival BB8 copula was best described as joint dependence for pair T–P, rotated BB8 270 degrees copula for T–H, while rotated Joe 270 degrees copula for P–H. The analysis of joint probability stress focused on both primary joint scenarios (for OR and AND-hazard conditions) and conditional return periods (RPs) for trivariate and bivariate case. Lower univariate RPs resulted in higher marginal quantiles for T and lower for H and P events. Lower trivariate (and bivariate) AND-joint RPs (or higher concurrence probabilities) were associated with higher T with lower P and H quantiles. The occurrence of trivariate (and bivariate) events was less frequent in the AND-joint case compared to the OR-joint case. The conditional joint RP of T (or T with P, or T with H) was significantly affected by different P (at 10th and 25th percentile) and H (at 5th and 25th percentile) (or P, or H) conditions. Lower conditional RPs of T (or T with H, or T with P) had resulted at given low P and H (or low P, or low H levels). In conclusion, the estimated risk statistics are vital for the study region, highlighting the need for effective adaptation and resilience planning in agriculture crop management.
Keywords: Infolettre_Septembre_2025

High-Resolution Daily XCH4 Prediction Using New Convolutional Neural Network Autoencoder Model and Remote Sensing Data - Awad, Mohamad M.; Homayouni, Saeid (Atmosphere, 2025)
Atmospheric methane (CH4) concentrations have increased to 2.5 times their pre-industrial levels, with a marked acceleration in recent decades. CH4 is responsible for approximately 30% of the global temperature rise since the Industrial Revolution. This growing concentration contributes to environmental degradation, including ocean acidification, accelerated climate change, and a rise in natural disasters. The column-averaged dry-air mole fraction of methane (XCH4) is a crucial indicator for assessing atmospheric CH4 levels. In this study, the Sentinel-5P TROPOMI instrument was employed to monitor, map, and estimate CH4 concentrations on both regional and global scales. However, TROPOMI data exhibits limitations such as spatial gaps and relatively coarse resolution, particularly at regional scales or over small areas. To mitigate these limitations, a novel Convolutional Neural Network Autoencoder (CNN-AE) model was developed. Validation was performed using the Total Carbon Column Observing Network (TCCON), providing a benchmark for evaluating the accuracy of various interpolation and prediction models. The CNN-AE model demonstrated the highest accuracy in regional-scale analysis, achieving a Mean Absolute Error (MAE) of 28.48 ppb and a Root Mean Square Error (RMSE) of 30.07 ppb. This was followed by the Random Forest (RF) regressor (MAE: 29.07 ppb; RMSE: 36.89 ppb), GridData Nearest Neighbor Interpolator (NNI) (MAE: 30.06 ppb; RMSE: 32.14 ppb), and the Radial Basis Function (RBF) Interpolator (MAE: 80.23 ppb; RMSE: 90.54 ppb). On a global scale, the CNN-AE again outperformed other methods, yielding the lowest MAE and RMSE (19.78 and 24.7 ppb, respectively), followed by RF (21.46 and 27.23 ppb), GridData NNI (25.3 and 32.62 ppb), and RBF (43.08 and 54.93 ppb).
Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Infolettre_Septembre_2025

Flooding stress influences productivity and modulates biodiversity effects in experimental grassland communities, shaping biodiversity–productivity relationships - Zhekov, Aleksandar; Bourgeois, Bérenger; Poulin, Monique (American Journal of Botany, 2025)
Abstract Premise Biodiversity loss and increasing extreme weather events disrupt the functioning of ecosystems and thus their ability to provide services. While the interplay among various climatic constraints, diversity and productivity has received increasing attention in the last decades, the role of flooding has been overlooked. Methods In a greenhouse experiment, we manipulated species richness and water regimes to evaluate the influence of flooding on species diversity–productivity relationships. We measured biomass production and partitioned net biodiversity effects into complementarity and selection effects. To link changes in biodiversity effects to underlying mechanisms, we evaluated the contribution of species richness, species identity, functional diversity and community‐level traits. Results Under flooding, biomass production decreased, and biodiversity effects were less frequently positive. By reducing the incidence of positive complementarity effects, flooding promoted a preponderance of selection effects. Flooding further favored competitive displacement by Phalaris arundinacea ; balanced contributions to selection effects from all functional groups at field capacity subsided under flooding when P. arundinacea became the single dominant species. As a result, its acquisitive leaf trait attributes contributed more to selection effects and biomass production under flooding, while root traits contributed less to complementarity effects at field capacity. Conclusions As an environmental stressor, flooding promoted the dominance of tolerant species and reduced the incidence of complementary species interactions in the experimental plant communities, clearly modulating the linkage between diversity and productivity.
Keywords: Infolettre_Septembre_2025

Projections of extreme rainfall and floods in Mediterranean basins from an ensemble of convection-permitting models - Poncet, Nils; Tramblay, Yves; Lucas-Picher, Philippe; Thirel, Guillaume; Caillaud, Cécile (Climatic Change, 2025)
Floods have major impacts on the Mediterranean region, but little is currently known about their potential evolution in the context of climate change. This is due in particular to the limited ability of climate models to reproduce extreme meteorological events such as heavy rains that lead to flash floods, especially at the local scale over smaller basins. This study is the first to explore future flood scenarios over 12 Mediterranean basins using an ensemble of 12 high-resolution convection-permitting climate models and the GR5H hourly rainfall-runoff model. The results indicate an overall increase in flood intensity across all basins, particularly for the most severe events, but also a strong spatial variability in the change signal depending on the geographic location. There is good agreement among the convection-permitting climate models on an increase in hourly and daily rainfall extremes in the Mediterranean, but these changes are not strongly correlated with changes in flood-peak intensity, indicating that change in rainfall intensity alone is a poor predictor of future flood hazards. At present, this type of analysis is hampered by the short duration of the available high-resolution climate simulations. Longer timeseries would be required to better assess the robustness of the projected changes against climate variability.
Keywords: Infolettre_Septembre_2025

Predicting synthetic rating curve adjustment factors with explainable machine learning for enhancing the United States operational flood inundation mapping framework - Baruah, Anupal; Spies, Ryan; Devi, Dipsikha; Cohen, Sagy; Aristizabal, Fernando; Nikrou, Parvaneh; Tian, Dan; Pruitt, Carson (Journal of Hydrology, 2025)
The increasing threats of global flood risk mandate rapid and accurate high-resolution flood modeling strategies over large scales. In the United States, the National Oceanic and Atmospheric Administration (NOAA) Office of Water Prediction (OWP) has operationalised a Flood Inundation Mapping (FIM) framework utilising the Height Above Nearest Drainage (HAND)-Synthetic Rating Curve (SRC) approach. It translates streamflow into stage and subsequently maps the inundation over the floodplain. It is a low-fidelity FIM framework, suitable for large-scale applications with much less computational effort. The SRCs are calculated for each river segment using Manning's equation; however, uncertainty in Manning's parameters and missing bathymetry impart bias in SRC calculation, and thus in FIM. An SRC adjustment factor (λsrc), introduced by OWP, calibrates SRCs against USGS rating curves, HEC-RAS 1D rating curves, and National Weather Service (NWS)-Categorical Flood Inundation Mapping (CatFIM) locations. Adjusted SRCs improve the FIM predictions but are limited to locations with the above data sources. In this paper, we develop machine learning models to predict the λsrc over the entire United States river network. Results show that the eXtreme Gradient Boosting model yielded the strongest predictability, with an R2 of 0.70. The impact of λsrc on FIM predictions is evaluated for Hurricane Matthew in North Carolina and synthetic flood events in 15 watersheds. For Hurricane Matthew flooding, the mean percentage improvements in Critical Success Index (CSI), Probability of Detection (POD), and F1 Score are 17.5%, 20% and 12.5%, while for synthetic events, the improvements are 2.59%, 4.93%, and 3.03%, respectively. © 2025 The Author(s)
Publisher: Elsevier B.V.

Agent-based vulnerability model for pedestrians exposed to urban floodwaters - Li, Qijie; Xia, Junqiang; Xu, Zheng; Liang, Dongfang; Hinkelmann, Reinhard (Journal of Hydrology, 2025)
Climate change-induced floods will have a profound impact on densely populated urban areas. The survey results indicate that a substantial proportion of respondents engaged in evacuation behavior during urban flooding events. However, current assessment methods may underestimate the impact of human motions in floodwaters on pedestrian evacuation safety. To quantitively study the dynamic vulnerability of individuals exposed to flooding scenarios, an agent-based vulnerability model was proposed based on mechanics modelling and experimentally calibrating. A full-scale physical testing platform was constructed and utilized to calibrate the proposed model and to determine the stability limits of pedestrian safety in floodwaters. Spatial and temporal dynamic characteristics of pedestrians were analyzed and results reveal significant variations in pedestrian movement and stability. The general temporal trend of movement speed changing as a power function of the specific flood force has been validated. It is also found that pedestrian stability is notably affected by movement in floodwaters, particularly when walking against the flow, which intensifies the risk of instability, leading to vulnerability indices that increase by 123.2 % at a depth of 0.3 m and by 82.7 % at 0.5 m compared to still-water conditions. In contrast, moving with the flow reduces hydrodynamic forces, although the rate of this reduction decreases with greater water depths, dropping to 16.0 % at 0.5 m and 9.7 % at 0.7 m. Additionally, this work provides guidelines for assessing pedestrian evacuation vulnerability that enhances evacuation safety and supports flood management. © 2025 Elsevier B.V.
Publisher: Elsevier B.V.

Optimizing ensemble learning for satellite-based multi-hazard monitoring and susceptibility assessment of landslides, land subsidence, floods, and wildfires - Razavi-Termeh, Seyed Vahid; Sadeghi-Niaraki, Abolghasem; Ali, Farman; Pradhan, Biswajeet; Choi, Soo-Mi (Scientific Reports, 2025)
The preparation of accurate multi-hazard susceptibility maps is essential to effective disaster risk management. Past studies have relied mainly on traditional machine learning models, but these models do not perform well for complex spatial patterns. To address this gap, this study uses two meta-heuristic algorithms (Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)) to provide an optimized Random Forest (RF) model with better predictive ability. We focus on four significant hazards—landslides, land subsidence, wildfires, and floods—in Kurdistan Province, Iran, using Sentinel-1 and Sentinel-2 satellite imagery collected between 2015 and 2022. Furthermore, two models of RF-GA and RF-PSO were utilized to create multi-hazard susceptibility, which were evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). The RF-GA algorithm achieved 91.1% accuracy for flood hazards, 83.8% for wildfires, and 99.1% for landslide hazards. In contrast, utilizing RF-PSO resulted in a 95.9% accuracy for land subsidence hazards. The combined RF-GA algorithm demonstrated superior accuracy to individual RF modeling techniques. Furthermore, eastern regions are more prone to floods and land subsidence, whereas western areas face more significant risks from landslides and wildfires. Additionally, floods and land subsidence exhibit a considerable correlation, impacting each other’s occurrence, while wildfires and landslides demonstrate interacting dynamics, influencing each other’s likelihood of occurrence. © The Author(s) 2025.
Publisher: Nature Research

Multi-criteria decision analysis for flood hazard mapping in the Itang watershed, lower Baro-Akobo Basin, Southwest Ethiopia - Chengu, Shibiru; Assen, Mohammed; Gebeyehu, Elias (Discover Environment, 2025)
Flooding remains a critical hydrological hazard in the Itang watershed within the Lower Baro-Akobo Basin, requiring an in-depth assessment of flood susceptibility. This study employs a multi-criteria evaluation method, integrating key geospatial and hydrological parameters such as topographic slope, elevation, land use/land cover, River proximity, drainage network density, precipitation intensity, and soil properties. Utilizing a Multi-Criteria Decision Analysis (MCDA) approach within the ArcMap 10.3.1 environment, a flood hazard zonation map was generated, classifying the watershed into five risk categories: Very high, high, moderate, low, and very low. The findings reveal that approximately 69.69% of the watershed falls within the high to very high flood risk zones, predominantly influenced by low-lying Elevation, gentle slopes, proximity to the river, land cover dynamics, high drainage density, and precipitation variability. These insights emphasize the necessity of integrating robust flood mitigation measures, early warning mechanisms, and sustainable watershed management interventions to enhance flood resilience and reduce hydrological risks in the study watershed. © The Author(s) 2025.
Publisher: Springer Nature

Black swans to gray rhinos: Robust decision making for Natech scenarios caused by floods - Hu, Xiangyang; Yang, Angbin; Wu, Shaohui; Tong, Ruipeng (Journal of Loss Prevention in the Process Industries, 2025)
Industrial facilities and critical infrastructure are affected by natural disasters with increasing probability, potentially resulting in serious health impacts, environmental pollution, and economic losses. Deep uncertainty about future scenarios leads to under-adaptation due to the inability of existing knowledge to cope with ambiguity and complexity. With scientific constraints, particularly in model limitations and scenario scarcity, estimating the likelihood of risk events and possible implications is challenging and error-prone. Using systems thinking to guide scenario planning, a Pressure-State-Response (PSR) model of Natech risk was developed to outline the uncertainty involved in the full course of the Natech event in this paper. Taking the flood-triggered Natech risks as an example, a robust decision-making (RDM) framework was adopted to analyze the impacts of future extreme rainfall scenarios on the city. Obtaining future rainfall scenarios through screening and quantitative analysis of uncertainties and their intervals of variability under the impact of climate change. By evaluating urban disaster curves that may be triggered in the future, an interpretive structural model (ISM) of the future urban response to the Natech accident scenario was constructed, and prioritized adaptation paths were selected to enhance urban resilience. © 2025 Elsevier Ltd
Publisher: Elsevier Ltd

Risk identification and prevention of multi-level flood and typhoon prevention emergency drills - Cao, Feifeng; Chen, Changhui; Zhang, Conglin; Xing, Jianwu (Progress in Disaster Science, 2025)
Amid increasing extreme weather events driven by global climate change, pre-emptive emergency drills are vital for strengthening disaster resilience. This paper focuses on risk identification and prevention in multi-level flood and typhoon prevention emergency drills, aiming to achieve effective risk management across administrative levels. Through literature review and expert consultation, 24 risk factors were hierarchically identified. A quantitative risk assessment model was developed by integrating the risk matrix and cloud model eigenvalues. The results show that risks are the most serious at municipal-level drills, with 20 risk factors (79.17 % of the total) at Level-III and above, decreasing at lower administrative levels (where risk level are categorized into Level-I (Major), Level-II (Large), Level-III (General), and Level-IV (Low) based on the risk matrix integrating likelihood and consequence levels, and Level-III and above risks may trigger resource wastage, drill failure, or even personnel casualties). Temporally, 39 risk factors at Level-III and above were concentrated in preparation stages across all administrative levels, declining to 3 such risk factors during rectification stage. Spatially, the number of risk factors peaked during the municipal-level and county-level preparation stages (11 risk factors respectively at Level-III and above), with their quantity gradually decreasing as the administrative level decreases and drill stages advance. Based on these findings, a systematic risk prevention matrix is proposed to offer targeted guidance for multi-level flood and typhoon prevention emergency drills in addressing climate change-induced disaster challenges. © 2025 The Authors
Publisher: Elsevier Ltd

Unveiling hidden risks in healthcare from flood-induced transportation disruption in Germany - Wassmer, Jonas; Bryant, Seth; Schimansky, Paul; Keegan, Lindsay T.; Pregnolato, Maria; Kurths, Jürgen; Marwan, Norbert; Merz, Bruno (Communications Earth and Environment, 2025)
Despite investments in disaster resilience, flooding continues to disrupt healthcare systems, both by limiting access and through failures in the surrounding transportation network. Existing models for mitigation planning often overlook critical dynamics, such as traffic rerouting, particularly at the national scales necessary for effective planning. Here we present a scalable method to identify hospitals at risk of emergency response delays and service disruptions caused by flood-induced traffic impacts. Our approach integrates a regional flood model with a gravity-based traffic model to simulate traffic flow from open-source road data. Our findings reveal hidden risks for hospitals located far from flood zones, showing how flood-related road disruptions and traffic rerouting can reduce access to critical healthcare services. In particular, we found 75 (of 2,475) hospitals at risk of patient surges beyond their regular capacity, driven solely by flood-related traffic disruptions. Of these, a third are more than 10 km from the nearest inundation, suggesting these facilities may be unaware and thus under-prepared — risks that have, until now, remained hidden from assessments. © The Author(s) 2025.
Publisher: Nature Publishing Group

Optimization of emergency logistics for urban flooding with consideration of rainfall effects - Zhang, Peiwen; Zhang, Chenxing; Zhang, Pan; Yan, Xuxian; Yang, Huawei (Scientific Reports, 2025)
Urban flooding frequently causes significant damage to infrastructure and facilities, leading to critical supply shortages in affected regions. Ensuring rapid and efficient distribution of relief supplies remains a key challenge during disaster response operations. This study proposes a two-stage optimization framework for emergency logistics. First, a supply distribution model is developed by integrating resource scarcity indices and disaster severity indices, optimized through a simulated annealing algorithm. Second, a vehicle routing model accounting for rainfall and dynamic vehicle speeds is established, solved using a hybrid Genetic Simulated Annealing algorithm to enhance computational efficiency. Ultimately, through simulation with randomly generated calculation examples, it was found that for the supply distribution model, the allocation model that takes into account both the resource scarcity index and the disaster index is more suitable for scenarios with an uneven distribution of disaster severity. The results of the model that takes into account the resource scarcity index, disaster index and waiting time index shows an improvement of 4% over the model that doesn’t consider the resource scarcity index. The experimental results show that the proposed methodology not only adapts to varying disaster spatial patterns but also balances efficiency and equity under supply constraints, offering a scalable tool for designing resilient urban flood response systems. © The Author(s) 2025.
Publisher: Nature Research

A novel and scalable flood risk assessment framework for cultural heritage based on unmanned aerial vehicle photogrammetry and multi-scale rain-on-grid hydraulic modeling - Alexopoulos, M.J.; Iliopoulou, T.; Modé, P.; Istrati, D.; Spyrakos, C.C.; Soile, S.; Verykokou, S.; Ioannidis, C.; Koutsoyiannis, D. (Science of the Total Environment, 2025)
This study presents a novel multi-scale flood risk assessment framework for cultural heritage sites, applied to the Temple of Apollo, Aegina Island, Greece. Three modeling configurations were developed and compared: (i) an island-wide Rain-on-Grid (RoG) hydraulic model at 5 m resolution, (ii) a site-only model driven by inflows from the island-scale simulation, and (iii) a high-resolution nested model coupling island-scale outputs with centimeter-scale site RoG simulations enabled by UAV photogrammetry. Simulations for 100-, 1000-, and 2000-year return periods revealed strong scale-dependent differences: island-wide inundation extents of 7.3–10.3 km2, site-specific inundation of 2–24 %, and water volumes of 92–1483 m3 depending on the model configuration and return period. Flow velocities remained below 1.0 m/s, indicating low erosive potential but possible material degradation. Limestone deterioration analysis showed 4–10 % compressive strength reduction, 3–9 % elastic modulus decrease, and mass losses of 0.64–26.08 kg after 24-h inundations. The nested approach provided more realistic water volume accumulation over the single-scale model and revealed critical micro-topographic controls on flood behavior. This scalable, built on readily accessible tools (HEC-RAS and UAV), framework supports rapid deployment to heritage sites globally, enabling quantitative risk assessments for adaptation planning and conservation prioritization. © 2025 The Authors
Publisher: Elsevier B.V.

Multiscale semantic segmentation and damage assessment of village houses in post-flood scenarios using an enhanced DeepLabv3 with dual attention mechanism - Wu, Luyuan; Cheng, Yi; Su, Aifang; Zhang, Boyang; Wang, Zifa; Tong, Jingbo; Li, Meng; Zhang, Anqi (Advanced Engineering Informatics, 2025)
Floods can cause varying degrees of damage to village houses, and rapid assessment of houses damage is crucial for post-disaster safety evaluations. To address this issue, the paper proposes a DeepLabv3-Dual Attention (DDA) model incorporating improved ResNet-50, Atrous Spatial Pyramid Pooling (ASPP), Selective Kernel(SK)-Attention, and Self-Attention mechanisms. In the DDA model, the ASPP structure is enhanced with Self-Attention, while the backbone network employs SK-Attention improved ResNet-50, enabling more effective feature extraction across both spatial and channel dimensions. Validated on the “7.20” heavy rain disaster dataset from Zhengzhou, DDA achieves optimal performance (learning rate: 0.01, batch_size: 16, epoch: 88) with 87.5% accuracy, 98.5% global accuracy, 77.8% MIoU, and 86.5% F1-score, outperforming DeepLabv3+, Swin-Unet, U-Net, YOLO baseline models. Ablation studies confirm dual-attention synergy improves MIoU by 2.5%, precision by 2.5% over single mechanisms. Further, a damage quantification framework is developed using OpenCV and Canny edge detection to extract contours, coupled with a maximum tangent circle algorithm for pixel-level width measurement and skeletonization-based pixel-level length calculation. The results of damage quantification model show that the proportion of images with damage width quantification error ⩽ 20% are 85.29%. This study serves as a reference for intelligent assessment and risk classification of structural damage to buildings affected by flooding. © 2025 Elsevier Ltd
Publisher: Elsevier Ltd

Editorial preface to special issue: Temporal and spatial patterns in Holocene floods under the influence of past global change, and their implications for forecasting “unpredecented” future events - Schulte, Lothar; Santisteban, Juan I.; Fuller, Ian C.; Ballesteros-Cánovas, Juan Antonio (Global and Planetary Change, 2025)
Floods constitute the most significant natural hazard to societies worldwide. Population growth and unchecked development have led to floodplain encroachment. Modelling suggests that climate change will regionally intensify the threat posed by future floods, with more people in harm's way. From a global change perspective, past flood events and their spatial-temporal patterns are of particular interest because they can be linked to former climate patterns, which can be used to guide future climate predictions. Millennial and centennial time series contain evidence of very rare extreme events, which are often considered by society as ‘unprecedented’. By understanding their timing, magnitude and frequency in conjunction with prevailing climate regime, we can better forecast their future occurrence. This Virtual Special Issue (VSI) entitled Temporal and spatial patterns in Holocene floods under the influence of past global change, and their implications for forecasting “unpredecented” future events comprises 14 papers that focus on how centennial and millennia-scale natural and documentary flood archives help improve future flood science. Specifically, documentation of large and very rare flood episodes challenges society's lack of imagination regarding the scale of flood disasters that are possible (what we term here, the “unknown unknowns”). Temporal and spatial flood behaviour and related climate patterns as well as the reconstruction of flood propagation in river systems are important foci of this VSI. These reconstructions are crucial for the provision of robust and reliable data sets, knowledge and baseline information for future flood scenarios and forecasting. We argue that it remains difficult to establish analogies for understanding flood risk during the current period of global warming. Most studies in this VSI suggest that the most severe flooding occurred during relatively cool climate periods, such as the Little Ice Age. However, flood patterns have been significantly altered by land use and river management in many catchments and floodplains over the last two centuries, thereby obscuring the climate signal. When the largest floods in instrumental records are compared with paleoflood records reconstructed from natural and documentary archives, it becomes clear that precedent floods should have been considered in many cases of flood frequency analysis and flood risk modelling in hydraulic infrastructure. Finally, numerical geomorphological analysis and hydrological simulations show great potential for testing and improving our understanding of the processes and factors involved in the temporal and spatial behaviour of floods. © 2025 The Authors
Publisher: Elsevier B.V.

Developing rejuvenation strategies and artificial flood mitigation plans for Indrani River: a case study - Muhammed, Shaz P.; Holla, B.R.K.; Balakrishna, K.; Warrier, Anish Kumar (Scientific Reports, 2025)
Artificial flooding of rainwater is most common in urban areas due to various reasons, such as improper drainage systems, obstruction of natural drainage by building constructions, and encroachment of stormwater nallahs. Flash floods lead to significant losses, disrupt transportation, and cause inconvenience to the public. Udupi, characterized by its porous lateritic strata, undulating topography, and proximity to the sea, experiences artificial flooding during the peak monsoon season in its low-lying areas, primarily due to the overflow of the Indrani River, which is also a potential water resource for Udupi, Karnataka. Currently, the river faces significant challenges due to increasing anthropogenic activities. Revitalizing the Indrani River offers numerous benefits, including its potential use as a drinking water source during periods of water scarcity. This study aims to propose flood and stormwater management measures for the river catchment and to evaluate selected water quality parameters (pH, dissolved oxygen, and conductivity) at fifteen strategic locations along the river course. Higher conductivity observed at downstream stations is attributed to sewage discharge from urban settlements and a sewage treatment plant. The study suggests short-term measures such as targeted clean-up operations and stricter enforcement of pollution control regulations. Additionally, it recommends long-term strategies, including the development of a comprehensive river basin management plan, community engagement initiatives, and improvements to wastewater treatment infrastructure. To maintain the health of the Indrani River, this research emphasizes the importance of continuous monitoring and the implementation of integrated management practices. © The Author(s) 2025.
Publisher: Nature Research

Effects of long-term wetland variations on flood risk assessments in the Yangtze River Basin - Guo, Ziying; Shi, Xiaogang; Zhang, Dingfan; Zhao, Qunshan (Environmental Impact Assessment Review, 2026)
Flooding is the most frequent natural disaster in the Yangtze River Basin (YRB), causing significant socio-economic damages. In recent decades, abundant wetland resources in the YRB have experienced substantial changes and played a significant role in strengthening the hydrological resilience to flood risks. However, wetland-related approaches remain underdeveloped for mitigating flood risks in the YRB due to the lack of considering long-term wetland effects in the flood risk assessment. Therefore, this study develops an wetland-related GIS-based spatial multi-index flood risk assessment model by incorporating the effects of wetland variations, to investigate the long-term implications of wetland variations on flood risks, to identify dominant flood risk indicators under wetland effects, and to provide wetland-related flood risk management suggestions. These findings indicate that wetlands in the Taihu Lake Basin, Wanjiang Plain, Poyang Lake Basin, and Dongting and Honghu Lake Basin could enhance flood control capacity and reduce flood risks in most years between 1985 and 2021 except years with extreme flood disasters. Wetlands in the Sichuan Basin have aggravated but limited impacts on flood risks. Precipitation in the Taihu Lake Basin and Poyang Lake Basin, runoff and vegetation cover in the Wanjiang Plain, GDP in the Taihu Lake Basin, population density in the Taihu lake Basin, Dongting and Honghu Lake Basin, and the Sichuan Basin are dominant flood risk indicators under wetland effects. Reasonably managing wetlands, maximizing stormwater storage capacity, increasing vegetation coverage in urbanized and precipitated regions are feasible suggestions for developing wetland-related flood resilience strategies in the YRB. © 2025 The Authors
Publisher: Elsevier Inc.

Development and validation of a predictive flux regression model for tubular membrane treatment of Polymer-Flooding produced water - Xu, Jun; Wu, Man; Hao, Jiahou; Lu, Jing; Zhao, Dongsheng; Zheng, Wenyu; Jiang, Gengmin; Yu, Shuili; Wang, Linna (Separation and Purification Technology, 2025)
This study established and validated a regression model for predicting membrane flux (Jv) during treatment of polymer-flooding produced water (PFPW) using PVDF ultrafiltration membranes hydrophilized by Nano-Al2O3 particles. A factorial crossover experimental design was employed to investigate the temporal flux variations and 24-hour average flux (Jv24) under different membrane surface velocities and transmembrane pressure differences. Based on Taylor's mathematical principles, a regression model for predicting Jv in PFPW treatment was developed using the experimental results. The coefficients, contour plots and response surface of the model were obtained through MATLAB software. Theoretical and experimental validations were conducted to assess the accuracy of the model. Theoretical validation demonstrated that the standard residuals of the model and predicted values were within ± 2.00, with the predicted and measured Jv exhibiting similar statistical distribution characteristics. Experimental validation revealed that, except for the relative errors at the endpoints of the model's independent variable intervals (approximately 7 %) of the model, all other errors were below 4 %, indicating high accuracy of the regression model. This work provides a methodological and theoretical basis for optimizing operational parameters in PFPW membrane treatment, and predicting Jv under specified conditions to support energy savings and consumption reduction. © 2025 Elsevier B.V.
Publisher: Elsevier B.V.

Intrinsic drivers of urban flood disasters from the resilience perspective in China - Li, Xiaojuan; Chen, Rixin; Ren, Yifei; Jim, C.Y. (Reliability Engineering and System Safety, 2026)
Urban flood disasters pose substantial threats to public safety and urban development, with climate change exacerbating the intensity, frequency, and consequences of such events. While existing research has predominantly concentrated on flood control and disaster response, limited attention has been paid to the underlying drivers and evolutionary mechanisms of urban flood resilience. This study applies the resilience framework to develop an integrated methodology for assessing urban flood resilience. Focusing on three coastal provinces in China that frequently experience severe flooding, the study identifies fifteen key resilience drivers to construct a compound driver system. The evolution of flood resilience is examined through the lens of the Pressure-State-Response (PSR) model, which categorizes the drivers into three distinct dimensions. The Decision Making Trial and Evaluation Laboratory (DEMATEL) and Interpretative Structural Model (ISM) methods are employed to analyze the interrelationships and hierarchical structure among drivers. In parallel, a system dynamics (SD) modeling approach is used to construct causal-loop and stock-flow diagrams, revealing the complex interdependencies and critical pathways across resilience dimensions. The analysis identifies rainfall intensity as the most influential driver in shaping urban flood resilience. Scenario simulations based on the SD model explore variations in resilience performance under three developmental pathways. Findings suggest that enhancing response resilience is crucial under current flood control trajectories. This study contributes novel conceptual and methodological insights into the measurement and evolution of urban flood resilience. It offers actionable guidance for policymakers aiming to strengthen flood risk governance and urban safety. © 2025 Elsevier Ltd
Publisher: Elsevier Ltd

Enhancing flood prediction in the Lower Mekong River Basin by scale-independent interpretable deep learning model - Qiu, Yangzi; Shi, Xiaogang; He, Xiaogang (Environmental Impact Assessment Review, 2026)
Climate change has increased the frequency and intensity of extreme floods in the Lower Mekong River Basin (LMB). This study leverages the Long Short-Term Memory (LSTM) model to evaluate its performance in predicting river discharge across the LMB and to identify the key variables contributing to flood prediction through SHapley Additive exPlanation (SHAP) and Universal Multifractal (UM) analyses, in a scale-dependent and scale-independent manner, respectively. The performance of the LSTM model is satisfactory, with Nash–Sutcliffe Efficiency (NSE) values exceeding 0.9 for all subbasins when using all input features. The model tends to underestimate the largest peak flows in the midstream subbasins that experienced extreme rainfall events. According to SHAP, soil-related variables are important contributors to discharge prediction, with their impacts partially manifested through interactions with precipitation and runoff. Furthermore, the dominant contributing variables influencing flood prediction vary over time: soil-related variables and vegetation-related variables played a more significant role in earlier years, whereas hydrometeorological variables became more dominant after 2017. The UM analysis investigates the scaling behaviours of contributing variables, showing that hydrometeorological-related variables have a greater influence on predicting extreme discharge across the small temporal scales. Additionally, the UM analysis indicates that the model's performance improves as the temporal variability in extremes of the combined features decreases across 1 to 16 days. Overall, this study provides a comprehensive assessment of the LSTM model's performance in discharge prediction, emphasising the impact of the variability in the extremes of combined features through the scale-independent interpretation. These findings will offer valuable insights for stakeholders to improve flood risk management across the LMB. © 2025 The Authors
Publisher: Elsevier Inc.

Reservoir Potential Unlocked: Synergies Between Low-Salinity Water Flooding, Nanoparticles and Surfactants in Enhanced Oil Recovery─A Review - Mumbere, Walidi; Sagala, Farad; Gupta, Uttam; Bbosa, Denis (ACS Omega, 2025)
This review explores the synergistic application of low-salinity water flooding (LSWF), nanoparticles, and surfactants in enhanced oil recovery (EOR), emphasizing their combined potential to address modern oil production challenges. It highlights the ability of LSWF to alter reservoir wettability, improve sweep efficiency, nanoparticles to enhance fluid mobility, and reduce interfacial tension, and surfactants to lower the interfacial tension and promote emulsification. All of this aim to provide practical, easy-to-use, and sustainable solutions for oil recovery. The review discusses existing research gaps in the long-term stability of nanoparticle-surfactant complexes, site-specific differences in rock-fluid interactions, and economic viability across diverse reservoirs. The review summarizes experimental findings, demonstrating recovery rates of 45–55% for nanoparticles, 50–60% for surfactants, and 40–50% for LSWF with improvements of 75–82% through this integrated approach. Additionally, the review addresses technological advancements, environmental considerations, and economic feasibility, highlighting challenges such as nanoparticle agglomeration and surfactant adsorption. A bibliographic analysis of global research trends, mechanisms, and field applications underscores the importance of interdisciplinary collaboration in optimizing this strategy for sustainable and efficient EOR processes. The findings aim to guide researchers and industry professionals in leveraging the synergistic effects of these methods to maximize oil recovery and reduce environmental footprints with a proposition to develop advanced characterization techniques, and verifying practicality through field implementation studies © 2025 The Authors. Published by American Chemical Society
Publisher: American Chemical Society

Impact of Climate Change on Human Health in Thailand: A Literature Review - Ratanawong, Pitcha; Nunthaitaweekul, Pachanat; Huynh, Phuong Trang; Weesakul, Uruya (Journal of Disaster Research, 2025)
This study aims to find and summarize published studies that examined the effects of climate change on human health and diseases in Thailand by conducting aliterature review using the preferred reporting items for systematic reviews and meta-analysis guidelines between October 17, 2023, and January 31, 2024. We earched PubMed and OvidSP for relevant research. We included studies that were written in English orThai; primary research focused on climate change or its subsets (natural disasters or climate issues, such as rising temperatures and altered weather patterns that increase the frequency, intensity, and severity of manynatural disasters and climate issues); focused on human health; indexed by PubMed or OvidSP; available as published research with full-text journal articles; and published in 2013 or later. Our search yielded 53 relevant articles. These articles identified five main categories of climate issues: temperature, rainfall/precipitation, humidity, wind speed, and flooding. We identified five categories of health issues: dengue, respiratory diseases and infections, malaria, skin diseases/symptoms, and other health issues. The most studied relationship is between temperature and dengue. Most articles reported the harmful effects of climate issues on health, although four reported opposite effects, and seven reported no significant associations. Among the 53 articles, ten utilized prediction models. The main goal of this review is to summarize current research to guide future studies and assist policymakers in prioritizing climate-related health policies in Thailand. Study limitations include the use of only two databases, the restriction to articles from 2013 onwards, and the inclusion of only articles in English and Thai, which may have limited the number of articles found for this literature review. © 2025, Fuji Technology Press. All rights reserved.
Publisher: Fuji Technology Press

Non-Aquatic Fauna of Amazonian Floodplain Forests and its Responses to Seasonal Flooding - Pedroza, Diego; Cohn-Haft, Mario; Haugaasen, Torbjørn (Wetlands, 2025)
The non-aquatic fauna (e.g. insects, birds, mammals) that occupies seasonally flooded floodplain forests in the Amazon is a major component of the region’s biodiversity, and the responses portrayed to cope with this inundation are varied. However, no systematic review of these species, including specialist species (exclusive to this environment), and their responses to seasonal inundation has yet been performed. Here, we provide an up-to-date and thorough examination of research on non-aquatic fauna that utilize Amazonian floodplain forests and their responses to seasonal flooding. We conducted a survey of published and unpublished studies from 1853 to 2023 through the Web of Science and Google Scholar platforms. We found a total of 445 studies, including 11,513 species of non-aquatic animals that inhabit floodplain forests. We identified ten main types of responses to flooding, the three most common being vertical migration, occupation of floating substrates and eggs submerged in a dormant state. Results suggest great behavioral, morphological and physiological plasticity among non-aquatic species, including those that are not floodplain forest specialists. Several types of responses occur independently in widely distinct taxonomic groups, emphasizing convergent strategies to deal with seasonal flooding. Our findings underline the uniqueness of the floodplain fauna and its importance for the regional biodiversity conservation agenda. © The Author(s), under exclusive licence to Society of Wetland Scientists 2025.
Publisher: Springer Science and Business Media B.V.

Harnessing Vegetation as a Nature-Based Solution for Integrated River Corridor Management: A Path Towards Harmonized Human–Nature Synergy - Maurya, Om Prakash; Nandi, Ketan Kumar; Dutta, Subashisa (Ecohydrology, 2025)
This review examines the role of vegetation as a nature-based solution (NBS) for sustainable river corridor management, integrating a wide range of interdisciplinary domains. It synthesizes studies addressing global challenges in river systems, the worldwide adoption of vegetation-based solutions and location-specific field observations from major Indian rivers such as the Brahmaputra and Ganga. This paper also reviews flume-scale experiments on vegetation–flow interactions and explores the biomechanical properties of vegetation, such as root reinforcement that contribute to riverbank stability. In addition, it discusses the selection of suitable species based on specific climatic regions, as reported in the literature. Building on this interdisciplinary understanding, this review highlights the vital role of vegetation in mitigating bank erosion, regulating sediment transport, attenuating floods and enhancing the overall health and resilience of riverine ecosystems and communities. It proposes an integrated framework that combines vegetation with biodegradable materials such as bamboo fencing and geo-bags and conventional engineering measures to address high-flow conditions and ensure long-term riverbank stability. Additionally, a flume-scale physical model study was conducted to investigate near-bank hydrodynamics in the presence of a series of three spurs and a combination of rigid and flexible vegetation. The results indicate that vegetation significantly reduces streamwise velocity near the bank, achieving performance comparable to that of the spur arrangement. This study identifies key challenges, including appropriate species selection, long-term maintenance of vegetation-based solutions and the need for adaptive management strategies. It further emphasizes the importance of stakeholder engagement for successful and sustainable implementation. © 2025 John Wiley & Sons Ltd.
Publisher: John Wiley and Sons Ltd

Managing floods and droughts synergistically: A transformative governance approach - Sánchez, Ana Núñez; Koehler, Johanna; Van Loon, Anne F. (PLOS Water, 2025)
Floods and droughts cause large economic and environmental impacts and incalculable human suffering. Despite growing evidence of important synergies in their management, floods and droughts tend to be mostly managed in silos. The synergistic management of flood and drought risk is limited by the inability of current governance systems to change at the scope, depth and speed required to address the emerging challenges of climate change induced hydroclimatic risks. Building on the concept of continuous transformational change and combining key elements across sectoral governance frameworks, this paper proposes a transformative governance conceptual framework that enables national governments to work across silos in a whole of government approach to lead a whole of society effort to manage the whole hydroclimatic spectrum. Spain, a country with an advanced hydroclimatic risk management system, is presented as an illustrative example to explore the possible idiosyncrasies of implementing the proposed changes on the ground. © 2025 Núñez Sánchez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Publisher: Public Library of Science

A systematic literature review of digital elevation models and hydrological models integration for advanced flood risk management - Ahmad, Raheel; Abdul Maulud, Khairul Nizam; Bin Zamir, Umair; Mohd Razali, Siti Fatin; Yaseen, Zaher Mundher; Pradhan, Biswajeet; Khan, Mohd Nazish; Eshquvvatov, Bekzod (Geomatics, Natural Hazards and Risk, 2025)
Floods are one of the most prevalent natural disasters, and advancements in geospatial technologies have revolutionized flood management, particularly the use of Digital Elevation Models (DEMs) in hydrological modelling. However, a comprehensive analysis DEMs integration in flood risk management is lacking. This study addresses this gap through a thorough Systematic Literature Review focusing on the combined application of DEMs and hydrological models in flood mitigation and risk management. The SLR scrutinized 21 articles, revealing eight key themes: DEM data sources and characteristics, DEM integration with hydrological models, flood hazard mapping applications, terrain impact assessment, model performance evaluation, machine learning in flood management, ecosystem services and resilience, and policy and governance implications. These findings emphasize the importance of precise DEM selection and correction for successful flood modelling, highlighting Advanced Land Observing Satellite as the most effective freely available DEM for use with the HEC-RAS unsteady flood model. This integration significantly enhances flood mitigation efforts and strengthens management strategies. Finally, this study underscores the pivotal role of DEM integration in crafting effective flood mitigation strategies, especially in addressing climate change challenges and bolstering community and ecosystem resilience. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Publisher: Taylor and Francis Ltd.

Climate-smart public health for global health resilience - Golden, Christopher D; Childs, Marissa L; Mudele, Oladimeji E; Andriamizarasoa, F Adolphe; Bouley, Timothy A; De Nicola, Giacomo; Fontaine, Max A; Huybers, Peter J; Mahatante, Paubert T; Rabemananjara, Rija; Rakotoarison, Norohasina; Ramambason, H Rakoto; et al. (The Lancet Planetary Health, 2025)
Climate change poses urgent public health risks from rising global temperatures and extreme weather events, including heatwaves, droughts, and floods, which disproportionately affect vulnerable populations. To address the current silos embedded in climate, environmental, and public health monitoring and surveillance systems, climate-smart public health (CSPH) creates an integrated platform for action across these sectors, enabling more rapid and efficient responses to climate-related public health challenges. In this Personal View, we introduce the concept of CSPH, a data-driven framework designed to monitor, assess, and adapt to climate-related health impacts. CSPH incorporates surveillance, risk assessment, early warning systems, and resilient health-care infrastructure to address the evolving challenges of climate change. The framework adopts an iterative, community-centred model that responds to local needs and incorporates feedback from health-care providers and policy makers. CSPH also leverages data science and artificial intelligence to address a wide range of health concerns, including infectious diseases, non-communicable diseases, nutrition, and mental health. We applied this framework in Madagascar, a region highly vulnerable to climate impacts, where poverty, malnutrition, and frequent extreme weather events make climate adaptation particularly urgent. Early data analysis has shown strong climate sensitivity in important diseases such as malaria and diarrhoea, which could enable preparedness efforts to target some regions more efficiently. CSPH provides a pathway to enhance resilience in such settings by improving the capacity of public health systems to withstand and respond to climate-related stressors. © 2025 The Author(s)
Publisher: Elsevier B.V.

Role of the internet of things in flood risk management: a critical review on current practices and future directions - Bakhtiari, Vahid; Kerchi, Hamed Darabi; Piadeh, Farzad; Behzadian, Kourosh; Nasirzadeh, Farnad (Natural Hazards, 2025)
The Internet of Things (IoT) has become increasingly important in flood risk management (FRM). This trend emerged as climate change intensified flooding events, driving the urgent need for localised early warning systems. Previous studies demonstrated the effectiveness of IoT sensors in forecasting potential floods and supporting flood modelling. However, comprehensive research addressing all FRM stages - prevention, mitigation, preparedness, response, and recovery - has remained limited. To address this research gap, this study identified five key IoT sensor categories: water quantity, water quality, rainfall intensity, weather conditions, and catchment characteristics. The roles, objectives, and applications of these sensors across FRM stages were then investigated. Results showed that water quantity sensors were the most common, accounting for 48% of documented IoT applications. Weather condition sensors (27%) and rainfall intensity sensors (21%) were also widely used, especially after 2021. Additionally, IoT-based FRM had three primary Objectives flood modelling (61%), alerting (25%), and visualisation (14%). Most cases (42%) focused on the preparedness stage, while prevention (8%) and recovery (5%) were underrepresented, highlighting clear gaps in existing research. The review also revealed several overlooked sensor types, including groundwater level, biochemical oxygen demand, and nitrite sensors. Despite their potential to enhance quality-based flood modelling, these sensors were rarely utilised. Consequently, the study emphasised the need for broader integration of IoT sensors throughout all FRM stages. Such integration could support more resilient, data-driven flood management strategies, particularly in regions where IoT deployment has remained limited. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.
Publisher: Springer Science and Business Media B.V.

Extreme and compound events in lakes - Woolway, R. Iestyn; Zhang, Yunlin; Jennings, Eleanor; Zohary, Tamar; Jane, Stephen F.; Jansen, Joachim; Weyhenmeyer, Gesa A.; Long, Di; Fleischmann, Ayan; Feng, Lian; Qin, Boqiang; Shi, Kun; et al. (Nature Reviews Earth and Environment, 2025)
Extreme and compound events disrupt lake ecosystems worldwide, with their frequency, intensity and duration increasing in response to climate change. In this Review we outline evidence of the occurrence, drivers and impact of extreme and compound events in lakes. Univariate extremes, which include lake heatwaves, droughts and floods, underwater dimming episodes and hypoxia, can occur concurrently, sequentially or simultaneously at different locations to form multivariate, temporal or spatial compound events, respectively. The probability of extreme and compound events is increasing owing to climate warming, declining lake water levels in half of lakes globally, and basin-scale anthropogenic stressors, such as nutrient pollution. Most in-lake extreme events are inherently compound in nature owing to tightly coupled physical, chemical and biological underlying processes. The cascading effects of compound events propagate or dissipate through lakes. For example, a heatwave might trigger stratification and oxygen depletion, subsequently leading to fish mortality or the proliferation of harmful algal blooms. Interactions between extremes are increasingly observed and can trigger feedback loops that exacerbate harmful algal blooms and fishery declines, leading to severe ecological and socio-economic consequences. Managing the increasing risk of compound events requires integrated models, coordinated monitoring and proactive adaptation strategies tailored to the vulnerabilities of lake ecosystems. © Springer Nature Limited 2025.
Publisher: Springer Nature

1st Main Report - Volume 1 now available! - IPBC (2025)
First Main Report“Drivers of behavioral change and non change in transition times” – First MAIN REPORT – VOLUME 1 IS NOW AVAILABLE! Download the Vol.1 of First Main Report The call for publication for this first volume that you are about to discover received an important number of proposals for chapters, with over 45 authors from […]

AI-Enhanced Coastal Flood Risk Assessment: A Real-Time Web Platform with Multi-Source Integration and Chesapeake Bay Case Study - Magoulick, Paul (Water (Switzerland), 2025)
A critical gap exists between coastal communities’ need for accessible flood risk assessment tools and the availability of sophisticated modeling, which remains limited by technical barriers and computational demands. This study introduces three key innovations through Coastal Defense Pro: (1) the first operational web-based AI ensemble for coastal flood risk assessment integrating real-time multi-agency data, (2) an automated regional calibration system that corrects systematic model biases through machine learning, and (3) browser-accessible implementation of research-grade modeling previously requiring specialized computational resources. The system combines Bayesian neural networks with optional LSTM and attention-based models, implementing automatic regional calibration and multi-source elevation consensus through a modular Python architecture. Real-time API integration achieves >99% system uptime with sub-3-second response times via intelligent caching. Validation against Hurricane Isabel (2003) demonstrates correction from 197% overprediction (6.92 m predicted vs. 2.33 m observed) to accurate prediction through automated identification of a Chesapeake Bay-specific reduction factor of 0.337. Comprehensive validation against 15 major storms (1992–2024) shows substantial improvement over standard methods (RMSE = 0.436 m vs. 2.267 m; R2 = 0.934 vs. −0.786). Economic assessment using NACCS fragility curves demonstrates 12.7-year payback periods for flood protection investments. The open-source Streamlit implementation democratizes access to research-grade risk assessment, transforming months-long specialist analyses into immediate browser-based tools without compromising scientific rigor. © 2025 by the author.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Research on the Comprehensive Evaluation Model of Risk in Flood Disaster Environments - Yu, Yan; Zhou, Tianhua (Water (Switzerland), 2025)
Losses from floods and the wide range of impacts have been at the forefront of hazard-triggered disasters in China. Affected by large-scale human activities and the environmental evolution, China’s defense flood situation is undergoing significant changes. This paper constructs a comprehensive flood disaster risk assessment model through systematic analysis of four key factors—hazard (H), exposure (E), susceptibility/sensitivity (S), and disaster prevention capabilities (C)—and establishes an evaluation index system. Using the Analytic Hierarchy Process (AHP), we determined indicator weights and quantified flood risk via the following formula R = H × E × V × C. After we applied this model to 16 towns in coastal Zhejiang Province, the results reveal three distinct risk tiers: low (R < 0.04), medium (0.04 ≤ R ≤ 0.1), and high (R > 0.1). High-risk areas (e.g., Longxi and Shitang towns) are primarily constrained by natural hazards and socioeconomic vulnerability, while low-risk towns benefit from a robust disaster mitigation capacity. Risk typology analysis further classifies towns into natural, social–structural, capacity-driven, or mixed profiles, providing granular insights for targeted flood management. The spatial risk distribution offers a scientific basis for optimizing flood control planning and resource allocation in the district. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Assessing Community Perception, Preparedness, and Adaptation to Urban Flood Risks in Malaysia - Kumaresen, Maniyammai; Teo, Fang Yenn; Selvarajoo, Anurita; Sivapalan, Subarna; Falconer, Roger A. (Water (Switzerland), 2025)
Urban flooding has significantly impacted the livelihoods of households and communities worldwide. It highlights the urgency of focusing on both flood preparedness and adaptation strategies to understand the community’s perception and adaptive capacity. This study investigates the levels of risk perception, flood preparedness, and adaptive capacity, while also exploring the inter-relationships among these factors within the context of urban flooding in Malaysia. A quantitative approach was employed, involving a structured questionnaire administered to residents in flood-prone urban areas across Greater Kuala Lumpur, Malaysia. A total of 212 responses were analysed using descriptive statistics, categorical index classification, and Spearman correlation analysis. The findings indicate that residents generally reported high levels of risk perception and preparedness, although adaptive capacity exhibited greater variability, with a mean score of 3.97 (SD = 0.64). Positive associations were found among risk perception, flood preparedness, and adaptive capacity. This study contributes to the existing knowledge by providing evidence on community resilience and highlighting key factors that can guide flood management policies and encourage adaptive planning at the community level. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Assessing Hydropower Impacts on Flood and Drought Hazards in the Lancang–Mekong River Using CNN-LSTM Machine Learning - Zhang, Muzi; Chi, Boying; Gu, Hongbin; Zhou, Jian; Chen, Honggang; Wang, Weiwei; Wang, Yicheng; Chen, Juanjuan; Yang, Xueqian; Zhang, Xuan (Water (Switzerland), 2025)
The efficient and rational development of hydropower in the Lancang–Mekong River Basin can promote green energy transition, reduce carbon emissions, prevent and mitigate flood and drought disasters, and ensure the sustainable development of the entire basin. In this study, based on publicly available hydrometeorological observation data and satellite remote sensing monitoring data from 2001 to 2020, a machine learning model of the Lancang–Mekong Basin was developed to reconstruct the basin’s hydrological processes, and identify the occurrence patterns and influencing mechanisms of water-related hazards. The results show that, against the background of climate change, the Lancang–Mekong Basin is affected by the increasing frequency and intensity of extreme precipitation events. In particular, Rx1day, Rx5day, R10mm, and R95p (extreme precipitation indicators determined by the World Meteorological Organization’s Expert Group on Climate Change Monitoring and Extreme Climate Events) in the northwestern part of the Mekong River Basin show upward trends, with the average maximum daily rainfall increasing by 1.8 mm/year and the total extreme precipitation increasing by 18 mm/year on average. The risks of flood and drought disasters will continue to rise. The flood peak period is mainly concentrated in August and September, with the annual maximum flood peak ranging from 5600 to 8500 m3/s. The Stung Treng Station exhibits longer drought duration, greater severity, and higher peak intensity than the Chiang Saen and Pakse Stations. At the Pakse Station, climate change and hydropower development have altered the non-drought proportion by −12.50% and +15.90%, respectively. For the Chiang Saen Station, the fragmentation degree of the drought index time series under the baseline, naturalized, and hydropower development scenarios is 0.901, 1.16, and 0.775, respectively. These results indicate that hydropower development has effectively reduced the frequency of rapid drought–flood transitions within the basin, thereby alleviating pressure on drought management efforts. The regulatory role of the cascade reservoirs in the Lancang River can mitigate risks posed by climate change, weaken adverse effects, reduce flood peak flows, alleviate hydrological droughts in the dry season, and decrease flash drought–flood transitions in the basin. The research findings can enable basin managers to proactively address climate change, develop science-based technical pathways for hydropower dispatch, and formulate adaptive disaster prevention and mitigation strategies. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

The Impact of Land Use Change on Improving Surface Runoff, Peak Flood Discharge, and Sedimentation in the Maros Watershed - Mansida, Amrullah; Gaffar, Farida; Zainuddin, Muh Amir; Syamsuri, Andi Makbul (Engineering, Technology and Applied Science Research, 2025)
The present study aims to analyze how land use changes affect surface runoff, flood peak discharge, and sedimentation. Moreover, it aims to assess the specific impact of these changes on the flood peak discharge and to propose effective strategies for reducing flood risks. Visual interpretation of the land use changes was utilized based on Landsat imagery from 2010, 2017, and 2021, along with SPOT 4 satellite data. Soil samples were collected to measure the erosion rates, water discharge, and sediment loads (both suspended and bedload). The findings showed a significant reduction in the secondary dryland forest, which shrank by 52.71 km² (a 7.99% decrease), while shrub and agricultural areas expanded by 51.03 km² (a 7.73% increase). This shift contributed to a greater surface runoff and an increased erosion, especially in dryland-shrubland areas, where erosion reached 4,248.33 tons/ha/year. The flood peak discharges rose sharply in areas converted to agriculture and settlements, halving the flood return period from 50 years to just 25 years. During the wet season, the sediment loads peaked at 782.17 tons/day (equivalent to 377,293.48 m³ per year), while the dry season sedimentation—mostly driven by quarrying—reached 10.45 tons/day. To address these issues, the current study proposes adopting adaptive spatial planning, restoring the watershed, and applying nature-based solutions, such as Biopore Absorption Holes (BAH), Rainwater Infiltration Wells (RIW), and similar technologies. © by the authors.
Publisher: Dr D. Pylarinos
Keywords: Scopus_Alert_22_Aout_2025

Identification of Critical Exposed Elements and Strategies for Mitigating Secondary Hazards in Flood-Induced Coal Mine Accidents - Yang, Xue; Liu, Chen; Pan, Langxuan; Su, Xiaona; He, Ke; Mao, Ziyu (Water (Switzerland), 2025)
Natech events, involving multi-hazard coupling and cascading effects, pose serious threats to coal mine safety. This paper addresses flood-induced Natech scenarios in coal mining and introduces a two-stage cascading analysis framework based on hazard systems theory. A tri-layered network—comprising natural hazards, exposed elements, and secondary hazards—models hazard propagation. In Stage 1, an improved adjacency information entropy algorithm with multi-hazard coupling coefficients identifies critical exposed elements. In Stage 2, Dijkstra’s algorithm extracts key risk transmission paths. A dual-dimensional classification method, based on entropy and transmission risk, is then applied to prioritize emergency responses. This method integrates the criticality of exposed elements with the risk levels associated with secondary disaster propagation paths. Case studies validate the framework, revealing: (1) Hierarchical heterogeneity in the network, with surface facilities and surrounding hydrological systems as central hubs; shaft and tunnel systems and surrounding geological systems are significantly affected by propagation from these core nodes, exhibiting marked instability. (2) Strong risk polarization in secondary hazard propagation, with core-node-originated paths being more efficient and urgent. (3) The entropy-risk classification enables targeted hazard control, improving efficiency. The study proposes chain-breaking strategies for precise, hierarchical, and timely emergency management, enhancing coal mine resilience to flood-induced Natech events. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Response of Grain Yield to Extreme Precipitation in Major Grain-Producing Areas of China Against the Background of Climate Change—A Case Study of Henan Province - Sheng, Keding; Li, Rui; Zhang, Fengqiuli; Chen, Tongde; Liu, Peng; Hu, Yanan; Li, Bingyin; Song, Zhiyuan (Water (Switzerland), 2025)
Based on the panel data of daily meteorological stations and winter wheat yield in Henan Province from 2000 to 2023, this study comprehensively used the Mann–Kendall trend test, wavelet coherence analysis (WTC), and other methods to reveal the temporal and spatial evolution of extreme precipitation and its multi-scale stress mechanism on grain yield. The results showed the following: (1) Extreme precipitation showed the characteristics of ‘frequent fluctuation-gentle trend-strong spatial heterogeneity’, and the maximum daily precipitation in spring (RX1DAY) showed a significant uplift. The increase in rainstorm events (R95p/R99p) in the southern region during the summer is particularly prominent; at the same time, the number of consecutive drought days (CDDs > 15 d) in the middle of autumn was significantly prolonged. It was also found that 2010 is a significant mutation node. Since then, the synergistic effect of ‘increasing drought days–increasing rainstorm frequency’ has begun to appear, and the short-period coherence of super-strong precipitation (R99p) has risen to more than 0.8. (2) The spatial pattern of winter wheat in Henan is characterized by the three-level differentiation of ‘stable core area, sensitive transition zone and shrinking suburban area’, and the stability of winter wheat has improved but there are still local risks. (3) There is a multi-scale stress mechanism of extreme precipitation on winter wheat yield. The long-period (4–8 years) drought and flood events drive the system risk through a 1–2-year lag effect (short-period (0.5–2 years) medium rainstorm intensity directly impacted the production system). This study proposes a ‘sub-scale governance’ strategy, using a 1–2-year lag window to establish a rainstorm warning mechanism, and optimizing drainage facilities for high-risk areas of floods in the south to improve the climate resilience of the agricultural system against the background of climate change. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Empirical Modelling of Ice-Jam Flood Hazards Along the Mackenzie River in a Changing Climate - Lindenschmidt, Karl-Erich; Gomez, Sergio; Saade, Jad; Perry, Brian; Das, Apurba (Water (Switzerland), 2025)
This study introduces a novel methodology for assessing ice-jam flood hazards along river channels. It employs empirical equations that relate non-dimensional ice-jam stage to discharge, enabling the generation of an ensemble of longitudinal profiles of ice-jam backwater levels through Monte-Carlo simulations. These simulations produce non-exceedance probability profiles, which indicate the likelihood of various flood levels occurring due to ice jams. The flood levels associated with specific return periods were validated using historical gauge records. The empirical equations require input parameters such as channel width, slope, and thalweg elevation, which were obtained from bathymetric surveys. This approach is applied to assess ice-jam flood hazards by extrapolating data from a gauged reach at Fort Simpson to an ungauged reach at Jean Marie River along the Mackenzie River in Canada’s Northwest Territories. The analysis further suggests that climate change is likely to increase the severity of ice-jam flood hazards in both reaches by the end of the century. This methodology is applicable to other cold-region rivers in Canada and northern Europe, provided similar fluvial geomorphological and hydro-meteorological data are available, making it a valuable tool for ice-jam flood risk assessment in other ungauged areas. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Hydrodynamic and Sedimentological Impacts of Intake Gate Opening Adjustments for Flood Mitigation in Water Systems - Rahmawati; Tumpu, Miswar; Yunianta, Andung (Engineering, Technology and Applied Science Research, 2025)
Sediment management poses a significant challenge in hydraulic systems, affecting the water flow efficiency, structural durability, and operational reliability. The operation of the intake gate greatly influences the sediment characteristics, including the transport, deposition, and distribution patterns. This study investigates how different intake gate openings impact the sediment behavior in hydraulic systems to improve the operational strategies and reduce sediment-related problems. An experimental method was employed using a scaled physical model in controlled laboratory conditions, where various intake gate configurations were tested at consistent flow rates to simulate real-world hydraulic structures. Sediment samples were analyzed for grain size distribution, deposition patterns, and transport process dynamics. Data were gathered through direct measurements and video recordings, and then processed using sediment analysis software. The results showed that larger intake openings promote the sediment transport downstream and reduce the localized deposition near the intake. Conversely, smaller openings lead to sediment accumulation at the gate, increasing the risk of blockage and operational inefficiencies. Over time, these patterns evolve, potentially causing long-term sediment accumulation or channel scouring depending on the frequency and the way the gate is adjusted. Based on these findings, the study proposes adaptive, long-term sediment management approaches, including periodic gate operation adjustments, sediment flushing protocols, and comprehensive monitoring systems. These strategies aim to balance the sediment transport and deposition over extended operational periods, enhancing the performance and sustainability of hydraulic infrastructure, such as irrigation channels, reservoirs, and hydropower plants. © 2025, Dr D. Pylarinos. All rights reserved.
Publisher: Dr D. Pylarinos
Keywords: Scopus_Alert_22_Aout_2025

Analysis of the Availability of Residential Locations Based on Flood Mitigation in Momunu District, Buol Regency - Assiddiqi, Moh. Hasbi; Lanuru, Mahatma; Tumpu, Miswar (Engineering, Technology and Applied Science Research, 2025)
The population growth and limited land availability for housing have forced some communities to reside in disaster-prone areas, particularly those vulnerable to flooding. This study, presents a spatial-based assessment that integrates physical and regulatory criteria to identify safe and appropriate residential zones. Using spatial analysis through map overlays, scoring, and weighting techniques, the research evaluates seven key physical variables: land slope, drainage, erosion, land use, road accessibility, access to essential facilities, and flood hazard vulnerability. The novelty of this study lies in the integration of flood mitigation into residential suitability mapping that is aligned with the Regional Spatial Plan (RTRW), offering a comprehensive and policy-relevant framework. The findings reveal that 20.85% of the study area is suitable for housing, 61.83% is conditionally suitable, and 17.32% is unsuitable. Based on the land availability and RTRW compliance, residential land is categorized into Available Location I (47 hectares) and Available Location II (423 hectares). These results provide not only a technical basis for guiding safe settlement, but also a strategic reference for planners and policymakers. The study proposes that future research incorporates socio-economic variables and real-time flood data for dynamic risk assessment. Furthermore, stakeholder engagement and community-based mapping are proposed to enhance the local resilience and ensure participatory planning. Ultimately, this research contributes to sustainable urban development by supporting informed decision-making for safer, flood-resilient settlements. © by the authors.
Publisher: Dr D. Pylarinos
Keywords: Scopus_Alert_22_Aout_2025

Assessing Flooding from Changes in Extreme Rainfall: Using the Design Rainfall Approach in Hydrologic Modeling - Jalowska, Anna M.; Line, Daniel E.; Spero, Tanya L.; Kurki-Fox, J. Jack; Doll, Barbara A.; Bowden, Jared H.; Gray, Geneva M. E. (Water (Switzerland), 2025)
Quantifying future changes in extreme events and associated flooding is challenging yet fundamental for stormwater managers. Along the U.S. Atlantic Coast, Eastern North Carolina (ENC) is frequently exposed to catastrophic floods from extreme rainfall that is typically associated with tropical cyclones. This study presents a novel approach that uses rainfall data from five dynamically and statistically downscaled (DD and SD) global climate models under two scenarios to visualize a potential future extent of flooding in ENC. Here, we use DD data (at 36-km grid spacing) to compute future changes in precipitation intensity–duration–frequency (PIDF) curves at the end of the 21st century. These PIDF curves are further applied to observed rainfall from Hurricane Matthew—a landfalling storm that created widespread flooding across ENC in 2016—to project versions of “Matthew 2100” that reflect changes in extreme precipitation under those scenarios. Each Matthew-2100 rainfall distribution was then used in hydrologic models (HEC-HMS and HEC-RAS) to simulate “2100” discharges and flooding extents in the Neuse River Basin (4686 km2) in ENC. The results show that DD datasets better represented historical changes in extreme rainfall than SD datasets. The projected changes in ENC rainfall (up to 112%) exceed values published for the U.S. but do not exceed historical values. The peak discharges for Matthew-2100 could increase by 23–69%, with 0.4–3 m increases in water surface elevation and 8–57% increases in flooded area. The projected increases in flooding would threaten people, ecosystems, agriculture, infrastructure, and the economy throughout ENC. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Machine learning-based ensemble of Global climate models and trend analysis for projecting extreme precipitation indices under future climate scenarios - Kumar, G. Praveen; Dwarakish, G.S. (Environmental Monitoring and Assessment, 2025)
Monitoring changes in climatic extremes is vital, as they influence current and future climate while significantly impacting ecosystems and society. This study examines trends in extreme precipitation indices over an Indian tropical river basin, analyzing and ranking 28 Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs) based on their performance against India Meteorological Department (IMD) data. The top five performing GCMs were selected to construct multi-model ensembles (MMEs) using Machine Learning (ML) algorithms, Random Forest (RF), Support Vector Machine (SVM), Multiple Linear Regression (MLR), and the Arithmetic Mean. Statistical metrics reveal that the application of an RF model for ensembling performs better than other models. The analysis focused on six IMD-convention indices and eight indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). Future projections were examined for three timeframes: near future (2025–2050), mid-future (2051–2075), and far future (2076–2100) for SSP245 and SSP585 scenarios. Statistical trend analysis, the Mann-Kendall test, Sen’s Slope estimator, and Innovative Trend Analysis (ITA), were applied to the MME to assess variability and detect changes in extreme precipitation trends. Compared to SSP245, in the SSP585 scenario, Total Precipitation (PRCPTOT) shows a significant decreasing trend in the near future, mid-future, and far future and Moderate Rain (MR) shows a decreasing trend in the near future and far future of monsoon season. The findings reveal significant future trends in extreme precipitation, impacting Sustainable Development Goals (SDGs) achievement and providing crucial insights for sustainable water resource management and policy planning in the Kali River basin. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.
Publisher: Springer Science and Business Media Deutschland GmbH
Keywords: Scopus_Alert_22_Aout_2025

Multi-Sensor Flood Mapping in Urban and Agricultural Landscapes of the Netherlands Using SAR and Optical Data with Random Forest Classifier - Narin, Omer Gokberk; Sekertekin, Aliihsan; Bayik, Caglar; Bektas Balcik, Filiz; Arıkan, Mahmut; Sanli, Fusun Balik; Abdikan, Saygin (Remote Sensing, 2025)
Floods stand as one of the most harmful natural disasters, which have become more dangerous because of climate change effects on urban structures and agricultural fields. This research presents a comprehensive flood mapping approach that combines multi-sensor satellite data with a machine learning method to evaluate the July 2021 flood in the Netherlands. The research developed 25 different feature scenarios through the combination of Sentinel-1, Landsat-8, and Radarsat-2 imagery data by using backscattering coefficients together with optical Normalized Difference Water Index (NDWI) and Hue, Saturation, and Value (HSV) images and Synthetic Aperture Radar (SAR)-derived Grey Level Co-occurrence Matrix (GLCM) texture features. The Random Forest (RF) classifier was optimized before its application based on two different flood-prone regions, which included Zutphen’s urban area and Heijen’s agricultural land. Results demonstrated that the multi-sensor fusion scenarios (S18, S20, and S25) achieved the highest classification performance, with overall accuracy reaching 96.4% (Kappa = 0.906–0.949) in Zutphen and 87.5% (Kappa = 0.754–0.833) in Heijen. For the flood class F1 scores of all scenarios, they varied from 0.742 to 0.969 in Zutphen and from 0.626 to 0.969 in Heijen. Eventually, the addition of SAR texture metrics enhanced flood boundary identification throughout both urban and agricultural settings. Radarsat-2 provided limited benefits to the overall results, since Sentinel-1 and Landsat-8 data proved more effective despite being freely available. This study demonstrates that using SAR and optical features together with texture information creates a powerful and expandable flood mapping system, and RF classification performs well in diverse landscape settings. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Predictive Flood Uncertainty Associated with the Overtopping Rates of Vertical Seawall on Coral Reef Topography - Zhang, Hongqian; Lu, Bin; Geng, Yumei; Liu, Ye (Water (Switzerland), 2025)
Accurate prediction of wave overtopping rates is essential for flood risk assessment along coral reef coastlines. This study quantifies the uncertainty sources affecting overtopping rates for vertical seawalls on reef flats, using ensemble simulations with a validated non-hydrostatic SWASH model. By generating extensive random wave sequences, we identify spectral resolution, wave spectral width, and wave groupiness as the dominant controls on the uncertainty. Statistical metrics, including the Coefficient of Variation ((Formula presented.)) and Range Uncertainty Level ((Formula presented.)), demonstrate that overtopping rates exhibit substantial variability under randomized wave conditions, with (Formula presented.) exceeding 40% for low spectral resolutions (50–100 bins), while achieving statistical convergence ((Formula presented.) around 20%) requires at least 700 frequency bins, far surpassing conventional standards. The (Formula presented.), which describes the ratio of extreme to minimal overtopping rates, also decreases markedly as the number of frequency bins increases from 50 to 700. It is found that the overtopping rate follows a normal distribution with 700 frequency bins in wave generation. Simulations further demonstrate that overtopping rates increase by a factor of 2–4 as the JONSWAP spectrum peak enhancement factor ((Formula presented.)) increases from 1 to 7. The wave groupiness factor ((Formula presented.)) emerges as a predictor of overtopping variability, enabling a more efficient experimental design through reduction in groupiness-guided replication. These findings establish practical thresholds for experimental design and highlight the critical role of spectral parameters in hazard assessment. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Innovative Approaches to Flood Hazard Assessment in Semi-Arid Environments: A Comparative Analysis of Multi-Criteria and Geospatial Techniques - Chomani, Kaifi; Al-Shrafany, Dleen M. (Iraqi Geological Journal, 2025)
Flood intensity has significantly increased globally, which poses significant challenges for the environment and urban areas. This research aimed to evaluate the performance of different flood hazard assessment approaches to identify flood risk areas in Erbil city, Kurdistan region of Iraq. The analytical hierarchy process and the new ArcGIS pro flood simulation tool were compared to identify flood-risk areas and assess their performance based on historical flood events. Multiple factors such as rainfall, aspect, topographic wetness index, elevation, flow accumulation, lithology, soil data, normalized difference vegetation index, normalized difference built-up index, land use land cover, slope, stream power index, drainage density, evapotranspiration, infiltration rates, and distance to roads were considered to identify flood risk areas. Using the Analytical Hierarchy Process, areas spanning over 35 km² (3.9%) and 74 km² (27%) of Erbil city were identified as very high and high flood susceptible, respectively. However, the results of AFS indicated that an area of 66.3 km² (7.3%) of Erbil city will be inundated during rainfall intensity of 60 mm/day. The receiver operating characteristic area under the curve assessments showed the accuracy of AFS to be 95.3% and that of the Analytical Hierarchy Process to be 92.2%. The comparison analysis emphasized the effectiveness of ArcGIS Pro flood simulation in terms of accurate flood inundation assessments. This research provides significant insights into suitable approaches to flood hazard assessment by considering different scales and data availability, helping policymakers and urban planners understand floods better and implement appropriate mitigation strategies accordingly. © 2025, Union of Iraqi Geologists. All rights reserved.
Publisher: Union of Iraqi Geologists
Keywords: Scopus_Alert_22_Aout_2025

Toward optimal rainfall for flood prediction in headwater basins – improving soil moisture initialization to close the water budget within observational uncertainty - Liao, Mochi; Barros, Ana P. (Journal of Hydrology: Regional Studies, 2025)
Keywords: Scopus_Alert_22_Aout_2025

A multi-hazard assessment approach to reveal and compare heat- and flood-related risks and inequalities in London, Boston, and Sydney - Longato, Davide; Maragno, Denis (International Journal of Disaster Risk Reduction, 2025)
Keywords: Scopus_Alert_22_Aout_2025

Floods, land loss, and gendered vulnerability: Assessing the social impacts of small hydropower in Vietnam - Swe, Khin Nilar; Phuong, Ho Thi; Thinh, Tran Duc; Chan, Nyien (Environmental Development, 2025)
Keywords: Scopus_Alert_22_Aout_2025

Pervious concrete pavements for climate change adaptation and mitigation: a systematic review of performance, sustainability, and future perspectives - Wu, Yinglong; López-Carreño, Rubén-Daniel; Aidarov, Stanislav; Álvarez, Pablo Pujadas (Road Materials and Pavement Design, 2025)
Keywords: Scopus_Alert_22_Aout_2025

Hydrology and Climate Change in Africa: Contemporary Challenges, and Future Resilience Pathways - Adeyeri, Oluwafemi E. (Water, 2025)
African hydrological systems are incredibly complex and highly sensitive to climate variability. This review synthesizes observational data, remote sensing, and climate modeling to understand the interactions between fluvial processes, water cycle dynamics, and anthropogenic pressures. Currently, these systems are experiencing accelerating warming (+0.3 °C/decade), leading to more intense hydrological extremes and regionally varied responses. For example, East Africa has shown reversed temperature–moisture correlations since the Holocene onset, while West African rivers demonstrate nonlinear runoff sensitivity (a threefold reduction per unit decline in rainfall). Land-use and land-cover changes (LULCC) are as impactful as climate change, with analysis from 1959–2014 revealing extensive conversion of primary non-forest land and a more than sixfold increase in the intensity of pastureland expansion by the early 21st century. Future projections, exemplified by studies in basins like Ethiopia’s Gilgel Gibe and Ghana’s Vea, indicate escalating aridity with significant reductions in surface runoff and groundwater recharge, increasing aquifer stress. These findings underscore the need for integrated adaptation strategies that leverage remote sensing, nature-based solutions, and transboundary governance to build resilient water futures across Africa’s diverse basins.
Keywords: Scopus_Alert_22_Aout_2025

Current Research on Quantifying Cotton Yield Responses to Waterlogging Stress: Indicators and Yield Vulnerability - Qian, Long; Luo, Yunying; Duan, Kai (Plants, 2025)
Cotton (Gossypium spp.) is an important industrial crop, but it is vulnerable to waterlogging stress. The relationship between cotton yields and waterlogging indicators (CY-WI) is fundamental for waterlogging disaster reduction. This review systematically summarized and analyzed literature containing CY-WI relations across 1970s–2020s. China conducted the most CY-WI experiments (67%), followed by Australia (17%). Recent decades (2010s, 2000s) contributed the highest proportion of CY-WI works (49%, 15%). Surface waterlogging form is mostly employed (74%) much more than sub-surface waterlogging. The flowering and boll-forming stage, followed by the budding stage, performed the most CY-WI experiments (55%), and they showed stronger negative relations of CY-WI than other stages. Some compound stresses enhance negative relations of CY-WI, such as accompanying high temperatures, low temperatures, and shade conditions, whereas some others weaken the negative CY-WI relations, such as prior/post drought and waterlogging. Anti-waterlogging applications significantly weaken negative CY-WI relations. Regional-scale CY-WI research is increasing now, and they verified the influence of compound stresses. In future CI-WI works, we should emphasize the influence of compound stresses, establish regional CY-WI relations regarding cotton growth features, examine more updated cotton cultivars, focus on initial and late cotton stages, and explore the consequence of high-deep submergence.
Keywords: Scopus_Alert_22_Aout_2025

Nature-Based Solutions for Water Management in Europe: What Works, What Does Not, and What’s Next? - Santos, Eleonora (Water, 2025)
Nature-based solutions (NbS) are increasingly recognized as strategic alternatives and complements to grey infrastructure for addressing water-related challenges in the context of climate change, urbanization, and biodiversity decline. This article presents a critical, theory-informed review of the state of NbS implementation in European water management, drawing on a structured synthesis of empirical evidence from regional case studies and policy frameworks. The analysis found that while NbS are effective in reducing surface runoff, mitigating floods, and improving water quality under low- to moderate-intensity events, their performance remains uncertain under extreme climate scenarios. Key gaps identified include the lack of long-term monitoring data, limited assessment of NbS under future climate conditions, and weak integration into mainstream planning and financing systems. Existing evaluation frameworks are critiqued for treating NbS as static interventions, overlooking their ecological dynamics and temporal variability. In response, a dynamic, climate-resilient assessment model is proposed—grounded in systems thinking, backcasting, and participatory scenario planning—to evaluate NbS adaptively. Emerging innovations, such as hybrid green–grey infrastructure, adaptive governance models, and novel financing mechanisms, are highlighted as key enablers for scaling NbS. The article contributes to the scientific literature by bridging theoretical and empirical insights, offering region-specific findings and recommendations based on a comparative analysis across diverse European contexts. These findings provide conceptual and methodological tools to better design, evaluate, and scale NbS for transformative, equitable, and climate-resilient water governance.
Keywords: Scopus_Alert_22_Aout_2025

The Paradigm Shift in Scientific Interest on Flood Risk: From Hydraulic Analysis to Integrated Land Use Planning Approaches - Franco, Ángela; García-Ayllón, Salvador (Water, 2025)
Floods are natural hazards that have the greatest socioeconomic impact worldwide, given that 23% of the global population live in urban areas at risk of flooding. In this field of research, the analysis of flood risk has traditionally been studied based mainly on approaches specific to civil engineering such as hydraulics and hydrology. However, these patterns of approaching the problem in research seem to be changing in recent years. During the last few years, a growing trend has been observed towards the use of methodology-based approaches oriented towards urban planning and land use management. In this context, this study analyzes the evolution of these research patterns in the field by developing a bibliometric meta-analysis of 2694 scientific publications on this topic published in recent decades. Evaluating keyword co-occurrence using VOSviewer software version 1.6.20, we analyzed how phenomena such as climate change have modified the way of addressing the study of this problem, giving growing weight to the use of integrated approaches improving territorial planning or implementing adaptive strategies, as opposed to the more traditional vision of previous decades, which only focused on the construction of hydraulic infrastructures for flood control.
Keywords: Scopus_Alert_22_Aout_2025

Exploring Waterlogging Challenges, Causes and Mitigating Strategies in Maize ( Zea mays L.) - Behera, Supriya; Kar, Ipsita; Yadav, Ashok; Sahu, Ankita (Journal of Agronomy and Crop Science, 2025)
ABSTRACT Waterlogging is a critical abiotic stress factor severely affecting maize, one of the World's most widely cultivated cereal crops. Globally, maize is a crucial food crop, grown in diverse agro‐climatic zones, from subtropical to temperate climates. Waterlogging, resulting from flooding, intense rainfall and inefficient drainage systems, continues to be a major abiotic stress factor influencing crop productivity globally. Prolonged exposure to excess soil moisture leads to oxygen depletion in the root zone, resulting in restricted aerobic respiration, impaired nutrient uptake and disruption of physiological processes. This review aims to provide a comprehensive overview of the morphological, physiological and biochemical changes maize undergoes in response to waterlogging stress. Key aspects such as root system adaptation, reduction in photosynthetic efficiency, accumulation of reactive oxygen species (ROS) and hormonal imbalances are systematically examined. Furthermore, we delve into the metabolic shifts that enable maize to survive under anaerobic conditions, including alterations in energy metabolism, carbohydrate partitioning, and activating antioxidant defence mechanisms. The role of key signalling molecules such as ethylene is explored, highlighting their involvement in regulating stress responses. Additionally, the review discusses agronomic and genetic approaches for improving waterlogging tolerance in maize, including the development of stress‐resilient cultivars through breeding and biotechnological interventions. By synthesising recent advances in understanding maize's response to waterlogging, this paper identifies gaps and proposes future research directions, focusing on the integration of molecular and field‐based strategies. The insights from this review are crucial for developing sustainable agricultural practices aimed at mitigating the adverse impacts of waterlogging on maize productivity, particularly in flood‐prone areas. Breeding for waterlogging resilience integrates the creation of robust varieties, plant morphology optimisation, and utilisation of tolerant secondary traits through combined conventional and biotechnological breeding strategies.
Keywords: Scopus_Alert_22_Aout_2025

Hydrological Analysis and Impacts of Natural Flood Management Strategies: A Systematic Review - Bagheri‐Gavkosh, Mehdi; Panici, Diego; Puttock, Alan; Dauben, Tom; Brazier, Richard E. (Journal of Flood Risk Management, 2025)
ABSTRACT Natural flood management strategies (NFMs) encompass a variety of measures implemented across catchments to mitigate flood risks while providing multiple benefits. In recent years, NFMs have gained increasing attention from researchers and policymakers. However, despite the growing body of research, there remains a lack of a critical review that quantitatively synthesises the reported performance of different NFMs by analysing their effects on key hydrological parameters. To address this gap, we conducted a systematic review of NFMs based on 145 peer‐reviewed papers covering 216 case studies across 37 countries, following the preferred reporting items for systematic reviews and meta‐analyses (PRISMA) guidelines. Our analysis moves from a descriptive overview of the evidence base to a novel, quantitative investigation of three critical themes: the characteristics of studied NFM schemes, the methodologies used for their assessment, and their quantitative hydrological performance and its influencing factors. Results indicate that 31% of the studies identified flood peak reduction as the most commonly targeted hydrological objective. A significant positive correlation was found between intervention diversity and intensity (Spearman's ρ = 0.53). Furthermore, our methodological analysis reveals a critical trade‐off in the literature, with empirical monitoring typically used in small catchments over shorter durations, while modelling is used to assess a greater diversity of interventions at larger scales, with truly combined approaches being notably rare (11%). Notably, river and floodplain management (RFM) demonstrated higher effectiveness, achieving an average flood peak reduction of 30%, particularly in larger catchments. Bearing the often multi‐faceted aims of NFMs in mind, this paper provides key suggestions for future research.
Keywords: Scopus_Alert_22_Aout_2025

Geoinformatics-based watershed-level flood hazard analysis using fuzzy analytic hierarchy process across the Ganga–Brahmaputra basin - Kaushik, Kavita; Pandey, Arvind Chandra; Parida, Bikash Ranjan; Dwivedi, Chandra Shekhar (Journal of Earth System Science, 2025)
The flood disasters are prevalent in the Ganga–Brahmaputra (GB) basin with recurrent occurrences and severe impacts across the major watersheds. The present study analyses the vulnerability of 44 watersheds to flood inundation and its impact on cropland, urban areas, and population. The Sentinel-1 dataset was utilised to analyse flood extent and frequency from 2015 to 2022, enabling the identification of flood-prone watersheds in the Ganga–Brahmaputra basin. The analysis revealed that 7 watersheds in the Ganga basin and 12 watersheds in the Brahmaputra basin are particularly vulnerable to flooding. The flood hazard analysis was performed using fuzzy-AHP (Analytic Hierarchy Process), focusing on six parameters, including topographic wetness index (TWI), elevation, precipitation, drainage density, distance from river, and NDVI for the selected 19 watersheds. The inundation analysis from 2015 to 2022 revealed that the maximum flood extent was observed in 2020, with an affected area of 33,537.6 km2 and 34,937.9 km2 in the Ganga–Brahmaputra basin, respectively. The flood hazard analysis identified Upper Ganga (8877.52 km2), Ghaghara (18573.9 km2) and Teesta (1543.06 km2) as having the highest proportion of their geographical area under very high-hazard zone and the highest percentage in the very low hazard zones were observed in Jamuneshwary (1093.55 km2), Atreyee (4410.42 km2), and Kulsi (1273.89 km2). By first mapping these watersheds with precision and then using various parameters for flood hazard analysis, it ensures accurate identification of flood-prone areas, offering valuable insights for flood management and mitigation in a critical region. © Indian Academy of Sciences 2025.
Publisher: Springer
Keywords: Scopus_Alert_15_Aout_2025

Quantifying the spatiotemporal dynamics of urban flooding susceptibility in the greater bay area under shared socio-economic pathways using the SD-PLUS-LightGBM framework - Zhou, Shiqi; Jia, Weiyi; Geng, Xiwen; Xu, Haowen; Diao, Haifeng; Liu, Zhiyu; Wang, Mo; Fu, Xiaoping; Wu, Yuwei; Qiao, Renlu; Wu, Zhiqiang (Resources, Conservation and Recycling, 2025)
Urbanization and climate change keep intensifying extreme rainfall events. Previous studies have explored urban flood susceptibility, yet a comprehensive approach that unifies these perspectives has remained underdeveloped. This study established a holistic framework using the SD-PLUS-LightGBM model with multiple variables under three SSP-RCP scenarios to predict spatial-temporal dynamics of flood susceptibility in the Greater Bay Area between 2030 and 2050. Compared with traditional models, LightGBM established superior predictive accuracy and operational reliability for urban flood susceptibility mapping. The results indicated a non-linear expansion of high-susceptibility zones, with SSP5–8.5 projections showing a two-fold increase in vulnerable areas by 2050 relative to 2020 baselines. Regions experiencing pronounced susceptibility transitions were expected to grow significantly (0.23 % of the total area), concentrated in historic urban cores and peri‑urban interfaces. This study offered an in-depth approach to stormwater management along with targeted recommendations for sustainable urban planning and design. © 2025
Publisher: Elsevier B.V.
Keywords: Scopus_Alert_15_Aout_2025

Deep learning-enhanced flood damage prediction: A DFNN-based hybrid approach with simplified inputs - Mok, Ji-Yoon; Moon, Hyeon-Tae; Kim, Gil-Ho; Kim, Kyung-Tak; Moon, Young-Il (International Journal of Disaster Risk Reduction, 2025)
This study proposes a hybrid urban flood damage prediction framework that integrates a Deep Feed-Forward Neural Network (DFNN) with a Rainfall-Runoff (R-R) model and the Korean Flood Risk Assessment Model (K-FRM). The model predicts 10 types of flood risk indicators (FRIs), including damage to residential and non-residential buildings, using only simplified rainfall variables (SRVs), eliminating the need for complex hydrodynamic simulations. Synthetic rainfall scenarios were generated for training and fed into the R-R model, whose outputs were processed through K-FRM to produce training data for the DFNN model. The optimized DFNN model was validated by comparing its predictions with flood damage estimates from K-FRM, demonstrating a Nash-Sutcliffe Efficiency (NSE) of up to 0.87 and an R2 of up to 0.88, indicating strong predictive performance across flood risk indicators. These results highlight the effectiveness of the DFNN-based hybrid approach in capturing flood damage patterns and providing rapid predictions using forecasted rainfall data. The proposed method offers a practical and computationally efficient tool for urban flood risk management and disaster mitigation planning. © 2025 The Authors
Publisher: Elsevier Ltd
Keywords: Scopus_Alert_15_Aout_2025

Seasonal Influences of Precipitation and River Stage on Groundwater Levels in Platte River Watersheds Vulnerable to Spring Floods - Kim, Incheol; Koya, Sinan Rasiya; Roy, Tirthankar; Eun, Jongwan (Journal of Hydrologic Engineering, 2025)
Spring floods occurring in the Midwest US are often aggravated by meteorological and hydrological conditions. In this study, the seasonal influences of precipitation (PRCP) and river stage (RS) on groundwater level (GWL) fluctuations were analyzed for the Middle and Lower Platte watersheds along the Platte River in a Midwestern catchment that is vulnerable to spring floods. Statistical analysis was conducted to simulate GWL with a moving average-based time lag consideration approach by using multiple hydrological data sets for 25 study sites. The results showed that the time lag consideration approach appropriately provided the regional information of water infiltration characteristics among GWL, PRCP, and RS for each study site. Also, the correlations of GWL with PRCP and RS were found to vary depending on the season. Especially in the early spring season, the correlation of GWL with PRCP is very weak (correlation coefficient=0.001 to 0.198). This may be due to entirely or partially frozen ground, which prevents rainwater from penetrating into the aquifer, causing large amounts of runoff and contributing to frequent flooding in early spring. In addition, statistical analysis showed that accounting for the time lag of PRCP and RS improved GWL simulation performance, and their influence varied by season. © 2025 American Society of Civil Engineers.
Publisher: American Society of Civil Engineers (ASCE)
Keywords: Scopus_Alert_15_Aout_2025

Comparative assessment of flood risk to critical infrastructure: The case of Utah, USA - Clark, Austin S.; Collins, Tim (International Journal of Disaster Risk Reduction, 2025)
During and after a disaster, selected services and systems are needed to recover and maintain important functions of society. These are deemed critical infrastructure (CI). When these services are disrupted due to the impacts of a disaster, response and recovery may be slowed or halted. As flooding events are occurring more often across larger geographic extents, advancing methods for assessing risks of flooding to CI is vital. We use Utah, USA as a case study to demonstrate a novel, transferable approach for assessing fine-scale flood risks to CI across large geographic areas. Specifically, our assessment approach integrates high-resolution building footprints of schools, first responder facilities, and hospitals, and flood risk maps from a state-of-the-art big data flood model and the U.S. Federal Emergency Management Agency (FEMA). We show that 94 CI facilities across Utah are at risk of severe flooding, and that those risks to CI are almost entirely overlooked by FEMA flood risk maps. Though nearly every CI building is located outside of FEMA flood zones, FEMA maps inaccurately and incompletely represent flood risks, indicating that future flood risk assessment approaches should use flood risk maps from other sources. The approach we introduce can be used to assess flood risks to CI elsewhere, and case study results can be applied to inform flood risk reduction efforts in Utah. © 2025 Elsevier Ltd
Publisher: Elsevier Ltd
Keywords: Scopus_Alert_15_Aout_2025

Identification of flood vulnerability areas using analytical hierarchy process techniques in the Wuseta watershed, Upper Blue Nile Basin, Ethiopia - Mulu, Arega; Kassa, Samuel Berihun; Wossene, Mindesilew Lakew; Adefris, Sintayehu; Meshesha, Taye Minchil (Scientific Reports, 2025)
Flooding, caused by the excessive accumulation of water on land, disrupts activities in floodplain regions, particularly during the rainy season. The main objective is to map Flood vulnerability areas and identify regions most vulnerable to flooding to inform effective flood management strategies using an integrated approach that combines remote sensing, geographic information systems (GIS), and the analytical hierarchy process (AHP) to assess Flood vulnerability in the Wuseta Watershed. The research was conducted in three phases: pre-fieldwork, fieldwork, and post-fieldwork. Key factors influencing Flood vulnerability such as drainage density, elevation, land use/land cover, and slope were hierarchically weighted to produce a Flood vulnerability map. Rainfall distribution was not considered as a contributing factor the Ethiopian Meteorological Agency has installed only one weather station in the study area, located in Wuseta watershed. As a result, the rainfall distribution is considered uniform throughout the watershed, making it unsuitable for flood susceptibility assessment. The Flood vulnerability map categorizes the watershed into five zones: very high (0.07 km2), high (4.65 km2), moderate (7.86 km2), slight (4.41 km2), and very slight (0.001 km2). The results show that the upstream, northern, northwestern, and northeastern areas of the watershed face slight to very slight Flood vulnerability, while the southern region is highly vulnerable to flooding. These findings provide valuable insights for policymakers and local communities, aiding in the development of targeted mitigation strategies and raising awareness of flood-prone areas. This study underscores the value of integrating geospatial technologies and multi-criteria decision analysis in flood risk assessment, particularly in data-scarce regions, to enhance disaster preparedness and climate resilience. © The Author(s) 2025.
Publisher: Nature Research
Keywords: Scopus_Alert_15_Aout_2025

Flood risk mapping in an urbanized tropical river basin in India using MCDA-AHP: a post-storm event evaluation - Ajin, Rajendran Shobha; Senan, Chandini Padmanabha Panicker Chandra; Devi, B. R. Anaswara; Costache, Romulus; Nagar, Jitendra K.; Rajaneesh, A.; Sajinkumar, K.S. (Smart Construction and Sustainable Cities, 2025)
Flooding is a persistent hazard in tropical regions of India, primarily driven by intense precipitation and further aggravated by anthropogenic activities. Despite ongoing efforts, a gap persists in the development of comprehensive risk models that integrate hazard, vulnerability, and exposure components at a watershed level. This research seeks to bridge that gap by implementing a multi-criteria decision analysis (MCDA) technique, specifically the Analytical Hierarchy Process (AHP), to generate a risk map for the tropical Meenachil River Basin (MRB), originating in the Western Ghats, southwest India. Nine conditioning factors (CFs) were evaluated to assess hazard, and the resulting hazard layer was integrated with vulnerability data and different exposure factors (EFs), such as built-up height, built-up surface, built-up volume, population, and total exposure, to produce a risk map. Validation of the hazard model utilizing the Receiver Operating Characteristic (ROC) curve achieved an excellent Area Under Curve (AUC) of 0.825, along with high accuracy (0.818), F1-score (0.802), precision (0.812), and recall (0.793). Approximately 11% of the MRB lies in a very high hazard zone and 1.51% in a very high risk zone. These results advocate for sustainable flood management by identifying key risk zones, thereby facilitating the implementation of focused site-specific mitigation strategies. © The Author(s) 2025.
Publisher: Springer Nature
Keywords: Scopus_Alert_15_Aout_2025

A holistic methodology for evaluating flood vulnerability, generating flood risk map and conducting detailed flood inundation assessment - Devi, Kamalini; Reddy, Chundi Chenna; Rahul, Kandakatla; Khuntia, Jnana Ranjan; Das, Bhabani Shankar (Scientific Reports, 2025)
Flood risk assessment (FRA) is a process of evaluating potential flood damage by considering vulnerability of exposed elements and consequences of flood events through risk analysis which recommends the mitigation measures to reduce the impact of floods. This flood risk analysis is a technique used to identify and rank the level of flood risk through modeling and spatial analysis. In the present study, Musi River in the Osmansagar basin is taken in to consideration to evaluate the flood risk, which is located at Hyderabad. The input data collected for the study encompasses Hydrological and Meteorological datasets from Gandipet Guage station in Hyderabad, raster grid data for Osmansagar basin along with several indicators data influencing flood vulnerability. The primary research objective is to conduct a quantitative assessment of the Flood vulnerability index (FVI), to develop a comprehensive flood risk map and to evaluate the magnitude of damaging flood parameters, inundated volume and to analyze the regions inundated in the study area. In risk analysis, FVI determines the degree of which an area is susceptible to the negative impact of flood through various influencing indicators, Flood hazard map segregate the regions based on flood risk level through spatial analysis in Arc-GIS. A part of this study includes an integrated methodology for assessing flood inundation using Quantum Geographic Information Systems (QGIS) data modelling for spatial analysis, Hydraulic Engineering Center’s River Analysis System (HEC-RAS) hydraulic modelling for unsteady flow analysis and a machine learning technique i.e. XGBoost, to enhance the accuracy and efficiency of flood risk assessment. Subsequently, inundation map produced using HEC-RAS is superimposed with building footprints to identify vulnerable structures. The results obtained by risk analysis using hydraulic modeling, GIS analysis, and machine learning technique illustrates the flood vulnerability, areas having high flood risk and inundated volume along with predicted flood levels for next 10 years. These findings demonstrate the efficiency of the holistic approach in identifying vulnerability, flood-prone areas and evaluating potential impacts on infrastructure and communities. The outcomes of the study assist the decision-makers to gain valuable insights into flood risk management strategies. © The Author(s) 2025.
Publisher: Nature Research
Keywords: Scopus_Alert_15_Aout_2025

Impact of climate change scenario on sea level rise and future coastal flooding in major coastal cities of India - Chakrabortty, Rabin; Ali, Tarig; Atabay, Serter; Roy, Paramita; Pande, Chaitanya Baliram (Scientific Reports, 2025)
This study evaluates the impacts of projected sea level rise (SLR) on coastal flooding across major Indian cities: Mumbai, Kolkata, Chennai, Visakhapatnam, Surat, Kochi, Thiruvananthapuram, and Mangaluru. Machine learning models, including Long Short-Term Memory (LSTM), Random Forest (RF), and Gradient Boosting (GB), has been employed to assess flood risks under four Shared Socioeconomic Pathways (SSP 126, 245, 370, and 585) emission scenarios. The research utilized these models because they demonstrate high performance in handling difficult data relationships and both temporal patterns and sophisticated environmental data. SLR projections provided by computers generate forecasts that combine with digital elevation models (DEMs) to determine coastal flooding risks and locate flood-prone areas. Results reveal that Mumbai and Kolkata face the highest flood risks, particularly under high emission scenarios, while Kochi and Mangaluru exhibit moderate exposure. Model performance is validated using residual analysis and Receiver Operating Characteristic (ROC) curves, confirming reliable predictive accuracy. These findings provide essential information for urban planners and policymakers to prioritize climate adaptation strategies in vulnerable coastal cities. © The Author(s) 2025.
Publisher: Nature Research
Keywords: Scopus_Alert_15_Aout_2025

Multi-Criteria Decision Analysis for Managed Aquifer Recharge (MAR): A Flood-Responsive Approach in Milpa Alta, Mexico City - Areu-Rangel, Omar S.; Singh, Amrie; Bonasia, Rosanna (Environmental Quality Management, 2025)
Milpa Alta, located southeast of Mexico City, is a key region for environmental sustainability due to its volcanic soil, biodiversity, and critical role in aquifer recharge, which supports the city's water supply. However, rapid urbanization has severely impacted the area, causing reduced vegetation cover, increased runoff, and diminished groundwater recharge, which intensify flooding, soil erosion, and water scarcity. This study aims to identify optimal sites for managed aquifer recharge (MAR) structures in Milpa Alta through a multi-criteria analysis incorporating criteria such as topography, land use, proximity to urban areas, and drainage networks. Uniquely, hydraulic simulations of flood scenarios were integrated into the analysis to improve the precision of site selection. Geographic information systems (GIS) were used to assess and combine these criteria, providing a spatial evaluation of suitability. Results indicate that the central and northern regions of Milpa Alta, particularly around San Francisco Tecoxpa and San Antonio Tecómitl, are most suitable for MAR implementation due to their permeable soils, gentle slopes, and proximity to agricultural lands and drainage networks. These MAR structures can enhance groundwater recharge and mitigate flood risks during extreme rainfall events, with the potential to capture up to 300,000 m3 of surface runoff during a single high-intensity storm event. Despite its strengths, the study acknowledges limitations such as the absence of detailed water quality analyses and the need for sensitivity testing of the criteria weighting. This research provides an innovative approach to MAR site selection by integrating flood simulations, offering a replicable model for similar regions. Successful implementation of MAR in Milpa Alta requires addressing water quality concerns, engaging stakeholders, and ensuring compliance with regulatory frameworks. The findings emphasize MAR's potential to balance urbanization pressures with sustainable water management and flood mitigation strategies in Mexico City's rapidly developing areas. © 2025 Wiley Periodicals LLC.
Publisher: John Wiley and Sons Inc
Keywords: Scopus_Alert_15_Aout_2025

HyEco: A hybrid hydrodynamic-cum-ecological modelling framework to demystify flood and human-health risks over flood-prone metropolis - Deopa, Rahul; Mohanty, Mohit Prakash (Water Research X, 2025)
Urban flooding, exacerbated by climate change and unregulated urbanization, poses significant risks to the built environment. In addition to physical damage, floodwaters often mobilize a hazardous mix of untreated sewage, industrial effluents, and undesirable pollutants, leading to severe microbial contamination in the floodwaters. This study introduces “HyEco”-an integrated framework comprising high-fidelity 3-way coupled hydrodynamic and ecological modelling with an aim to capture the “unhidden tangible flood risks” and “hidden intangible public-health risks” in tandem. Focusing on Delhi, India, a densely populated metropolis prone to recurrent urban flooding and associated health crises, the framework simulates the 2023 mega-flood event. Results show that approximately 63.5 % of the region is categorized under ‘high’ to ‘very high’ flood risk zones, with over 20 % of these areas housing around 15 % of the city's dense population. The hydrodynamic model outputs were forced into the ecological model to simulate the fate and transport of microbial contamination in floodwaters. Escherichia coli concentrations ranged from 772,868 to 790,000 MPN/100 mL, far exceeding established safety thresholds. A Quantitative Microbial Risk Assessment (QMRA) reveals elevated infection probabilities, particularly among children, with risks up to 2.60×10⁻³ under repeated exposure and 8.38×10⁻⁴ to 8.57×10⁻⁴ for pedestrian splash exposures. Unlike prior approaches that examine flood and microbial risks in isolation or depend on static datasets, HyEco overcomes key methodological gaps by dynamically integrating flood and microbial processes at high spatio-temporal resolution. The HyEco framework offers a scalable and actionable tool for integrated flood risk management and climate-resilient public health planning. © 2025
Publisher: Elsevier Ltd
Keywords: Scopus_Alert_15_Aout_2025

Pedestrian vulnerability assessment of underground staircases in urban flooding - Wu, Wenqi; Zhu, Zhongfan; Zheng, Xinyu; Liu, Shuyou; Zhang, Dawei (Sustainable Cities and Society, 2025)
Urban underground flooding occurs frequently worldwide in the context of climate change and rapid urbanization, posing a serious threat to the travel safety of urban populations; in particular, staircases play an important role in the emergency evacuation of pedestrians in floodwater. Previous studies have identified the staircase configuration as a crucial factor influencing the evacuation difficulty of pedestrians in floodwater. However, the correlation between the geometric characteristics of staircase structures and pedestrian vulnerability is not fully understood, and few parametric studies have focused on the effects of wind intrusion into underground spaces and the effects of various engineering measures. This study thereby aims to assess pedestrian vulnerability in underground staircase floodwater as the width of the lower segment of the staircase increases, the effect of wind in the staircase is incorporated, and several flood prevention and/or windproof measures are implemented. Computational fluid dynamics (CFD) simulations were performed to reproduce the mean floodwater flow field and wind flow field on underground staircases. The findings show that (i) a variation in the width of the lower staircase after the rest platform affects pedestrian vulnerability, i.e., an increasing lower staircase width decreases the pedestrian risk to a certain degree; however, the jet behind the rest platform intensifies it; (ii) the incorporation of the wind effect when it intrudes the staircase obviously deteriorates the pedestrian vulnerability, and a discrepancy exists in the evacuation speeds of different pedestrian groups under a joint effect of wind and floodwater; and (iii) some engineering measures, especially windproof measures, have the potential to mitigate pedestrian vulnerability. These findings can serve as a reference for policymakers and stakeholders in coping with urban underground flooding hazards and guiding the emergency evacuation of people trapped in floodwater in the context of resilient city construction. © 2025 Elsevier Ltd
Publisher: Elsevier Ltd
Keywords: Scopus_Alert_15_Aout_2025

Rapid-Mapping Maximum Water Depth Map of Urban Flood Using a Highly Adaptable Machine Learning Based Model - Li, Jingru; Pan, Guiying; Chen, Yangyu; Wang, Xiaoling; Huang, Peizhi; Zhang, Li; Zhou, Haijun (Journal of Flood Risk Management, 2025)
Rapid urban flood mapping is crucial for timely risk alerts and emergency relief. Machine learning (ML)-based mapping models emerge as a promising approach for fast, accurate inundation forecasts. However, current ML models often use precipitation features as inputs and predict maximum flood depth for all grid cells of a specific region simultaneously. This special design improves their prediction efficiency but limits their application in new regions. This study aims to create a highly adaptable, rapid urban maximum flood water depth mapping model based on the random forest regression algorithm and the extreme gradient boosting algorithm. Our mapping model additionally incorporates terrain and land-use features, besides the precipitation feature, as input variables and generates the maximum water depth only for a grid cell in each mapping. Thus, it can be unchangeably applied to the grid cells in a new area when the model is fully trained. In the case study of Shenzhen, China, our ML-based mapping model demonstrated excellent mapping ability in both training and validation sets. The coefficient of determination (R2) is consistently greater than or close to 95%. Furthermore, it revealed good generalization ability when directly applied to a new rainfall event (R2 = 0.875) and a new area (R2 = 0.810). Meanwhile, the time cost of the mapping model is less than 3 s, meeting the requirement for real-time mapping. These results indicate that this highly adaptable model, once appropriately trained, can be applied to rapid urban flood severity mapping, which significantly reduces its use cost in urban flood management. © 2025 The Author(s). Journal of Flood Risk Management published by Chartered Institution of Water and Environmental Management and John Wiley & Sons Ltd.
Publisher: John Wiley and Sons Inc
Keywords: Scopus_Alert_15_Aout_2025

Extreme precipitation risk assessment with improved WOA-Optimized copula model under composite conditions - Wang, Zhaocai; Ma, Chao; Wu, Junhao; Wu, Tunhua (Theoretical and Applied Climatology, 2025)
An accurate study of extreme precipitation risk events is crucial for flood control, urban planning, and engineering design. The Copula function effectively handles uncertainties and nonlinear interactions among multiple hydrological variables, capturing complex correlations in extreme precipitation events for more precise risk assessments. Selecting the parameters of the Copula function is critical, as it defines the function’s shape and the dependence structure between variables, influencing its application. Traditional parameterization methods, like maximum likelihood estimation and least squares, often require large datasets and distribution assumptions, making them cumbersome for high-dimensional data. This research presents a model using an enhanced whale optimization algorithm to estimate Copula parameters (CLCWOA-Copula), aiming to assess return period (RP) and failure probability associated with extreme precipitation risk events. Monthly precipitation data from Zhengzhou, China, from 1950 to 2024 is analyzed, using the 90th percentile as the extreme precipitation threshold. Marginal distributions are fitted using the P-III and gamma distributions, etc., which are then combined using CLCWOA-Copula to analyze coincident RP, joint RP, Kendall RP, and failure probability under composite conditions. The results demonstrate that this optimization method possesses strong global search capabilities and parallel computing abilities, yielding optimal Copula parameter values within few iterations and selecting the best-fit Copula function based on AIC, R², and RMSE. The Kendall RP and failure probability offer more accurate tools for extreme precipitation risk analysis; when Pmax reaches 540 mm, P90 reaches 1080 mm, or R90 reaches 0.83, a one-in-a-century extreme precipitation event is indicated. This study provides important insights for risk metrics applicable to extreme weather. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2025.
Publisher: Springer
Keywords: Scopus_Alert_15_Aout_2025

Climate-smart water management in rice paddies: a meta-synthesis on greenhouse gas emissions and yield impacts - Minamikawa, Kazunori (Paddy and Water Environment, 2025)
Water management practices in rice paddies, particularly alternate wetting and drying and midseason drainage followed by intermittent irrigation, are widely recognized for reducing methane (CH4) emissions and irrigation water use compared to continuous flooding (CF). However, these practices also increase nitrous oxide (N2O) emissions and their effect on rice yield remains unclear, especially in the context of technology dissemination to farmers. This study (1) reviews 11 recent meta-analyses on CH4 and N2O emissions and rice yield and (2) synthesizes their reported effects on rice growth and yield. Aggregated data show that CH4 emissions decreased by 31–62% (n = 10), while N2O emissions increased by 37–445% (n = 7), relative to CF. Rice yield change ranged from − 5.4% to + 11% with a mean of + 1.3% (n = 8). The impact of water management on rice yield varied depending on the timing and intensity of drainage events, with excessive water stress—particularly during the heading stage—and prolonged reductive soil conditions being key risk factors. Results indicate that mild-intensity drainage practices, such as ‘safe AWD,’ not only avoid yield penalties but can significantly enhance rice productivity when tailored to favorable environmental and agronomic conditions. For effective dissemination of these practices, leveraging yield improvement as an incentive for farmers is essential. Optimizing drainage schedules in accordance with rice physiological stages and local conditions is critical. With appropriate localization, water management can serve as a climate-smart strategy that simultaneously improves water efficiency, reduces greenhouse gas emissions, and maintains or increases rice productivity. © The Author(s) 2025.
Publisher: Springer Science and Business Media Deutschland GmbH
Keywords: Scopus_Alert_15_Aout_2025

A REVIEW OF THE IMPACT OF EXTREME WEATHER EVENTS ON FRESHWATER, TERRESTRIAL AND MARINE ECOSYSTEMS - Eichelmann, Elke; Naber, Nadeem; Battamo, Ashenafi Yohannes; O’Sullivan, John J.; Salauddin; Kelly-Quinn, Mary (Biology and Environment, 2025)
Extreme weather events (EWEs), including floods, droughts, heatwaves and storms, are increasingly recognised as major drivers of biodiversity loss and ecosystem degradation. In this systematic review, we synthesise 251 studies documenting the impacts of extreme weather events on freshwater, terrestrial and marine ecosystems, with the goal of informing effective conservation and management strategies for areas of special conservation or protection focus in Ireland.Twenty-two of the reviewed studies included Irish ecosystems. In freshwater systems, flooding (34 studies) was the most studied EWE, often linked to declines in species richness, abundance and ecosystem function. In terrestrial ecosystems, studies predominantly addressed droughts (60 studies) and extreme temperatures (48 studies), with impacts including increase in mortality, decline in growth and shift in species composition. Marine and coastal studies focused largely on storm events (33 studies), highlighting physical damages linked to wave actions, behavioural changes in macrofauna, changes in species composition and distribution, and loss in habitat cover. Results indicate that most EWEs lead to negative ecological responses, although responses are context specific.While positive responses to EWEs are rare, species with adaptive traits displayed some resilience, especially in ecosystems with high biodiversity or refuge areas.These findings underscore the need for conservation strategies that incorporate EWE projections, particularly for protected habitats and species. © 2025 Royal Irish Academy. All rights reserved.
Publisher: Royal Irish Academy
Keywords: Scopus_Alert_15_Aout_2025

Systematic review of flood resilience strategies in Lagos Metropolis: pathways toward the 2030 sustainable development agenda - Orimoogunje, Oluwagbenga; Aniramu, Opeyemi (Frontiers in Climate, 2025)
Flooding presents a significant challenge in the Lagos metropolis, driven by rapid urbanization, poor drainage infrastructure, and climate change. This study evaluates flood resilience strategies in Lagos, analyzing their effectiveness in mitigating flood risks and their alignment with the 2030 Agenda. The research utilizes the PICO (Population, Intervention, Control, and Outcomes) framework to refine research questions and follows PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines for study selection, search strategies, and data extraction. A thorough search across databases such as Google Scholar, SCOPUS, and government data repositories was conducted to ensure the inclusion of relevant studies while minimizing selection bias. The study emphasizes the severe impacts of flooding, referencing the 2022–2023 flood event which resulted in USD 262,500 damages and displaced 8000 residents in Lagos State. Current flood resilience strategies are inadequate to meet the Sustainable Development Goals (SDGs) due to insufficient urban flood infrastructure, poor waste disposal practices, and worsening climatic conditions. The livelihoods, income, health, and overall survival of vulnerable communities are at significant risk. Key gaps identified include the weak enforcement of urban planning regulations, limited community engagement, ineffective early warning systems, and poor intervention initiatives. This study suggests a multi-stakeholder approach that enhances both structural and non-structural flood resilience. Improving drainage systems, promoting sustainable waste management, improving climate adaptation policies, and fostering community-based flood mitigation strategies are crucial for achieving long-term urban resilience. These findings offer valuable insights for policymakers, urban planners, and climate resilience advocates working toward the Sustainable Development Agenda in Lagos metropolis. Copyright © 2025 Orimoogunje and Aniramu.
Publisher: Frontiers Media SA
Keywords: Scopus_Alert_15_Aout_2025

Advances in flow and civil structures - Wang, Benshuo; Zhang, Xuelin; Li, Cruz Y.; Chen, Zengshun; Tse, Tim K. T. (Physics of Fluids, 2025)
The Flow and Civil Structures special collection is one of the earliest and largest efforts to consolidate transformative research bridging fluid mechanics and civil engineering. It addresses mutual and escalating challenges posed by extreme environmental loads and rapid urbanization, linking these two massive research fields. With nearly 200 papers, contributions span fluid-structure interactions in bridges, building, and high-speed railways; hydrodynamic resilience of offshore infrastructure; granular flows in urban drainage systems; turbulence-driven pollutant dispersion; and much beyond. The collection features advances in experiments, numerical simulations, field measurements, and analytical methods to improve predictions of wind-induced vibrations, optimize wave-resistant design, and mitigate urban flooding hazards. By integrating artificial intelligence and machine learning analysis, it advances infrastructure resilience for compound hazards in an increasingly dynamic climate, addressing both global and local scales. © 2025 Author(s).
Publisher: American Institute of Physics
Keywords: Scopus_Alert_15_Aout_2025

Projections of extreme weather events according to climate change scenarios and populations at-risk in Brazil - Dantas, Leydson Galvíncio; Ferreira, Andrêa Jacqueline Fortes; Pinto Junior, Jony Arrais; Cortes, Taísa Rodrigues; Neves, Danielson Jorge Delgado; de Oliveira, Beatriz Fátima Alves; da Silveira, Ismael Henrique (Climatic Change, 2025)
Extreme weather events, such as heat waves, heavy rainfall and droughts, have become more frequent and intense in Brazil. According to climate change scenarios, this trend, which has a negative impact on people’s health and living conditions, will continue. Here, we analysed indicators for extreme weather events resulting from climate change, projected for the 21st century, alongside socio-demographic indicators for Brazilian municipalities, in an attempt to identify populations exposed to the risks of the climate crisis. We calculated the values of indicators for extreme air temperature and precipitation events, based on NEX-GDDP-CMIP6 data, for a reference period and for the future, as well as socio-demographic indicators based on recent census data. Using Spearman’s coefficient, we then calculated anomaly indicators for the future time intervals and analysed correlations with the socio-demographic indicators. Our results indicate a reduction in cold days and an increase in hot days and heat waves in both scenarios (SSP2-4.5 and SSP5-8.5), with the most changes occurring in the highest emission scenario. The extreme precipitation indicators suggest both an increase and a reduction in intense precipitation and droughts in a number of the country’s regions. The projected changes are more intense in the highest emission scenario, and in the North and Northeast regions. We noted a trend for greatest occurrence of extreme events in locations with a higher proportion of Black, Parda/Brown, Indigenous and Quilombola populations, and the socially vulnerable. We recommend that policies to adapt and mitigate the impacts of climate change focus on reducing inequalities and promoting climate justice. © The Author(s) 2025.
Publisher: Springer Science and Business Media B.V.
Keywords: Scopus_Alert_15_Aout_2025

Future Projection of Rainstorm and Flood Disaster Risk in Sichuan-Chongqing Region under CMIP6 Different Climate Change Scenarios - Yao, Ying; Li, Xiehui; Wang, Lei; Li, Hongying (Plateau Meteorology, 2025)
In recent years，rapid urbanization and global warming have led to frequent and severe rainstorm and flood disasters in the Sichuan-Chongqing region. This change will not only have a serious impact on the ecological environment and socio-economic development of the area，but also significantly increase the pressure on urban infrastructure and threaten the safety of people's lives and property. Therefore，it is particularly important to scientifically and accurately analyze the disaster risk of rainstorm and flood in Sichuan-Chongqing region in the past and future. This paper utilized daily precipitation data from 50 selected meteorological stations in the Sichuan-Chongqing region，precipitation data from 5 CMIP6 models，gridded population and economic data under Shared Socioeconomic Pathways（SSPs），as well as DEM and land use remote sensing data. Firstly，using Taylor diagrams，quantitative indices（S），and standardized anomaly sequences，the study evaluated the simulation performance of 5 individual CMIP6 models，an equal-weighted aggregation of 5 models（EWA-5），and unequally-weighted aggregations of 5 models（UEWA-5）for five selected extreme precipitation indices. Then，by building a comprehensive risk assessment model of rainstorm and flood disaster based on disaster risk and vulnerability of disaster bearing body，the study conducted risk assessments，future projections，and comparative analyses of rainstorm and flood disasters during baseline（1995-2014）and future near-term（2025-2044）and long-term （2045-2064）periods under three different climate change scenarios（SSP1-2. 6，SSP2-4. 5，SSP5-8. 5）. Results indicated：（1）The EC-Earth3 model performed best in simulating the five extreme precipitation indices，with correlation coefficients between simulated and observed values of 0. 78 for R95p，0. 90 for RX1day，and 0. 77 for RX5day. Overall，the simulation performance of UEWA-5 exceeded that of EWA-5.（2）During the baseline period，central Sichuan exhibited high values for the five extreme precipitation indices，followed by eastern Sichuan and Chongqing，while western Sichuan showed lower values. The year 1998 recorded peak values for all five indices，with a maximum single-day precipitation of 86 mm for RX1day and an intensity（SDII）value of 11. 3 mm·d-1.（3）In future periods，the five extreme precipitation indices display a spatial distribution characterized by higher values in central regions and lower values around the periphery. Higher levels of social vulnerability and radiative forcing correlate with larger values of extreme precipitation indices. Comparing the two future periods，values of the indices are larger in the long term，notably with R95p averaging 846. 8 mm，an increase of 169. 2 mm compared to the near term.（4）During historical periods，areas with higher comprehensive risk of rainstorm and flood disasters were concentrated in central Sichuan and downtown Chongqing. In the two future periods，the high and moderately high-risk areas in central Sichuan are expected to expand，while the moderate-risk areas will shrink. The range of low-risk areas in the western Sichuan Plateau will also decrease，and the risk levels in southern Sichuan and eastern Sichuan-Chongqing border areas will respectively decrease to moderate-low and low-risk zones. Comparing the two future periods，the range of moderately high and moderate-risk areas in central Sichuan is expected to expand，while southwestern Chongqing will transition to a moderate-risk area in the long term. Other regions will generally maintain their original risk levels. Changes in disaster risk levels in the Sichuan-Chongqing region are less pronounced with increasing social vulnerability and radiative forcing，especially in the western Sichuan Plateau and northeastern Sichuan，where changes in disaster risk levels are minimal. The study results can provide important references for reducing disaster risks，enhancing emergency response capabilities，and making scientifically informed decisions for disaster prevention in the Sichuan-Chongqing region. © Editorial Department of Plateau Meteorology.
Publisher: Science China Press
Keywords: Scopus_Alert_15_Aout_2025

Interactive Effects of Climate Change and Contaminants in Aquatic Ecosystems on Environmental-Human Health - Yu, Kaifeng; Mohapatra, Sanjeeb; Chen, Yihan; Jiang, Peng; Tong, Xuneng (Current Pollution Reports, 2025)
Purpose of the Review: Climate change is intensifying the pressures on aquatic ecosystems by altering the dynamics of contaminants, with cascading effects on ecological and human health. This review synthesizes recent evidence on how rising temperatures, altered precipitation patterns, and extreme weather events influence chemical and microbial contaminant dynamics in aquatic environments. Recent Findings: Key findings reveal that elevated temperatures enhance phosphorus pollution and algal blooms, increase heavy metal release from sediments, and promote the mobilization of organic pollutants. Concurrently, climate change exacerbates microbial contamination by facilitating the spread of waterborne microbial contaminants, especially posing more pressure to antimicrobial resistance-related contaminants through temperature-driven horizontal gene transfer and extreme precipitation events. Complex interactions between chemical and microbial contaminants like heavy metals co-selecting for antibiotic resistance further amplify risks. The compounded effects of climate change and contaminants threaten water quality, ecosystem resilience, and public health, particularly through increased toxicant exposure via seafood and waterborne disease outbreaks. Despite growing recognition of these interactions, critical gaps remain in understanding their synergistic mechanisms, especially in data-scarce regions. Summary: This review highlights the urgent need for integrated monitoring, predictive modeling, and adaptive policies under a One Health framework to mitigate the multifaceted impacts of climate-driven contamination. Future research should prioritize real-world assessments of temperature effects, urban overflow dynamics during extreme weather, and the socio-behavioral dimensions of contaminant spread to inform effective mitigation strategies. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.
Publisher: Springer Science and Business Media Deutschland GmbH
Keywords: Scopus_Alert_15_Aout_2025

A novel explainable stacking ensemble model for estimating design floods: A data-driven approach for ungauged regions - Kanani-Sadat, Yousef; Safari, Abdolreza; Nasseri, Mohsen; Homayouni, Saeid (Advanced Engineering Informatics, 2025)
Keywords: Infolettre_Ete_2025

Performance and durability of passive direct formate fuel cells with Nafion- or PTFE-based cathodes - Shyu, Jin-Cherng; Khoiroh, Ikhwatinah; He, Jie-An (Fuel, 2025)
Keywords: Infolettre_Ete_2025

HurricaneLog: A serious game for data collection and analysis of hurricane preparedness and response operations - Correia Pereira, Thiago; Aloise, Daniel; Rancourt, Marie-Ève (International Journal of Disaster Risk Reduction, 2025)
Keywords: Infolettre_Ete_2025

The Needs, Challenges, and Priorities for Advancing Global Flood Research - Samadi, Vidya; Fowler, Hayley J.; Lamond, Jessica; Wagener, Thorsten; Brunner, Manuela; Gourley, Jonathan; Moradkhani, Hamid; Popescu, Ioana; Wasko, Conrad; Wright, Daniel; Wu, Huan; Zhang, Ke; et al. (WIREs Water, 2025)
ABSTRACT In recent years, numerous flood events have caused loss of life, widespread disruption, and damage across the globe. These devastating impacts highlight the importance of a better understanding of flood generating processes, their impacts, and their variability under climate and landscape changes. Here, we argue that the ability to better model flooding is underpinned by the grand challenge of understanding flood generation mechanisms and potential impacts. To address this challenge, the World Meteorological Organization‐Global Energy and Water Exchanges (GEWEX) Hydrometeorology Panel (GHP) aims to establish a Global Flood Crosscutting project to propagate flood modeling and research knowledge across regions and to synthesize results at the global scale. This paper outlines a framework for understanding the dynamics and impacts of runoff generation processes and a rationale for the role of a Global Flood Crosscutting project to address these challenges. Within this Global Flood Crosscutting project, we will establish a common terminology and methods to enable the global research community to exchange knowledge and experiences, and to design experiments toward developing actionable recommendations for more effective flood management practices and policies for improved resilience. This harmonization of rich perspectives across disciplines will foster the co‐production of knowledge primed to advance flood research, particularly in the current period of heightened climate variability and rapid change. It will create a new transdisciplinary paradigm for flood science, wherein different dimensions of mechanistic understanding and processes are rigorously considered alongside socioeconomic impacts, early warning communications, and longer‐term adaptation to alleviate flood risks in society.
Keywords: Infolettre_Ete_2025

Projecting climate and socioeconomic contributions to global flood-induced displacements using a data-driven approach - Del Rio Amador, Lenin; Boudreault, Mathieu; Carozza, David A. (Natural Hazards, 2025)
Keywords: Infolettre_Ete_2025

Full-scale characterization of the effects of a bioretention system on water quality and quantity following the replacement of a mixed stormwater and combined sewer system - Le Cauchois, Pia; Doucet, Samuel; Bouattour, Ons; McQuaid, Natasha; Beral, Henry; Kõiv-Vainik, Margit; Bichai, Françoise; McCarthy, David; St-Laurent, Julien; Dagenais, Danielle; Bennekrela, Nesrine; Guerra, Juan; et al. (Blue-Green Systems, 2025)
ABSTRACT Urbanization is leading to more frequent flooding as cities have more impervious surfaces and runoff exceeds the capacity of combined sewer systems. In heavy rainfall, contaminated excess water is discharged into the natural environment, damaging ecosystems and threatening drinking water sources. To address these challenges aggravated by climate change, urban blue-green water management systems, such as bioretention cells, are increasingly being adopted. Bioretention cells use substrate and plants adapted to the climate to manage rainwater. They form shallow depressions, allowing infiltration, storage, and gradual evacuation of runoff. In 2018, the City of Trois-Rivières (Québec, Canada) installed 54 bioretention cells along a residential street, several of which were equipped with access points to monitor performance. Groundwater quality was monitored through the installation of piezometers to detect potential contamination. This large-scale project aimed to improve stormwater quality and reduce sewer flows. The studied bioretention cells reduced the flow and generally improved water quality entering the sewer system, as well as the quality of stormwater, with some exceptions. Higher outflow concentrations were observed for contaminants such as manganese and nitrate. The results of this initiative provide useful recommendations for similar projects for urban climate change adaptation.
Keywords: Infolettre_Ete_2025

Non-stationary and multivariate spring floods estimation of the Saint John River (eastern Canada) - Yousfi, Nawres; El Adlouni, Salah; Gachon, Philippe (Stochastic Environmental Research and Risk Assessment, 2025)
Keywords: Infolettre_Ete_2025

The vertical premium: Relationship between relative height of properties from real flood elevation and housing prices - Kim, Youjung; Koo, Bon Woo; Lee, Sungmin (Cities, 2025)
Keywords: Infolettre_Ete_2025

The anatomy of a flash flood: Why the Texas flood was so deadly - Bonakdari, Hossein (The Conversation, 2025)
Understanding the combination of meteorological, geomorphological and hydrological factors that led to the Texas flood could help prevent future disasters.
Keywords: Infolettre_Ete_2025

Development of an under-ice river discharge forecasting system in Delft-Flood Early Warning System (Delft-FEWS) for the Chaudière River based on a coupled hydrological-hydrodynamic modelling approach - Usman, Kh Rahat; Montero, Rodolfo Alvarado; Ghobrial, Tadros; Anctil, François; van Loenen, Arnejan (Geoscientific Model Development Discussions, 2024)
Abstract. Year-round river discharge estimation and forecasting is a critical component of sustainable water resource management. However, in cold climate regions such as Canada, this basic task gets intricated due to the challenge of river ice conditions. River ice conditions are dynamic and can change quickly in a short period of time. This dynamic nature makes river ice conditions difficult to forecast. Moreover, the observation of under-ice river discharge also remains a challenge since no reliable method for its estimation has been developed till date. It is therefore an active field of research and development. The integration of river ice hydraulic models in forecasting systems has remained relatively uncommon. The current study has two main objectives: first is to demonstrate the development and capabilities of a river ice forecasting system based on coupled hydrological and hydraulic modelling approach for the Chaudière River in Québec; and second is to assess its functionality over selected winter events. The forecasting system is developed within a well-known operational forecasting platform: the Delft Flood Early Warning System (Delft-FEWS). The current configuration of the systems integrates (i) meteorological products such as the Regional Ensemble Prediction System (REPS); (ii) a hydrological module implemented through the HydrOlOgical Prediction LAboratory (HOOPLA), a multi-model based hydrological modelling framework; and (iii) hydraulic module implemented through a 1D steady and unsteady HEC-RAS river ice models. The system produces ensemble forecasts for discharge and water level and provides flexibility to modify various dynamic parameters within the modelling chain such as discharge timeseries, ice thickness, ice roughness as well as carryout hindcasting experiments in a batch production way. Performance of the coupled modelling approach was assessed using “Perfect forecast” over winter events between 2020 and 2023 winter seasons. The root mean square error (RMSE) and percent bias (Pbias) metrics were calculated. The hydrologic module of the system showed significant deviations from the observations. These deviations could be explained by the inherent uncertainty in the under-ice discharge estimates as well as uncertainty in the modelling chain. The hydraulic module of the system performed better and the Pbias was within ±10 %.
Publisher: Copernicus GmbH

Flood Risk and Community Resilience: An Interdisciplinary Approach - McEwen, Lindsey (2024)
This book details the impact of flooding on our environment, and the ways in which communities, and those that work with them, can act to manage the associated risks. Flooding is an increasingly significant environmental hazard which inflicts major costs to the economies and livelihoods of developed countries. This book explores how local communities can identify, manage, and adapt to the ever-increasing damage flooding causes. Focusing on the future role of local communities, the benefits and c

A Flood Risk Management Model to Identify Optimal Defence Policies in Coastal Areas Considering Uncertainties in Climate Projections - Cioffi, Francesco; De Bonis Trapella, Alessandro; Giannini, Mario; Lall, Upmanu (Water, 2022)
Coastal areas are particularly vulnerable to flooding from heavy rainfall, sea storm surge, or a combination of the two. Recent studies project higher intensity and frequency of heavy rains, and progressive sea level rise continuing over the next decades. Pre-emptive and optimal flood defense policies that adaptively address climate change are needed. However, future climate projections have significant uncertainty due to multiple factors: (a) future CO2 emission scenarios; (b) uncertainties in climate modelling; (c) discount factor changes due to market fluctuations; (d) uncertain migration and population growth dynamics. Here, a methodology is proposed to identify the optimal design and timing of flood defense structures in which uncertainties in 21st century climate projections are explicitly considered probabilistically. A multi-objective optimization model is developed to minimize both the cost of the flood defence infrastructure system and the flooding hydraulic risk expressed by Expected Annual Damage (EAD). The decision variables of the multi-objective optimization problem are the size of defence system and the timing of implementation. The model accounts for the joint probability density functions of extreme rainfall, storm surge and sea level rise, as well as the damages, which are determined dynamically by the defence system state considering the probability and consequences of system failure, using a water depth–damage curve related to the land use (Corine Land Cover); water depth due to flooding are calculated by hydraulic model. A new dominant sorting genetic algorithm (NSGAII) is used to solve the multi-objective problem optimization. A case study is presented for the Pontina Plain (Lazio Italy), a coastal region, originally a swamp reclaimed about a hundred years ago, that is rich in urban centers and farms. A set of optimal adaptation policies, quantifying size and timing of flood defence constructions for different climate scenarios and belonging to the Pareto curve obtained by the NSGAII are identified for such a case study to mitigate the risk of flooding and to aid decision makers.
Publisher: MDPI AG

Adaptation of Dual Drainage to Control Flooding and Enhance Combined Sewer Systems in Highly Urbanized Areas - Ossa Ossa, Juan Esteban; Duchesne, Sophie; Pelletier, Geneviève (2024)
Combined sewer surcharges in densely urbanized areas have become more frequent due to the expansion of impervious surfaces and intensified precipitation caused by climate change. These surcharges can generate system overflows, causing urban flooding and pollution of urban areas. This paper presents a novel methodology to mitigate sewer system surcharges and control surface water. In this methodology, flow control devices and urban landscape retrofitting are proposed as strategies to reduce water inflow into the sewer network and manage excess water on the surface during extreme rainfall events. For this purpose, a 1D/2D dual drainage model was developed for two case studies located in Montreal, Canada. Applying the proposed methodology to these two sites led to a reduction of the volume of wastewater overflows by 100% and 86%, and a decrease in the number of surface overflows by 100% and 71%, respectively, at the two sites for a 100-year return period 3-h Chicago design rainfall. It also controlled the extent of flooding, reduced the volume of uncontrolled surface floods by 78% and 80% and decreased flooded areas by 68% and 42%, respectively, at the two sites for the same design rainfall.

Understanding Flood Risk Perception: A Case Study from Canada - Oubennaceur, Khalid; Chokmani, Karem; Lessard, Florence; Gauthier, Yves; Baltazar, Catherine; Toussaint, Jean-Patrick (Sustainability, 2022)
In recent years, understanding and improving the perception of flood risk has become an important aspect of flood risk management and flood risk reduction policies. The aim of this study was to explore perceptions of flood risk in the Petite Nation River watershed, located in southern Quebec, Canada. A survey was conducted with 130 residents living on a floodplain in this river watershed, which had been affected by floods in the spring of 2017. Participants were asked about different aspects related to flood risk, such as the flood hazard experience, the physical changes occurring in the environment, climate change, information accessibility, flood risk governance, adaptation measures, and finally the perception of losses. An analysis of these factors provided perspectives for improving flood risk communication and increasing the public awareness of flood risk. The results indicated that the analyzed aspects are potentially important in terms of risk perception and showed that the flood risk perceptions varied for each aspect analyzed. In general, the information regarding flood risk management is available and generally understandable, and the level of confidence was good towards most authorities. However, the experiences of flood risk and the consequences of climate change on floods were not clear among the respondents. Regarding the adaptation measures, the majority of participants tended to consider non-structural adaptation measures as being more relevant than structural ones. Moreover, the long-term consequences of flooding on property values are of highest concern. These results provide a snapshot of citizens’ risk perceptions and their opinions on topics that are directly related to such risks.
Number: 5 Publisher: Multidisciplinary Digital Publishing Institute

Flood Risk Communication Using ArcGIS StoryMaps - Oubennaceur, Khalid; Chokmani, Karem; El Alem, Anas; Gauthier, Yves (Hydrology, 2021)
In Canada, flooding is the most common and costly natural hazard. Flooding events significantly impact communities, damage infrastructures and threaten public security. Communication, as part of a flood risk management strategy, is an essential means of countering these threats. It is therefore important to develop new and innovative tools to communicate the flood risk with citizens. From this perspective, the use of story maps can be very effectively implemented for a broad audience, particularly to stakeholders. This paper details how an interactive web-based story map was set up to communicate current and future flood risks in the Petite-Nation River watershed, Quebec (Canada). This web technology application combines informative texts and interactive maps on current and future flood risks in the Petite-Nation River watershed. Flood risk and climate maps were generated using the GARI tool, implemented using a geographic information system (GIS) supported by ArcGIS Online (Esri). Three climate change scenarios developed by the Hydroclimatic Atlas of Southern Quebec were used to visualize potential future impacts. This study concluded that our story map is an efficient flood hazard communication tool. The assets of this interactive web mapping tool are numerous, namely user-friendly mapping, use and interaction, and customizable displays.
Publisher: MDPI AG

Flood inundation modeling in ungauged basins using Unmanned Aerial Vehicles imagery - Yavari, Adel; Homayouni, Saeid; Oubennaceur, Khalid; Chokmani, Karem (Earth Observation and Geomatics Engineering, 2020)
This paper presents a new framework for floodplain inundation modeling in an ungauged basin using unmanned aerial vehicles (UAVs) imagery. This method is based on the integrated analysis of high-resolution ortho-images and elevation data produced by the structure from motion (SfM) technology. To this end, the Flood-Level Marks (FLMs) were created from high-resolution UAV ortho-images and compared to the flood inundated areas simulated using the HEC-RAS hydraulic model. The flood quantiles for 25, 50, 100, and 200 return periods were then estimated by synthetic hydrographs using the Natural Resources Conservation Service (NRCS). The proposed method was applied to UAV image data collected from the Khosban village, in Taleghan County, Iran, in the ungauged sub-basin of the Khosban River. The study area is located along one kilometre of the river in the middle of the village. The results showed that the flood inundation areas modeled by the HEC-RAS were 33%, 19%, and 8% less than those estimated from the UAV’s FLMs for 25, 50, and 100 years return periods, respectively. For return periods of 200 years, this difference was overestimated by more than 6%, compared to the UAV’s FLM. The maximum flood depth in our four proposed scenarios of hydraulic models varied between 2.33 to 2.83 meters. These analyses showed that this method, based on the UAV imagery, is well suited to improve the hydraulic modeling for seasonal inundation in ungauged rivers, thus providing reliable support to flood mitigation strategies
Publisher: University of Tehran Press

Imaging Floods and Glacier Geohazards with Remote Sensing - Cigna, Francesca; Xie, Hongjie (Remote Sensing, 2020)
Geohazards associated with the dynamics of the liquid and solid water of the Earth’s hydrosphere, such as floods and glacial processes, may pose significant risks to populations, activities and properties [...]
Number: 23 Publisher: Multidisciplinary Digital Publishing Institute

Development of an approach based on historical Landsat data for delineating Canadian flood zones at different return periods - Chokmani, Karem; Zidi, Haythem; El Alem, Anas; Gill-Fortin, Jasmin (EGU General Assembly Conference Abstracts, 2024)
The study addresses the need for flood risk anticipation and planning, through the development of a flood zone mapping approach for different return periods, in order to best prevent and protect populations. Today, traditional methods are too costly, too slow or require too many requirements to be applied over large areas. As part of a project funded by the Canadian Space Agency, Geosapiens and the Institut National de la Recherche Scientifique set themselves the goal of designing an automatic process to generate water presence maps for different return periods at a resolution of 30 m, based on the historical database of Landsat missions from 1982 to the present day. This involved the design, implementation and training of a deep learning algorithm model based on the U-Net architecture for the detection of water pixels in Landsat imagery. The resulting maps were used as the basis for applying a frequency analysis model to fit a probability of occurrence function for the presence of water at each pixel. The frequency analysis data were then used to obtain maps of water occurrence at different return preiods such as 2, 5 and 20 years.

Flood Models: An Exploratory Analysis and Research Trends - Morante-Carballo, Fernando; Montalván-Burbano, Néstor; Arias-Hidalgo, Mijaíl; Domínguez-Granda, Luis; Apolo-Masache, Boris; Carrión-Mero, Paúl (Water, 2022)
Floods can be caused by heavy rainfall and the consequent overflow of rivers, causing low-lying areas to be affected. Populated regions close to riverbeds are the sectors most affected by these disasters, which requires modelling studies to generate different scenarios. The work focuses on the bibliometric analysis of the search for topics such as flood modelling focused on the research, risk, and assessment of these catastrophes, aiming to determine new trends and tools for their application in the prevention of these natural disasters. The methodology consists of: (i) search criteria and database selection, (ii) pre-processing of the selected data and software, and (iii) analysis and interpretation of the results. The results show a wide range of studies for dimensional analysis in different flood scenarios, which greatly benefit the development of flood prevention and risk strategies. In addition, this work provides insight into the different types of software and modelling for flood analysis and simulation and the various trends and applications for future modelling.
Publisher: MDPI AG

A PCA spatial pattern based artificial neural network downscaling model for urban flood hazard assessment - Carreau, J.; Guinot, V. (Advances in Water Resources, 2021)
Publisher: Elsevier BV

Global Asymmetries in the Influence of ENSO on Flood Risk Based on 1,600 Years of Hybrid Simulations - Del Rio Amador, L.; Boudreault, M.; Carozza, D. A. (Geophysical Research Letters, 2023)
AbstractEl Niño‐Southern Oscillation (ENSO) is often considered as a source of long‐term predictability for extreme events via its teleconnection patterns. However, given that its characteristic cycle varies from two to 7 years, it is difficult to obtain statistically significant conclusions based on observational periods spanning only a few decades. To overcome this, we apply the global flood risk modeling framework developed by Carozza and Boudreault to an equivalent of 1,600 years of bias‐corrected General Circulation Model outputs. The results show substantial anomalies in flood occurrences and impacts for El Niño and La Niña when compared to the all‐year baseline. We were able to obtain a larger global coverage of statistically significant results than previous studies limited to observational data. Asymmetries in anomalies for both ENSO phases show a larger global influence of El Niño than La Niña on flood hazard and risk.
Publisher: American Geophysical Union (AGU)

A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada - Bourget, Mathilde; Boudreault, Mathieu; Carozza, David A.; Boudreault, Jérémie; Raymond, Sébastien (ASTIN Bulletin: The Journal of the IAA, 2024)
There is mounting pressure on (re)insurers to quantify the impacts of climate change, notably on the frequency and severity of claims due to weather events such as flooding. This is however a very challenging task for (re)insurers as it requires modeling at the scale of a portfolio and at a high enough spatial resolution to incorporate local climate change effects. In this paper, we introduce a data science approach to climate change risk assessment of pluvial flooding for insurance portfolios over Canada and the United States (US). The underlying flood occurrence model quantifies the financial impacts of short-term (12–48 h) precipitation dynamics over the present (2010–2030) and future climate (2040–2060) by leveraging statistical/machine learning and regional climate models. The flood occurrence model is designed for applications that do not require street-level precision as is often the case for scenario and trend analyses. It is applied at the full scale of Canada and the US over 10–25 km grids. Our analyses show that climate change and urbanization will typically increase losses over Canada and the US, while impacts are strongly heterogeneous from one state or province to another, or even within a territory. Portfolio applications highlight the importance for a (re)insurer to differentiate between future changes in hazard and exposure, as the latter may magnify or attenuate the impacts of climate change on losses.

Adapting to Rising Flood Risk: An Analysis of Insurance Solutions for Canada - Task Force on Flood Insurance and Relocation (Public Safety Canada, 2022)
Last Modified: 2022-08-30

Incentivizing Flood Risk Reduction for Homeowners - Boudreault, M (Global Risk Institute, 2024)
Read the latest report from UQAM and GRI, looking at options to reduce flood risk for Canadian homeowners living in flood-prone areas.

A Global Flood Risk Modeling Framework Built With Climate Models and Machine Learning - Carozza, David A.; Boudreault, Mathieu (Journal of Advances in Modeling Earth Systems, 2021)
AbstractLarge scale flood risk analyses are fundamental to many applications requiring national or international overviews of flood risk. While large‐scale climate patterns such as teleconnections and climate change become important at this scale, it remains a challenge to represent the local hydrological cycle over various watersheds in a manner that is physically consistent with climate. As a result, global models tend to suffer from a lack of available scenarios and flexibility that are key for planners, relief organizations, regulators, and the financial services industry to analyze the socioeconomic, demographic, and climatic factors affecting exposure. Here we introduce a data‐driven, global, fast, flexible, and climate‐consistent flood risk modeling framework for applications that do not necessarily require high‐resolution flood mapping. We use statistical and machine learning methods to examine the relationship between historical flood occurrence and impact from the Dartmouth Flood Observatory (1985–2017), and climatic, watershed, and socioeconomic factors for 4,734 HydroSHEDS watersheds globally. Using bias‐corrected output from the NCAR CESM Large Ensemble (1980–2020), and the fitted statistical relationships, we simulate 1 million years of events worldwide along with the population displaced in each event. We discuss potential applications of the model and present global flood hazard and risk maps. The main value of this global flood model lies in its ability to quickly simulate realistic flood events at a resolution that is useful for large‐scale socioeconomic and financial planning, yet we expect it to be useful to climate and natural hazard scientists who are interested in socioeconomic impacts of climate.
Publisher: American Geophysical Union (AGU)

Multi-tracer approach to understand nitrate contamination and groundwater-surface water interactions in the Mediterranean coastal area of Guerbes-Senhadja, Algeria - Boumaiza, Lamine; Walter, Julien; Chesnaux, Romain; Huneau, Frédéric; Garel, Émilie; Erostate, Mélanie; Johannesson, Karen H.; Vystavna, Yuliya; Bougherira, Nabil; Bordeleau, Geneviève; Stotler, Randy L.; Blarasin, Mónica; et al. (Journal of Contaminant Hydrology, 2022)

Evaluating potential impacts of industrial activities at depth on shallow groundwater: Holistic integration of results from multidisciplinary research in eastern Canada - Rivard, C.; Lavoie, D.; Bordeleau, G.; Huchet, F.; Lefebvre, R.; Duchesne, M.J.; Pinet, N.; Séjourné, S.; Crow, H.; Bellefleur, G.; Brake, V.; Hinds, S. (Groundwater for Sustainable Development, 2024)

Saline and hydrocarbon-bearing fluids detected in shallow aquifers of southern New Brunswick, Canada: Natural occurrence, or deep migration along faults and industrial wellbores? - Bordeleau, G.; Lavoie, D.; Rivard, C.; Pinet, N.; Barton, D.; Hinds, S.; Al, Tom (Science of The Total Environment, 2024)

Large‐scale turbulent mixing at a mesoscale confluence assessed through drone imagery and eddy‐resolved modelling - Duguay, Jason; Biron, Pascale; Buffin‐Bélanger, Thomas (Earth Surface Processes and Landforms, 2022)
Abstract Confluences are sites of intense turbulent mixing in fluvial systems. The large‐scale turbulent structures largely responsible for this mixing have been proposed to fall into three main classes: vertically orientated (Kelvin–Helmholtz) vortices, secondary flow helical cells and smaller, strongly coherent streamwise‐orientated vortices. Little is known concerning the prevalence and causal mechanisms of each class, their interactions with one another and their respective contributions to mixing. Historically, mixing processes have largely been interpreted through statistical moments derived from sparse pointwise flow field and passive scalar transport measurements, causing the contribution of the instantaneous flow field to be largely overlooked. To overcome the limited spatiotemporal resolution of traditional methods, herein we analyse aerial video of large‐scale turbulent structures made visible by turbidity gradients present along the mixing interface of a mesoscale confluence and complement our findings with eddy‐resolved numerical modelling. The fast, shallow main channel (Mitis) separates over the crest of the scour hole's avalanche face prior to colliding with the slow, deep tributary (Neigette), resulting in a streamwise‐orientated separation cell in the lee of the avalanche face. Nascent large‐scale Kelvin–Helmholtz instabilities form along the collision zone and expand as the high‐momentum, separated near‐surface flow of the Mitis pushes into them. Simultaneously, the strong downwelling of the Mitis is accompanied by strong upwelling of the Neigette. The upwelling Neigette results in ∼50% of the Neigette's discharge crossing the mixing interface over the short collision zone. Helical cells were not observed at the confluence. However, the downwelling Mitis, upwelling Neigette and separation cell interact to generate considerable streamwise vorticity on the Mitis side of the mixing interface. This streamwise vorticity is strongly coupled to the large‐scale Kelvin–Helmholtz instabilities, which greatly enhances mixing. Comparably complex interactions between large‐scale Kelvin–Helmholtz instabilities and coherent streamwise vortices are expected at other typical asymmetric confluences exhibiting a pronounced scour hole.

Climate‐Driven Variations in Nitrogen Retention From a Riverine Submerged Aquatic Vegetation Meadow - Botrel, M.; Hudon, C.; Heffernan, J. B.; Biron, P. M.; Maranger, R. (Water Resources Research, 2022)
Abstract Large rivers can retain a substantial amount of nitrogen (N), particularly in submerged aquatic vegetation (SAV) meadows that may act as disproportionate control points for N retention. However, the temporal variation of N retention in large rivers remains unknown since past measurements were snapshots in time. Using high‐frequency plants and NO 3 − measurements over the summers 2012–2017, we investigated how the climate variation influenced N retention in a SAV meadow (∼10 km 2 ) at the confluence zone of two agricultural tributaries entering the St. Lawrence River. Distinctive combinations of water temperature and level were recorded between years, ranging from extreme hot‐low (2012) and cold‐high (2017) summers (2°C and 1.4 m interannual range). Using an indicator of SAV biomass, we found that these extreme hot‐low and cold‐high years had reduced biomass compared to hot summers with intermediate levels. In addition, changes in main stem water levels were asynchronous with the tributary discharges that controlled NO 3 − inputs at the confluence. We estimated daily N uptake rates from a moored NO 3 − sensor and partitioned these into assimilatory and dissimilatory pathways. Measured rates were variable but among the highest reported in rivers (median 576 mg N m −2 d −1 , range 60–3,893 mg N m −2 d −1 ) and SAV biomass promoted greater proportional retention and permanent N loss through denitrification. We estimated that the SAV meadow could retain up to 0.8 kt N per year and 87% of N inputs, but this valuable ecosystem service is contingent on how climate variations modulate both N loads and SAV biomass. , Plain Language Summary Large rivers remove significant amounts of nitrogen pollution generated by humans in waste waters and from fertilizers applied to agricultural lands. Underwater meadows of aquatic plants remove nitrogen particularly well. To keep the river clean, plants use the nitrogen themselves and promote conditions where bacteria can convert this pollution into a gas typically found in air. Measuring nitrogen removal in rivers is really difficult, and we do not know how climate conditions influence this removal or plant abundance. We successfully measured nitrogen pollution removal from an underwater plant meadow in a large river over six summers. We found that plant abundance and river nitrogen inputs were critical to determine how much pollution was removed, and that these were controlled by climatic conditions. Plant abundance was controlled by both water temperatures and levels. When water was warm and levels were neither too high nor too low, conditions were perfect for lots of plants to grow, which mainly stimulated bacteria that permanently eliminated nitrogen. We showed that the amount of nitrogen pollution removed over the summer by the meadow changes with climatic conditions but in general represents the amount produced by a city of half a million people. , Key Points Nitrogen retention and biomass were measured at a high resolution over six summers in a submerged aquatic vegetation meadow of a large river Among the highest riverine, nitrate uptake rates were recorded, and 47%–87% of loads were retained with plants favoring denitrification Interannual climate variations influenced nitrate retention by altering water levels, temperature, plant biomass, and tributary nitrate load

Combining quadrat, rake, and echosounding to estimate submerged aquatic vegetation biomass at the ecosystem scale - Botrel, Morgan; Hudon, Christiane; Biron, Pascale M.; Maranger, Roxane (Limnology and Oceanography: Methods, 2023)
Abstract Measuring freshwater submerged aquatic vegetation (SAV) biomass at large spatial scales is challenging, and no single technique can cost effectively accomplish this while maintaining accuracy. We propose to combine and intercalibrate accurate quadrat‐scuba diver technique, fast rake sampling, and large‐scale echosounding. We found that the overall relationship between quadrat and rake biomass is moderately strong (pseudo R 2 = 0.61) and varies with substrate type and SAV growth form. Rake biomass was also successfully estimated from biovolume (pseudo R 2 = 0.57), a biomass proxy derived from echosounding. In addition, the relationship was affected, in decreasing relevance, by SAV growth form, flow velocity, acoustic data quality, depth, and wind conditions. Sequential application of calibrations yielded predictions in agreement with quadrat observations, but echosounding predictions underestimated biomass in shallow areas (< 1 m) while outperforming point estimation in deep areas (> 3 m). Whole‐system quadrat‐equivalent biomass from echosounding differed by a factor of two from point survey estimates, suggesting echosounding is more accurate at larger scales owing to the increased sample size and better representation of spatial heterogeneity. To decide when an individual or a combination of techniques is profitable, we developed a step‐by‐step guideline. Given the risks of quadrat‐scuba diver technique, we recommend developing a one‐time quadrat–rake calibration, followed by the use of rake and echosounding when sampling at larger spatial and temporal scales. In this case, rake sampling becomes a valid ground truthing method for echosounding, also providing valuable species information and estimates in shallow waters where echosounding is inappropriate.

Density effects on streamwise-orientated vorticity at river confluences: a laboratory investigation - Duguay, J.M.; Biron, P.M.; Lacey, R.W.J. (Journal of Fluid Mechanics, 2023)
Small differences in the densities of a river confluence's tributaries (i.e. 0.5 kg m ${-3}$ ) have been proposed to cause coherent streamwise-oriented vortices (SOVs) in its mixing interface. These secondary flow structures are thought to result from density-driven gravity currents being laterally confined between the converging flows. However, empirical evidence for density SOVs and the confined gravity current mechanism is lacking. To this end, experiments are carried out in a laboratory confluence permitting a spectrum of thermal density differences between its tributaries. Particle image velocimetry and laser-induced fluorescence are used simultaneously to study the mixing interface's dynamics. The sensitivity of the mixing interface's secondary flow structure to the confluence's momentum ratio and the magnitude of the density difference is evaluated. Density SOVs are confirmed in the mixing interface and are caused by the gravity currents being confined laterally as the opposing flows merge and accelerate downstream. The SOVs are largest and most coherent when the momentum of the dense channel is greater than that of the light channel. The dynamics of these secondary flow structures is strongly coupled to periodic vertically orientated Kelvin–Helmholtz instabilities. The striking similarities between the empirically reproduced SOVs herein and those recently observed at the Coaticook-Massawippi confluence (Quebec, Canada), despite a two-order magnitude difference in physical scale, suggest density SOVs are a scale-independent flow structure at confluences when specific, yet relatively common, hydraulic and density conditions align.

Trajectoires et visées de l'hydrogéomorphologie au Québec - Buffin‐Bélanger, Thomas; Lachapelle, Félix; Biron, Pascale; Boivin, Maxime (Canadian Geographies / Géographies canadiennes, 2024)
Résumé L'hydrogéomorphologie étudie la dynamique des rivières en se concentrant sur les interactions liant la structure des écoulements, la mobilisation et le transport des sédiments et les morphologies qui caractérisent les cours d'eau et leur bassin‐versant. Elle offre un cadre d'analyse et des outils pour une meilleure intégration des connaissances sur la dynamique des rivières pour la gestion des cours d'eau au sens large, et plus spécifiquement, pour leur restauration, leur aménagement et pour l'évaluation et la prévention des risques liés aux aléas fluviaux. Au Québec, l'hydrogéomorphologie émerge comme contribution significative dans les approches de gestion et d'évaluation du risque et se trouve au cœur d'un changement de paradigme dans la gestion des cours d'eau par lequel la restauration des processus vise à augmenter la résilience des systèmes et des sociétés et à améliorer la qualité des environnements fluviaux. Cette contribution expose la trajectoire de l'hydrogéomorphologie au Québec à partir des publications scientifiques de géographes du Québec et discute des visées de la discipline en recherche et en intégration des connaissances pour la gestion des cours d'eau . , Abstract Hydrogeomorphology studies river dynamics, focusing on the interactions between flow structure, sediment transport, and the morphologies that characterize rivers and their watersheds. It provides an analytical framework and tools for better integrating knowledge of river dynamics into river management in the broadest sense, and more specifically, into river restoration as well as into the assessment and prevention of risks associated with fluvial hazards. In Quebec, hydrogeomorphology is emerging as a significant contribution to risk assessment and management approaches, and is at the heart of a paradigm shift in river management whereby process restoration aims to increase the resilience of fluvial systems and societies, and improve the quality of fluvial environments. This contribution outlines the trajectory of hydrogeomorphology in Quebec, based on scientific publications by Quebec geographers, and discusses the discipline's aims in research and knowledge integration for river management . , Messages clés Les géographes du Québec ont contribué fortement au développement des connaissances et outils de l'hydrogéomorphologie. L'hydrogéomorphologie a évolué d'une science fondamentale à une science où les connaissances fondamentales sont au service de la gestion des cours d'eau. L'hydrogéomorphologie et le cortège de connaissances et d'outils qu'elle promeut font de cette discipline une partenaire clé pour une gestion holistique des cours d'eau.

Societal drivers for the integration of hydrogeomorphology and human benefits in river restoration projects - Gariépy‐Girouard, Étienne; Buffin‐Bélanger, Thomas; Biron, Pascale M. (River Research and Applications, 2025)
Abstract Integrating hydrogeomorphological (HGM) principles into the restoration of degraded rivers can achieve sustainable results and provide various human benefits. HGM principles mainly involve understanding the context and processes that shape a fluvial system before any intervention, in order to support its dynamism and to align with its potential functioning and uses. Despite recent management approaches inspired by HGM principles, most restoration projects carried out in Quebec (Canada) are not process‐based and target specific one‐dimensional objectives. Although there is an overall lack of post‐project monitoring, several projects appear to have failed or had mixed success. This research aims to shed light on the diversity of societal drivers behind river restoration projects and to examine how they influence the integration of HGM principles and human benefits. Four restoration projects were characterized through participant observation and interviews with the organizations running them. Representatives of two ministries involved in river restoration and management were also interviewed. The results show that projects were mainly shaped by public acceptance disregarding HGM principles, which can lead to poorly‐informed action. Project funding and stakeholders' expertise have also challenged project implementation and played a key role in defining their objectives. The addition of these components improve the current analytical frameworks for identifying river restoration objectives. Depending on specific sociocultural, political and legislative contexts, funding programs and stakeholders' expertise may either facilitate or restrict the integration of HGM principles and human benefits in the projects. Recognizing these key drivers reframes river restoration as a fundamentally social activity and enlightens how they could impel innovative approaches towards more sustainable results.

Determination of critical hydraulic parameters affecting erosion in spillways using experimental and numerical analyses - Motahari Moghadam, Elaheh (Université du Québec à Chicoutimi, 2025)
Dam spillways are susceptible to a range of engineering challenges including structural deficiencies, insufficient discharge capacity, and mechanical failures; however, a particularly significant issue is hydraulic erosion, which poses a significant threat to dam infrastructure. This necessitates a comprehensive assessment of both hydraulic and rock mechanical parameters to ensure structural integrity and operational resilience. In the rock mechanical aspect of hydraulic erosion, the resistive capacity of the material holds great importance, while in the hydraulic aspect, the erosive force of water plays a pivotal role. Hence, neglecting these incidents would increase the risk of overtopping and subsequent downstream flooding, thereby impacting the overall safety and operational reliability of the dam. This study focuses on investigating the hydraulic parameters of a smooth surface unlined open channel spillway. By utilizing both numerical modeling and experimental analysis, we aim to explore how variations in these parameters impact erosion in dams’ spillways. The research centers on the Romaine 4 dam spillway, situated in the northeastern region of Quebec in Canada as a representative case study. The physical model of this spillway was constructed at the Université du Québec à Chicoutimi, where we carried out the experimental analyses. In this research, we also conducted a comprehensive numerical analysis using Finite Volume Method (FVM), enabling a detailed examination of three-dimensional flow behavior within the spillway. This enabled a precise monitoring of the fluid motion patterns. Moreover, an experimental approach was utilized to enhance the accuracy and reliability of the results. This involved conducting detailed tests on the reduced-scale model using a XYZ robotic system capable of movement in X,Y,Z directions and capturing position, velocity and pressure. The results of numerical and experimental analyses reveal that the numerical model effectively captures the overall flow characteristics, closely predicting the average velocity throughout the channel. However, it indicates limitations in accurately predicting extreme velocities, such as maximum and minimum values. The results show that the maximum discrepancies between experimental and numerical data primarily concern extreme velocities, with the numerical model underestimating maximum velocities and overestimating minimum velocities, with errors more pronounced at higher flow rates and upstream. This discrepancy can reach up to 60% in certain areas. Furthermore, the study examined the effects of gates on variability of hydraulic parameters like flow depth and velocity. The analysis of a number of gate configurations revealed that double-gate spillways maintain more consistent flow depths across all significant cross-sections. By explaining the complex interaction between hydraulic behavior and spillway design, this research attempts to advance our understanding of hydraulic-prone erosion areas in dam spillways and ensure the long-term resilience of dam infrastructure. Les évacuateurs de crues des barrages sont sujets à divers défis d'ingénierie, incluant des défaillances structurelles, une capacité d'évacuation insuffisante et des pannes mécaniques; cependant, l'érosion hydraulique constitue une problématique particulièrement importante qui menace l'infrastructure des barrages. Il est donc nécessaire d’évaluer de manière approfondie les paramètres hydrauliques et mécaniques des roches afin d’assurer l’intégrité structurelle et la résilience opérationnelle. Dans l’aspect mécanique des roches concernant l’érosion hydraulique, la capacité de résistance du matériau revêt une grande importance, tandis que dans l’aspect hydraulique, la force érosive de l’eau joue un rôle essentiel. Par conséquent, ignorer ces phénomènes augmenterait le risque de débordement et d’inondation en aval, impactant ainsi la sécurité et la fiabilité opérationnelle globale du barrage. Cette étude se concentre sur l’analyse des paramètres hydrauliques d'un évacuateur de crues à canal ouvert non revêtu et à surface lisse. En utilisant à la fois la modélisation numérique et l’analyse expérimentale, nous visons à explorer comment les variations de ces paramètres influencent l’érosion dans les évacuateurs de crues des barrages. La recherche porte sur l’évacuateur de crues du barrage Romaine 4, situé dans la région nord-est du Québec au Canada, en tant qu’étude de cas représentative. Le modèle physique de cet évacuateur a été construit à l’Université du Québec à Chicoutimi, où nous avons effectué les analyses expérimentales. Dans cette recherche, nous avons également réalisé une analyse numérique complète en utilisant la méthode des volumes finis (FVM), permettant un examen détaillé du comportement tridimensionnel de l’écoulement dans l’évacuateur. Cela a permis un suivi précis des schémas de mouvement du fluide. En outre, une approche expérimentale a été utilisée pour accroître la précision et la fiabilité des résultats, en réalisant des tests détaillés sur le modèle réduit à l’aide d’un système robotisé XYZ qui est capable de se déplacer dans trois directions (X, Y, Z), pour effectuer des prises de mesures de position, vitesse et pression. Les résultats des analyses numériques et expérimentales révèlent que le modèle numérique capture efficacement les caractéristiques générales de l’écoulement, prédisant de manière précise la vitesse moyenne dans le canal. Cependant, il présente des limitations dans la prédiction précise des pression dynamique et statique extrêmes comme les valeurs maximales et minimales. Les résultats montrent que les écarts maximaux entre les données expérimentales et numériques concernent principalement les vitesses extrêmes, le modèle numérique sous-estimant les vitesses maximales et surestimant les minimales, avec des erreurs plus marquées aux débits élevés et en amont. Cet écart peut aller jusqu’aux 60% à certains endroits. Par ailleurs, l’étude a examiné les effets des vannes sur la variabilité des paramètres hydrauliques tels que la profondeur de l’écoulement et la vitesse. L’analyse de plusieurs configurations de vannes a révélé que les évacuateurs à double vanne maintiennent des profondeurs d’écoulement plus constantes à travers toutes les sections transversales significatives. En expliquant l’interaction complexe entre le comportement hydraulique et la conception des évacuateurs de crues, cette recherche vise à améliorer notre compréhension des zones sujettes à l’érosion hydraulique dans les évacuateurs de barrages et à assurer la résilience à long terme de l’infrastructure des barrages.

Dynamique de l'aléa torrentiel au long de la rivière Chaudière : analyse historique et modélisation - Constantineau, Jo-Annie (UQAM, 2025)
Dans le bassin-versant de la rivière Chaudière, les inondations sont partie intégrante de la réalité territoriale. En effet, de nombreuses études ont été réalisées dans les dernières années concernant les inondations en eau libre et par embâcle. Néanmoins, on observe que les inondations torrentielles, ou crues torrentielles, bien qu’omniprésentes dans la région, sont très peu documentées à ce jour. Le présent mémoire s’intéresse à la dynamique spatio-temporelle de ces évènements et aux facteurs aggravants présents sur le territoire qui tendent à amplifier le phénomène. Par une double approche qualitative et quantitative, qui combine une recension historique, la caractérisation des sous-bassins-versants et la modélisation des facteurs de vulnérabilité environnementale, nous avons dressé un premier portrait de l’aléa torrentiel à l’échelle du bassin-versant de la rivière Chaudière. Ainsi, nous avons pu répertorier 53 évènements à caractère torrentiel pour la période de 1900 à aujourd’hui. La collecte des informations liées aux crues torrentielles, soit les facteurs météorologiques, anthropiques et géomorphologiques ont permis d’établir des constats généraux quant à l’occurrence de celles-ci. L’occurrence des évènements à caractère torrentiel semble premièrement liée aux passages d’évènements météorologiques extrêmes. Les facteurs aggravants consistent en un aménagement du territoire qui accroît le ruissellement (augmentation des surfaces minéralisées et diminution des forêts, prairies et milieux humides) et une disposition géomorphologique des tributaires (forte pente et compacité) qui provoque une amplification du ruissellement lors de fortes précipitations. L’analyse multicritère repose sur l’addition d’indices amplifiant le ruissellement lors de fortes précipitations (pente, occupation du sol et potentiel de ruissellement). La comparaison entre les sous-bassins-versants présentant les valeurs les plus élevées et ceux ayant connu le plus d'événements d'inondation selon la recension historique a démontré la pertinence de cette méthode pour identifier, de manière préliminaire, les sous-bassins-versants potentiellement vulnérables à l’aléa torrentiel. Cette étude se veut donc un premier jalon dans l’acquisition de connaissances sur la dynamique torrentielle dans le bassin-versant de la rivière Chaudière. _____________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : inondation, torrents, crues torrentielles, pluies torrentielles, aléas torrentiels, bassin-versant de la rivière Chaudière, facteurs aggravants, conditions hydrométéorologiques
Place: Montréal (Québec) Publisher: Université du Québec à Montréal

Information Seeking and Information Sharing Related to Hurricane Harvey - Yang, Janet Z.; Zhuang, Jun (Journalism & Mass Communication Quarterly, 2020)
This study is focused on social cognitive variables that motivate information seeking and information sharing related to Hurricane Harvey. Survey results from a nationally representative sample and a quota sample of Houston residents indicate that climate change beliefs and issue salience are consistent predictors of risk perception, which increases individuals’ negative emotions and information insufficiency. This need for information subsequently motivates information seeking and information sharing. Informational subjective norms are significantly related to seeking and sharing in the Houston sample, whereas perceived information gathering capacity and trust in media are significant predictors in the national sample.

Twitter communication during winter storm Uri in San Antonio, Texas - Implications for climate resiliency planning - Terracciano, Emmalyn; Han, Albert Tonghoon (Cities, 2023)

Review of social influence in crisis communications and evacuation decision-making - Sadri, Arif Mohaimin; Ukkusuri, Satish V.; Ahmed, Md Ashraf (Transportation Research Interdisciplinary Perspectives, 2021)

A Meta-Cognitive Approach to Predicting Hurricane Evacuation Behavior - Goldberg, Matthew H.; Marlon, Jennifer R.; Rosenthal, Seth A.; Leiserowitz, Anthony (Environmental Communication, 2020)

Flood Risk Management via Risk Communication, Cognitive Appraisal, Collective Efficacy, and Community Action - Lin, Carolyn A. (Sustainability, 2023)
Climate change and more frequent severe storms have caused persistent flooding, storm surges, and erosion in the northeastern coastal region of the United States. These weather-related disasters have continued to generate negative environmental consequences across many communities. This study examined how coastal residents’ exposure to flood risk information and information seeking behavior were related to their threat appraisal, threat-coping efficacy, and participation in community action in the context of building social resilience. A random sample of residents of a coastal community in the Northeastern United States was selected to participate in an online survey (N = 302). Key study results suggested that while offline news exposure was weakly related to flood vulnerability perception, online news exposure and mobile app use were both weakly associated with flood-risk information seeking. As flood vulnerability perception was strongly connected to flood severity perception but weakly linked to lower self-efficacy beliefs, flood severity perception was weakly and moderately associated with response-efficacy beliefs and information seeking, respectively. Furthermore, self-efficacy beliefs, response efficacy beliefs, and flood-risk information seeking were each a weak or moderate predictor of collective efficacy beliefs. Lastly, flood risk information-seeking was a strong predictor and collective efficacy beliefs were a weak predictor of community action for flood-risk management. This study tested a conceptual model that integrated the constructs from risk communication, information seeking, and protection motivation theory. Based on the modeling results reflecting a set of first-time findings, theoretical and practical implications are discussed.

The role of public relations in building community resilience to natural disasters: perspectives from Sri Lanka and New Zealand - Dharmasena, M. K. Gayadini Imesha; Toledano, Margalit; Weaver, C. Kay (Journal of Communication Management, 2020)
The paper identifies a role for public relations in disaster management by analysing disaster and communication managers' understanding of community resilience and their use of communication in the context of two different cultural environments.,The research study comprised 51 in-depth qualitative interviews with disaster managers in Sri Lanka and New Zealand, which were thematically analysed using the software programme NVivo 10.,The study identified cultural differences in Sri Lanka and New Zealand that impact on how managers' communicate in natural disaster situations. The findings indicated that public relations’ understanding of communities’ cultures, their communication, networking and lobbying skills could further enhance the effectiveness of efforts to build community resilience to disasters.,Nations are complex multicultural realities; the findings cannot be generalized to make claims about how natural disasters are managed in different national contexts.,The paper identifies the unrealized potential of public relations’ expertise in communication, community relations, networking and lobbying to contribute to building community resilience to natural disasters.,By supporting efforts to build community resilience to disasters, public relations practitioners can contribute to social well-being in times of catastrophic natural disasters.,The paper adds an innovative perspective to public relations crisis literature by identifying the potential contribution of public relations’ concepts and practices to build community resilience to natural disasters. It demonstrates how sociocultural differences may affect disaster communication strategies.
Publisher: Emerald Publishing Limited

When We Don't Want to Know More: Information Sufficiency and The Case Of Swedish Flood Risks - Lakew, Yuliya; Olausson, Ulrika (Journal of International Crisis and Risk Communication Research, 2023)
This study investigates the phenomenon of information (in)sufficiency in the context of flood risks. Individuals’ perception of how much risk information they need is a major trigger and driver of information-seeking behavior, and therefore it is an important part of creating effective preventive risk-communication campaigns. To understand factors that contribute to individuals’ sense of information (in)sufficiency, the roles played by prior experiences of floods and general risk sensitivity were analyzed using survey data from residents in flood-risk zones. The findings highlight that every third respondent reported a state of information sufficiency. Residents with prior experience evaluate their information sufficiency level based on their perception of consequences of future floods. But it is general risk sensitivity that best explains need for more information.

How to Exchange Stories of Local Flood Resilience From Flood Rich Areas to the Flooded Areas of the Future - Holmes, Andrew; McEwen, Lindsey (Environmental Communication, 2020)

Personal Stories Can Shift Climate Change Beliefs and Risk Perceptions: The Mediating Role of Emotion - Gustafson, Abel; Ballew, Matthew T.; Goldberg, Matthew H.; Cutler, Matthew J.; Rosenthal, Seth A.; Leiserowitz, Anthony (Communication Reports, 2020)

Addressing the climate change adaptation puzzle: a psychological science perspective - Bechtoldt, Myriam N.; Götmann, Alexander; Moslener, Ulf; Pauw, W. Pieter (Climate Policy, 2021)

The Usefulness of Global and Regional Precipitation and Temperature Reanalyses for Flood Modeling at the Catchment Scale - Valdez, Emixi; Anctil, Francois; Ramos, Maria-Helena (AGU Fall Meeting Abstracts, 2022)
Atmospheric reanalysis data provides a numerical description of global and regional water cycles by combining models and observations. These datasets are increasingly valuable as a substitute for observations in regions where these are scarce. They could significantly contribute to reducing losses by feeding flood early warning systems that can inform the population and guide civil security action. We assessed the suitability of two different precipitation and temperature reanalysis products readily available for predicting historic flooding of the La Chaudière River in Quebec: 1) Environment and Climate Change Canada's Regional Deterministic Reanalysis System (RDRS-v2) and 2) ERA5 from the Copernicus Climate Change Service. We exploited a multi-model hydrological ensemble prediction system that considers three sources of uncertainty: initial conditions, model structure, and weather forcing to produce streamflow forecasts up to 5 days into the future with a time step of 3 hours. These results are compared to a provincial reference product based on gauge measurements of the Ministère de l'Environnement et de la Lutte contre les Changements Climatiques. Then, five conceptual hydrological models were calibrated with three different meteorological datasets (RDRS-v2, ERA5, and observational gridded) and fed with two ensemble weather forecast products: 1) the Regional Ensemble Prediction System (REPS) from the Environment and Climate Change Canada and 2) the ensemble forecast issued by the European Centre for Medium-Range Weather Forecasts (ECMWF). Results reveal that the calibration of the model with reanalysis data as input delivered a higher accuracy in the streamflow simulation providing a useful resource for flood modeling where no other data is available. However, although the selection of the reanalysis is a determinant of capturing the flood volumes, selecting weather forecasts is more critical in anticipating discharge threshold exceedances.

Lessons learned from the NSERC Canadian FloodNet on improving flood forecasting systems and management capacity - Xenopoulos, Marguerite; Coulibaly, Paulin; Anctil, Francois; Burn, Donald; Nguyen, Van-Thanh-Van (AGU Fall Meeting Abstracts, 2021)
In Canada, floods are the most common largely distributed hazard to life, property, the economy, water systems, and the environment costing the Canadian economy billions of dollars. Arising from this is FloodNet: a transdisciplinary strategic research network funded by Canadas Natural Sciences and Engineering Research Council, as a vehicle for a concerted nation-wide effort to improve flood forecasting and to better assess risk and manage the environmental and socio-economic consequences of floods. Four themes were explored in this network which include 1) Flood regimes in Canada; 2) Uncertainty of floods; 3) Development of a flood forecasting and early warning system and 4) Physical, socio-economic and environmental effects of floods. Over the years a range of statistical, hydrologic, modeling, and economic and psychometric analyses were used across the themes. FloodNet has made significant progress in: assessing spatial and temporal variation of extreme events; updating intensity-duration-frequency (IDF) curves; improving streamflow forecasting using novel techniques; development and testing of a Canadian adaptive flood forecasting and early warning system (CAFFEWS); a better understanding of flood impacts and risk. Despite these advancements FloodNet ends at a time when the World is still grappling with severe floods (e.g., Europe, China, Africa) and we report on several lessons learned. Mitigating the impact of flood hazards in Canada remains a challenging task due to the countrys varied geography, environment, and jurisdictional political boundaries. Canadian technical guide for developing IDF relations for infrastructure design in the climate change context has been recently updated. However, national guidelines for flood frequency analyses are needed since across the country there is not a unified approach to flood forecasting as each jurisdiction uses individual models and procedures. From the perspective of risk and vulnerability, there remains great need to better understand the direct and indirect impacts of floods on society, the economy and the environment.

Following up on flood adaptation in Québec households four years later: A prospective exploratory study - Valois, Pierre; Anctil, François; Cloutier, Geneviève; Tessier, Maxime; Herpin-Saunier, Naomie (International Journal of Disaster Risk Reduction, 2023)

High-resolution mapping of tree species and associated uncertainty by combining aerial remote sensing data and convolutional neural networks ensemble - Sylvain, Jean-Daniel; Drolet, Guillaume; Thiffault, Évelyne; Anctil, François (International Journal of Applied Earth Observation and Geoinformation, 2024)

A global analysis of ice phenology for 3702 lakes and 1028 reservoirs across the Northern Hemisphere using Sentinel-2 imagery - Domart, Doris; Nadeau, Daniel F.; Thiboult, Antoine; Anctil, François; Ghobrial, Tadros; Prairie, Yves T.; Bédard-Therrien, Alexis; Tremblay, Alain (Cold Regions Science and Technology, 2024)

Impacts of forest canopy heterogeneity on plot-scale hydrometeorological variables - Insights from an experiment in the humid boreal forest with the Canadian Land Surface Scheme - Lagueux, Philippe; Sylvain, Jean-Daniel; Drolet, Guillaume; Isabelle, Pierre-Erik; Leonardini, Gonzalo; Nadeau, Daniel F.; Anctil, François (Agricultural and Forest Meteorology, 2024)

Assessing the hydroclimatic sensitivity of tree species in Northeastern America through spatiotemporal modelling of annual tree growth - Sylvain, Jean-Daniel; Drolet, Guillaume; Kiriazis, Nicholas; Thiffault, Évelyne; Anctil, François (Agricultural and Forest Meteorology, 2024)

How does a warm and low-snow winter impact the snow cover dynamics in a humid and discontinuous boreal forest? Insights from observations and modeling in eastern Canada - Bouchard, Benjamin; Nadeau, Daniel F.; Domine, Florent; Anctil, François; Jonas, Tobias; Tremblay, Étienne (Hydrology and Earth System Sciences, 2024)
Abstract. In the boreal forest of eastern Canada, winter temperatures are projected to increase substantially by 2100. This region is also expected to receive less solid precipitation, resulting in a reduction in snow cover thickness and duration. These changes are likely to affect hydrological processes such as snowmelt, the soil thermal regime, and snow metamorphism. The exact impact of future changes is difficult to pinpoint in the boreal forest, due to its complex structure and the fact that snow dynamics under the canopy are very different from those in the gaps. In this study, we assess the influence of a low-snow and warm winter on snowmelt dynamics, soil freezing, snowpack properties, and spring streamflow in a humid and discontinuous boreal catchment of eastern Canada (47.29° N, 71.17° W; ≈ 850 m a.m.s.l.) based on observations and SNOWPACK simulations. We monitored the soil and snow thermal regimes and sampled physical properties of the snowpack under the canopy and in two forest gaps during an exceptionally low-snow and warm winter, projected to occur more frequently in the future, and during a winter with conditions close to normal. We observe that snowmelt was earlier but slower, top soil layers were cooler, and gradient metamorphism was enhanced during the low-snow and warm winter. However, we observe that snowmelt duration increased in forest gaps, that soil freezing was enhanced only under the canopy, and that snow permeability increased more strongly under the canopy than in either gap. Our results highlight that snow accumulation and melt dynamics are controlled by meteorological conditions, soil freezing is controlled by forest structure, and snow properties are controlled by both weather forcing and canopy discontinuity. Overall, observations and simulations suggest that the exceptionally low spring streamflow in the winter of 2020–2120 was mainly driven by low snow accumulation, slow snowmelt, and low precipitation in April and May rather than enhanced percolation through the snowpack and soil freezing.

Using the ERA5 and ERA5-Land reanalysis datasets for river water temperature modelling in a data-scarce region - Gatien, Philippe; Arsenault, Richard; Martel, Jean-Luc; St-Hilaire, André (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2023)

Ice accumulation at a water intake: a case study on the Mille-Iles River, Québec - Ghobrial, Tadros; Pierre, Amandine; Boyd, Sean; Loewen, Mark (Canadian Journal of Civil Engineering, 2023)
The blockage of water intakes by ice is recurrent in northern rivers during winter. Previous field studies have monitored field conditions leading to ice blockage and provided a review of mitigations methods. However, to improve the efficacy of these measures, the mechanisms that create the blockage need to be locally measured. For this purpose, a field campaign was implemented to monitor a water intake on the Mille-Iles River at Terrebonne, Quebec, during the winter of 2020–2021. Results from this study showed that ice accumulation on the trash rack had an average growth rate of 1.35 cm/h and reached a maximum thickness of 24 cm. The release rate of these trash rack accumulation events was on average 1.8 cm/h, which is 30% faster than the deposition rate. A minimum cumulative degree minutes of supercooling of 4.5 °C.min was required for the start of a trash-rack ice-accumulation event.

Novel Dynamic Technique, Nano-DIHM, for Rapid Detection of Oil, Heavy Metals, and Biological Spills in Aquatic Systems - Hall, Ryan; Pal, Devendra; Ariya, Parisa A. (Analytical Chemistry, 2022)

Future flow and water temperature scenarios in an impounded drainage basin: implications for summer flow and temperature management downstream of the dam - Khorsandi, Mostafa; St-Hilaire, André; Arsenault, Richard; Martel, Jean-Luc; Larabi, Samah; Schnorbus, Markus; Zwiers, Francis (Climatic Change, 2023)

Multisite calibration of a semi-distributed hydrologic and thermal model in a large Canadian watershed - Khorsandi, Mostafa; St-Hilaire, Andre; Arsenault, Richard (Hydrological Sciences Journal, 2022)

Ice processes in culverts with two fish passage designs: a case study in southern Quebec - Ladouceur, Jean-Robert; Ghobrial, Tadros (2023)
According to Department of Fisheries and Oceans Canada, culverts and other stream crossings must be designed to ensure fish passage. The effects of ice processes on these fish passage designs have never been assessed. This study is the first to document ice processes on two different types of fish passage designs (streambed simulation and baffle). The results of a 2 year field monitoring campaign showed that the culvert simulating the streambed retains a natural ice regime, i.e., both freeze-up and break-up occurred concurrently with the rest of the stream, while multiple supercooling events were recorded under a thin ice cover. As for the culvert with baffles, it was observed that the ice cover formed earlier and stayed longer in the culvert, which can create a barrier for fish transiting through them.

Geovisualization of Hydrological Flow in Hexagonal Grid Systems - Li, Mingke; McGrath, Heather; Stefanakis, Emmanuel (Geographies, 2022)
Recent research has extended conventional hydrological algorithms into a hexagonal grid and noted that hydrological modeling on a hexagonal mesh grid outperformed that on a rectangular grid. Among the hydrological products, flow routing grids are the base of many other hydrological simulations, such as flow accumulation, watershed delineation, and stream networks. However, most of the previous research adopted the D6 algorithm, which is analogous to the D8 algorithm over a rectangular grid, to produce flow routing. This paper explored another four methods regarding generating flow directions in a hexagonal grid, based on four algorithms of slope aspect computation. We also developed and visualized hexagonal-grid-based hydrological operations, including flow accumulation, watershed delineation, and hydrological indices computation. Experiments were carried out across multiple grid resolutions with various terrain roughness. The results showed that flow direction can vary among different approaches, and the impact of such variation can propagate to flow accumulation, watershed delineation, and hydrological indices production, which was reflected by the cell-wise comparison and visualization. This research is practical for hydrological analysis in hexagonal, hierarchical grids, such as Discrete Global Grid Systems, and the developed operations can be used in flood modeling in the real world.

The Great Lakes Runoff Intercomparison Project Phase 4: the Great Lakes (GRIP-GL) - Mai, Juliane; Shen, Hongren; Tolson, Bryan A.; Gaborit, Étienne; Arsenault, Richard; Craig, James R.; Fortin, Vincent; Fry, Lauren M.; Gauch, Martin; Klotz, Daniel; Kratzert, Frederik; O'Brien, Nicole; et al. (Hydrology and Earth System Sciences, 2022)
Abstract. Model intercomparison studies are carried out to test and compare the simulated outputs of various model setups over the same study domain. The Great Lakes region is such a domain of high public interest as it not only resembles a challenging region to model with its transboundary location, strong lake effects, and regions of strong human impact but is also one of the most densely populated areas in the USA and Canada. This study brought together a wide range of researchers setting up their models of choice in a highly standardized experimental setup using the same geophysical datasets, forcings, common routing product, and locations of performance evaluation across the 1×106 km2 study domain. The study comprises 13 models covering a wide range of model types from machine-learning-based, basin-wise, subbasin-based, and gridded models that are either locally or globally calibrated or calibrated for one of each of the six predefined regions of the watershed. Unlike most hydrologically focused model intercomparisons, this study not only compares models regarding their capability to simulate streamflow (Q) but also evaluates the quality of simulated actual evapotranspiration (AET), surface soil moisture (SSM), and snow water equivalent (SWE). The latter three outputs are compared against gridded reference datasets. The comparisons are performed in two ways – either by aggregating model outputs and the reference to basin level or by regridding all model outputs to the reference grid and comparing the model simulations at each grid-cell. The main results of this study are as follows: The comparison of models regarding streamflow reveals the superior quality of the machine-learning-based model in the performance of all experiments; even for the most challenging spatiotemporal validation, the machine learning (ML) model outperforms any other physically based model. While the locally calibrated models lead to good performance in calibration and temporal validation (even outperforming several regionally calibrated models), they lose performance when they are transferred to locations that the model has not been calibrated on. This is likely to be improved with more advanced strategies to transfer these models in space. The regionally calibrated models – while losing less performance in spatial and spatiotemporal validation than locally calibrated models – exhibit low performances in highly regulated and urban areas and agricultural regions in the USA. Comparisons of additional model outputs (AET, SSM, and SWE) against gridded reference datasets show that aggregating model outputs and the reference dataset to the basin scale can lead to different conclusions than a comparison at the native grid scale. The latter is deemed preferable, especially for variables with large spatial variability such as SWE. A multi-objective-based analysis of the model performances across all variables (Q, AET, SSM, and SWE) reveals overall well-performing locally calibrated models (i.e., HYMOD2-lumped) and regionally calibrated models (i.e., MESH-SVS-Raven and GEM-Hydro-Watroute) due to varying reasons. The machine-learning-based model was not included here as it is not set up to simulate AET, SSM, and SWE. All basin-aggregated model outputs and observations for the model variables evaluated in this study are available on an interactive website that enables users to visualize results and download the data and model outputs.

The sensitivity of simulated streamflow to individual hydrologic processes across North America - Mai, Juliane; Craig, James R.; Tolson, Bryan A.; Arsenault, Richard (Nature Communications, 2022)
Abstract Streamflow sensitivity to different hydrologic processes varies in both space and time. This sensitivity is traditionally evaluated for the parameters specific to a given hydrologic model simulating streamflow. In this study, we apply a novel analysis over more than 3000 basins across North America considering a blended hydrologic model structure, which includes not only parametric, but also structural uncertainties. This enables seamless quantification of model process sensitivities and parameter sensitivities across a continuous set of models. It also leads to high-level conclusions about the importance of water cycle components on streamflow predictions, such as quickflow being the most sensitive process for streamflow simulations across the North American continent. The results of the 3000 basins are used to derive an approximation of sensitivities based on physiographic and climatologic data without the need to perform expensive sensitivity analyses. Detailed spatio-temporal inputs and results are shared through an interactive website.

Improved historical reconstruction of daily flows and annual maxima in gauged and ungauged basins - Martel, Jean-Luc; Arsenault, Richard; Lachance-Cloutier, Simon; Castaneda-Gonzalez, Mariana; Turcotte, Richard; Poulin, Annie (Journal of Hydrology, 2023)

CMIP5 and CMIP6 Model Projection Comparison for Hydrological Impacts Over North America - Martel, J.‐L.; Brissette, F.; Troin, M.; Arsenault, R.; Chen, J.; Su, T.; Lucas‐Picher, P. (Geophysical Research Letters, 2022)
Abstract A warmer climate impacts streamflows and these changes need to be quantified to assess future risk, vulnerability, and to implement efficient adaptation measures. The climate simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), which have been the basis of most such assessments over the past decade, are being gradually superseded by the more recent Coupled Model Intercomparison Project Phase 6 (CMIP6). Our study portrays the added value of the CMIP6 ensemble over CMIP5 in a first North America wide comparison using 3,107 catchments. Results show a reduced spread of the CMIP6 ensemble compared to the CMIP5 ensemble for temperature and precipitation projections. In terms of flow indicators, the CMIP6 driven hydrological projections result in a smaller spread of future mean and high flow values, except for mountainous areas. Overall, we assess that the CMIP6 ensemble provides a narrower band of uncertainty of future climate projections, bringing more confidence for hydrological impact studies. , Plain Language Summary Greenhouse gas emissions are causing the climate to warm significantly, which in turn impacts flows in rivers worldwide. To adapt to these changes, it is essential to quantify them and assess future risk and vulnerability. Climate models are the primary tools used to achieve this. The main data set that provides scientists with state‐of‐the‐art climate model simulations is known as the Coupled Model Intercomparison Project (CMIP). The fifth phase of that project (CMIP5) has been used over the past decade in multiple hydrological studies to assess the impacts of climate change on streamflow. The more recent sixth phase (CMIP6) has started to generate projections, which brings the following question: is it necessary to update the hydrological impact studies performed using CMIP5 with the new CMIP6 models? To answer this question, a comparison between CMIP5 and CMIP6 using 3,107 catchments over North America was conducted. Results show that there is less spread in temperature and precipitation projections for CMIP6. This translates into a smaller spread of future mean, high and low flow values, except for mountainous areas. Overall, we assess that using the CMIP6 data set would provide a more concerted range of future climate projections, leading to more confident hydrological impact studies. , Key Points A comparison of hydrological impacts using Coupled Model Intercomparison Project version 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) ensembles is performed over 3,107 catchments in North America The CMIP6 ensembles provide a narrower band of uncertainty for hydrological indicators in the future It is recommended to update hydrological impact studies performed using CMIP5 with the CMIP6 ensemble

Calibration of a 3D hydrodynamic model for a hypertidal estuary with complex irregular bathymetry using adaptive parametrization of bottom roughness and eddy viscosity - Mohammadian, Abdolvahid; Morse, Brian; Robert, Jean-Loup (Estuarine, Coastal and Shelf Science, 2022)

Exposure to natural hazard events unassociated with policy change for improved disaster risk reduction - Nohrstedt, Daniel; Mazzoleni, Maurizio; Parker, Charles F.; Di Baldassarre, Giuliano (Nature Communications, 2021)
Abstract Natural hazard events provide opportunities for policy change to enhance disaster risk reduction (DRR), yet it remains unclear whether these events actually fulfill this transformative role around the world. Here, we investigate relationships between the frequency (number of events) and severity (fatalities, economic losses, and affected people) of natural hazards and DRR policy change in 85 countries over eight years. Our results show that frequency and severity factors are generally unassociated with improved DRR policy when controlling for income-levels, differences in starting policy values, and hazard event types. This is a robust result that accounts for event frequency and different hazard severity indicators, four baseline periods estimating hazard impacts, and multiple policy indicators. Although we show that natural hazards are unassociated with improved DRR policy globally, the study unveils variability in policy progress between countries experiencing similar levels of hazard frequency and severity.

Arctic precipitation and surface wind speed associated with cyclones in a changing climate - Oh, Seok-Geun; Sushama, Laxmi; Teufel, Bernardo (Climate Dynamics, 2020)

Mercury, selenium and arsenic concentrations in Canadian freshwater fish and a perspective on human consumption intake and risk - Ponton, Dominic E.; Ruelas-Inzunza, Jorge; Lavoie, Raphael A.; Lescord, Gretchen L.; Johnston, Thomas A.; Graydon, Jennifer A.; Reichert, Megan; Donadt, Caitlyn; Poesch, Mark; Gunn, John M.; Amyot, Marc (Journal of Hazardous Materials Advances, 2022)

Evaluation of a Coupled CFD and Multi-Body Motion Model for Ice-Structure Interaction Simulation - Pourshahbaz, Hanif; Ghobrial, Tadros; Shakibaeinia, Ahmad (Water, 2024)
The interaction of water flow, ice, and structures is common in fluvial ice processes, particularly around Ice Control Structures (ICSs) that are used to manage and prevent ice jam floods. To evaluate the effectiveness of ICSs, it is essential to understand the complex interaction between water flow, ice and the structure. Numerical modeling is a valuable tool that can facilitate such understanding. Until now, classical Eulerian mesh-based methods have not been evaluated for the simulation of ice interaction with ICS. In this paper we evaluate the capability, accuracy, and efficiency of a coupled Computational Fluid Dynamic (CFD) and multi-body motion numerical model, based on the mesh-based FLOW-3D V.2023 R1 software for simulation of ice-structure interactions in several benchmark cases. The model’s performance was compared with results from meshless-based models (performed by others) for the same laboratory test cases that were used as a reference for the comparison. To this end, simulation results from a range of dam break laboratory experiments were analyzed, encompassing varying numbers of floating objects with distinct characteristics, both in the presence and absence of ICS, and under different downstream water levels. The results show that the overall accuracy of the FLOW-3D model under various experimental conditions resulted in a RMSE of 0.0534 as opposed to an overall RMSE of 0.0599 for the meshless methods. Instabilities were observed in the FLOW-3D model for more complex phenomena that involve open boundaries and a larger number of blocks. Although the FLOW-3D model exhibited a similar computational time to the GPU-accelerated meshless-based models, constraints on the processors speed and the number of cores available for use by the processors could limit the computational time.
Keywords: Infolettre; Infolettre_Octobre_2024

Understanding the influence of “hot” models in climate impact studies: a hydrological perspective - Rahimpour Asenjan, Mehrad; Brissette, Francois; Martel, Jean-Luc; Arsenault, Richard (Hydrology and Earth System Sciences, 2023)
Abstract. Efficient adaptation strategies to climate change require the estimation of future impacts and the uncertainty surrounding this estimation. Over- or underestimating future uncertainty may lead to maladaptation. Hydrological impact studies typically use a top-down approach in which multiple climate models are used to assess the uncertainty related to the climate model structure and climate sensitivity. Despite ongoing debate, impact modelers have typically embraced the concept of “model democracy”, in which each climate model is considered equally fit. The newer Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations, with several models showing a climate sensitivity larger than that of Phase 5 (CMIP5) and larger than the likely range based on past climate information and understanding of planetary physics, have reignited the model democracy debate. Some have suggested that “hot” models be removed from impact studies to avoid skewing impact results toward unlikely futures. Indeed, the inclusion of these models in impact studies carries a significant risk of overestimating the impact of climate change. This large-sample study looks at the impact of removing hot models on the projections of future streamflow over 3107 North American catchments. More precisely, the variability in future projections of mean, high, and low flows is evaluated using an ensemble of 19 CMIP6 general circulation models (GCMs), 5 of which are deemed hot based on their global equilibrium climate sensitivity (ECS). The results show that the reduced ensemble of 14 climate models provides streamflow projections with reduced future variability for Canada, Alaska, the Southeast US, and along the Pacific coast. Elsewhere, the reduced ensemble has either no impact or results in increased variability in future streamflow, indicating that global outlier climate models do not necessarily provide regional outlier projections of future impacts. These results emphasize the delicate nature of climate model selection, especially based on global fitness metrics that may not be appropriate for local and regional assessments.

Time-Varying Univariate and Bivariate Frequency Analysis of Nonstationary Extreme Sea Level for New York City - Razmi, Ali; Mardani-Fard, Heydar Ali; Golian, Saeed; Zahmatkesh, Zahra (Environmental Processes, 2022)

A stochastic wavelet-based data-driven framework for forecasting uncertain multiscale hydrological and water resources processes - Quilty, John; Adamowski, Jan (Environmental Modelling & Software, 2020)

Comparing a long short-term memory (LSTM) neural network with a physically-based hydrological model for streamflow forecasting over a Canadian catchment - Sabzipour, Behmard; Arsenault, Richard; Troin, Magali; Martel, Jean-Luc; Brissette, François; Brunet, Frédéric; Mai, Juliane (Journal of Hydrology, 2023)
Keywords: Brunet_Alain

Coupling large-scale climate indices with a stochastic weather generator to improve long-term streamflow forecasts in a Canadian watershed - Sohrabi, Samaneh; Brissette, François P.; Arsenault, Richard (Journal of Hydrology, 2021)

Climate Gentrification: Risk, Rent, and Restructuring in Greater Miami - Taylor, Zac J.; Aalbers, Manuel B. (Annals of the American Association of Geographers, 2022)

Catchment Scale Evaluation of Multiple Global Hydrological Models from ISIMIP2a over North America - Troin, Magali; Arsenault, Richard; Fournier, Elyse; Brissette, François (Water, 2021)
A satisfactory performance of hydrological models under historical climate conditions is considered a prerequisite step in any hydrological climate change impact study. Despite the significant interest in global hydrological modeling, few systematic evaluations of global hydrological models (gHMs) at the catchment scale have been carried out. This study investigates the performance of 4 gHMs driven by 4 global observation-based meteorological inputs at simulating weekly discharges over 198 large-sized North American catchments for the 1971–2010 period. The 16 discharge simulations serve as the basis for evaluating gHM accuracy at the catchment scale within the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). The simulated discharges by the four gHMs are compared against observed and simulated weekly discharge values by two regional hydrological models (rHMs) driven by a global meteorological dataset for the same period. We discuss the implications of both modeling approaches as well as the influence of catchment characteristics and global meteorological forcing in terms of model performance through statistical criteria and visual hydrograph comparison for catchment-scale hydrological studies. Overall, the gHM discharge statistics exhibit poor agreement with observations at the catchment scale and manifest considerable bias and errors in seasonal flow simulations. We confirm that the gHM approach, as experimentally implemented through the ISIMIP2a, must be used with caution for regional studies. We find the rHM approach to be more trustworthy and recommend using it for hydrological studies, especially if findings are intended to support operational decision-making.

Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years - Troin, Magali; Arsenault, Richard; Wood, Andrew W.; Brissette, François; Martel, Jean‐Luc (Water Resources Research, 2021)
Abstract Ensemble forecasting applied to the field of hydrology is currently an established area of research embracing a broad spectrum of operational situations. This work catalogs the various pathways of ensemble streamflow forecasting based on an exhaustive review of more than 700 studies over the last 40 years. We focus on the advanced state of the art in the model‐based (dynamical) ensemble forecasting approaches. Ensemble streamflow prediction systems are categorized into three leading classes: statistics‐based streamflow prediction systems, climatology‐based ensemble streamflow prediction systems and numerical weather prediction‐based hydrological ensemble prediction systems. For each ensemble approach, technical information, as well as details about its strengths and weaknesses, are provided based on a critical review of the studies listed. Through this literature review, the performance and uncertainty associated with the ensemble forecasting systems are underlined from both operational and scientific viewpoints. Finally, the remaining key challenges and prospective future research directions are presented, notably through hybrid dynamical ‐ statistical learning approaches, which obviously present new challenges to be overcome in order to allow the successful employment of ensemble streamflow forecasting systems in the next decades. Targeting students, researchers and practitioners, this review provides a detailed perspective on the major features of an increasingly important area of hydrological forecasting. , Key Points This work summarizes the 40 years of research in the generation of streamflow forecasts based on an exhaustive review of studies Ensemble prediction systems are categorized into three classes: statistics‐based, climatology‐based and numerical weather prediction‐based hydrological ensemble prediction systems For each ensemble forecasting system, thorough technical information is provided

A database of Holocene temperature records for north‐eastern North America and the north‐western Atlantic - Van Bellen, Simon; De Vernal, Anne; To, Anna; Ouellet‐Bernier, Marie‐Michèle; Roy, Natasha; ClimHuNor Members (Geoscience Data Journal, 2020)
Abstract Centennial‐to‐millennial temperature records of the past provide a context for the interpretation of current and future changes in climate. Quaternary climates have been relatively well studied in north‐east North America and the adjacent Atlantic Ocean over the last decades, and new research methods have been developed to improve reconstructions. We present newly inferred reconstructions of sea surface temperature for the north‐western Atlantic region, together with a compilation of published temperature records. The database thus comprises a total of 86 records from both marine and terrestrial sites, including lakes, peatlands, ice and tree rings, each covering at least part of the Holocene. For each record, we present details on seasons covered, chronologies and information on radiocarbon dates and analytical time steps. The 86 records contain a total of 154 reconstructions of temperature and temperature‐related variables. Main proxies include pollen and dinocysts, while summer was the season for which the highest number of reconstructions were available. Many records covered most of the Holocene, but many dinocyst records did not extend to the surface, due to sediment mixing, and dendroclimate records were limited to the last millennium. The database allows for the exploration of linkages between sea ice and climate and may be used in conjunction with other palaeoclimate and palaeoenvironmental records, such as wildfire records and peatland dynamics. This inventory may also aid the identification of gaps in the geographic distribution of past temperature records thus guiding future research efforts.
Keywords: Gachon_Philippe

Hydrological ensemble forecasting using a multi-model framework - Dion, Patrice; Martel, Jean-Luc; Arsenault, Richard (Journal of Hydrology, 2021)

Climate justice and home-buyout programs: renters as a forgotten population in managed retreat actions - Dundon, Leah A.; Camp, Janey S. (Journal of Environmental Studies and Sciences, 2021)

Prediction of frost resistance and multiobjective optimisation of low-carbon concrete on the basis of machine learning - Dai, Jinpeng; Zhang, Zhijie; Dong, Xuwei; He, Jie; Yang, Xiaoyuan; Wang, Qicai (Materials Today Communications, 2024)
Keywords: Infolettre; Infolettre_Ete_2024

Designing a green-resilient closed-loop supply chain to preserve business continuity under interrelated disruptions (a case study of the automotive battery industry) - Dehghani Sadrabadi, Mohammad Hossein; Makui, Ahmad; Ghousi, Rouzbeh; Jabbarzadeh, Armin (Computers & Chemical Engineering, 2024)

Integrating Multiple Research Methods to Unravel the Complexity of Human‐Water Systems - Di Baldassarre, Giuliano; Cloke, Hannah; Lindersson, Sara; Mazzoleni, Maurizio; Mondino, Elena; Mård, Johanna; Odongo, Vincent; Raffetti, Elena; Ridolfi, Elena; Rusca, Maria; Savelli, Elisa; Tootoonchi, Faranak (AGU Advances, 2021)
Abstract Predicting floods and droughts is essential to inform the development of policy in water management, climate change adaptation and disaster risk reduction. Yet, hydrological predictions are highly uncertain, while the frequency, severity and spatial distribution of extreme events are further complicated by the increasing impact of human activities on the water cycle. In this commentary, we argue that four main aspects characterizing the complexity of human‐water systems should be explicitly addressed: feedbacks, scales, tradeoffs and inequalities. We propose the integration of multiple research methods as a way to cope with complexity and develop policy‐relevant science. , Plain Language Summary Several governments today claim to be following the science in addressing crises caused by the occurrence of extreme events, such as floods and droughts, or the emergence of global threats, such as climate change and COVID‐19. In this commentary, we show that there are no universal answers to apparently simple questions such as: Do levees reduce flood risk? Do reservoirs alleviate droughts? We argue that the best science we have consists of a plurality of legitimate interpretations and a range of foresights, which can be enriched by integrating multiple disciplines and research methods. , Key Points Accounting for both power relations and cognitive heuristics is key to unravel the interplay of floods, droughts and human societies Flood and drought predictions are complicated by the increasing impact of human activities on the water cycle We propose the integration of multiple research methods as a way to cope with uncertainty and develop policy‐relevant science

Quantifying the evolution of ensemble water temperature forecasts as a function of weather forecast lead-time: case study on the Nechako River watershed - Charles, Paul; Arsenault, Richard; Martel, Jean-Luc; Gatien, Philippe; St-Hilaire, André (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2023)

Future shift in winter streamflow modulated by the internal variability of climate in southern Ontario - Champagne, Olivier; Arain, M. Altaf; Leduc, Martin; Coulibaly, Paulin; McKenzie, Shawn (Hydrology and Earth System Sciences, 2020)
Fluvial systems in southern Ontario are regularly affected by widespread early-spring flood events primarily caused by rain-on-snow events. Recent studies have shown an increase in winter floods in this region due to increasing winter temperature and precipitation. Streamflow simulations are associated with uncertainties mainly due to the different scenarios of greenhouse gas emissions, global climate models (GCMs) or the choice of the hydrological model. The internal variability of climate, defined as the chaotic variability of atmospheric circulation due to natural internal processes within the climate system, is also a source of uncertainties to consider. Uncertainties of internal variability can be assessed using hydrological models fed by downscaled data of a global climate model large ensemble (GCM-LE), but GCM outputs have too coarse of a scale to be used in hydrological modeling. The Canadian Regional Climate Model Large Ensemble (CRCM5-LE), a 50-member ensemble downscaled from the Canadian Earth System Model version 2 Large Ensemble (CanESM2-LE), was developed to simulate local climate variability over northeastern North America under different future climate scenarios. In this study, CRCM5-LE temperature and precipitation projections under an RCP8.5 scenario were used as input in the Precipitation Runoff Modeling System (PRMS) to simulate streamflow at a near-future horizon (2026–2055) for four watersheds in southern Ontario. To investigate the role of the internal variability of climate in the modulation of streamflow, the 50 members were first grouped in classes of similar projected change in January–February streamflow and temperature and precipitation between 1961–1990 and 2026–2055. Then, the regional change in geopotential height (Z500) from CanESM2-LE was calculated for each class. Model simulations showed an average January–February increase in streamflow of 18 % (±8.7) in Big Creek, 30.5 % (±10.8) in Grand River, 29.8 % (±10.4) in Thames River and 31.2 % (±13.3) in Credit River. A total of 14 % of all ensemble members projected positive Z500 anomalies in North America's eastern coast enhancing rain, snowmelt and streamflow volume in January–February. For these members the increase of streamflow is expected to be as high as 31.6 % (±8.1) in Big Creek, 48.3 % (±11.1) in Grand River, 47 % (±9.6) in Thames River and 53.7 % (±15) in Credit River. Conversely, 14 % of the ensemble projected negative Z500 anomalies in North America's eastern coast and were associated with a much lower increase in streamflow: 8.3 % (±7.8) in Big Creek, 18.8 % (±5.8) in Grand River, 17.8 % (±6.4) in Thames River and 18.6 % (±6.5) in Credit River. These results provide important information to researchers, managers, policymakers and society about the expected ranges of increase in winter streamflow in a highly populated region of Canada, and they will help to explain how the internal variability of climate is expected to modulate the future streamflow in this region.
Publisher: Copernicus GmbH

Mechanisms of Co enrichment in the Zhubu Ni–Co–PGE deposit in the Emeishan LIP, SW China: Constraints from mineral geochemistry and Fe–S isotopes of sulfides - Bao, Yawen; Zhang, Mingjie; Zhang, Hongfu; Feng, Yantong; Li, Xiaofei; He, Jie (Ore Geology Reviews, 2024)
Keywords: Infolettre; Infolettre_Octobre_2024

Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model - Barzegar, Rahim; Aalami, Mohammad Taghi; Adamowski, Jan (Stochastic Environmental Research and Risk Assessment, 2020)

Exploring the hydrogeochemical evolution of cold and thermal waters in the Sarein-Nir area, Iran using stable isotopes (δ18O and δD), geothermometry and multivariate statistical approaches - Barzegar, Rahim; Asghari Moghaddam, Asghar; Tziritis, Evangelos; Adamowski, Jan; Bou Nassar, Jessica; Noori, Mohammad; Aalami, Mohammad Taghi; Kazemian, Naeimeh (Geothermics, 2020)

Science of Lakes - Multidisciplinary Approach - Assani, A. Ali; Summers, J. Kevin (IntechOpen, 2024)
Keywords: Site_internet_RIISQ

Assessment of 30 gridded precipitation datasets over different climates on a country scale - Araghi, Alireza; Adamowski, Jan F. (Earth Science Informatics, 2024)

The PAVICS-Hydro platform: A virtual laboratory for hydroclimatic modelling and forecasting over North America - Arsenault, Richard; Huard, David; Martel, Jean-Luc; Troin, Magali; Mai, Juliane; Brissette, François; Jauvin, Christian; Vu, Long; Craig, James R.; Smith, Trevor J.; Logan, Travis; Tolson, Bryan A.; et al. (Environmental Modelling & Software, 2023)

Comparison of wavelet-based hybrid models for the estimation of daily reference evapotranspiration in different climates - Araghi, Alireza; Adamowski, Jan; Martinez, Christopher J. (Journal of Water and Climate Change, 2020)
Abstract Reference evapotranspiration (ETo) is one of the most important factors in the hydrologic cycle and water balance studies. In this study, the performance of three simple and three wavelet hybrid models were compared to estimate ETo in three different climates in Iran, based on different combinations of input variables. It was found that the wavelet-artificial neural network was the best model, and multiple linear regression (MLR) was the worst model in most cases, although the performance of the models was related to the climate and the input variables used for modeling. Overall, it was found that all models had good accuracy in terms of estimating daily ETo. Also, it was found in this study that large numbers of decomposition levels via the wavelet transform had noticeable negative effects on the performance of the wavelet-based models, especially for the wavelet-adaptive network-based fuzzy inference system and wavelet-MLR, but in contrast, the type of db wavelet function did not have a detectable effect on the performance of the wavelet-based models.

Field observations of stratification in stormwater wet ponds - Ahmed, Sherif S.; Loewen, Mark R.; Zhang, Wenming; Ghobrial, Tadros R.; Zhu, David Z.; Mahmood, Khizar; Van Duin, Bert (Journal of Environmental Management, 2022)

Photooxidation of arsenic in pristine and mine-impacted Canadian subarctic freshwater systems - Amyot, Marc; Bélanger, Dominic; Simon, Dana F.; Chételat, John; Palmer, Mike; Ariya, Parisa (Journal of Hazardous Materials Advances, 2021)

A century of observations reveals increasing likelihood of continental-scale compound dry-hot extremes - Alizadeh, Mohammad Reza; Adamowski, Jan; Nikoo, Mohammad Reza; AghaKouchak, Amir; Dennison, Philip; Sadegh, Mojtaba (Science Advances, 2020)
Compound dry-hot events enlarge homogenously due to teleconnected land-atmosphere feedbacks. , Using over a century of ground-based observations over the contiguous United States, we show that the frequency of compound dry and hot extremes has increased substantially in the past decades, with an alarming increase in very rare dry-hot extremes. Our results indicate that the area affected by concurrent extremes has also increased significantly. Further, we explore homogeneity (i.e., connectedness) of dry-hot extremes across space. We show that dry-hot extremes have homogeneously enlarged over the past 122 years, pointing to spatial propagation of extreme dryness and heat and increased probability of continental-scale compound extremes. Last, we show an interesting shift between the main driver of dry-hot extremes over time. While meteorological drought was the main driver of dry-hot events in the 1930s, the observed warming trend has become the dominant driver in recent decades. Our results provide a deeper understanding of spatiotemporal variation of compound dry-hot extremes.

A Mutual Catastrophe Insurance Framework for Horizontal Collaboration in Prepositioning Strategic Reserves - Zbib, Hani; Balcik, Burcu; Rancourt, Marie-Ève; Laporte, Gilbert (Operations Research, 2024)
Improving Disaster Preparedness Through Mutual Catastrophe Insurance In “A Mutual Catastrophe Insurance Framework for Horizontal Collaboration in Prepositioning Strategic Reserves,” H. Zbib, B. Balcik, M.-È. Rancourt, and G. Laporte present an innovative approach to collaborative disaster preparedness. The novel framework considers a risk-averse mutual insurer offering multiyear insurance contracts with coverage deductibles and limits to a portfolio of risk-averse policyholders. It is designed to foster horizontal collaboration among policyholders for joint disaster preparedness by effectively integrating operational and financial functions. The problem is modeled as a large-scale nonlinear multistage stochastic program and solved by using an effective Benders decomposition algorithm. The framework is validated with real data from 18 Caribbean countries focusing on hurricane preparedness. Given the predicted impacts of climate change, the proposed multiyear mutual catastrophe insurance framework promises to reshape global disaster preparedness and make a profound societal impact by providing a transparent disaster financing plan to protect vulnerable regions. The study’s findings stress the importance of long-term cooperation, prenegotiation of indemnification policies, and strategic setting of deductibles and limits by taking into account the correlation between policyholders. , We develop a mutual catastrophe insurance framework for the prepositioning of strategic reserves to foster horizontal collaboration in preparedness against low-probability high-impact natural disasters. The framework consists of a risk-averse insurer pooling the risks of a portfolio of risk-averse policyholders. It encompasses the operational functions of planning the prepositioning network in preparedness for incoming insurance claims, in the form of units of strategic reserves, setting coverage deductibles and limits of policyholders, and providing insurance coverage to the claims in the emergency response phase. It also encompasses the financial functions of ensuring the insurer’s solvency by efficiently managing its capital and allocating yearly premiums among policyholders. We model the framework as a very large-scale nonlinear multistage stochastic program, and solve it through a Benders decomposition algorithm. We study the case of Caribbean countries establishing a horizontal collaboration for hurricane preparedness. Our results show that the collaboration is more effective when established over a longer planning horizon, and is more beneficial when outsourcing becomes expensive. Moreover, the correlation of policyholders affected simultaneously under the extreme realizations and the position of their claims in their global claims distribution directly affects which policyholders get deductibles and limits. This underlines the importance of prenegotiating policyholders’ indemnification policies at the onset of collaboration. Funding: G. Laporte and M.-È. Rancourt were funded by the Canadian Natural Sciences and Engineering Research Council (NSERC) [Grants 2015-06189 and 2022-04846]. Funding was also provided by the Institute for Data Valorisation (IVADO) and the Canada Research Chair in Humanitarian Supply Chain Analytics. B. Balcik was partially supported by a grant from the Scientific and Technological Research Council of Turkey (TUBITAK) 2219 program. This support is gratefully acknowledged. Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2021.0141 .
Keywords: Infolettre; Infolettre_Avril_2024

A global algorithm for identifying changing streamflow regimes: application to Canadian natural streams (1966–2010) - Zaerpour, Masoud; Hatami, Shadi; Sadri, Javad; Nazemi, Ali (Hydrology and Earth System Sciences, 2021)
Abstract. Climate change affects natural streamflow regimes globally. To assess alterations in streamflow regimes, typically temporal variations in one or a few streamflow characteristics are taken into account. This approach, however, cannot see simultaneous changes in multiple streamflow characteristics, does not utilize all the available information contained in a streamflow hydrograph, and cannot describe how and to what extent streamflow regimes evolve from one to another. To address these gaps, we conceptualize streamflow regimes as intersecting spectrums that are formed by multiple streamflow characteristics. Accordingly, the changes in a streamflow regime should be diagnosed through gradual, yet continuous changes in an ensemble of streamflow characteristics. To incorporate these key considerations, we propose a generic algorithm to first classify streams into a finite set of intersecting fuzzy clusters. Accordingly, by analyzing how the degrees of membership to each cluster change in a given stream, we quantify shifts from one regime to another. We apply this approach to the data, obtained from 105 natural Canadian streams, during the period of 1966 to 2010. We show that natural streamflow in Canada can be categorized into six regime types, with clear hydrological and geographical distinctions. Analyses of trends in membership values show that alterations in natural streamflow regimes vary among different regions. Having said that, we show that in more than 80 % of considered streams, there is a dominant regime shift that can be attributed to simultaneous changes in streamflow characteristics, some of which have remained previously unknown. Our study not only introduces a new globally relevant algorithm for identifying changing streamflow regimes but also provides a fresh look at streamflow alterations in Canada, highlighting complex and multifaceted impacts of climate change on streamflow regimes in cold regions.
Keywords: Infolettre; Infolettre_Janvier_2022; Site_internet_RIISQ

A dynamics model of the emergency medical supply chain in epidemic considering deprivation cost - Shi, Wenqiang; He, Jie; Wang, Mingyue; Yang, Fang (Socio-Economic Planning Sciences, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Failure mechanism, existing constitutive models and numerical modeling of landslides in sensitive clay: a review - Urmi, Zinan Ara; Saeidi, Ali; Chavali, Rama Vara Prasad; Yerro, Alba (Geoenvironmental Disasters, 2023)
Abstract Landslides involving sensitive clays are recurrent events in the world's northern regions and are especially notorious in eastern Canada. The two critical factors that separate sensitive clay landslides from traditional slope stability analysis are the highly brittle behavior in undrained conditions (strain-softening) characteristic of progressive or retrogressive failures and the large deformations associated with them. Conventional limit equilibrium analysis has numerous shortcomings in incorporating these characteristics when assessing landslides in sensitive clays. This paper presents an extensive literature review of the failure mechanics characteristics of landslides in sensitive clays and the existing constitutive models and numerical tools to analyze such slopes' stability and post-failure behavior. The advantages and shortcomings of the different techniques to incorporate strain-softening and large deformation in the numerical modeling of sensitive clay landslides are assessed. The literature review depicts that elastoviscoplastic soil models with non-linear strain-softening laws and rate effects represent the material behavior of sensitive clays. Though several numerical models have been proposed to analyze post-failure runouts, the amount of work performed in line with sensitive clay landslides is very scarce. That creates an urgent need to apply and further develop advanced numerical tools for better understanding and predicting these catastrophic events.
Keywords: Infolettre; Infolettre_Juin_2023

Hybrid forecasting: blending climate predictions with AI models - Slater, Louise J.; Arnal, Louise; Boucher, Marie-Amélie; Chang, Annie Y.-Y.; Moulds, Simon; Murphy, Conor; Nearing, Grey; Shalev, Guy; Shen, Chaopeng; Speight, Linda; Villarini, Gabriele; Wilby, Robert L.; et al. (Hydrology and Earth System Sciences, 2023)
Abstract. Hybrid hydroclimatic forecasting systems employ data-driven (statistical or machine learning) methods to harness and integrate a broad variety of predictions from dynamical, physics-based models – such as numerical weather prediction, climate, land, hydrology, and Earth system models – into a final prediction product. They are recognized as a promising way of enhancing the prediction skill of meteorological and hydroclimatic variables and events, including rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. Hybrid forecasting methods are now receiving growing attention due to advances in weather and climate prediction systems at subseasonal to decadal scales, a better appreciation of the strengths of AI, and expanding access to computational resources and methods. Such systems are attractive because they may avoid the need to run a computationally expensive offline land model, can minimize the effect of biases that exist within dynamical outputs, benefit from the strengths of machine learning, and can learn from large datasets, while combining different sources of predictability with varying time horizons. Here we review recent developments in hybrid hydroclimatic forecasting and outline key challenges and opportunities for further research. These include obtaining physically explainable results, assimilating human influences from novel data sources, integrating new ensemble techniques to improve predictive skill, creating seamless prediction schemes that merge short to long lead times, incorporating initial land surface and ocean/ice conditions, acknowledging spatial variability in landscape and atmospheric forcing, and increasing the operational uptake of hybrid prediction schemes.
Keywords: Infolettre; Infolettre_Juin_2023

A Hydrograph-Based Approach to Improve Satellite-Derived Snow Water Equivalent at the Watershed Scale - Whittaker, Charles; Leconte, Robert (Water, 2022)
For the past few decades, remote sensing has been a valuable tool for deriving global information on snow water equivalent (SWE), where products derived from space-borne passive microwave radiometers are favoured as they respond to snow depth, an important component of SWE. GlobSnow, a novel SWE product, has increased the accuracy of global-scale SWE estimates by combining remotely sensed radiometric data with other physiographic characteristics, such as snow depth, as quantified by climatic stations. However, research has demonstrated that passive microwaves algorithms tend to underestimate SWE for deep snowpack. Approaches were proposed to correct for such underestimation; however, they are computer intensive and complex to implement at the watershed scale. In this study, SWEmax information from the near real time 5-km GlobSnow product, provided by Copernicus and the European Space Agency (ESA) and GlobSnow product at 25 km resolution were corrected using a simple bias correction approach for watershed scale applications. This method, referred to as the Watershed Scale Correction (WSC) approach, estimates the bias based on the direct runoff that occurs during the spring melt season. Direct runoff is estimated on the one hand from SWEmax information as main input. Infiltration is also considered in computing direct runoff. An independent estimation of direct runoff from gauged stations is also performed. Discrepancy between these estimates allows for estimating the bias correction factor. This approach is advantageous as it exploits data that commonly exists i.e., flow at gauged stations and remotely sensed/reanalysis data such as snow cover and precipitation. The WSC approach was applied to watersheds located in Eastern Canada. It was found that the average bias moved from 33.5% with existing GlobSnow product to 18% with the corrected product, using the recommended recursive filter coefficient β of 0.925 for baseflow separation. Results show the usefulness of integrating direct runoff for bias correction of existing GlobSnow product at the watershed scale. In addition, potential benefits are offered using the recursive filter approach for baseflow separation of watersheds with limited in situ SWE measurements, to further reduce overall uncertainties and bias. The WSC approach should be appealing for poorly monitored watersheds where SWE measurements are critical for hydropower production and where snowmelt can pose serious flood-related damages.
Keywords: Infolettre; Infolettre_Fevrier_2023

Meteorological Analysis and Damage Survey Study of the Impact of Hurricane Elsa in Barbados - Sandiford, Sanola; Romanic, Djordje; Gyakum, John (Natural Hazards Review, 2024)
Keywords: Infolettre; Infolettre_Ete_2024

Experiencing Trauma During or Before Pregnancy: Qualitative Secondary Analysis After Two Disasters - Severson, Emily; Olson, Joanne K.; Hyde, Ashley; Brémault-Phillips, Suzette; Spiers, Jude; King, Suzanne; Bick, Johanna; Lipschutz, Rebecca; Verstraeten, Barbara S.E.; Olson, David M. (Maternal and Child Health Journal, 2023)
Keywords: Infolettre; Infolettre_Avril_2023

Extreme Sea Level Estimation Combining Systematic Observed Skew Surges and Historical Record Sea Levels - Saint Criq, Laurie; Gaume, Eric; Hamdi, Yasser; Ouarda, Taha B. M. J. (Water Resources Research, 2022)
Abstract The estimation of sea levels corresponding to high return periods is crucial for coastal planning and for the design of coastal defenses. This paper deals with the use of historical observations, that is, events that occurred before the beginning of the systematic tide gauge recordings, to improve the estimation of design sea levels. Most of the recent publications dealing with statistical analyses applied to sea levels suggest that astronomical high tide levels and skew surges should be analyzed and modeled separately. Historical samples generally consist of observed record sea levels. Some extreme historical skew surges can easily remain unnoticed if they occur at low or moderate astronomical high tides and do not generate extreme sea levels. The exhaustiveness of historical skew surge series, which is an essential criterion for an unbiased statistical inference, can therefore not be guaranteed. This study proposes a model combining, in a single Bayesian inference procedure, information of two different natures for the calibration of the statistical distribution of skew surges: measured skew surges for the systematic period and extreme sea levels for the historical period. A data‐based comparison of the proposed model with previously published approaches is presented based on a large number of Monte Carlo simulations. The proposed model is applied to four locations on the French Atlantic and Channel coasts. Results indicate that the proposed model is more reliable and accurate than previously proposed methods that aim at the integration of historical records in coastal sea level or surge statistical analyses. , Plain Language Summary Coastal facilities must be designed as to be protected from extreme sea levels. Sea levels at high tide are the combination of astronomical high tides, which can be predicted, and skew surges. The estimation of the statistical distribution of skew surges is usually based on the skew surges measured by tide gauges and can be improved with the use of historical information, observations that occurred before the beginning of the tide gauge recordings. Extreme skew surges combined with low or moderate astronomical high tides would not necessarily generate extreme sea levels, and consequently some extreme historical skew surges could be missed. The exhaustiveness of historical information is an essential criterion for an unbiased estimation, but it cannot be guaranteed in the case of historical skew surges. The present study proposes to combine skew surges for the recent period and extreme sea levels for the historical period. The proposed model is compared to previously published approaches and appears to be more reliable and accurate. The proposed model is applied to four case studies on the French Atlantic and Channel coasts. , Key Points The exhaustiveness of historical sea record information is demonstrated based on French Atlantic coast data A comparative analysis of approaches to integrate historical information is carried out The efficiency of a new method for the combination of systematic skew surges and historical records is verified
Keywords: Infolettre; Infolettre_Juillet_2022; Site_internet_RIISQ

Hydrological connectivity controls dissolved organic carbon exports in a peatland-dominated boreal catchment stream - Prijac, Antonin; Gandois, Laure; Taillardat, Pierre; Bourgault, Marc-André; Riahi, Khawla; Ponçot, Alex; Tremblay, Alain; Garneau, Michelle (Hydrology and Earth System Sciences, 2023)
The magnitudes of dissolved organic carbon (DOC) exports from boreal peatlands to streams through lateral subsurface flow vary during the ice-free season. Peatland water table depth and the alternation of low and high flow in peat-draining streams are thought to drive this DOC export variability. However, calculation of the specific DOC exports from a peatland can be challenging considering the multiple potential DOC sources within the catchment. A calculation approach based on the hydrological connectivity between the peat and the stream could help to solve this issue, which is the approach used in the present research. This study took place from June 2018 to October 2019 in a boreal catchment in northeastern Canada, with 76.7 % of the catchment being covered by ombrotrophic peatland. The objectives were to (1) establish relationships between DOC exports from a headwater stream and the peatland hydrology; (2) quantify, at the catchment scale, the amount of DOC laterally exported to the draining stream; and (3) define the patterns of DOC mobilization during high-river-flow events. At the peatland headwater stream outlet, the DOC concentrations were monitored at a high frequency (hourly) using a fluorescent dissolved organic matter (fDOM) sensor, a proxy for DOC concentration. Hydrological variables, such as stream outlet discharge and peatland water table depth (WTD), were continuously monitored at hourly intervals for 2 years. Our results highlight the direct and delayed control of subsurface flow from peat to the stream and associated DOC exports. Rain events raised the peatland WTD, which increased hydrological connectivity between the peatland and the stream. This led to increased stream discharge (Q) and a delayed DOC concentration increase, typical of lateral subsurface flow. The magnitude of the WTD increase played a crucial role in influencing the quantity of DOC exported. Based on the observations that the peatland is the most important contributor to DOC exports at the catchment scale and that other DOC sources were negligible during high-flow periods, we propose a new approach to estimate the specific DOC exports attributable to the peatland by distinguishing between the surfaces used for calculation during high-flow and low-flow periods. In 2018–2019, 92.6 % of DOC was exported during flood events despite the fact that these flood events accounted for 59.1 % of the period. In 2019–2020, 93.8 % of DOC was exported during flood events, which represented 44.1 % of the period. Our analysis of individual flood events revealed three types of events and DOC mobilization patterns. The first type is characterized by high rainfall, leading to an important WTD increase that favours the connection between the peatland and the stream and leading to high DOC exports. The second is characterized by a large WTD increase succeeding a previous event that had depleted DOC available to be transferred to the stream, leading to low DOC exports. The third type corresponds to low rainfall events with an insufficient WTD increase to reconnect the peatland and the stream, leading to low DOC exports. Our results suggest that DOC exports are sensitive to hydroclimatic conditions; moreover, flood events, changes in rainfall regime, ice-free season duration, and porewater temperature may affect the exported DOC and, consequently, partially offset the net carbon sequestration potential of peatlands.
Keywords: Infolettre; Infolettre_Mars_2024

Climate scenarios of extreme precipitation using a combination of parametric and non-parametric bias correction methods in the province of Québec - Roy, Philippe; Rondeau-Genesse, Gabriel; Jalbert, Jonathan; Fournier, Élyse (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2023)
Keywords: Infolettre; Infolettre_Ete_2023

Multi-proxy paleohydrological and paleoecological reconstruction of a subaquatic cave in western Cuba - Peros, Matthew C.; Collins, Shawn; Martínez-López, Joao Gabriel; Viñola López, Lázaro W.; Sosa, Miguel Angel Pereira; Brisson, Laurence Forget; Hardy, François; Lamothe, Michel; Van Hengstum, Peter J.; Phillips, Bil; Broad, Kenneth; Heinerth, Jill; et al. (Palaeogeography, Palaeoclimatology, Palaeoecology, 2023)
Keywords: Infolettre; Infolettre_Septembre_2023

Planning for the Lake Izabal Basin Research Endeavor (LIBRE) continental scientific drilling project in eastern Guatemala - Obrist-Farner, Jonathan; Eckert, Andreas; Douglas, Peter M. J.; Perez, Liseth; Correa-Metrio, Alex; Konecky, Bronwen L.; Bauersachs, Thorsten; Zimmerman, Susan; Scheidt, Stephanie; Brenner, Mark; Kutterolf, Steffen; Maurer, Jeremy; et al. (Scientific Drilling, 2023)
As Earth's atmospheric temperatures and human populations increase, more people are becoming vulnerable to natural and human-induced disasters. This is particularly true in Central America, where the growing human population is experiencing climate extremes (droughts and floods), and the region is susceptible to geological hazards, such as earthquakes and volcanic eruptions, and environmental deterioration in many forms (soil erosion, lake eutrophication, heavy metal contamination, etc.). Instrumental and historical data from the region are insufficient to understand and document past hazards, a necessary first step for mitigating future risks. Long, continuous, well-resolved geological records can, however, provide a window into past climate and environmental changes that can be used to better predict future conditions in the region. The Lake Izabal Basin (LIB), in eastern Guatemala, contains the longest known continental records of tectonics, climate, and environmental change in the northern Neotropics. The basin is a pull-apart depression that developed along the North American and Caribbean plate boundary ∼ 12 Myr ago and contains > 4 km of sediment. The sedimentological archive in the LIB records the interplay among several Earth System processes. Consequently, exploration of sediments in the basin can provide key information concerning: (1) tectonic deformation and earthquake history along the plate boundary; (2) the timing and causes of volcanism from the Central American Volcanic Arc; and (3) hydroclimatic, ecologic, and geomicrobiological responses to different climate and environmental states. To evaluate the LIB as a potential site for scientific drilling, 65 scientists from 13 countries and 33 institutions met in Antigua, Guatemala, in August 2022 under the auspices of the International Continental Scientific Drilling Program (ICDP) and the US National Science Foundation (NSF). Several working groups developed scientific questions and overarching hypotheses that could be addressed by drilling the LIB and identified optimal coring sites and instrumentation needed to achieve the project goals. The group also discussed logistical challenges and outreach opportunities. The project is not only an outstanding opportunity to improve our scientific understanding of seismotectonic, volcanic, paleoclimatic, paleoecologic, and paleobiologic processes that operate in the tropics of Central America, but it is also an opportunity to improve understanding of multiple geological hazards and communicate that knowledge to help increase the resilience of at-risk Central American communities.
Keywords: Infolettre; Infolettre_Avril_2024

A Kriging Method for the Estimation of ALS Point-Cloud Accuracy without Ground Truth - Pashaei, Zahra; Guilbert, Éric; Badard, Thierry (Remote Sensing, 2023)
Airborne LiDAR scanning is a promising approach to providing high-resolution products that are appropriate for different applications, such as flood management. However, the vertical accuracy of airborne LiDAR point clouds is not constant and varies in space. Having a better knowledge of their accuracy will assist decision makers in more accurately estimating the damage caused by flood. Data producers often report the total estimation of errors by means of comparison with a ground truth. However, the reliability of such an approach depends on various factors including the sample size, accessibility to ground truth, distribution, and a large enough diversity of ground truth, which comes at a cost and is somewhat unfeasible in the larger scale. Therefore, the main objective of this article is to propose a method that could provide a local estimation of error without any third-party datasets. In this regard, we take advantage of geostatistical ordinary kriging as an alternative accuracy estimator. The challenge of considering constant variation across the space leads us to propose a non-stationary ordinary kriging model that results in the local estimation of elevation accuracy. The proposed method is compared with global ordinary kriging and a ground truth, and the results indicate that our method provides more reliable error values. These errors are lower in urban and semi-urban areas, especially in farmland and residential areas, but larger in forests, due to the lower density of points and the larger terrain variations.
Keywords: Infolettre

Convolutional neural network and long short-term memory models for ice-jam predictions - Madaeni, Fatemehalsadat; Chokmani, Karem; Lhissou, Rachid; Homayouni, Saeid; Gauthier, Yves; Tolszczuk-Leclerc, Simon (The Cryosphere, 2022)
In cold regions, ice jams frequently result in severe flooding due to a rapid rise in water levels upstream of the jam. Sudden floods resulting from ice jams threaten human safety and cause damage to properties and infrastructure. Hence, ice-jam prediction tools can give an early warning to increase response time and minimize the possible damages. However, ice-jam prediction has always been a challenge as there is no analytical method available for this purpose. Nonetheless, ice jams form when some hydro-meteorological conditions happen, a few hours to a few days before the event. Ice-jam prediction can be addressed as a binary multivariate time-series classification. Deep learning techniques have been widely used for time-series classification in many fields such as finance, engineering, weather forecasting, and medicine. In this research, we successfully applied convolutional neural networks (CNN), long short-term memory (LSTM), and combined convolutional–long short-term memory (CNN-LSTM) networks to predict the formation of ice jams in 150 rivers in the province of Quebec (Canada). We also employed machine learning methods including support vector machine (SVM), k-nearest neighbors classifier (KNN), decision tree, and multilayer perceptron (MLP) for this purpose. The hydro-meteorological variables (e.g., temperature, precipitation, and snow depth) along with the corresponding jam or no-jam events are used as model inputs. Ten percent of the data were excluded from the model and set aside for testing, and 100 reshuffling and splitting iterations were applied to 80 % of the remaining data for training and 20 % for validation. The developed deep learning models achieved improvements in performance in comparison to the developed machine learning models. The results show that the CNN-LSTM model yields the best results in the validation and testing with F1 scores of 0.82 and 0.92, respectively. This demonstrates that CNN and LSTM models are complementary, and a combination of both further improves classification.
Publisher: Copernicus GmbH
Keywords: Infolettre; Infolettre_Juillet_2022; Site_internet_RIISQ

Regional estimation of river water temperature at ungauged locations - Ouarda, Taha B.M.J.; Charron, Christian; St-Hilaire, André (Journal of Hydrology X, 2022)
Keywords: Infolettre; Infolettre_Octobre_2022; Site_internet_RIISQ

Trend and teleconnection analysis of temperature extremes in New South Wales, Australia - Laz, Orpita U.; Rahman, Ataur; Ouarda, Taha B. M. J. (Natural Hazards, 2024)
Abstract This study investigates possible trends and teleconnections in temperature extremes in New South Wales (NSW), Australia. Daily maximum and minimum temperature data covering the period 1971–2021 at 26 stations located in NSW were used. Three indices, which focus on daily maximum temperature, daily minimum temperature, and average daily temperature in terms of Excessive Heat Factor (EHF) were investigated to identify the occurrence of heatwaves (HWs). The study considered HWs of different durations (1-, 5-, and 10-days) in relation to intensity, frequency, duration, and their first occurrence parameters. Finally, the influences of three global climate drivers, namely – the El Niño/Southern Oscillation (ENSO), the Southern Annular Mode (SAM), and the Indian Ocean Dipole (IOD) were investigated with associated heatwave attributes for extended Austral summers. In this study, an increasing trend in both hot days and nights was observed for most of the selected stations within the study area. The increase was more pronounced for the last decade (2011–2021) of the investigated time period. The number, duration and frequency of the heatwaves increased over time considering the EHF criterion, whereas no particular trend was detected in cases of TX90 and TN90. It was also evident that the first occurrence of all the HWs shifted towards the onset of the extended summer while considering the EHF criterion of HWs. The correlations between heatwave attributes and climate drivers depicted that heatwave over NSW was positively influenced by both the IOD and ENSO and negatively correlated with SAM. The findings of this study will be useful in formulating strategies for managing the impacts of extreme temperature events such as bushfires, floods, droughts to the most at-risk regions within NSW.
Keywords: Infolettre; Infolettre_Novembre_2024

Rainfall-triggered waste dump instability analysis based on surface 3D deformation in physical model test - Li, Hanlin; Jin, Xiaoguang; He, Jie; Xue, Yunchuan; Yang, Zhongping (Journal of Mountain Science, 2024)
Keywords: Infolettre; Infolettre_Ete_2024

Enhanced Bioaccumulation and Transfer of Monomethylmercury through Periphytic Biofilms in Benthic Food Webs of a River Affected by Run-of-River Dams - Leclerc, Maxime; Ponton, Dominic E.; Bilodeau, François; Planas, Dolors; Amyot, Marc (Environmental Science & Technology, 2023)
Keywords: Infolettre; Infolettre_Janvier_2024

Alternatives for sustained disaster risk reduction: A re-assessment - Le De, Loic; Baumann, Louise L.; Moatty, Annabelle; Le Masson, Virginie; Kikano, Faten; Fayazi, Mahmood; Fernandez, Manuela; Tomassi, Isabella; Cadag, Jake Rom D. (Jàmbá Journal of Disaster Risk Studies, 2023)
Keywords: Infolettre; Infolettre_Novembre_2023

Trends, Shifting, or Oscillations? Stochastic Modeling of Nonstationary Time Series for Future Water-Related Risk Management - Lee, Taesam; Ouarda, Taha B. M. J. (Earth's Future, 2023)
Hydrological time series often present nonstationarities such as trends, shifts, or oscillations due to anthropogenic effects and hydroclimatological variations, including global climate change. For water managers, it is crucial to recognize and define the nonstationarities in hydrological records. The nonstationarities must be appropriately modeled and stochastically simulated according to the characteristics of observed records to evaluate the adequacy of flood risk mitigation measures and future water resources management strategies. Therefore, in the current study, three approaches were suggested to address stochastically nonstationary behaviors, especially in the long-term variability of hydrological variables: as an overall trend, shifting mean, or as a long-term oscillation. To represent these options for hydrological variables, the autoregressive model with an overall trend, shifting mean level (SML), and empirical mode decomposition with nonstationary oscillation resampling (EMD-NSOR) were employed in the hydrological series of the net basin supply in the Lake Champlain-River Richelieu basin, where the International Joint Committee recently managed and significant flood damage from long consistent high flows occurred. The detailed results indicate that the EMD-NSOR model can be an appropriate option by reproducing long-term dependence statistics and generating manageable scenarios, while the SML model does not properly reproduce the observed long-term dependence, that are critical to simulate sustainable flood events. The trend model produces too many risks for floods in the future but no risk for droughts. The overall results conclude that the nonstationarities in hydrological series should be carefully handled in stochastic simulation models to appropriately manage future water-related risks.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022EF003049
Keywords: Infolettre; Infolettre_Octobre_2023; Infolettre_Septembre_2023

Synthesis of a novel flocculant with dimethylamino propylmethacrylamide and polyether and its flocculation performance - He, Jie; Duan, Ming; Zhou, Shouwei; Zhao, Liqiang; Luo, Zhifeng; Fang, Shenwen (Journal of Dispersion Science and Technology, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Synthesis of a water‐soluble high hydroxymethyl content phenolic resin crosslinker and the associated polyacrylamide weak gel property investigation - He, Jie; Ye, Zi; Liao, Dong; Chen, Qing‐mei; Liu, Hang‐rui; Fan, Hai‐bo; Luo, Min; Zhong, Cheng (Journal of Polymer Science, 2024)
Abstract As an in‐depth profile control agent, water‐soluble phenolic resin crosslinking polyacrylamide weak gel has been widely used in the middle and high water cut stage of water flooding reservoir. In this study, the phenolic resin was synthesized by two‐step alkali catalysis. Factors influencing the synthesis of phenolic resin, including the molar ratio of phenol and formaldehyde, catalyst types, reaction time, were investigated with hydroxylmethyl and aldehyde content as the criterion. When the molar ratio of phenolic resin was 1:2 and NaOH was catalyst, at 80°C for 4 h, the phenolic resin had the highest hydroxymethyl content (49.37%) and the lowest free aldehyde content (2.95%). Weak gel was formed by the reaction of LT002‐polyacrylamide with phenolic resin. Taking the gelation time and strength as criteria, the factors influencing the crosslinking property, including hydroxymethyl content, crosslinker addition, and polyacrylamide concentration were investigated respectively. Under optimal formulation, the property investigation shows that the hydroxymethyl group in the phenolic resin can be crosslinked with the amide group in polyacrylamide, the gelation time is long (50–60 h), and the gelation strength is larger than 5 × 10 4 mPa s, which is conductive to the plugging of deep oil layers. When the permeability was 5061 × 10 −3 μm 2 , the plugging rate was 72.73%.
Keywords: Infolettre; Infolettre_Ete_2024

Discrete Element Method Analyses of Bond Degradation Evolutions for Cemented Soils - He, Jie; Li, Tao; Rui, Yi (Fractal and Fractional, 2024)
The degradation of soil bonding, which can be described by the evolution of bond degradation variables, is essential in the constitutive modeling of cemented soils. A degradation variable with a value of 0/1.0 indicates that the applied stress is completely sustained by bonded particles/unbounded grains. The discrete element method (DEM) was used for cemented soils to analyze the bond degradation evolution and to evaluate the degradation variables at the contact scale. Numerical cemented soil samples with different bonding strengths were first prepared using an advanced contact model (CM). Constant stress ratio compression, one-dimensional compression, conventional triaxial tests (CTTs), and true triaxial tests (TTTs) were then implemented for the numerical samples. After that, the numerical results were adopted to investigate the evolution of the bond degradation variables BN and B0. In the triaxial tests, B0 evolves to be near to or larger than BN due to shearing, which indicates that shearing increases the bearing rate of bond contacts. Finally, an approximate stress-path-independent bond degradation variable Bσ was developed. The evolution of Bσ with the equivalent plastic strain can be effectively described by an exponential function and a hyperbolic function.
Keywords: Infolettre; Infolettre_Mars_2024

Fine Particle Migration in a Gas Hydrate Sand: Single- and Two-Phase Fluid Using a Device for Observation at the Pore Scale - He, Jie; Huang, Xiang; Cao, Pei (Journal of Marine Science and Engineering, 2024)
The production of natural gas hydrates will change the cementation strength, porosity, and effective stress in the stratum, which may lead to engineering and geological disasters. Sand production is a phenomenon where sand particles are carried out of the reservoir along with fluids during gas extraction, posing challenges to safe and sustainable production. This study explored the mechanism of fine particle migration in multiphase flow by a microscopic visualization test device. The device can inject a gas–liquid–solid phase at the same time and allow real-time observation. Experimental tests on fine particle migration of single- and two-phase fluid flow were carried out considering different conditions, i.e., fine particle concentration, fine particle size, fluid flow rate, and gas–liquid ratio. The results show that in single-phase fluid flow, the original gas will gradually dissolve in the liquid phase, and finally stay in the test device as bubbles, which can change the pore structures, resulting in the accumulation of fine particles at the gas–liquid interface. In two-phase fluid flow with mixed gas–water fluids, there are two flow modes of gas–liquid flow: mixed flow and separated flow. The interfacial tension at the gas–liquid interface can effectively migrate fine particles when the gas–liquid flows alternately and the sand production rate further increases as the gas–liquid ratio increases. In addition, changes in the concentration of fine particles, particle size, fluid flow rate, and the gas–liquid ratio will affect the migration of fine particles, leading to differences in the final sand production.
Keywords: Infolettre; Infolettre_Fevrier_2024

Determination of duration, threshold and spatiotemporal distribution of extreme continuous precipitation in nine major river basins in China - Jin, Haoyu; Chen, Xiaohong; Adamowski, Jan; Hatami, Shadi (Atmospheric Research, 2024)
Keywords: Infolettre; Infolettre_Mars_2024

Use of Mixed Methods in the Science of Hydrological Extremes: What Are Their Contributions? - Kabo, Raymond; Bourgault, Marc-André; Barrette, Nathalie; Tanguay, Louis (Hydrology, 2023)
Research in hydrological sciences is constantly evolving to provide adequate answers to address various water-related issues. Methodological approaches inspired by mathematical and physical sciences have shaped hydrological sciences from its inceptions to the present day. Nowadays, as a better understanding of the social consequences of extreme meteorological events and of the population’s ability to adapt to these becomes increasingly necessary, hydrological sciences have begun to integrate knowledge from social sciences. Such knowledge allows for the study of complex social-ecological realities surrounding hydrological phenomena, such as citizens’ perception of water resources, as well as individual and collective behaviors related to water management. Using a mixed methods approach to combine quantitative and qualitative approaches has thus become necessary to understand the complexity of hydrological phenomena and propose adequate solutions for their management. In this paper, we detail how mixed methods can be used to research flood hydrology and low-flow conditions, as well as in the management of these hydrological extremes, through the analysis of case studies. We frame our analysis within the three paradigms (positivism, post-positivism, and constructivism) and four research designs (triangulation, complementary, explanatory, and exploratory) that guide research in hydrology. We show that mixed methods can notably contribute to the densification of data on extreme flood events to help reduce forecasting uncertainties, to the production of knowledge on low-flow hydrological states that are insufficiently documented, and to improving participatory decision making in water management and in handling extreme hydrological events.
Number: 6 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Infolettre; Infolettre_Ete_2023

Interpolation of Precipitation Extremes on a Large Domain Toward IDF Curve Construction at Unmonitored Locations - Jalbert, Jonathan; Genest, Christian; Perreault, Luc (Journal of Agricultural, Biological and Environmental Statistics, 2022)
Abstract An intensity–duration–frequency (IDF) curve describes the relationship between rainfall intensity and duration for a given return period and location. Such curves are obtained through frequency analysis of rainfall data and commonly used in infrastructure design, flood protection, water management, and urban drainage systems. However, they are typically available only in sparse locations. Data for other sites must be interpolated as the need arises. This paper describes how extreme precipitation of several durations can be interpolated to compute IDF curves on a large, sparse domain. In the absence of local data, a reconstruction of the historical meteorology is used as a covariate for interpolating extreme precipitation characteristics. This covariate is included in a hierarchical Bayesian spatial model for extreme precipitations. This model is especially well suited for a covariate gridded structure, thereby enabling fast and precise computations. As an illustration, the methodology is used to construct IDF curves over Eastern Canada. An extensive cross-validation study shows that at locations where data are available, the proposed method generally improves on the current practice of Environment and Climate Change Canada which relies on a moment-based fit of the Gumbel extreme-value distribution.
Keywords: Infolettre; Infolettre_Avril_2022; Site_internet_RIISQ

Projected Changes in Extreme Precipitation Patterns across Algerian Sub-Regions - Hamitouche, Yasmine; Zeroual, Ayoub; Meddi, Mohamed; Assani, Ali A.; Alkama, Ramdane; Şen, Zekâi; Zhang, Xinhua (Water, 2024)
Extreme precipitation events play a crucial role in shaping the vulnerability of regions like Algeria to the impacts of climate change. To delve deeper into this critical aspect, this study investigates the changing patterns of extreme precipitation across five sub-regions of Algeria using data from 33 model simulations provided by the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP-CMIP6). Our analysis reveals a projected decline in annual precipitation for four of these regions, contrasting with an expected increase in desert areas where annual precipitation levels remain low, typically not exceeding 120 mm. Furthermore, key precipitation indices such as maximum 1-day precipitation (Rx1day) and extremely wet-day precipitation (R99p) consistently show upward trends across all zones, under both SSP245 and SSP585 scenarios. However, the number of heavy precipitation days (R20mm) demonstrates varied trends among zones, exhibiting stable fluctuations. These findings provide valuable foresight into future precipitation patterns, offering essential insights for policymakers and stakeholders. By anticipating these changes, adaptive strategies can be devised to mitigate potential climate change impacts on crucial sectors such as agriculture, flooding, water resources, and drought.
Keywords: Infolettre; Infolettre_Ete_2024; Site_internet_RIISQ

Geomechanical Properties of Deep-Sea Pore-Filled Methane Hydrate-Bearing Soils at Critical State Using DEM Analysis - He, Jie; Li, Tao; Rui, Yi (Fractal and Fractional, 2023)
The recognition of the geomechanical properties of methane hydrate-bearing soil (MHBS) is crucial to exploring energy resources. The paper presents the mechanical properties of a pore-filled MHBS at a critical state using the distinct element method (DEM). The pore-filled MHBS was simulated as cemented MH agglomerates to fill the soil pores at varying levels of methane hydration (MH) saturation. A group of triaxial compression (TC) tests were conducted, subjecting MHBS samples to varying effective confining pressures (ECPs). The mechanical behaviors of a pore-filled MHBS were analyzed, as it experienced significant strains leading to a critical state. The findings reveal that the proposed DEM successfully captures the qualitative geomechanical properties of MHBS. As MH saturation increases, the shear strength of MHBS generally rises. Moreover, higher ECPs result in increased shear strength and volumetric contraction. The peak shear strength of MHBS increases with rising MH saturation, while the residual deviator stress remains mainly unchanged at a critical state. There is a good correlation between fabric changes of the MHBS with variations in principal stresses and principal strains. With increasing axial strain, the coordination number (CN) and mechanical coordination number (MCN) increase to peak values as the values of MH saturation and ECPs increase, and reach a stable value at a larger axial strain.
Keywords: Infolettre; Infolettre_Octobre_2023

Benefit of assimilating satellite all-sky infrared radiances on the cloud and precipitation prediction of a long-lasting mesoscale convective system over the Tibetan plateau - He, Jie; Ma, Xulin; Chen, Xingchao (Quarterly Journal of the Royal Meteorological Society, 2023)
Heavy rainfall events in the warm season (May–September) over the Tibetan Plateau (TP) region and its downstream areas are often closely related to eastward-propagating Tibetan Plateau Vortices (TPVs). Hence, improving the prediction of TPVs and their associated convective activity is of paramount importance, given the significant potential impacts they can have on densely populated downstream regions, including but not limited to flooding and damages. In this study, a typical long-lived TPV that occurred in July 2008 was used for the first time to explore the benefit of assimilating satellite all-sky infrared radiances on the cloud and precipitation prediction of the TPV-induced eastward-propagating mesoscale convective system (MCS). The all-sky infrared radiances from the water vapor (WV) channel of the geostationary Meteosat-7 and other conventional observations were assimilated into a 4-km grid spacing regional model using the ensemble Kalman filter. The results revealed that the all-sky infrared data assimilation improved the cloud, precipitation, dynamical, and thermodynamical analyses as well as 0–12-hr deterministic and ensemble forecasts. Compared with the experiment in which the all-sky infrared radiances were not assimilated (non-radiance experiment), the experiment with assimilated all-sky infrared radiances yielded clearly improved initial wind and cloud fields, 1–12-hr cloud forecasts, and 1–6-hr precipitation forecasts. This study indicates that assimilation of all-sky satellite radiances has the potential for improving the operational cloud and precipitation forecasts over the TP and its downstream areas.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4529
Keywords: Infolettre; Infolettre_Septembre_2023

Do civil engineering fronts emerge from interdisciplinary research? - He, Jie; Yao, Junlan; Chen, Xin; Liu, Fang; Zhu, Hehua (Frontiers of Structural and Civil Engineering, 2023)
Abstract Interdisciplinary research is considered a source of innovativeness and creativity, serving as a key mechanism for creating recombination necessary for the evolution of science systems. The aim of this study is to quantitatively establish the connection between interdisciplinary research and the research fronts that have recently emerged in civil engineering. The degree of interdisciplinarity of the research fronts was measured by developing metrics from bibliographic analyses. As indicated by the consistent increase in the metrics of interdisciplinarity over time, research fronts tend to emerge in studies with increasing diversity in the disciplines involved. The active disciplines involved in the fronts vary over time. The most active disciplines are no longer fundamental but those associated with energy, environment, and sustainable development, focusing on solutions to climate change and integrating intelligence technologies.
Keywords: Infolettre; Infolettre_Fevrier_2023

Numerical and experimental analyses of methane leakage in shield tunnel - He, Jie; Zhu, Hehua; Wei, Xiangyang; Jin, Rui; Jiao, Yaji; Yin, Mei (Frontiers of Structural and Civil Engineering, 2023)
Abstract Tunnels constructed in gas-bearing strata are affected by the potential leakage of harmful gases, such as methane gas. Based on the basic principles of computational fluid dynamics, a numerical analysis was performed to simulate the ventilation and diffusion of harmful gases in a shield tunnel, and the effect of ventilation airflow speed on the diffusion of harmful gases was evaluated. As the airflow speed increased from 1.8 to 5.4 m/s, the methane emission was diluted, and the methane accumulation was only observed in the area near the methane leakage channels. The influence of increased ventilation airflow velocity was dominant for the ventilation modes with two and four fans. In addition, laboratory tests on methane leakage through segment joints were performed. The results show that the leakage process can be divided into “rapid leakage” and “slight leakage”, depending on the leakage pressure and the state of joint deformation. Based on the numerical and experimental analysis results, a relationship between the safety level and the joint deformation is established, which can be used as guidelines for maintaining utility tunnels.
Keywords: Infolettre; Infolettre_Octobre_2023

Smooth Spatial Modeling of Extreme Mediterranean Precipitation - Hammami, Hela; Carreau, Julie; Neppel, Luc; Elasmi, Sadok; Feki, Haifa (Water, 2022)
Extreme precipitation events can lead to disastrous floods, which are the most significant natural hazards in the Mediterranean regions. Therefore, a proper characterization of these events is crucial. Extreme events defined as annual maxima can be modeled with the generalized extreme value (GEV) distribution. Owing to spatial heterogeneity, the distribution of extremes is non-stationary in space. To take non-stationarity into account, the parameters of the GEV distribution can be viewed as functions of covariates that convey spatial information. Such functions may be implemented as a generalized linear model (GLM) or with a more flexible non-parametric non-linear model such as an artificial neural network (ANN). In this work, we evaluate several statistical models that combine the GEV distribution with a GLM or with an ANN for a spatial interpolation of the GEV parameters. Key issues are the proper selection of the complexity level of the ANN (i.e., the number of hidden units) and the proper selection of spatial covariates. Three sites are included in our study: a region in the French Mediterranean, the Cap Bon area in northeast Tunisia, and the Merguellil catchment in central Tunisia. The comparative analysis aim at assessing the genericity of state-of-the-art approaches to interpolate the distribution of extreme precipitation events.
Number: 22 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Infolettre; Infolettre_Fevrier_2023

Evaluation of Concrete Constitutive Models for Finite Element Simulation of Dam Shear Keys - Freitas, Mario; Ben Ftima, Mahdi; Léger, Pierre; Bouaanani, Najib (Proceedings of the Canadian Society of Civil Engineering Annual Conference 2022, 2023)
Keywords: Infolettre; Infolettre_Septembre_2024

Concepts and evolution of urban hydrology - Fletcher, Tim D.; Burns, Matthew J.; Russell, Kathryn L.; Hamel, Perrine; Duchesne, Sophie; Cherqui, Frédéric; Roy, Allison H. (Nature Reviews Earth & Environment, 2024)
Keywords: Infolettre; Infolettre_Novembre_2024

Combining large-scale and regional hydrological forecasts using simple methods - Fontaine, Nicolas; Boucher, Marie-Amélie; Anctil, François; Odry, Jean; Lachance-Cloutier, Simon; Fortin, Vincent; Turcotte, Richard (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2024)
Keywords: Infolettre; Infolettre_Novembre_2023

Anthropogenic exacerbations of summer-autumn compound dry-hot severity in the middle and lower reaches of the Yangtze River - Feng, Shuyun; Gu, Xihui; Guan, Yansong; Wang, Quan J.; Wang, Lunche; Du, Lingtong; He, Jie; Zhang, Xiang; Kong, Dongdong (Journal of Hydrology, 2025)
Keywords: Infolettre; Infolettre_Decembre_2024

Deciphering the sedimentary imprint of tsunamis and storms in the Lesser Antilles (Saint Martin): A 3500-year record in a coastal lagoon - Fabbri, Stefano C.; Sabatier, Pierre; Paris, Raphaël; Falvard, Simon; Feuillet, Nathalie; Lothoz, Amélie; St-Onge, Guillaume; Gailler, Audrey; Cordrie, Louise; Arnaud, Fabien; Biguenet, Maude; Coulombier, Thibault; et al. (Marine Geology, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Aerial photogrammetry to characterise and numerically model an ice jam in Southern Quebec - Duguay, Jason; Lindenschmidt, Karl-Erich; Trudel, Mélanie; Pruneau, Antoine (Hydrology Research, 2023)
Abstract Collecting data on the dynamic breakup of a river's ice cover is a notoriously difficult task. However, such data are necessary to reconstruct the events leading to the formation of ice jams and calibrate numerical ice jam models. Photogrammetry using images from remotely piloted aircraft (RPA) is a cost-effective and rapid technique to produce large-scale orthomosaics and digital elevation maps (DEMs) of an ice jam. Herein, we apply RPA photogrammetry to document an ice jam that formed on a river in southern Quebec in the winter of 2022. Composite orthomosaics of the 2-km ice jam provided evidence of overbanking flow, hinge cracks near the banks and lengthy longitudinal stress cracks in the ice jam caused by sagging as the flow abated. DEMs helped identify zones where the ice rubble was grounded to the bed, thus allowing ice jam thickness estimates to be made in these locations. The datasets were then used to calibrate a one-dimensional numerical model of the ice jam. The model will be used in subsequent work to assess the risk of ice interacting with the superstructure of a low-level bridge in the reach and assess the likelihood of ice jam flooding of nearby residences.
Keywords: Infolettre; Infolettre_Novembre_2023

The role of internal climate variability on future streamflow projections - Faghih, Mina; Brissette, François (Journal of Hydrology, 2023)
Keywords: Infolettre; Infolettre_Octobre_2023

Effects of the Water-Cement Ratio and the Molding Temperature on the Hydration Heat of Cement - Dai, Jinpeng; He, Jie; Wang, Qicai; Lou, Xuyu (Journal of Wuhan University of Technology-Mater. Sci. Ed., 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Machine learning prediction of electric flux in concrete and mix proportion optimization design - Dai, Jinpeng; Yang, Xiaoyuan; He, Jie; Wang, Qicai; Zhang, Zhijie (Materials Today Communications, 2024)
Keywords: Infolettre; Infolettre_Fevrier_2024

Updating the intensity-duration-frequency curves in major Canadian cities under changing climate using CMIP5 and CMIP6 model projections - Crévolin, Vincent; Hassanzadeh, Elmira; Bourdeau-Goulet, Sarah-Claude (Sustainable Cities and Society, 2023)
Keywords: Bourdeau-Brien_Michael; Infolettre; Infolettre_Avril_2023

Spatiotemporal variability of runoff events in response to rainfall, snowmelt, and rain-on-snow in the Lake Erie Basin - Ali, Geneviève; Siebert, Krystal; Mizero, Steven Mugisha (Journal of Hydrology: Regional Studies, 2024)
Keywords: Infolettre

Uncertainty propagation within a water level ensemble prediction system - Bessar, Mohammed Amine; Anctil, François; Matte, Pascal (Journal of Hydrology, 2021)
Keywords: Infolettre; Infolettre_Janvier_2022; Site_internet_RIISQ

Operations research approaches for improving coordination, cooperation, and collaboration in humanitarian relief chains: A framework and literature review - Adsanver, Birce; Balcik, Burcu; Bélanger, Valérie; Rancourt, Marie-Ève (European Journal of Operational Research, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Normative Influences on Farmers’ Intentions to Practice Conservation Without Compensation - Vaske, Jerry J.; Landon, Adam C.; Miller, Craig A. (Environmental Management, 2020)
Keywords: Ouvrage_Collectif_Numéro1

Stream habitat provided by large wood at risk under drainage law - Shirey, Patrick D.; Kenny, Jillian B.; Brueseke, Michael A.; Lamberti, Gary A. (Earth Surface Processes and Landforms, 2020)
Watershed management efforts in agriculturally dominated landscapes of North America face nearly two centuries of laws and policies that encouraged habitat destruction. Although streams and wetlands in these landscapes are actively being restored using designs that incorporate science and engineering, watershed drainage laws can constrain action or impact passively restored or naturalized habitat. In general, drainage laws require removal of any riparian vegetation or wood deemed to obstruct flow in streams regulated as drains. We use a case study from Indiana (USA) to introduce the shortcomings of drainage laws for allowing large wood, which is an important habitat feature, to remain in stream ecosystems. Removals of large wood from monitored stream reaches in a regulated drain were associated with subsequent declines in fish biomass. Such legal activities represent an important environmental management problem that exists under drainage laws which apply to streams over a widespread geographic region of North America. Recent litigation in Wisconsin (USA) suggests that if state legislatures fail to update these antiquated laws, the courts may act in favour of science-based management of drains. The statutes and regulations that govern agricultural drainage warrant careful consideration if streams within drainage districts are to be managed to improve ecological function. © 2020 John Wiley & Sons, Ltd.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/esp.4828
Keywords: Ouvrage_Collectif_Numéro1

ERA5-Land: a state-of-the-art global reanalysis dataset for land applications - Muñoz-Sabater, Joaquín; Dutra, Emanuel; Agustí-Panareda, Anna; Albergel, Clément; Arduini, Gabriele; Balsamo, Gianpaolo; Boussetta, Souhail; Choulga, Margarita; Harrigan, Shaun; Hersbach, Hans; Martens, Brecht; Miralles, Diego G.; et al. (Earth System Science Data, 2021)
Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parameterizations that guarantees the use of the state-of-the-art land surface modelling applied to numerical weather prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed performance when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available has extended from January 1981 to the near present, with a 2- to 3-month delay with respect to real time. The segment prior to 1981 is in production, aiming for a release of the whole dataset in summer/autumn 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialize NWP and climate models, and to support diverse applications dealing with water resource, land, and environmental management. The full ERA5-Land hourly (Muñoz-Sabater, 2019a) and monthly (Muñoz-Sabater, 2019b) averaged datasets presented in this paper are available through the C3S Climate Data Store at https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.
Publisher: Copernicus GmbH
Keywords: Ouvrage_Collectif_Numéro1

The ERA5 global reanalysis - Hersbach, Hans; Bell, Bill; Berrisford, Paul; Hirahara, Shoji; Horányi, András; Muñoz‐Sabater, Joaquín; Nicolas, Julien; Peubey, Carole; Radu, Raluca; Schepers, Dinand; Simmons, Adrian; Soci, Cornel; et al. (Quarterly Journal of the Royal Meteorological Society, 2020)
Abstract Within the Copernicus Climate Change Service (C3S), ECMWF is producing the ERA5 reanalysis which, once completed, will embody a detailed record of the global atmosphere, land surface and ocean waves from 1950 onwards. This new reanalysis replaces the ERA‐Interim reanalysis (spanning 1979 onwards) which was started in 2006. ERA5 is based on the Integrated Forecasting System (IFS) Cy41r2 which was operational in 2016. ERA5 thus benefits from a decade of developments in model physics, core dynamics and data assimilation. In addition to a significantly enhanced horizontal resolution of 31 km, compared to 80 km for ERA‐Interim, ERA5 has hourly output throughout, and an uncertainty estimate from an ensemble (3‐hourly at half the horizontal resolution). This paper describes the general set‐up of ERA5, as well as a basic evaluation of characteristics and performance, with a focus on the dataset from 1979 onwards which is currently publicly available. Re‐forecasts from ERA5 analyses show a gain of up to one day in skill with respect to ERA‐Interim. Comparison with radiosonde and PILOT data prior to assimilation shows an improved fit for temperature, wind and humidity in the troposphere, but not the stratosphere. A comparison with independent buoy data shows a much improved fit for ocean wave height. The uncertainty estimate reflects the evolution of the observing systems used in ERA5. The enhanced temporal and spatial resolution allows for a detailed evolution of weather systems. For precipitation, global‐mean correlation with monthly‐mean GPCP data is increased from 67% to 77%. In general, low‐frequency variability is found to be well represented and from 10 hPa downwards general patterns of anomalies in temperature match those from the ERA‐Interim, MERRA‐2 and JRA‐55 reanalyses.
Keywords: Ouvrage_Collectif_Numéro1

The human cost of disasters: an overview of the last 20 years (2000-2019) - UNDRR (UN Office for Disaster Risk Reduction, 2020)
UNDRR report published to mark the International Day for Disaster Risk Reduction on October 13, 2020, confirms how extreme weather events have come to dominate the disaster landscape in the 21st century.
Keywords: Ouvrage_Collectif_Numéro1

Privatizing climate adaptation: How insurance weakens solidaristic and collective disaster recovery - Lucas, Chloe H.; Booth, Kate I. (WIREs Climate Change, 2020)
Abstract As losses from extreme weather events grow, many governments are looking to privatize the financing and incentivization of climate adaptation through insurance markets. In a pure market approach to insurance for extreme weather events, individuals become responsible for ensuring they are adequately covered for risks to their own properties, and governments no longer contribute funds to post‐disaster recovery. Theoretically, insurance premiums signal the level of risk faced by each household, and incentivize homeowners to invest in adaptive action, such as retrofitting, or drainage work, to reduce premiums. Where risk is considered too high by insurance markets, housing is devalued, in theory leading to retreat from risky areas. In this review article, we evaluate the suitability of private insurance as a mechanism for climate adaptation at a household and community level. We find a mismatch between social understandings of responsibility for climate risks, and the technocratic, market‐based home insurance products offered by private insurance markets. We suggest that by constructing increasingly individualized, technical, and calculative evaluations of risk, market‐based models of insurance for extreme weather events erode the solidaristic and collective discourses and practices that support adaptive behavior. This article is categorized under: Vulnerability and Adaptation to Climate Change > Institutions for Adaptation
Keywords: Ouvrage_Collectif_Numéro1

How to use artificial intelligence to downscale climate change models’ data - Salimi, Amirhossein; Ghobrial, Tadros; Bonakdari, Hossein (Intelligence Systems for Earth, Environmental and Planetary Sciences, 2024)

Comparison of the Performance of CMIP5 and CMIP6 in the Prediction of Rainfall Trends, Case Study Quebec City - Salimi, Amirhossein; Ghobrial, Tadros; Bonakdari, Hossein (ECWS-7 2023, 2023)

Numerical Investigation Of Structural Responses Impacted By Flood Flow - Wang, Jianguo (Polytechnique Montréal, 2024)
RÉSUMÉ: «RÉSUMÉ: Les inondations sont reconnues comme l’une des catastrophes naturelles les plus fréquentes et destructrices à l’échelle mondiale. Leur gravité est exacerbée par les effets du changement climatique (augmentation des précipitations) et de la construction humaine (réduction de la capacité naturelle à absorber l’eau). Les structures construites dans des zones sujettes à l’eau, telles que les ponts et les barrages, sont généralement vulnérables aux événements d’inondation sévères. Pour les problèmes impliquant de l’eau fluide, les chercheurs en hydraulique supposent généralement que les structures sont "infinitement" rigides et utilisent des limites de paroi imperméables pour représenter les structures dans les modèles numériques. Cependant, les structures se déformeront, vibreront et pourraient même être endommagées lors d’un événement d’inondation sévère. Du point de vue d’un ingénieur structurel, il est important d’incorporer la flexibilité structurelle dans l’analyse de l’interaction fluide-structure (FSI). Étant donné que la taille du domaine fluide est significativement plus grande que celle des structures, un grand nombre d’éléments est généré, rendant l’analyse FSI chronophage, surtout pour les cas avec un canal 3D long et des maillages raffinés. Par conséquent, une méthode de modélisation simplifiée efficace et précise est nécessaire. De plus, le comportement hydrodynamique des structures telles que le pont dans un cours d’eau et la structure du barrage à l’extrémité d’un canal partiellement recouvert de glace n’est pas bien connu. Pour aborder ce problème, cette recherche a examiné numériquement les réponses structurelles avec l’impact de l’écoulement des inondations en tenant compte de la flexibilité structurelle, en se concentrant sur l’interaction dynamique entre l’eau fluide et les structures solides, les effets 3D des fluides et des structures, le glissement des structures (par exemple, le glissement du tablier du pont), et la présence d’une couverture de glace partielle positionnée au sommet de l’eau dans un canal.» ABSTRACT: «ABSTRACT: Floods are recognized as one of the most frequent and destructive natural disasters globally. Their severity is exacerbated by the effects of climate change (increased precipitation) and human construction (reduced natural capacity to absorb water). Structures built in waterprone areas, such as bridges and dams, are usually vulnerable to severe flood events. For problems involving fluid water, hydraulic researchers commonly assume that structures are "infinitely" rigid and use impervious wall boundaries to present the structures in numerical models. However, structures will deform, vibrate, and even be damaged during a severe flood event. From a structural engineer’s perspective, it is important to incorporate structural flexibility into the fluid-structure interaction (FSI) analysis. Because the size of the fluid domain is significantly larger than that of the structures, a large set of elements is generated, making the FSI analysis time-consuming, especially for cases with a long 3D channel and refined meshes. As a result, an efficient and accurate simplified modeling method is needed. Also, the hydrodynamic behavior of structures such as the bridge in a stream and the dam structure at the end of a partially ice-covered channel is not well known. To address this problem, this research numerically investigated the structural responses with the impact of flood flow considering the structural flexibility, focusing on the dynamic interaction between fluid water and solid structures, the 3D effects of fluid and structures, the sliding of structures (e.g. sliding of bridge deck), and the presence of partial ice cover positioned at the top of the water in a channel.»

QUIC Protocol : Resilience against flooding attacks and defense mechanism - Teyssier, Benjamin (Concordia University, 2024)
QUIC is a modern transport layer internet protocol designed to be more efficient and secure than TCP. It has gained popularity quickly in recent years and has been adopted by a number of prominent tech companies. Its efficiency comes from its handshake design. The server and the client make both the transport layer acknowledgment and the TLS agreement during the same round trip. However this process makes the packets heavy and requires more processing on the server-side than TCP. This characteristic can be used as leverage by an attacker to compromise the computing resources of its victim. This thesis investigates the resilience of QUIC Protocol against handshake flood attacks and proposes a detection mechanism (QUICShield). I conducted comprehensive experiments to evaluate the resource consumptions of both the attacker and the target during incomplete handshake attacks, including CPU, memory, and bandwidth. We compared the results against TCP Syn Cookies under Syn flood attacks. The DDoS amplification factor was measured and analyzed based on the results. This work also proposes a detection mechanism based on a Bloom filter combined with Generalized Likelihood Ratio Cumulative Sum (GLR-CUSUM) to adapt to evolving attack patterns. It was implemented and deployed against real attacks to evaluate its efficiency. We showed that the QUIC Protocol design has a much larger DDoS amplification factor compared to the TCP, which means QUIC is more vulnerable to handshake DDoS attacks. However the mechanism proposed is accurate and efficient in terms of resources.

Valeur ajoutée de l’information sur la distribution spatiale du couvert de neige pour la prédiction des débits de crues - Tiwari, Dipti (2024)
Abstract: In Canada, the annual runoff is predominantly influenced by snowmelt following the winter season, with a substantial portion (40-80\%) occurring during the spring period, leading to flooding in low-lying areas. Accurate prediction of streamflow is essential for hydropower production, effective flood management, necessitating the incorporation of comprehensive spatially distributed snow observations into hydrological models. This draws the attention to the research question " How can we utilize spatially distributed snow information at various spatial and temporal scales to enhance our understanding of snow processes and apply it for enhanced model calibration to improve hydrological model performance?" The first objective of this thesis is to investigate the utilization of spatially distributed snow information (SNODAS- SNOw Data Assimilation System) for the calibration of a hydrological model and to determine its impact on model performance. A distributed hydrological model, HYDROTEL, has been implemented in the Au Saumon River watershed using input data from ERA-5 Land for temperature data and MSWEP for precipitation data. Seven different calibration experiments are conducted, employing three different objective functions: Nash-Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE), and the SPAtial EFficiency metric (SPAEF). These objective functions are utilized individually or in combination as part of multi-objective calibration processes. This study indicates that utilizing SPAEF for spatial calibration of snow parameters improved streamflow prediction compared to the conventional practice of using RMSE for calibration. SPAEF is further implied to be a more effective metric than RMSE for both sequential and multi-objective calibration. During validation, the calibration experiment incorporating multi-objective SPAEF exhibits enhanced performance in terms of NSE and KGE compared to calibration experiment solely based on NSE. The findings of this study hold significant relevance and potential applicability in emerging satellite technology, particularly the future Terrestrial Snow Mass Mission (TSMM). The study then explores the impact of temporal resolution and signal saturation for model calibration by using SNODAS data as proxy SWE observations mimicking the characteristics of the TSMM product to calibrate the HYDROTEL model. Despite the limitations of it's temporal resolution and signal saturation it is noteworthy that TSMM data exhibits significant potential for enhancing model performance thereby highlighting its utility for hydrological modeling. This study then focuses on the spatio-temporal analysis of snow processes influencing the spatial variability and distribution of snow depth in a small-scale experimental watershed. Drone photogrammetry is employed to capture spatially distributed snow information over the watershed during the winter seasons of 2022 and 2023. The photogrammetric data facilitated the generation of high-resolution digital surface models (DSMs). Empirical Orthogonal Function (EOF) analysis is applied to understand the spatial distribution of snow, enabling a detailed examination of various snow processes at the watershed scale. This thesis explores the added value of spatially distributed snow cover information in predicting spring runoff. Each part of the study contributes to a comprehensive understanding of the spatial distribution of snow and its significance in hydrology.
Accepted: 2024-05-30T19:00:46Z Publisher: Université de Sherbrooke

Occurrence and transport of pollutants from spilled oil and microplastics in the coastal areas - Wang, Zheng (Concordia University, 2023)
The coast is a complex environment that comprises seawater, underwater, soil, atmosphere, and other environmental factors. Traditional and new pollutants, represented by oil spills and microplastic (MPs), persist in posing a constant threat to the ecosystems and social-economic features of coastal regions. Besides, the shoreline is exposed to various environment conditions, which may significantly affect the behaviors of pollutants on beaches. An in-depth understanding of the occurrence and fate of pollutants in coastal areas is a prerequisite for the development of sound prevention and remediation strategies. Firstly, the physicochemical behavior of crude oil on various types of shorelines under different environmental conditions were reviewed. The penetration, remobilization, and retention of stranded oil on shorelines are affected by the beach topography and the natural environment. The attenuation and fate of oil on shorelines from laboratory and field experiments were discussed. In addition, the source, type, distribution, and factors of MPs in the coastal areas were summarized. What is more, the occurrence and environmental risk of emerging plastics waste—personal protective equipment (PPE)—in the coastal environment during and pandemic were discussed. Then, the role of natural nanobubbles (NBs) in the fate and transport of spilled oil were investigated through laboratory experiments and model simulations. NBs significantly increased the concentration of dissolved oxygen as well as changed the pH, zeta potential, and surface tension of the water. With the assistance of external energy, the bulk NBs enhanced the efficiency in oil detachment from the surface of the substrate. At the same time, the surface NBs on the substrate obstructed the downward transport of oil colloids. Considering the behavior between the NBs in two different phases and the oil droplets, the oil droplets tended to bind to the NBs. Next, the behavior and movement of various MPs in the presence of bulk NBs was explored. In the presence of NBs, the binding of MPs and NBs resulted in an increase in the measured average particle size and concentration. The velocity of motion of MPs driven by NBs varies under different salinity conditions. The increase in ionic strength reduced the energy barrier between particles and promoted their aggregation. Thus, the binding of NBs and MPs became more stable, which in turn affected the movement of MPs in the water. Polyethylene (PE1) with small particle size was mainly affected by Brownian motion and its rising was limited, therefore polyethylene (PE2) with large particle size rose faster than PE1 in suspension, especially in the presence of NBs. The effect of nanobubbles on the mobilization of MPs in shorelines subject to seawater infiltration was further studied. The motion of MPs under continuous and transient conditions, as well as the upward transport induced with flood were considered. Salinity altered the energy barriers between particles, which in turn affected the movement of MPs within the matrix. In addition, hydrophilic MPs were more likely to infiltrate within the substrate and had different movement patterns under both continuous and transient conditions. The motion of the MPs within the substrate varied with flow rate, and NBs limited the vertical movement of MPs in the tidal zone. It was also observed that NBs adsorbed readily onto substrates, altering the surface properties of substrates, particularly their ability to attach and detach from other substances. Finally, the changing characteristics and environmental behaviors of PPE wastes when exposed to the shoreline environment were examined. The transformation of chain structure and chemical composition of masks and gloves as well as the decreased mechanical strength after UV weathering were observed. In addition, the physical abrasion caused by sand further exacerbated the release of MPs and leachable hazardous contaminates from masks and gloves. In conclusion, the coastal zone is threatened by various pollutants, including traditional pollutants (like the oil spill) and emerging pollutants (like MPs). Due to the complexity of the coastal zone, the occurrence, transport and fate of pollutants can be controlled by many factors, and some factors that are ignored before can also alter the environmental behavior of pollutants in the coastal zone. Natural NBs can change the properties of the water environment and affect the surface properties of the substrate. Bulk NBs contribute to the oil detachment from the sand surface, and surface nanobubbles in the substrate obstruct the downward transport of oil colloids. The behavior and mobilization of MPs in the coastal `zone are subject to mutual forces between the substrate, MPs, NBs, and other factors. Coastal zones are not only the main receptor of pollutants from oceans and lands but also play a key role in their fate and transport.

Design and Implementation of Machine Learning Models and Algorithms for Flood, Drought and Frazil Prediction - Yagnik, Bhargav Charudatt (Concordia University, 2023)
Natural calamities like floods and droughts pose a significant threat to humanity, impacting millions of people each year and incurring substantial economic losses to society. In response to this challenge, this thesis focuses on developing advanced machine learning techniques to improve water height prediction accuracy that can aid municipalities in effective flood mitigation. The primary objective of this study is to evaluate an innovative architecture that leverages Long Short Term Networks - neural networks to predict water height accurately in three different environmental scenarios, i.e., frazil, droughts and floods due to snow spring melt. A distinguishing feature of our approach is the incorporation of meteorological forecast as an input parameter into the prediction model. By modeling the intricate relationships between water level data, historical meteorological data and meteorological forecasts, we seek to evaluate the impact of meteorological forecasts and if any inaccuracies could impact water-level prediction. We compare the outcomes obtained by incorporating next-hour, next-day and next-week meteorological data into our novel LSTM model. Our results indicate a comprehensive comparison of the usage of various parameters as input and our findings suggest that accurate weather forecasts are crucial in achieving reliable water height predictions. Additionally, this study focuses on the utilization of IoT sensor data in combination with ML models to enhance the effectiveness of flood prediction and management. We present an online machine learning approach that performs online training of the model using real-time data from IoT sensors. The integration of live sensor data provides a dynamic and adaptive system that demonstrates superior predictive capabilities compared to traditional static models. By adopting these advanced techniques, we can mitigate the adverse impacts of natural catastrophes and work towards building more resilient and disaster-resistant communities.

Uncertainty and sensitivity analyses in wind resource assessment / Analyses d'incertitude et de sensibilité dans l'évaluation des ressources éoliennes. - Tsvetkova, Olga (Doctorat en sciences de la terre, 2022)
Cette thèse traite des aspects de la quantification de l'incertitude dans l'évaluation des ressources éoliennes avec les pratiques d'analyses d'incertitude et de sensibilité. Les objectifs de cette thèse sont d'examiner et d'évaluer la qualité des pratiques d'analyse de sensibilité dans l'évaluation des ressources éoliennes, de décourager l'utilisation d'une analyse de sensibilité à la fois, d'encourager l'utilisation d'une analyse de sensibilité globale à la place, d'introduire des méthodes d'autres domaines., et montrer comment les analyses d'incertitude et de sensibilité globale ajoutent de la valeur au processus d'aide à la décision. Cette thèse est organisée en quatre articles : I. Une revue des pratiques d'analyse de sensibilité dans l'évaluation des ressources éoliennes avec une étude de cas de comparaison d'analyses de sensibilité individuelles et globales du coût actualisé de l'énergie éolienne offshore ; II. Technique Quasi-Monte Carlo dans l'analyse de sensibilité globale dans l'évaluation des ressources éoliennes avec une étude de cas sur les Émirats Arabes Unis; III. Utilisation de la famille de distribution Halphen pour l'estimation de la vitesse moyenne du vent avec une étude de cas sur l'Est du Canada; IV. Étude d'évaluation des ressources éoliennes offshore du golfe Persique avec les données satellitaires QuikSCAT.Les articles I à III ont chacun donné lieu à une publication évaluée par des pairs, tandis que l'article IV - à une soumission. L'article I propose des classifications par variable de sortie d'analyse de sensibilité, méthode, application, pays et logiciel. L'article I met en évidence les lacunes de la littérature, fournit des preuves des pièges, conduisant à des résultats d'évaluation erronés et coûteux des ressources éoliennes. L'article II montre comment l'analyse de sensibilité globale offre une amélioration au moyen du quasi-Monte Carlo avec ses plans d'échantillonnage élaborés permettant une convergence plus rapide. L'article III introduit la famille de distribution Halphen pour l'évaluation des ressources éoliennes. Article IV utilise les données satellitaires SeaWinds/QuikSCAT pour l'évaluation des ressources éoliennes offshore du golfe Persique. Les principales contributions à l'état de l'art avec cette thèse suivent. À la connaissance de l'auteur, aucune revue de l'analyse de sensibilité dans l'évaluation des ressources éoliennes n'est actuellement disponible dans la littérature, l'article I en propose une. L'article II relie la modélisation mathématique et l'évaluation des ressources éoliennes en introduisant la technique de quasi-Monte Carlo dans l'évaluation des ressources éoliennes. L'article III présente la famille de distribution de Halphen, de l'analyse de la fréquence des crues à l'évaluation des ressources éoliennes. This dissertation deals with the aspects of quantifying uncertainty in wind resource assessment with the practices of uncertainty and sensitivity analyses. The objectives of this dissertation are to review and assess the quality of sensitivity analysis practices in wind resource assessment, to discourage the use of one-at-a-time sensitivity analysis, encourage the use of global sensitivity analysis instead, introduce methods from other fields, and showcase how uncertainty and global sensitivity analyses adds value to the decision support process. This dissertation is organized in four articles: I. Review article of 102 feasibility studies: a review of sensitivity analysis practices in wind resource assessment with a case study of comparison of one-at-a-time vs. global sensitivity analyses of the levelized cost of offshore wind energy; II. Research article: Quasi-Monte Carlo technique in global sensitivity analysis in wind resource assessment with a case study on United Arab Emirates; III. Research article: Use of the Halphen distribution family for mean wind speed estimation with a case study on Eastern Canada; IV. Application article: Offshore wind resource assessment study of the Persian Gulf with QuikSCAT satellite data. Articles I-III have each resulted in a peer-reviewed publication, while Article IV – in a submission. Article I offers classifications by sensitivity analysis output variable, method, application, country, and software. It reveals the lack of collective agreement on the definition of sensitivity analysis in the literature, the dominance of nonlinear models, the prevalence of one-at a-time sensitivity analysis method, while one-at-a-time method is only valid for linear models. Article I highlights gaps in the literature, provides evidence of the pitfalls, leading to costly erroneous wind resource assessment results. Article II shows how global sensitivity analysis offers improvement by means of the quasi-Monte Carlo with its elaborate sampling designs enabling faster convergence. Article III introduces the Halphen distribution family for the purpose of wind recourse assessment. Article IV uses SeaWinds/QuikSCAT satellite data for offshore wind resource assessment of the Persian Gulf. The main contributions to the state-of-the-art with this dissertation follow. To the best of author’s knowledge, no review of sensitivity analysis in wind resource assessment is currently available in the literature, Article I offers such. Article II bridges mathematical modelling and wind resource assessment by introducing quasi-Monte Carlo technique to wind resource assessment. Article III introduces the Halphen distribution family from flood frequency analysis to wind resource assessment.

Improving hydrological forecasting at multiple lead-times for hydropower reservoir management - Sabzipour, Behmard (École de technologie supérieure, 2023)
Streamflow forecasting is important for managing water resources in sectors like agriculture, hydropower, drought management, and urban flood prevention planning. Our study examines short and long lead-times to create a framework for streamflow forecasting that can benefit water resource management and related sectors. To improve streamflow forecasts for up to ten days of lead-time, the study first focuses on improving initial conditions using an ensemble Kalman filter as a data assimilation method. The goal is to regulate the hyperparameters of the ensemble Kalman filter for each season to produce more accurate forecasts. A sensitivity analysis is conducted to identify the best hyperparameter sets for each season, including uncertainty in temperature, precipitation, observed streamflow, and the water content of three state variables - vadose zone, saturated zone, and snowpack - from the CEQUEAU model. Results indicate that improving initial conditions with the ensemble Kalman filter produces more skillful forecasts until a 6-day leadtime. Temperature uncertainty is particularly sensitive and varies across seasons. The vadose zone state variable was identified as the most important and sensitive state variable, and updating all state variables systematically may not be necessary for improving forecast skill. Recent machine learning advances are improving short-term streamflow forecasting. One such method is the Long Short-Term Memory (LSTM) model. In general, neural networks learn from regression as relationships exist between input-output. However, LSTM models have a feature named ‘forget gate’, which enables them to learn the relationship between inputs (e.g., temperature and precipitation) and output (streamflow), and also to capture temporal dependencies in the data. The study aimed to compare the performance of the Long ShortTerm Memory (LSTM) model with data assimilation-based and process-based hydrological models in short-term streamflow forecasting. All three models were tested using the same ensemble weather forecasts. The LSTM model demonstrated good performance in forecasting streamflow, with a Kling-Gupta efficiency (KGE) greater than 0.88 for 9 lead-times. The LSTM model did not incorporate data assimilation, but it benefited from observed streamflow until the last day before the forecast. This is because the LSTM model learned and incorporated knowledge from the previous days while issuing forecasts, similar to how data assimilation updates initial conditions. The study results also showed that the LSTM model had better performance up to day 6 of lead-time compared to the data assimilation-based models. However, training the LSTM model separately for each lead-time is a time-consuming process and is a disadvantage compared to the data assimilation-based methods. Nonetheless, the study demonstrated the potential of machine learning techniques in improving streamflow forecasting. The forecasting of streamflow for long lead-times such as a month usually involves the use of historical meteorological data to create probable future scenarios, as meteorological forecasts become unreliable beyond this lead-time. In this study, we proposed a novel method for streamflow forecasting based on ensemble streamflow forecasting (ESP) filtering, using a Genetic Algorithm (GA) to filter forecast scenarios. This method quantifies the potential of historical data for each basin. This potential could be utilized to enhance the accuracy of streamflow forecasts. We sorted the selected and unselected scenarios to find out the common features between them, but the results did not help distinguish between the two groups. Nonetheless, the GA method can be used as a benchmark for future studies to improve longterm streamflow forecasting. This method can also be used to compare different forecast methods based on the potential shown by the GA method for a specific size of ESP members. For instance, if a method uses large-scale climate signals to filter ESP members, the forecast skill result could be compared with the potential of historical data for that particular size of ESP members.

Using a stochastic weather generator to account for climate non-stationarity in extended streamflow forecasts - Sohrabi Molla Yousef, Samaneh (École de technologie supérieure, 2020)
Reliable long-term streamflow forecast is essential in water resources management and plays a key role in reservoir management and hydropower generation. Properly framing the uncertainty is the key issue in providing a reliable long-term streamflow forecast, and probabilistic forecasts have been used to this effect. In a probabilistic approach, each observed historical data is taken as a possible realization of the future. Non stationarity of hydrometeorological variables, either due to the climate internal variability or anthropogenic change, is another important problem for long-term streamflow forecasts as it is becoming increasingly clearer that past historical data may not adequately represent the current climate. Therefore, there is a need to develop flexible approaches taking into account non-stationarity for long-term streamflow forecasts. Resampling past historical time series is the main approach used for probabilistic long term streamflow forecasts. However, non-stationarity is a key issue of resampling approaches. One possible approach is to make use of a stochastic weather generator coupled to a hydrological model to generate long-term probabilistic streamflow forecasts. Weather generators can easily be modified to account for climatic trends and therefore have the potential to take non-stationarity into account. However, before weather generators can be modified to account for climate non-stationarity, it is first necessary to evaluate whether the modeling chain consisting of a stochastic weather generator and a hydrological model can generate probabilistic streamflow forecasts with a performance similar to that of more traditional resampling approaches. The first objective of this study is therefore, to compare the performance of a stochastic weather generator against that of resampling historical meteorological time series in order to produce ensemble streamflow forecasts. Results indicate that while there are differences between both methods, they nevertheless largely both perform similarly, thus showing that weather generators can be used as substitutes to resampling the historical past. Based on these results, two approaches for taking non-stationarity into account have been proposed. Both approaches are based on a climate-based perturbation of the stochastic weather generator parameters. The first approach explored a simple perturbation method in which the entire length of the historical record is used to quantify internal variability, while a subset of recent years is used to characterize mean climatic values for precipitation, minimum and maximum temperatures. Results show that the approach systematically improves long-term streamflow forecasts accuracy, and that results are dependent on the time window used to estimate current mean climatic estimates. The second approach conditioned the parameters of a stochastic weather generator on largescale climate indices. In this approach, the most important climate indices are identified by looking at yearly correlations between a set of 40 indices and precipitation and temperature. A linear model is then constructed to identify precipitation and temperature anomalies which are then used to induce perturbations in the stochastic weather generator. Five different time windows are defined to determine the optimal linear model. Results show that temperatures are significantly correlated with large-scale climate indices, whereas precipitation is only weakly related to the same indices. The length of the time window has a considerable impact on the prediction ability of the linear models. The precipitation models based on short-duration time windows performed better than those based on longer windows, while the reverse was found for the temperature models. Results show that the proposed method improves long-term streamflow forecasting, particularly around the spring flood.

Risk-based seismic safety assessment of concrete gravity dams with uncertainty quantification - Patra, Bikram Kesharee (Concordia University, 2024)
Dams are vital national assets that play a crucial role in water storage, hydroelectric power generation, and flood control. Globally, over 61,000 large dams have surpassed 50 years of service, and many show signs of deterioration. With over 300 dam failures recorded worldwide, the potential for catastrophic damage remains alarmingly high if these aging structures are not properly maintained and upgraded. Further, many of the existing dams were built upon outdated standards, and there is an increase in seismic hazards making it imperative to reevaluate their seismic performance to align with current safety standards. The need for improved dam safety measures is urgent, as dam owners, regulators, and policymakers grapple with the challenges of ensuring the structural integrity of aging dams in the face of growing risks. A key solution is shifting from traditional safety approaches to a modern, risk-based methodology, which addresses safety concerns more efficiently and economically. Various, global agencies have developed risk-based safety assessment guidelines; however, these often lack systematic implementation frameworks and sufficient reference studies, making them difficult for dam owners to adopt effectively. Furthermore, various uncertainties can impact the risk assessment and can complicate efforts to ensure dam safety. In this context, this research investigates uncertainties impacting seismic risk assessments for dams, including modeling choices, ground motion selection, aging, and material variability. Case studies of the Koyna Dam and Pine Flat Dam were used to evaluate these factors at each stage of performance evaluation: system response, fragility, and risk assessment. Key findings indicate that dam-foundation-reservoir (DFR) models incorporating acoustic elements exhibit less variability in system response, regardless of model complexity and solution procedure. Ground motion derived from the conditional mean spectrum (CMS) method yields better fragility estimates than the ASCE 7-16 standard, particularly for moderate to severe damage states. Additionally, aging and material variability significantly affect the dynamic characteristics of dams, with increased failure probabilities correlating with both age and return period. Based on these findings, the research proposes a comprehensive, systematic framework for risk-based seismic safety evaluation. This framework aligns with safety assessment objectives and ensures optimal use of computational resources.

Design and Implementation of an IoT Platform for Flood Prediction - Mehta, Meet Divyesh (Concordia University, 2023)
Flooding, a major natural calamity, severely threatens communities and infrastructures in areas susceptible to floods. Consequently, implementing an Internet of Things (IoT)-based flood monitoring system becomes crucial. Existing flood monitoring systems lack a comprehensive and scalable IoT platform to collect real-time data from diverse sensors efficiently, visualize flood information, and provide accurate water level forecasts. This thesis proposes a complete system designed to address the challenges associated with efficient data collection and flood monitoring from diverse IoT sensors. Our proposition involves creating and deploying a centralized system known as HYDROSIGHT, which facilitates the real-time gathering, monitoring, and visualization of flooding-related sensor data. HYDROSIGHT system also provides a log monitoring feature for effective debugging and troubleshooting. The IoT environment for flood monitoring and prediction system was designed to promote sustainability and autonomy by preferring sensors with minimal footprints and compatibility with solar panels. The system architecture leverages a 4G network for seamless data transmission. To validate the practical applicability of the proposed design,HYDROSIGHT system was tested at two municipalities of Quebec, namely Terrebonne, and Lac-Supérieur. In addition, the platform was also deployed at the Ericsson facility in Montreal to test the 5G capabilities. The deployment in these locations allowed us to evaluate the performance and effectiveness of the HYDROSIGHT system in a real flood monitoring environment. In addition to implementing the IoT testbed, a preliminary machine learning tool was developed on water level forecasting. In this experiment, we opted for an online machine-learning approach, recognizing the significance of real-time updates and low computational resources of IoT devices. Leveraging the constantly updating data from HYDROSIGHT, we trained and tested our online machine-learning model, enhancing its forecasting capabilities. We conducted a comparative analysis to understand the advantages of online machine learning over traditional batch learning. This analysis involved examining the water level forecasting results obtained from both methods using time series data from the HYDROSIGHT system deployed at Lac-Supérieur in Quebec.

Développement d'un modèle numérique topographique et bathymétrique multisource du fleuve Saint-Laurent dans la région de la Communauté métropolitaine du Québec (CMQuébec) pour la modélisation hydrodynamique - Noman, Juzer (2023)
Les inondations sont une préoccupation majeure avec un potentiel de risques importants pour la sécurité publique ainsi qu'un impact économique et social négatif. Pour développer un modèle hydrodynamique permettant de cartographier et d'évaluer les risques d'inondation, un modèle d'élévation est un élément essentiel. La grande disponibilité de données de télédétection multisources facilite la création d'un modèle numérique d'élévation topo-bathymétrique (TBDEM). Cependant, il peut être très difficile de créer un modèle d'élévation à haute résolution homogène adapté à la cartographie des inondations en raison des divergences entre les données topographiques et bathymétriques causées par des changements temporels, des systèmes de référence horizontaux et verticaux différents, et des différences significatives en termes de résolution, incertitude et zone de couverture. Cette étude présente une méthodologie qui élargit les études précédentes axées sur la cartographie côtière à basse résolution en résolvant les différences spatiales et temporelles des jeux de données multisources tout en maintenant l'intégrité de la morphologie des berges et de l'environnement proche du rivage. Ceci est réalisé en appliquant une nouvelle méthodologie de fusion qui est mieux adaptée aux sources de données en jeu. Une méthode de moindre coût est appliquée aux données topographiques alors qu'une méthode de feathering est appliquée aux données bathymétriques. Pour ce qui est de la zone intermédiaire à l'interface de la terre et de l'eau, des transects sont utilisés pour interpoler entre les données manquantes afin de garantir l'intégrité du littoral. Enfin, une méthode de krigeage empirique bayésien appliqué à l'ensemble des données permet de produire une surface sans discontinuité accompagnée d'une surface d'erreur pour analyser l'incertitude en chaque point du modèle. Des données LiDAR aéroporté ainsi que des données de bathymétrie multifaisceau de la section supérieure du fleuve Saint-Laurent au Québec, Canada ont été combinées en utilisant la méthodologie proposée. Le TBDEM produit dans cette étude constitue une meilleure représentation que les modèles précédents et minimise l'erreur dans les données. La capacité de ce TBDEM à être plus performant que les modèles précédents dans les simulations hydrodynamiques sera testée dans des études futures en utilisant des événements de crue enregistrés précédemment.

The river meanders still: Curation as research-creation for an unknowable exhibition. - Pullen-Legassie, Treva (Concordia University, 2022)
The canalized southernmost section of Wonscotonach (the Don River) in Tkarón:to (Toronto), also known as The Narrows, is a highly disturbed urban natural landscape. Following the 1886 Don Improvement Project, the Keating Channel, and today the Port Lands Revitalization and Flood Protection Project, these Lands have been harnessed and developed through settler colonization to tame and control the once-winding river. This research-creation—in the form of a curated online exhibition and written thesis—presents a critical (re)reading of the notion of improvement, becoming allied to the pre-colonial landscape and the knowledge it carried. This exhibition and thesis develop the concept of the meander, inspired by the non-linear trajectory of the pre-canalized Don River, as a model for the curatorial. The curatorial process of improvement becomes a wall, and the river meanders still began before the global COVID-19 pandemic and, subsequently, was derailed in March 2020. The exhibition’s final form was unknowable throughout much of the curatorial process. Thus, following the meander as a research-creation technique, the curatorial process, exhibitionary structure, and content had to adapt through lingering uncertainty. This thesis, contributing to the theoretical and practical knowledge of research-creation, looks to intersections with the curatorial following the theoretical underpinnings of Erin Manning and Brian Massumi, Natalie Loveless and Stefanie Springgay and Sarah E. Truman. As a project untethered from institutional timelines and normative requirements to ‘know a project in advance,’ as well as the conventions of a physical exhibition, this research-creation manifested through process-led, creative and exploratory techniques (such as walking and drawing) and slowed pace allowed by the COVID-19 pandemic’s reframing of time. This research-creation exhibition and written thesis develop a responsive and resilient curatorial process deeply indebted to Land-based knowledge.

Integrated Modeling of Short-Term Flood Forecasting in the Ottawa River - Ousoukhman, Hamza (Polytechnique Montréal, 2021)
RÉSUMÉ: Les inondations sont considérées comme l'un des risques naturels les plus dangereux au monde. Plusieurs pays souffrent des conséquences néfastes des inondations. Au Canada, plusieurs provinces ont subi des inondations au cours du siècle dernier. Par exemple, la rivière des Outaouais a été confrontée à de nombreuses inondations comme en 2017 et 2019. La population d'Ottawa continue à augmenter d'une année à l'autre. C'est pour cela que nous avons choisi la rivière des Outaouais comme étude de cas pour ce projet dans le but de protéger la société contre les risques causés par les inondations. Les pays adoptent plusieurs solutions basées sur différentes méthodes afin de minimiser les dommages causés par les crues. La plupart des scientifiques s'accordent que la prévision des crues est la meilleure façon de limiter les conséquences des crues. Les systèmes de prévision des crues sont indispensables dans les pays fréquemment confrontés à des crues. Ils visent à fournir un long délai d'exécution et à fournir aux autorités et aux décideurs des informations suffisantes. Par conséquent, ils auront suffisamment de temps pour prendre les mesures adéquates pour sauver la vie de la population et limiter les catastrophes économiques dues aux inondations. ABSTRACT: Floods are one of the most catastrophic natural disasters in Canada and around the world that can cause loss of life and damages to properties and infrastructures. Saguenay flood (1996), southern Alberta flood (2013), and Ottawa floods (2017, 2019), are a few examples of Canadian floods with tremendous socio-economic impacts. Flood forecasting and predicting its characteristics (e.g., its magnitude and extent) has an important role in preventing and mitigating such flood impacts. Particularly, short-term forecasting is crucial for early warning systems and emergency response to floods. This study presents an integrated hydraulic-hydrologic modeling system for flood prediction. In this system, the Delft3D two-dimensional hydrodynamic model is connected with a HEC-HMS hydrologic model and observation data to provide an automatic exchange of data and results. Delft3D and HEC-HMS were chosen for this study because they were widely used and provided good results. In addition, they were applied in several flood forecasting studies. The prediction weather data and watershed characteristics provide input to the hydrological model to predict streamflow conditions, which are then automatically fed into the hydrodynamic model. The hydrodynamic model simulates the flood characteristics such as water level, 2D depth-averaged velocity field, and flood extent.

Assessing the influence of the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation on discharge variability in western North America - Noel, Duane D. (Concordia University, 2021)
The frequency of natural hazards in North America presents a significant challenge for governments due to the damages they cause to the environment. Floods are severe hydrological events caused by spring snowmelt and intense rain events. Flood frequency analysis studies assumes that annual peak flood events occur independently of each other, regardless of previous flood events (the independent and identically distributed (i.i.d.) assumption); however, annual peak flood records do not necessarily appear to conform to these assumptions. First, a review of the literature on the effects of climate oscillations on extreme flood frequencies in North America was conducted. Then, the i.i.d. flood event assumption was tested by analyzing the effects of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) on 250 naturally flowing annual peak flood records across the entire western North American margin. Using permutation tests on quantile-quantile (Q-Q) plots, I found that the PDO has a greater impact on the magnitude of annual peak floods than the AMO. Twenty-six percent of the gauges have higher magnitude annual floods depending on the PDO phase (p < 0.1). Next, I examined the interacting effects of the PDO and AMO on the frequencies of lower and upper quartile annual peak floods, and found reinforcing, cancelling, and dominating effects. Since these two climate oscillations have significant effects on the magnitudes of annual peak floods, the i.i.d. assumption does not hold. Hence, I advocate for the need to re-assess baseline flood analysis in western North America to improve flood management strategies.

Assessing the coupled impact of hydrological model structures and snow observations on spring season flow forecasts through data assimilation - Farhoodi, Sepehr (2024)
Abstract: Accurate spring flow forecasts, primarily driven by snow accumulation and melt processes, are essential for decision-makers aiming to optimize hydro-electricity production and mitigate potential flood damages in snow-dominated regions. By integrating snowpack data from diverse sources (in-situ, remote sensing, and reanalysis) with modeled snow-related state variables through Data Assimilation (DA), there is the potential to leverage both modeling and observations for more accurate estimation of the resulting spring flow. However, challenges such as the lack of sufficient snow station networks and issues with optical and microwave sensors to provide Snow Water Equivalent (SWE) can hinder progress, particularly in regions with heterogeneous snowpack characteristics. Overcoming these challenges is crucial to realizing the full potential of snow DA in advancing spring flow forecasts. This thesis aims to optimize spring flow forecasting effectiveness using snow DA, where snow-related observations are incorporated into hydrological models. It investigates the best hydrological model structure (a lumped model: HSAMI, and a distributed model: HYDROTEL) for leveraging distributed SWE data provided by SNODAS (SNOw Data Assimilation System) dataset, which serves as the observation. This DA framework is applied on a large, heterogeneous northern Québec watershed (Outardes 4). It does so by updating SWE model states of HYDROTEL and HSAMI using the Ensemble Kalman Filter (EnKF) DA method. The simulated spring flow are then compared to observed spring flow data. Another scope of the thesis is to compare two reanalysis products with varying spatial resolutions and SWE representations (SNODAS and ERA5-Land) for improving 1-day spring flow forecasts in HYDROTEL over a smaller southern Québec watershed (Au Saumon). Finally, the thesis assesses the forecasting skill of the optimal model-observation combination over an extended 30-day forecast horizon using various probabilistic and deterministic metrics. The forecasting skills are evaluated in terms of SWE estimations during the snowpack accumulation and melt periods, and their impacts on spring flow. Among the two hydrological models considered (i.e., HYDROTEL and HSAMI), HYDROTEL proves to be a better candidate to unlock the full potential of distributed SNODAS SWE dataset through DA over a large watershed with spatially variable SWE. This is seen by improved 1-day spring flow forecasts metrics over many years (2014-2017). From the observation source point of view, SNODAS DA results in a more consistent 1-day spring flow forecasts compared to ERA5-Land over Au Saumon. However, the improvements in 1-day spring flow forecasts induced by SNODAS DA are comparatively modest over Au Saumon compared to Outardes 4, with NSE changing from 0.44 to 0.45, 0.31 to 0.34, and 0.59 to 0.61 for the 2014-2017 time period. This could be rooted in alignments between the physiographic characteristics of the watershed and the frequency of DA updates. The results obtained from the first two chapters of the thesis provide a snow DA framework with the capability to improve short-term and mid-term SWE forecasts with varying influence over the forecast horizon given the snowpack period considered (i.e., formation and ablation). The improved SWE estimations lead to increased accuracy and better uncertainty representations, as measured by Nash-Sutcliffe Efficiency (NSE), Relative Bias (RB), and Continuous Ranked Probability Score (CRPS), in spring flow forecasts for the Outardes 4 watershed over the study period (2014-2017).
Accepted: 2024-08-29T17:36:39Z Publisher: Université de Sherbrooke

Deep learning methods for high-dimensional fluid dynamics problems : application to flood modeling with uncertainty quantification - Jacquier, Pierre (École de technologie supérieure, 2020)
While impressive results have been achieved in the well-known fields where Deep Learning allowed for breakthroughs such as computer vision, its impact on different older areas is still vastly unexplored. In Computational Fluid Dynamics and especially in Flood Modeling, many phenomena are very high-dimensional, and predictions require the use of numerical simulations, which can be, while very robust and tested, computationally heavy and may not prove useful in the context of real-time predictions. This issue led to various attempts at developing Reduced-Order Modeling techniques, both intrusive and non-intrusive. One recent relevant addition is a combination of Proper Orthogonal Decomposition with Deep Neural Networks (POD-NN). Yet, to our knowledge, little has been performed in implementing uncertainty-aware regression tools in the example of the POD-NN framework. In this work, we aim at comparing different novel methods addressing uncertainty quantification in Neural Networks, pushing forward the POD-NN concept with Deep Ensembles and Bayesian Neural Networks, which we first test on benchmark problems, and then apply to a real-life application: flooding predictions in the Mille-Iles river in Laval, QC, Canada. Building a non-intrusive surrogate model, able to know when it doesn’t know, is still an open research area as far as neural networks are concerned.

Investigating the modelling uncertainties associated with the generation of flood projections - Castaneda-Gonzalez, Mariana (École de technologie supérieure, 2022)
Extreme flood events continue to be one of the most threatening natural disasters around the world due to their pronounced social, environmental and economic impacts. Changes in the magnitude and frequency of floods have been documented during the last years, and it is expected that a changing climate will continue to affect their occurrence. Therefore, understanding the impacts of climate change through hydroclimatic simulations has become essential to prepare adaptation strategies for the future. However, the confidence in flood projections is still low due to the considerable uncertainties associated with their simulations, and the complexity of local features influencing these events. The main objective of this doctoral thesis is thus to improve our understanding of the modelling uncertainties associated with the generation of flood projections as well as evaluating strategies to reduce these uncertainties to increase our confidence in flood simulations. To address the main objective, this project aimed at (1) quantifying the uncertainty contributions of different elements involved in the modelling chain used to produce flood projections and, (2) evaluating the effects of different strategies to reduce the uncertainties associated with climate and hydrological models in regions with diverse hydroclimatic conditions. A total of 96 basins located in Quebec (basins dominated by snow-related processes) and Mexico (basins dominated by rain-related processes), covering a wide range of climatic and hydrological regimes were included in the study. The first stage consisted in decomposing the uncertainty contributions of four main uncertainty sources involved in the generation of flood projections: (1) climate models, (2) post-processing methods, (3) hydrological models, and (4) probability distributions used in flood frequency analyses. A variance decomposition method allowed quantifying and ranking the influence of each uncertainty source on floods over the two regions studied and by seasons. The results showed that the uncertainty contributions of each source vary over the different regions and seasons. Regions and seasons dominated by rain showed climate models as the main uncertainty source, while those dominated by snowmelt showed hydrological models as the main uncertainty contributor. These findings not only show the dangers of relying on single climate and hydrological models, but also underline the importance of regional uncertainty analyses. The second stage of this research project focused in evaluating strategies to reduce the uncertainties arising from hydrological models on flood projections. This stage includes two steps: (1) the analysis of the reliability of hydrological model’s calibration under a changing climate and (2) the evaluation of the effects of weighting hydrological simulations on flood projections. To address the first part, different calibration strategies were tested and evaluated using five conceptual lumped hydrological models under contrasting climate conditions with datasets lengths varying from 2 up to 21 years. The results revealed that the climatic conditions of the calibration data have larger impacts on hydrological model’s performance than the lengths of the climate time series. Moreover, changes on precipitation generally showed greater impacts than changes in temperature across all the different basins. These results suggest that shorter calibration and validation periods that are more representative of possible changes in climatic conditions could be more appropriate for climate change impact studies. Following these findings, the effects of different weighting strategies based on the robustness of hydrological models (in contrasting climatic conditions) were assessed on flood projections of the different studied basins. Weighting the five hydrological models based on their robustness showed some improvements over the traditional equal-weighting approach, particularly over warmer and drier conditions. Moreover, the results showed that the difference between these approaches was more pronounced over flood projections, as contrasting flood magnitudes and climate change signals were observed between both approaches. Additional analyses performed over four selected basins using a semi-distributed and more physically-based hydrological model suggested that this type of models might have an added value when simulating low-flows, and high flows on small basins (of about 500 km2). These results highlight once again the importance of working with ensembles of hydrological models and presents the potential impacts of weighting hydrological models on climate change impact studies. The final stage of this study focused on evaluating the impacts of weighting climate simulations on flood projections. The different weighting strategies tested showed that weighting climate simulations can improve the mean hydrograph representation compared to the traditional model “democracy” approach. This improvement was mainly observed with a weighting approach proposed in this thesis that evaluates the skill of the seasonal simulated streamflow against observations. The results also revealed that weighting climate simulations based on their performance can: (1) impact the floods magnitudes, (2) impact the climate change signals, and (3) reduce the uncertainty spreads of the resulting flood projection. These effects were particularly clear over rain-dominated basins, where climate modelling uncertainty plays a main role. These finding emphasize the need to reconsider the traditional climate model democracy approach, especially when studying processes with higher levels of climatic uncertainty. Finally, the implications of the obtained results were discussed. This section puts the main findings into perspective and identifies different ways forward to keep improving the understanding of climate change impacts in hydrology and increasing our confidence on flood projections that are essential to guide adaptation strategies for the future.

An urban political ecology of flood control and population relocation in Ouagadougou - Burkina Faso - Bamba, Madiara (Concordia University, 2022)
Globally, the number of people at risk from flooding has been increasing since 2000, with the population from the South being more vulnerable. Millions of households are displaced by disasters every year. In 2009, the city of Ouagadougou in Burkina Faso experienced its most disastrous flood ever recorded. As a response, the government designed a permanent relocation plan in Yagma, a village located outside the city of Ouagadougou. The relocation plan disrupted the livelihoods of the households that were affected by the flood, leading many of them to return and rebuild their houses in flood prone areas. This paper contributes to a body of literature analyzing the heritage of postcolonialism on the flood vulnerability on the poorer communities in Ouagadougou. Using a political ecology frame, the thesis attempts to understand how the government of Burkina Faso and flood victims understand land and belongings, and how that understanding shaped the relocation program. After interviewing flood victims and government officials, an analysis revealed that contrasting views are at work. A perspective based on technical calculations and a neo-colonialist vision of development, on the one hand, and a grounded perspective based on relationships to the land and each other, on the other.

Estimating flood impact on residential values (housing price) : the case of Laval (Canada), 1995-2007 - Abdelhalim, Maha (2020)
Cette thèse vise à améliorer notre compréhension du modèle hédonique et de son application sur les données des biens immobiliers afin d'étudier l'impact d'un événement / externalité / environnementale liée à la présence d'inondation sur la valeur des propriétés résidentielles. Étant donné que les données immobilières sont réparties dans l'espace et dans le temps, des "corrections" temporelles et spatiales sont nécessaires dans le processus de modélisation économétrique. La recherche prend appui sur l’équation de prix hédonique. L’analyse empirique recours également à l’estimateur de type différence de différences spatio-temporelles (STDID) afin d’étudier l’effet d’une inondation survenue en 1998 sur le prix des résidences dans la ville de Laval au Canada entre 1995-2007. Les résultats suggèrent que l’utilisation des informations sur les zones inondables dans le but d’évaluer l’impact des inondations sur les valeurs résidentielles n’est pas une approche nécessairement appropriée. Les conclusions suggèrent que la grande hétérogénéité des résultats notés dans la littérature n’est probablement pas étrangère à la façon de définir les résidences touchées par les inondations. Cela signifie que les recherches empiriques sur les effets des inondations sur la valeur immobilière mesurent en réalité la valeur liée à la perception du risque d'inondation et non l’effet réel de l'inondation. Les résultats suggèrent que les applications futures dans la littérature devront porter une attention particulière à la manière de définir les zones inondables et d’identifier les résidences réellement touchées.

Developing an ensemble machine learning framework for enhanced climate projections using CMIP6 data in the Middle East - Khosravi, Younes; Ouarda, Taha B.M.J.; Homayouni, Saeid (npj Climate and Atmospheric Science, 2025)
Abstract Climate change in the Middle East has intensified with rising temperatures, shifting rainfall patterns, and more frequent extreme events. This study introduces the Stacking-EML framework, which merges five machine learning models three meta-learners to predict maximum temperature, minimum temperature, and precipitation using CMIP6 data under SSP1-2.6, SSP2-4.5, and SSP5-8.5. The results indicate that Stacking-EML not only significantly improves prediction accuracy compared to individual models and traditional CMIP6 outputs but also enhances climate projections by integrating multiple ML models, offering more reliable, regionally refined forecasts. Findings show R² improvements to 0.99 for maximum temperature, 0.98 for minimum temperature, and 0.82 for precipitation. Under SSP5-8.5, summer temperatures in southern regions are expected to exceed 45 °C, exacerbating drought conditions due to reduced rainfall. Spatial analysis reveals that Saudi Arabia, Oman, Yemen, and Iran face the greatest heat and drought impacts, while Turkey and northern Iran may experience increased precipitation and flood risks.
Keywords: Infolettre; Infolettre_Mai_2025

Phosphorus retention and hydraulic performance in borrow sand-based wastewater soil treatment units in impermeable settings: Case study in Abitibi-Témiscamingue, Québec - Sheibani, Sorour; Nasrallah, Michelle; Courcelles, Benoît; Rosa, Eric; Maylal, Brahim; Claveau-Mallet, Dominique (Journal of Water Process Engineering, 2025)
Keywords: Infolettre; Infolettre_Mai_2025

Quantifying the mitigation effect of natural landscapes during an extraordinary flood: the prominent role of the Otter Creek wetlands to middlebury, Vermont, USA, during Tropical Storm Irene - Lachapelle, Simon; Rousseau, Alain N.; Blanchette, Marianne; Foulon, Etienne; Savary, Stéphane (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2025)
Keywords: Infolettre; Infolettre_Avril_2025

Quantitative assessment of hydrological multifunctionality of headwater wetlands - Wu, Yanfeng; Ni, Bingbo; Xue, Zhenshan; Dong, Liqin; Zhang, Kun; Rousseau, Alain N.; Zhang, Guangxin; Song, Kaishan (Journal of Hydrology, 2025)
Keywords: Infolettre; Infolettre_Avril_2025

Novel statistical analysis illustrates the importance of flow source for extreme variation in dissolved organic carbon in a eutrophic reservoir in the Great Plains - Baron, Anthony A. P.; Baulch, Helen M.; Nazemi, Ali; Whitfield, Colin J. (Hydrology and Earth System Sciences, 2025)
Abstract. Dissolved organic carbon (DOC) trends, predominantly showing long-term increases in concentration, have been observed across many regions of the Northern Hemisphere. Elevated DOC concentrations are a major concern for drinking water treatment plants, owing to the effects of disinfection byproduct formation, the risk of bacterial regrowth in water distribution systems, and treatment cost increases. Using a unique 30-year data set encompassing both extreme wet and dry conditions in a eutrophic drinking water reservoir in the Great Plains of North America, we investigate the effects of changing source-water and in-lake water chemistry on DOC. We employ novel wavelet coherence analyses to explore the coherence of changes in DOC with other environmental variables and apply a generalized additive model to understand predictor–DOC responses. We found that the DOC concentration was significantly coherent with (and lagging behind) flow from a large upstream mesotrophic reservoir at long (> 18-month) timescales. DOC was also coherent with (lagging behind) sulfate and in phase with total phosphorus, ammonium, and chlorophyll a concentrations at short (≤ 18-month) timescales across the 30-year record. These variables accounted for 56 % of the deviance in DOC from 1990 to 2019, suggesting that water-source and in-lake nutrient and solute chemistry are effective predictors of the DOC concentration. Clearly, climate and changes in water and catchment management will influence source-water quality in this already water-scarce region. Our results highlight the importance of flow management to shallow eutrophic reservoirs; wet periods can exacerbate water quality issues, and these effects can be compounded by reducing inflows from systems with lower DOC. These flow management decisions address water level and flood risk concerns but also have important impacts on drinking water treatability.
Keywords: Infolettre; Infolettre_Avril_2025

Vegetation and channel adjustment trajectories in cold regions: The effects of ice disturbances in two Gaspesian rivers - Prugne, Matthieu; Corenblit, Dov; Boivin, Maxime; Buffin‐Bélanger, Thomas (Earth Surface Processes and Landforms, 2025)
Abstract Fluvial biogeomorphology has proven to be efficient in understanding the evolution of rivers in terms of vegetation succession and channel adjustment. The role of floods as the primary disturbance regime factor has been widely studied, and our knowledge of their effects on vegetation and channel adjustment has grown significantly in the last two decades. However, cold rivers experiencing ice dynamics (e.g., ice jams and mechanical breakups) as an additional disturbance regime have not yet been studied within a biogeomorphological scope. This study investigated the long‐term effects of ice dynamics on channel adjustments and vegetation trajectories in two rivers with different geomorphological behaviours, one laterally confined (Matapédia River) and one mobile (Petite‐Cascapédia River), in Quebec, Canada. Using dendrochronological analysis, historical data and aerial photographs from 1963 to 2016, this study reconstructed ice jam chronologies, characterized flood regimes and analysed vegetation and channel changes through a photointerpretation approach. The main findings of this study indicate that geomorphological impacts of mechanical ice breakups are not significant at the decadal and reach scales and that they might not be the primary factors of long‐term geomorphological control. However, results have shown that vegetation was more sensitive to ice dynamics. Reaches presenting frequent ice jams depicted high regression rates and turnovers even during years with very low floods, suggesting that ice dynamics significantly increase shear stress on plant patches. This study also highlights the high resiliency of both rivers to ice jam disturbances, with vegetation communities and channel forms recovering within a decade. With the uncertainties following the reach/corridor and decadal scales, future research should focus on long‐term monitoring and refined spatial scales to better understand the mechanisms behind the complex interactions among ice dynamics, vegetation and hydrogeomorphological processes in cold rivers.
Keywords: Infolettre; Infolettre_Avril_2025

Economic Exposure of Canadian Residential Properties to Flooding - Morin, Gabriel; Boudreault, Mathieu; Thistlethwaite, Jason; Bourdeau‐Brien, Michael; Chenette, Jacob; Henstra, Daniel; Raikes, Jonathan (Journal of Flood Risk Management, 2025)
ABSTRACT Flood risk management (FRM) involves planning proactively for flooding in high‐risk areas to reduce its impacts on people and property. A key challenge for governments pursuing FRM is to pinpoint assets that are highly economically exposed and vulnerable to flood hazards in order to prioritize them in policy and planning. This paper presents a novel flood risk assessment, making use of a dataset that identifies the location, dwelling type, property characteristics, and potential economic losses of Canadian residential properties. The findings reveal that the average annual costs are $1.4B, but most of the risks are concentrated in high‐risk areas. Data gaps are uncovered that justify replication through local validation studies. The results provide a novel evidence base for specific reforms in Canada's approach to FRM, with a focus on insurance that improves both implementation and effectiveness.
Keywords: Infolettre; Infolettre_Mars_2025

Limits of Blue and Green Infrastructures to Adapt Actual Urban Drainage Systems to the Impact of Climate Change - Benoit, Thomas; Martel, Jean-Luc; Bilodeau, Émilie; Brissette, François; Charron, Alain; Brulé, Dominic; Rivard, Gilles; Deslauriers, Simon (Journal of Irrigation and Drainage Engineering, 2025)
Keywords: Infolettre; Infolettre_Mars_2025

Assessing hydrological erosion estimation using the Revised Universal Soil Loss Equation (RUSLE) model in Google Earth Engine: a case study of Medjerda River Catchment, Tunisia - Cherif, Mouna; Saidi, Salwa; Ezzine, Ahmed; Darragi, Fadila; Homayouni, Saeid (Euro-Mediterranean Journal for Environmental Integration, 2025)
Keywords: Infolettre; Infolettre_Mars_2025

Flooding: Contributing factors to residential flood damage in Canada - Deschamps, Bernard; Boudreault, Mathieu; Gachon, Philippe (International Journal of Disaster Risk Reduction, 2025)
Keywords: Gachon_Philippe; Infolettre; Infolettre_Avril_2025; Infolettre_Mars_2025

Multi-sensor remote sensing to map glacier debris cover in the Greater Caucasus, Georgia - Holobâcă, Iulian-Horia; Tielidze, Levan G.; Ivan, Kinga; Elizbarashvili, Mariam; Alexe, Mircea; Germain, Daniel; Petrescu, Sorin Hadrian; Pop, Olimpiu Traian; Gaprindashvili, George (Journal of Glaciology, 2021)
Abstract Global warming is causing glaciers in the Caucasus Mountains and around the world to lose mass at an accelerated pace. As a result of this rapid retreat, significant parts of the glacierized surface area can be covered with debris deposits, often making them indistinguishable from the surrounding land surface by optical remote-sensing systems. Here, we present the DebCovG-carto toolbox to delineate debris-covered and debris-free glacier surfaces from non-glacierized regions. The algorithm uses synthetic aperture radar-derived coherence images and the normalized difference snow index applied to optical satellite data. Validating the remotely-sensed boundaries of Ushba and Chalaati glaciers using field GPS data demonstrates that the use of pairs of Sentinel-1 images (2019) from identical ascending and descending orbits can substantially improve debris-covered glacier surface detection. The DebCovG-carto toolbox leverages multiple orbits to automate the mapping of debris-covered glacier surfaces. This new automatic method offers the possibility of quickly correcting glacier mapping errors caused by the presence of debris and makes automatic mapping of glacierized surfaces considerably faster than the use of other subjective methods.

Empirical Rainfall Thresholds for Landslide Occurrence in Serra do Mar, Angra dos Reis, Brazil - Germain, Daniel; Roy, Sébastien; Jose Teixera Guerra, Antonio (Landslides, 2022)
In the tropical environment such as Brazil, the frequency of rainfall-induced landslides is particularly high because of the rugged terrain, heavy rainfall, increasing urbanization, and the orographic effect of mountain ranges. Since such landslides repeatedly interfere with human activities and infrastructures, improved knowledge related to spatial and temporal prediction of the phenomenon is of interest for risk management. This study is an analysis of empirical rainfall thresholds, which aims to establish local and regional scale correlations between rainfall and the triggering of landslides in Angra dos Reis in the State of Rio de Janeiro. A statistical analysis combining quantile regression and binary logistic regression was performed on 1640 and 526 landslides triggered by daily rainfall over a 6-year period in the municipality and the urban center of Angra dos Reis, in order to establish probabilistic rainfall duration thresholds and assess the role of antecedent rainfall. The results show that the frequency of landslides is highly correlated with rainfall events, and surprisingly the thresholds in dry season are lower than those in wet season. The aspect of the slopes also seems to play an important role as demonstrated by the different thresholds between the southern and northern regions. Finally, the results presented in this study provide new insight into the spatial and temporal dynamics of landslides and rainfall conditions leading to their activation in this tropical and mountainous environment.

Snow-avalanche hazard assessment based on dendrogeomorphic reconstructions and classification tree algorithms for ski area development, Parâng Mountains, Romania - Germain, Daniel; Pop, Olimpiu Traian; Gratton, Mathieu; Holobâcă, Iulian-Horea; Burada, Cristina (Cold Regions Science and Technology, 2022)

Disaster Risk Resilience: Conceptual Evolution, Key Issues, and Opportunities - Graveline, Marie-Hélène; Germain, Daniel (International Journal of Disaster Risk Science, 2022)
Abstract Resilience has become a cornerstone for risk management and disaster reduction. However, it has evolved extensively both etymologically and conceptually in time and across scientific disciplines. The concept has been (re)shaped by the evolution of research and practice efforts. Considered the opposite of vulnerability for a long time, resilience was first defined as the ability to resist, bounce back, cope with, and recover quickly from the impacts of hazards. To avoid the possible return to conditions of vulnerability and exposure to hazards, the notions of post-disaster development, transformation, and adaptation (build back better) and anticipation, innovation, and proactivity (bounce forward) were then integrated. Today, resilience is characterized by a multitude of components and several classifications. We present a selection of 25 components used to define resilience, and an interesting linkage emerges between these components and the dimensions of risk management (prevention, preparedness, response, and recovery), offering a perspective to strengthen resilience through the development of capacities. Despite its potential, resilience is subject to challenges regarding its operationalization, effectiveness, measurement, credibility, equity, and even its nature. Nevertheless, it offers applicability and opportunities for local communities as well as an interdisciplinary look at global challenges.

Environmental drivers of paraglacial time duration and intensity for scree slopes dynamics in forested environments - Germain, Daniel; Stabile‐Caillé, Ludwig (Earth Surface Processes and Landforms, 2023)
Abstract The highly fissile lithology of the rockwalls and the diversity of mass‐wasting processes provide a specific character to the active talus slopes of the northern Gaspé Peninsula since deglaciation. At a regional scale, the geology of the rockwalls, the patterns and modalities of deglaciation and the evolution towards a cold temperate morphoclimatic regime in a maritime context still influence the geomorphological dynamics of scree slopes today. At a local scale, the south–north orientation of the main coastal valleys influences insolation and exposure to prevailing winds, which in turn influence the snow cover regime and the occurrence of freeze–thaw cycles. The statistical analyses carried out from the mapping of 43 talus slopes and their geometric variables allowed the identification of significant environmental factors for the characterization of the dominant geomorphic processes: snow avalanches, frost‐coasted clast flows, debris flows and rockfalls. Slope aspect appears to be a key parameter in the nature of the processes acting on the talus slopes. East‐ and north‐facing talus slopes are generally covered by a significant snowpack in winter and the dominant processes are snow avalanches and debris flows. West‐ and south‐facing talus slopes face prevailing winds and insolation and are subject to frost‐coated clast flows, the main driver for forest regression, and rockfalls. However, the evolution of scree slopes in forested environments remains extremely complex due to the multiscale components that affect their evolution in the short, medium and long term.

An overcooled coarse‐grained talus slope at low elevation: New insights on air circulation and environmental impacts, Cannon Cliff, New Hampshire, USA - Germain, Daniel; Milot, Jean‐François (Earth Surface Processes and Landforms, 2024)
Abstract Overcooled talus slopes are generally described as islands of sporadic permafrost below the lower alpine limit of permafrost. The negative thermal anomaly of the ground is mainly consecutive to the internal ventilation of the deposit, but it is also conditioned by multiple factors as topography, slope aspect and incline, openwork structure and coarseness of the deposit, air temperature, solar radiation and wind regime. Therefore, the study of the spatiotemporal dynamics of ventilation processes allows a better understanding of the phenomenon. At Cannon Cliff, New Hampshire (USA), several field visits and environmental monitoring allowed us to describe the varying nature and significance of the ventilation mechanisms that can be observed at the ground surface and associated with both the intensity and direction of the airflows in a talus debris accumulation/protalus rampart system. The thermal negative anomalies are strong enough to lower the ground temperature to the point of preserving ice during the late spring and summer seasons. The monitoring of the gradient between external (air) and internal (talus) temperatures coupled with several dendroecological and geomorphological analyses provided a complete environmental picture of the impacts, feedback and extent of the phenomenon.

Farmers Perceptions of Climate Change Issues in Tetritskaro Municipality, Georgia - Elizbarashvili, Mariam; Kvirkvelia, Bela; Chikhradze, Nino; Germaın, Daniel; Pal, Jeremy; Khuntselia, Tamar (Selcuk Journal of Agricultural and Food Sciences, 2024)
Agriculture is the traditional and leading field of economy of Tetritskaro Municipality, but faces the challenge of changing climate. The study investigates male and female farmers’ perception of climate change issues in Tetritskaro, their main source of information, adaptation measures choosen and their needs. Climate change data available in Tetritskaro focused on characteristic extreme weather events coupled with face-to-face interviews from 254 farmers (male - 53%, female - 47%) was analyzed. The study revealed that men and women have more or less similar perceptions of climate change issues. For male farmers, the main source of information on climate, seasonal prediction and weather forecast is conversations with fellow farmers, and for female farmers it is indigenous knowledge of the local environment. Male and female farmers, have adapted to the changes in climate similarly applying measures such as pesticides, fertilizer and irrigation, early sowing, and earlier harvest, while the exchange of information between fellow farmers, use of various hail protection products and crop diversification techniques is more frequent among male farmers. Farmers expressed the need for low interest loans to purchase agricultural products, equipment and restore/create windbreak zones. Most of the male farmers indicate the need for introduction new technologies, while female farmers are more in need of information and training in agricultural activities. The study shows the need for development of climate change adaptation policies and interventions in Tetritskaro. Obtained results can be used not only in other agricultural regions of Georgia, but in other countries with the same problems. , Agriculture is the traditional and leading field of economy of Tetritskaro Municipality, but faces the challenge of changing climate. The study investigates male and female farmers’ perception of climate change issues in Tetritskaro, their main source of information, adaptation measures choosen and their needs. Climate change data available in Tetritskaro focused on characteristic extreme weather events coupled with face-to-face interviews from 254 farmers (male - 53%, female - 47%) was analyzed. The study revealed that men and women have more or less similar perceptions of climate change issues. For male farmers, the main source of information on climate, seasonal prediction and weather forecast is conversations with fellow farmers, and for female farmers it is indigenous knowledge of the local environment. Male and female farmers, have adapted to the changes in climate similarly applying measures such as pesticides, fertilizer and irrigation, early sowing, and earlier harvest, while the exchange of information between fellow farmers, use of various hail protection products and crop diversification techniques is more frequent among male farmers. Farmers expressed the need for low interest loans to purchase agricultural products, equipment and restore/create windbreak zones. Most of the male farmers indicate the need for introduction new technologies, while female farmers are more in need of information and training in agricultural activities. The study shows the need for development of climate change adaptation policies and interventions in Tetritskaro. Obtained results can be used not only in other agricultural regions of Georgia, but in other countries with the same problems.

Hidden engineers of the earth: Investigating the geomorphic impacts of small fossorial rodents in the Vaud Pre-Alps, Switzerland - Germain, Daniel (CATENA, 2025)

A novel statistical model for flood prediction in the Eel River watershed, New Brunswick, Canada - Faghfouri, Ali; Hentati, Achraf; Fortin, Guillaume; Germain, Daniel (Water Science, 2023)

Drone-based ground-penetrating radar (GPR) application to snow hydrology - Valence, Eole; Baraer, Michel; Rosa, Eric; Barbecot, Florent; Monty, Chloe (The Cryosphere, 2022)
Seasonal snowpack deeply influences the distribution of meltwater among watercourses and groundwater. During rain-on-snow (ROS) events, the structure and properties of the different snow and ice layers dictate the quantity and timing of water flowing out of the snowpack, increasing the risk of flooding and ice jams. With ongoing climate change, a better understanding of the processes and internal properties influencing snowpack outflows is needed to predict the hydrological consequences of winter melting episodes and increases in the frequency of ROS events. This study develops a multi-method approach to monitor the key snowpack properties in a non-mountainous environment in a repeated and non-destructive way. Snowpack evolution during the winter of 2020–2021 was evaluated using a drone-based, ground-penetrating radar (GPR) coupled with photogrammetry surveys conducted at the Ste-Marthe experimental watershed in Quebec, Canada. Drone-based surveys were performed over a 200 m2 area with a flat and a sloped section. In addition, time domain reflectometry (TDR) measurements were used to follow water flow through the snowpack and identify drivers of the changes in snowpack conditions, as observed in the drone-based surveys. The experimental watershed is equipped with state-of-the-art automatic weather stations that, together with weekly snow pit measurements over the ablation period, served as a reference for the multi-method monitoring approach. Drone surveys conducted on a weekly basis were used to generate georeferenced snow depth, density, snow water equivalent and bulk liquid water content maps. Despite some limitations, the results show that the combination of drone-based GPR, photogrammetric surveys and TDR is very promising for assessing the spatiotemporal evolution of the key hydrological characteristics of the snowpack. For instance, the tested method allowed for measuring marked differences in snow pack behaviour between the first and second weeks of the ablation period. A ROS event that occurred during the first week did not generate significant changes in snow pack density, liquid water content and water equivalent, while another one that happened in the second week of ablation generated changes in all three variables. After the second week of ablation, differences in density, liquid water content (LWC) and snow water equivalent (SWE) between the flat and the sloped sections of the study area were detected by the drone-based GPR measurements. Comparison between different events was made possible by the contact-free nature of the drone-based measurements.
Publisher: Copernicus GmbH
Keywords: Baraer_Michel; Infolettre; Infolettre_Octobre_2022; Site_internet_RIISQ

Comparing the performance of three methods to assess DOM dynamics within two distinct glacierized watersheds of the tropical Andes - Rodriguez-Avella, K.A.; Baraer, M.; Mark, B.; McKenzie, J.; Somers, L. (Environmental Pollution, 2020)
Keywords: Baraer_Michel

Proglacial icings as records of winter hydrological processes - Chesnokova, Anna; Baraër, Michel; Bouchard, Émilie (The Cryosphere, 2020)
Abstract. The ongoing warming of cold regions is affecting hydrological processes, causing deep changes, such as a ubiquitous increase in river winter discharges. The drivers of this increase are not yet fully identified mainly due to the lack of observations and field measurements in cold and remote environments. In order to provide new insights into the sources generating winter runoff, the present study explores the possibility of extracting information from icings that form over the winter and are often still present early in the summer. Primary sources detection was performed using time-lapse camera images of icings found in both proglacial fields and upper alpine meadows in June 2016 in two subarctic glacierized catchments in the upper part of the Duke watershed in the St. Elias Mountains, Yukon. As images alone are not sufficient to entirely cover a large and hydrologically complex area, we explore the possibility of compensating for that limit by using four supplementary methods based on natural tracers: (a) stable water isotopes, (b) water ionic content, (c) dissolved organic carbon, and (d) cryogenic precipitates. The interpretation of the combined results shows a complex hydrological system where multiple sources contribute to icing growth over the studied winter. Glaciers of all sizes, directly or through the aquifer, represent the major parent water source for icing formation in the studied proglacial areas. Groundwater-fed hillslope tributaries, possibly connected to suprapermafrost layers, make up the other detectable sources in icing remnants. If similar results are confirmed in other cold regions, they would together support a multi-causal hypothesis for a general increase in winter discharge in glacierized catchments. More generally, this study shows the potential of using icing formations as a new, barely explored source of information on cold region winter hydrological processes that can contribute to overcoming the paucity of observations in these regions.
Keywords: Baraer_Michel

Trace Metal Stream Contamination in a Post Peak Water Context: Lessons from the Cordillera Blanca, Peru - Guittard, Alexandre; Baraer, Michel; McKenzie, Jeffrey M.; Mark, Bryan G.; Rapre, Alejo C.; Bury, Jeffrey; Carey, Mark; Young, Kenneth R. (ACS Earth and Space Chemistry, 2020)
Keywords: Baraer_Michel

Linking Mountain Glacier Retreat and Hydrological Changes in Southwestern Yukon - Chesnokova, A.; Baraër, M.; Laperrière‐Robillard, T.; Huh, K. (Water Resources Research, 2020)
Abstract This study aims to isolate and quantify the role of shrinking glaciers in recent hydrological changes in eight watersheds in the southwestern Yukon (Canada) by using an original dual approach that consists of (i) watershed hydrological regime identification, followed by a trend analysis of discharge time series, and (ii) a model‐based peak water (PW) analysis using glacier cover change measurements. A distinction between hydrological regimes is a necessary add‐up to commonly used trend attribution methods as the lake runoff regime shares common characteristics with the glacier regime. Results show a link between shrinking glaciers and hydrological changes in the region, but the link is complex, and glacier retreat does not explain all the observed changes. Model outputs show that the two watersheds with a glacierized area exceeding 30% and one watershed with 2.9% glacierized area have not reached PW, whereas a 9.2% glacierized watershed and another watershed with 2.1% glacierized area have already passed it. These results suggest that glacierized area alone cannot explain short‐term changes related to watershed current position in terms of PW, and the rate of glacier retreat must be considered. By contrast, the actual rate of glacier retreat does not influence long‐term changes, such as the magnitude of PW and of the consequent drop in discharge. Once glaciers will have retreated to a point close to extinction, declines in summer discharge from 10% to 70% and proportional to the actual glacier cover are anticipated at watersheds that are currently more than 9% glacierized. , Plain Language Summary In this study, we aim to understand how shrinking glacier cover affects river discharges. In conditions of continuous retreat, glaciers produce an initial increase in runoff as they lose mass. The discharge then reaches a turning point, a plateau called peak water, and subsequently declines as the volume of glacial ice continues to decrease. When analyzing eight watersheds with different glacier covers in the southwestern Yukon, we found that two watersheds that are 30% covered by glaciers have not yet reached this plateau, and therefore, the discharge will continue to increase. Several watersheds with smaller glacierized portions have passed peak water, which means that the discharge will now continue to decrease. We were also able to estimate the magnitudes of these changes in discharge. We show that two watersheds with 30% glacierized area can still experience a 1.5‐ to 2‐fold increase in discharge and that watersheds currently more than 9% glacierized are predicted to show noticeable changes after peak water, with the possibility of discharge decreasing by a factor of 3 to 5 by the time glaciers have retreated to a point when their hydrological influence at the watershed scale becomes insignificant. , Key Points Noticeable acceleration of glacier retreat occurred in southwestern Yukon since 1999 with measured consequences for the regional hydrology Various hydrological changes have been detected at the study watersheds. Glacier retreat explains many but not all of those changes Long‐term hydrological changes are glacier cover dependent while decadal‐scale changes are driven by glacier retreat rate
Keywords: Baraer_Michel

Using ground-based thermal imagery to estimate debris thickness over glacial ice: fieldwork considerations to improve the effectiveness - Aubry-Wake, Caroline; Lamontagne-Hallé, Pierrick; Baraër, Michel; McKenzie, Jeffrey M.; Pomeroy, John W. (Journal of Glaciology, 2023)
Abstract Debris-covered glaciers are an important component of the mountain cryosphere and influence the hydrological contribution of glacierized basins to downstream rivers. This study examines the potential to make estimates of debris thickness, a critical variable to calculate the sub-debris melt, using ground-based thermal infrared radiometry (TIR) images. Over four days in August 2019, a ground-based, time-lapse TIR digital imaging radiometer recorded sequential thermal imagery of a debris-covered region of Peyto Glacier, Canadian Rockies, in conjunction with 44 manual excavations of debris thickness ranging from 10 to 110 cm, and concurrent meteorological observations. Inferring the correlation between measured debris thickness and TIR surface temperature as a base, the effectiveness of linear and exponential regression models for debris thickness estimation from surface temperature was explored. Optimal model performance ( R 2 of 0.7, RMSE of 10.3 cm) was obtained with a linear model applied to measurements taken on clear nights just before sunrise, but strong model performances were also obtained under complete cloud cover during daytime or nighttime with an exponential model. This work presents insights into the use of surface temperature and TIR observations to estimate debris thickness and gain knowledge of the state of debris-covered glacial ice and its potential hydrological contribution.
Keywords: Baraer_Michel

Effect of odor treatment systems on bioaerosol microbial concentration and diversity from wastewater treatment plants - Ouradou, A.; Veillette, M.; Bélanger Cayouette, A.; Corbin, S.; Boulanger, C.; Dorner, S.; Duchaine, C.; Bédard, E. (Science of The Total Environment, 2023)
Keywords: Dorner_Sarah

Impact of Hydrometeorological Events for the Selection of Parametric Models for Protozoan Pathogens in Drinking‐Water Sources - Sylvestre, Émile; Burnet, Jean‐Baptiste; Dorner, Sarah; Smeets, Patrick; Medema, Gertjan; Villion, Manuela; Hachad, Mounia; Prévost, Michèle (Risk Analysis, 2021)
Abstract Temporal variations in concentrations of pathogenic microorganisms in surface waters are well known to be influenced by hydrometeorological events. Reasonable methods for accounting for microbial peaks in the quantification of drinking water treatment requirements need to be addressed. Here, we applied a novel method for data collection and model validation to explicitly account for weather events (rainfall, snowmelt) when concentrations of pathogens are estimated in source water. Online in situ β ‐ d ‐glucuronidase activity measurements were used to trigger sequential grab sampling of source water to quantify Cryptosporidium and Giardia concentrations during rainfall and snowmelt events at an urban and an agricultural drinking water treatment plant in Quebec, Canada. We then evaluate if mixed Poisson distributions fitted to monthly sampling data ( = 30 samples) could accurately predict daily mean concentrations during these events. We found that using the gamma distribution underestimated high Cryptosporidium and Giardia concentrations measured with routine or event‐based monitoring. However, the log‐normal distribution accurately predicted these high concentrations. The selection of a log‐normal distribution in preference to a gamma distribution increased the annual mean concentration by less than 0.1‐log but increased the upper bound of the 95% credibility interval on the annual mean by about 0.5‐log. Therefore, considering parametric uncertainty in an exposure assessment is essential to account for microbial peaks in risk assessment.
Keywords: Dorner_Sarah

Changes in Escherichia coli to enteric protozoa ratios in rivers: Implications for risk-based assessment of drinking water treatment requirements - Sylvestre, Émile; Dorner, Sarah; Burnet, Jean-Baptiste; Smeets, Patrick; Medema, Gertjan; Cantin, Philippe; Villion, Manuela; Robert, Caroline; Ellis, Donald; Servais, Pierre; Prévost, Michèle (Water Research, 2021)
Keywords: Dorner_Sarah

Demonstrating the reduction of enteric viruses by drinking water treatment during snowmelt episodes in urban areas - Sylvestre, Émile; Prévost, Michèle; Burnet, Jean-Baptiste; Pang, Xiaoli; Qiu, Yuanyuan; Smeets, Patrick; Medema, Gertjan; Hachad, Mounia; Dorner, Sarah (Water Research X, 2021)
Keywords: Dorner_Sarah

Using surrogate data to assess risks associated with microbial peak events in source water at drinking water treatment plants - Sylvestre, Émile; Prévost, Michèle; Burnet, Jean-Baptiste; Smeets, Patrick; Medema, Gertjan; Hachad, Mounia; Dorner, Sarah (Water Research, 2021)
Keywords: Dorner_Sarah

Impact of vacuum UV on natural and algal organic matter from cyanobacterial impacted waters - Visentin, Flavia; Bhartia, Siddharth; Mohseni, Madjid; Peldszus, Sigrid; Dorner, Sarah; Barbeau, Benoit (Environmental Science: Water Research & Technology, 2020)
Cyanobacterial bloom events produce toxins and taste and odor issues, disturbing drinkable water quality. Vacuum UV (VUV) is a promising advanced oxidation process used to treat impacted water, with potential applicability in small and remote communities. , Cyanobacterial blooms are a growing concern around the world. A feasible approach for small treatment plants fed by sources contaminated with cyanobacteria is vacuum UV (VUV). VUV is a promising advanced oxidation process used to treat water impacted by cyanobacterial blooms, with potential applicability in small and remote communities because of its simplicity. In this work, water samples from three Canadian lakes periodically affected by cyanobacteria were used to assess the impact of natural and algal organic matter (NOM/AOM) on treatment with VUV. NOM and AOM were characterized before and after VUV treatment by size exclusion chromatography (SEC) and fluorescence emission–excitation matrix (FEEM). FEEM spectra were analyzed with the parallel factor analysis (PARAFAC) tool. As a result, we found seven principal components describing the whole dataset. Disinfection by-product (DBP) formation after VUV treatment was analyzed and trihalomethanes (THM) yield was calculated. THM yield increased by 15–20% after VUV treatment. Regarding DBP formation and NOM/AOM fractions from SEC, we found that humic substances are the most important fraction causing the increase in DBP formation with at least 3 times higher yield than the other fractions: biopolymers, building blocks, low weight molecular acids and neutrals.
Keywords: Dorner_Sarah

Evidence-based framework to use in situ phycocyanin readings for cyanobacterial risk assessment within drinking water treatment plants - Ma, Liya; Dorner, Sarah; Prévost, Michèle (Environmental Science: Water Research & Technology, 2024)
A framework is proposed using multi-stream phycocyanin probe readings to manage cyanobacterial risks at the source water and across the drinking water treatment processes. , In situ phycocyanin (PC) probes have been deployed as a cost-effective and efficient way to monitor cyanobacterial (CB) abundance in drinking water sources and to identify periods of potential risk at drinking water treatment plants (DWTPs). Monitoring CB removal efficacies in near real-time by sequentially using a single probe for multiple streams across the treatment plant provides a more useful assessment of CB risk breakthrough in treated water. Removal efficacies were measured in three DWTPs using integrated mass fluxes estimated from PC readings and grab sample total CB biovolume estimations in raw, clarified, filtered, and treated water. Selective CB species removal during the treatment processes was also evaluated. In addition, relationships between physio-chemical parameters (turbidity, pH, dissolved oxygen, conductivity, chlorophyll-a and temperature) and PC across the treatment processes were investigated. Finally, a framework to use in situ multi-stream PC monitoring, gathering data across the treatment chain, is proposed to manage risks of CB cells breakthrough in treated water. Estimates of 2 hour moving average PC metrics are proposed to provide short term alert in raw water and establish periods of treatment vulnerability or dysfunction, while daily mean PC values can be used to estimate total and process specific log removals to justify treatment adjustments. Benefits and limitations of the tested in situ probes for the application of alert levels are discussed, and key knowledge gaps for future research and guidance are identified.
Keywords: Dorner_Sarah

Comparative study of deterministic and probabilistic assessments of microbial risk associated with combined sewer overflows upstream of drinking water intakes - Kammoun, Raja; McQuaid, Natasha; Lessard, Vincent; Prévost, Michèle; Bichai, Françoise; Dorner, Sarah (Environmental Challenges, 2023)
Keywords: Dorner_Sarah

Monitoring of cyanobacterial breakthrough and accumulation by in situ phycocyanin probe system within full-scale treatment plants - Ma, Liya; Maldonado, Juan Francisco Guerra; Zamyadi, Arash; Dorner, Sarah; Prévost, Michèle (Environmental Monitoring and Assessment, 2023)
Abstract Worldwide, there has been an increase in the presence of potentially toxic cyanobacterial blooms in drinking water sources and within drinking water treatment plants (DWTPs). The objective of this study is to validate the use of in situ probes for the detection and management of cyanobacterial breakthrough in high and low-risk DWTPs. In situ phycocyanin YSI EXO2 probes were devised for remote control and data logging to monitor the cyanobacteria in raw, clarified, filtered, and treated water in three full-scale DWTPs. An additional probe was installed inside the sludge holding tank to measure the water quality of the surface of the sludge storage tank in a high-risk DWTP. Simultaneous grab samplings were carried out for taxonomic cell counts and toxin analysis. A total of 23, 9, and 4 field visits were conducted at the three DWTPs. Phycocyanin readings showed a 93-fold fluctuation within 24 h in the raw water of the high cyanobacterial risk plant, with higher phycocyanin levels during the afternoon period. These data provide new information on the limitations of weekly or daily grab sampling. Also, different moving averages for the phycocyanin probe readings can be used to improve the interpretation of phycocyanin signal trends. The in situ probe successfully detected high cyanobacterial biovolumes entering the clarification process in the high-risk plant. Grab sampling results revealed high cyanobacterial biovolumes in the sludge for both high and low-risk plants.
Keywords: Dorner_Sarah

Factors Affecting the Interpretation of Online Phycocyanin Fluorescence to Manage Cyanobacteria in Drinking Water Sources - Ma, Liya; Moradinejad, Saber; Guerra Maldonado, Juan Francisco; Zamyadi, Arash; Dorner, Sarah; Prévost, Michèle (Water, 2022)
Recently, in situ YSI EXO2 phycocyanin fluorescence probes have been widely deployed as a means to determine cyanobacterial abundance in drinking water sources, yet few studies have evaluated the effects of natural organic matter (NOM) and the ambient water temperature on the probe readings. In this study, Suwannee River NOM was added to laboratory cultivated cyanobacterial species to test the performance of the phycocyanin probe. The impact of temperature on phycocyanin fluorescence was evaluated by monitoring the laboratory cultivated cyanobacterial species and extracted phycocyanin pigment. Additionally, in situ phycocyanin fluorescence of the field samples from the water intake of a drinking water treatment plant (DWTP) in 2018 were compared with grab sample laboratory taxonomic analyses. We found: (1) the presence of Suwannee River NOM leads to the decrease in cell-bound cyanobacterial phycocyanin readings; (2) increasing ambient water temperature reduces dissolved and cell-bound cyanobacterial phycocyanin readings; (3) field study phycocyanin probe readings significantly correlated with the total cyanobacterial biovolume (R = 0.73, p < 0.1), and the relationship depends on the biovolume of dominant cyanobacterial species; (4) phycocyanin probe readings have a strong positive correlation with the natural light intensities; and (5) probe users should be fully aware of the sources of interferences when interpreting the results and apply the other physical-chemical parameters data simultaneously generated by the fluorometry to improve the probe’s measurements.
Keywords: Dorner_Sarah

Impact of Stagnation on the Diversity of Cyanobacteria in Drinking Water Treatment Plant Sludge - Jalili, Farhad; Trigui, Hana; Maldonado, Juan Francisco Guerra; Dorner, Sarah; Zamyadi, Arash; Shapiro, B. Jesse; Terrat, Yves; Fortin, Nathalie; Sauvé, Sébastien; Prévost, Michèle (Toxins, 2022)
Health-related concerns about cyanobacteria-laden sludge of drinking water treatment plants (DWTPs) have been raised in the past few years. Microscopic taxonomy, shotgun metagenomic sequencing, and microcystin (MC) measurement were applied to study the fate of cyanobacteria and cyanotoxins after controlled sludge storage (stagnation) in the dark in a full-scale drinking water treatment plant within 7 to 38 days. For four out of eight dates, cyanobacterial cell growth was observed by total taxonomic cell counts during sludge stagnation. The highest observed cell growth was 96% after 16 days of stagnation. Cell growth was dominated by potential MC producers such as Microcystis, Aphanocapsa, Chroococcus, and Dolichospermum. Shotgun metagenomic sequencing unveiled that stagnation stress shifts the cyanobacterial communities from the stress-sensitive Nostocales (e.g., Dolichospermum) order towards less compromised orders and potential MC producers such as Chroococcales (e.g., Microcystis) and Synechococcales (e.g., Synechococcus). The relative increase of cyanotoxin producers presents a health challenge when the supernatant of the stored sludge is recycled to the head of the DWTP or discharged into the source. These findings emphasize the importance of a strategy to manage cyanobacteria-laden sludge and suggest practical approaches should be adopted to control health/environmental impacts of cyanobacteria and cyanotoxins in sludge.
Keywords: Dorner_Sarah

Shotgun Metagenomic Sequencing to Assess Cyanobacterial Community Composition following Coagulation of Cyanobacterial Blooms - Le, Kim Thien Nguyen; Maldonado, Juan Francisco Guerra; Goitom, Eyerusalem; Trigui, Hana; Terrat, Yves; Nguyen, Thanh-Luan; Husk, Barry; Shapiro, B. Jesse; Sauvé, Sébastien; Prévost, Michèle; Dorner, Sarah (Toxins, 2022)
The excessive proliferation of cyanobacteria in surface waters is a widespread problem worldwide, leading to the contamination of drinking water sources. Short- and long-term solutions for managing cyanobacterial blooms are needed for drinking water supplies. The goal of this research was to investigate the cyanobacteria community composition using shotgun metagenomics in a short term, in situ mesocosm experiment of two lakes following their coagulation with ferric sulfate (Fe2(SO4)3) as an option for source water treatment. Among the nutrient paramenters, dissolved nitrogen was related to Microcystis in both Missisquoi Bay and Petit Lac St. François, while the presence of Synechococcus was related to total nitrogen, dissolved nitrogen, dissolved organic carbon, and dissolved phosphorus. Results from the shotgun metagenomic sequencing showed that Dolichospermum and Microcystis were the dominant genera in all of the mesocosms in the beginning of the sampling period in Missisquoi Bay and Petit Lac St. François, respectively. Potentially toxigenic genera such as Microcystis were correlated with intracellular microcystin concentrations. A principal component analysis showed that there was a change of the cyanobacterial composition at the genus level in the mesocosms after two days, which varied across the studied sites and sampling time. The cyanobacterial community richness and diversity did not change significantly after its coagulation by Fe2(SO4)3 in all of the mesocosms at either site. The use of Fe2(SO4)3 for an onsite source water treatment should consider its impact on cyanobacterial community structure and the reduction of toxin concentrations.
Keywords: Dorner_Sarah

Evidence-Based Framework to Manage Cyanobacteria and Cyanotoxins in Water and Sludge from Drinking Water Treatment Plants - Jalili, Farhad; Moradinejad, Saber; Zamyadi, Arash; Dorner, Sarah; Sauvé, Sébastien; Prévost, Michèle (Toxins, 2022)
Freshwater bodies and, consequently, drinking water treatment plants (DWTPs) sources are increasingly facing toxic cyanobacterial blooms. Even though conventional treatment processes including coagulation, flocculation, sedimentation, and filtration can control cyanobacteria and cell-bound cyanotoxins, these processes may encounter challenges such as inefficient removal of dissolved metabolites and cyanobacterial cell breakthrough. Furthermore, conventional treatment processes may lead to the accumulation of cyanobacteria cells and cyanotoxins in sludge. Pre-oxidation can enhance coagulation efficiency as it provides the first barrier against cyanobacteria and cyanotoxins and it decreases cell accumulation in DWTP sludge. This critical review aims to: (i) evaluate the state of the science of cyanobacteria and cyanotoxin management throughout DWTPs, as well as their associated sludge, and (ii) develop a decision framework to manage cyanobacteria and cyanotoxins in DWTPs and sludge. The review identified that lab-cultured-based pre-oxidation studies may not represent the real bloom pre-oxidation efficacy. Moreover, the application of a common exposure unit CT (residual concentration × contact time) provides a proper understanding of cyanobacteria pre-oxidation efficiency. Recently, reported challenges on cyanobacterial survival and growth in sludge alongside the cell lysis and cyanotoxin release raised health and technical concerns with regards to sludge storage and sludge supernatant recycling to the head of DWTPs. According to the review, oxidation has not been identified as a feasible option to handle cyanobacterial-laden sludge due to low cell and cyanotoxin removal efficacy. Based on the reviewed literature, a decision framework is proposed to manage cyanobacteria and cyanotoxins and their associated sludge in DWTPs.
Keywords: Dorner_Sarah

Oxidation to Control Cyanobacteria and Cyanotoxins in Drinking Water Treatment Plants: Challenges at the Laboratory and Full-Scale Plants - Jalili, Farhad; Trigui, Hana; Maldonado, Juan Francisco Guerra; Dorner, Sarah; Zamyadi, Arash; Shapiro, B. Jesse; Terrat, Yves; Fortin, Nathalie; Sauvé, Sébastien; Prévost, Michèle (Water, 2022)
The impact of oxidation on mitigation of cyanobacteria and cyanotoxins in drinking water treatment sludge was investigated at the laboratory and treatment plant scales. Two common oxidants, KMnO4 (5 and 10 mg/L) and H2O2 (10 and 20 mg/L) were applied under controlled steady-state conditions. Non-oxidized and oxidized sludge was left to stagnate in the dark for 7 to 38 days. Controlled laboratory trials show that KMnO4 and H2O2 decreased cell counts up to 62% and 77%, respectively. The maximum total MC level reduction achieved after oxidation was 41% and 98% using 20 mg/L H2O2 and 10 mg/L KMnO4, respectively. Stagnation caused cell growth up to 2.6-fold in 8 out of 22 oxidized samples. Microcystin (MC) producer orders as Chroococcales and Synechococcales were persistent while Nostocales was sensitive to combined oxidation and stagnation stresses. In parallel, two on-site shock oxidation treatments were performed in the DWTP’s sludge holding tank using 10 mg/L KMnO4. On-site shock oxidation decreased taxonomic cell counts by up to 43% within 24 h. Stagnation preceded by on-site shock oxidation could increase total cell counts by up to 55% as compared to oxidation alone. The increase of cell counts and mcyD gene copy numbers during stagnation revealed the impact of oxidation/stagnation on cyanobacterial cell growth. These findings show the limitations of sludge oxidation as a strategy to manage cyanobacteria and cyanotoxins in sludge and suggest that alternative approaches to prevent the accumulation and mitigation of cyanobacteria in sludge should be considered.
Keywords: Dorner_Sarah

Can Cyanobacterial Diversity in the Source Predict the Diversity in Sludge and the Risk of Toxin Release in a Drinking Water Treatment Plant? - Jalili, Farhad; Trigui, Hana; Guerra Maldonado, Juan Francisco; Dorner, Sarah; Zamyadi, Arash; Shapiro, B. Jesse; Terrat, Yves; Fortin, Nathalie; Sauvé, Sébastien; Prévost, Michèle (Toxins, 2021)
Conventional processes (coagulation, flocculation, sedimentation, and filtration) are widely used in drinking water treatment plants and are considered a good treatment strategy to eliminate cyanobacterial cells and cell-bound cyanotoxins. The diversity of cyanobacteria was investigated using taxonomic cell counts and shotgun metagenomics over two seasons in a drinking water treatment plant before, during, and after the bloom. Changes in the community structure over time at the phylum, genus, and species levels were monitored in samples retrieved from raw water (RW), sludge in the holding tank (ST), and sludge supernatant (SST). Aphanothece clathrata brevis, Microcystis aeruginosa, Dolichospermum spiroides, and Chroococcus minimus were predominant species detected in RW by taxonomic cell counts. Shotgun metagenomics revealed that Proteobacteria was the predominant phylum in RW before and after the cyanobacterial bloom. Taxonomic cell counts and shotgun metagenomic showed that the Dolichospermum bloom occurred inside the plant. Cyanobacteria and Bacteroidetes were the major bacterial phyla during the bloom. Shotgun metagenomics also showed that Synechococcus, Microcystis, and Dolichospermum were the predominant detected cyanobacterial genera in the samples. Conventional treatment removed more than 92% of cyanobacterial cells but led to cell accumulation in the sludge up to 31 times more than in the RW influx. Coagulation/sedimentation selectively removed more than 96% of Microcystis and Dolichospermum. Cyanobacterial community in the sludge varied from raw water to sludge during sludge storage (1–13 days). This variation was due to the selective removal of coagulation/sedimentation as well as the accumulation of captured cells over the period of storage time. However, the prediction of the cyanobacterial community composition in the SST remained a challenge. Among nutrient parameters, orthophosphate availability was related to community profile in RW samples, whereas communities in ST were influenced by total nitrogen, Kjeldahl nitrogen (N- Kjeldahl), total and particulate phosphorous, and total organic carbon (TOC). No trend was observed on the impact of nutrients on SST communities. This study profiled new health-related, environmental, and technical challenges for the production of drinking water due to the complex fate of cyanobacteria in cyanobacteria-laden sludge and supernatant.
Keywords: Dorner_Sarah

β-D-glucuronidase activity triggered monitoring of fecal contamination using microbial and chemical source tracking markers at drinking water intakes - Hachad, Mounia; Burnet, Jean-Baptiste; Sylvestre, Émile; Duy, Sung Vo; Villemur, Richard; Sauvé, Sébastien; Prévost, Michèle; Qiu, Judy Y.; Pang, Xiaoli; Dorner, Sarah (Water Research, 2024)
Keywords: Dorner_Sarah

Occurrence and partitioning behavior of E. coli and wastewater micropollutants following rainfall events - Hachad, Mounia; Yarahmadi, Hadis; Vo Duy, Sung; Sauvé, Sébastien; Prévost, Michèle; Dorner, Sarah (Resources, Environment and Sustainability, 2022)
Keywords: Dorner_Sarah

Automated Targeted Sampling of Waterborne Pathogens and Microbial Source Tracking Markers Using Near-Real Time Monitoring of Microbiological Water Quality - Burnet, Jean-Baptiste; Habash, Marc; Hachad, Mounia; Khanafer, Zeinab; Prévost, Michèle; Servais, Pierre; Sylvestre, Emile; Dorner, Sarah (Water, 2021)
Waterborne pathogens are heterogeneously distributed across various spatiotemporal scales in water resources, and representative sampling is therefore crucial for accurate risk assessment. Since regulatory monitoring of microbiological water quality is usually conducted at fixed time intervals, it can miss short-term fecal contamination episodes and underestimate underlying microbial risks. In the present paper, we developed a new automated sampling methodology based on near real-time measurement of a biochemical indicator of fecal pollution. Online monitoring of β-D-glucuronidase (GLUC) activity was used to trigger an automated sampler during fecal contamination events in a drinking water supply and at an urban beach. Significant increases in protozoan parasites, microbial source tracking markers and E. coli were measured during short-term (<24 h) fecal pollution episodes, emphasizing the intermittent nature of their occurrence in water. Synchronous triggering of the automated sampler with online GLUC activity measurements further revealed a tight association between the biochemical indicator and culturable E. coli. The proposed event sampling methodology is versatile and in addition to the two triggering modes validated here, others can be designed based on specific needs and local settings. In support to regulatory monitoring schemes, it should ultimately help gathering crucial data on waterborne pathogens more efficiently during episodic fecal pollution events.
Keywords: Dorner_Sarah

Near real-time notification of water quality impairments in recreational freshwaters using rapid online detection of β-D-glucuronidase activity as a surrogate for Escherichia coli monitoring - Cazals, Margot; Stott, Rebecca; Fleury, Carole; Proulx, François; Prévost, Michèle; Servais, Pierre; Dorner, Sarah; Burnet, Jean-Baptiste (Science of The Total Environment, 2020)
Keywords: Dorner_Sarah

Pour une défense collective face à la fatigue pandémique: L’urgence de renforcer les facteurs protecteurs - Généreux, Mélissa; Blouin-Genest, Gabriel; Landaverde, Elsa; Torres Orozco, Et Natalia (Global Health Promotion, 2024)
Résumé: De nombreux articles publiés récemment ont laissé apparaître l’émergence d’un nouveau phénomène dans notre rapport avec la pandémie de COVID-19 : la fatigue pandémique. Ce phénomène suggère l’apparition d’une tendance générale de lassitude face aux mesures sanitaires et à l’état d’urgence devenu permanent. L’objectif de cet article est de replacer cet enjeu dans le contexte de la réalisation d’un projet de recherche portant sur les impacts psychosociaux durant la pandémie. Si relativement peu de recherches se sont intéressées à la fatigue pandémique, la réalité de ce phénomène a été mise en évidence dans le cadre d’un projet de recherche multi-annuelle effectuée durant la pandémie. En termes de méthode, notre équipe multidisciplinaire à l’Université de Sherbrooke a développé un protocole d’enquête permettant d’évaluer les effets de la pandémie de COVID-19 sur la santé mentale à travers des études transversales répétées. La dernière phase de l’enquête inclut un volet additionnel qui cherche à comprendre de quelle manière les conséquences de la pandémie peuvent s’appliquer à d’autres crises systémiques, notamment aux changements climatiques. Différentes vagues d'enquêtes nationales et internationales ont ainsi été réalisées (8 pays, taille minimale de l’échantillon 1000–1500 et échantillonnage par quota mis en oeuvre adapté à chaque pays et basé sur les données démographiques disponibles), et suivant l’évolution de la pandémie, nous avons introduit la notion de fatigue pandémique, ainsi que de fatigue climatique, afin de pouvoir mesurer l’impact de l’exposition prolongée à ces crises mondiales. Ces nouvelles données confirment nos résultats originaux : l’impact psychosocial de la pandémie est immense, en particulier en termes de fatigue pandémique, phénomène qui se retrouve à la fois au niveau comportemental et informationnel. Cette fatigue est un indicateur important à considérer afin d’améliorer notre capacité de réaction et d’adaptation à cette crise, mais également à celles futures.
Keywords: Généreux_Mélissa

Visual assessment of tree vigour in Canadian northern hardwood forests: The need for a simplified system - Moreau, Guillaume; Cecil-Cockwell, Malcolm J.L.; Pothier, David; Achim, Alexis; Bédard, Steve; Guillemette, François; Caspersen, John (Forest Ecology and Management, 2023)
Keywords: Guillemette_Francois

Sapling growth dynamics after partial cutting in temperate mixedwood stands - Power, Hugues; Auger, Isabelle; Guillemette, François; Raymond, Patricia; Dumais, Daniel (Canadian Journal of Forest Research, 2022)
The temperate mixedwood forests of eastern North America have been managed by partial cutting for several decades. To ensure that regeneration contributes to replacing the commercial-size stems that are removed by partial cutting, forest managers need to anticipate how saplings (i.e., regenerating trees with a diameter at breast height >1.0 cm) develop in terms of number and diameter. Using up to 20 years of monitoring data from three study sites, we developed a transition matrix model to predict the future number of saplings and their diameter distribution for mixed yellow birch ( Betula alleghaniensis Britton) – conifer stands. Our results show that partial cutting allowed yellow birch, red maple ( Acer rubrum L.), red spruce ( Picea rubens Sarg.), and balsam fir ( Abies balsamea (L.) Mill.) saplings to reach merchantable size faster and in greater numbers than in untreated control plots. We also found that fewer hardwood saplings (yellow birch and red maple) than softwood saplings (red spruce and balsam fir) were required to produce 1 m 2 ·ha −1 of merchantable basal area after 20–40 years. Finally, our model provides a tool for forest managers to predict sapling development in mixed hardwood and softwood stands over a full cutting cycle.
Keywords: Guillemette_Francois

Simplified tree marking guidelines enhance value recovery as well as stand vigour in northern hardwood forests under selection management - Moreau, Guillaume; Chagnon, Catherine; Cecil-Cockwell, Malcolm J L; Pothier, David; Achim, Alexis; Bédard, Steve; Guillemette, François; Caspersen, John (Forestry: An International Journal of Forest Research, 2024)
Abstract In northern hardwood forests, tree markers select the trees to be harvested during logging operations using classification systems that assign harvest priorities based on the presence of a wide range of individual defects. According to the most recent advances in our understanding of the impact of defects on both tree vigour (the risk of mortality or decline in growth) and quality (the potential for recovering valuable sawlogs), tree markers should adopt a simpler classification system that considers fewer defects than the current operational practice, and they should prioritize the removal of trees with crown dieback. Since the probability of developing defects and dying increases substantially with tree diameter, tree markers should also favour the removal of larger trees that have maintained their quality. However, these recommendations were developed based on tree-level analyses. To provide further validation at the stand scale, we compared stand improvement and value recovery under three tree marking regimes: a new, simplified regime based on the recommendations above, and two regimes used in the province of Quebec, Canada. To do so, we conducted tree marking simulations and value recovery assessments in 14 managed stands distributed across the northern hardwood range of Quebec. Our results confirmed that the simplified tree marking regime not only facilitated stand improvement by removing a greater proportion of low-vigour trees, but also recovered significantly more value (17% on average) at the stand scale. By prioritizing the removal of trees with crown dieback, the simplified regime was superior at salvaging the current value of low-vigour trees before they die or decline in quality. Based on our results, we propose simplified and empirically-validated tree marking guidelines for northern hardwood forests.
Keywords: Guillemette_Francois

Quantifying the Probability of Decline in Quality: Implications for Selection Management in Northern Hardwood Forests - Moreau, Guillaume; Cecil-Cockwell, Malcolm J. L.; Achim, Alexis; Bédard, Steve; Guillemette, François; Caspersen, John (Forests, 2023)
Northern hardwoods are susceptible to a wide range of defects that can reduce the amount of sound wood with desirable qualities, such as the clear sapwood of sugar maple trees. Yet, the rate at which trees decline in quality due to the development of such defects has never been quantified in northern hardwood forests due to a dearth of repeat inventories that record the appearance of defects over time. As a result, it remains uncertain whether, and how, selection management reduces the probability of decline in quality. In this study, we quantify the rate at which trees decline in quality due to the development of defects, and we test several hypotheses regarding the influence of selection management on quality. Our results show that (1) the probability of decline in quality increases as trees grow larger; (2) crown dieback also increases the probability of decline in quality; (3) the probability of decline in quality is slightly lower in managed stands than in unmanaged stands, and (4) the probability of decline in quality increases with the mean annual temperature of the site. Finally, we combined our estimates of the probability of decline in quality with previous estimates of the probability of mortality to assess the overall risk associated with retaining trees of different species, sizes, and vigour profiles. The resulting metric can inform efforts to improve the management of northern hardwood forests by providing an integrated estimate of the risk that the value of a tree will be reduced, or eliminated, due to mortality or decline in quality.
Keywords: Guillemette_Francois

How many plots are needed to estimate sapling density and stocking in temperate forests? - Guillemette, François; Lambert, Marie-Claude; Power, Hugues; Raymond, Patricia (The Forestry Chronicle, 2023)
Performing a complete silvicultural diagnosis before a silvicultural treatment generally requires assessing the state of regeneration with the help of an inventory by sampling, particularly for stands dominated by sugar maple (Acer saccharum Marsh.) or yellow birch (Betula alleghaniensis Britt.), in which partial cuts are recommended. This inventory may then be compared to the standard or used in a growth model for saplings (trees for which the diameter measured at 1.3 m above the ground (DBH) varies from 1.1 cm to 9.0 cm). Some of these tools are based on sapling density, while others are based on the stocking of the saplings or on the stocking of total regeneration (combining saplings and seedlings with a DBH ≤ 1.0 cm). We assessed the number of plots required to estimate the density and the stocking of saplings with a given margin of error in 28 stands. The results show that more plots are required than usual in practice to inventory sapling density. The stocking is much easier to estimate precisely.
Keywords: Guillemette_Francois

Assessing Post-Harvest Regeneration in Northern Hardwood and Mixedwood Stands: Evolution of Species Composition and Dominance within 15-Year-Old Group Selection and Patch Cutting - Bilodeau-Gauthier, Simon; Bédard, Steve; Guillemette, François (Forests, 2020)
Multi-cohort forest management in northern hardwood stands may well be the best way to successfully regenerate tree species of intermediate shade tolerance, such as yellow birch (Betula alleghaniensis Britt.). The creation of large enough gaps in the canopy favors increased light availability within the opening, while soil scarification provides suitable germination seedbeds. Evidence of these methods’ success nonetheless remains mostly the purview of experimental studies rather than operational tests. In Quebec, Canada, the multi-cohort methods promoted include group selection cutting and patch cutting. The present study tested their implementation at an operational scale and over a large territory in both hardwood-dominated and mixedwood stands. We assessed their efficacy in promoting natural regeneration of commercial hardwood trees, notably yellow birch and sugar maple (Acer saccharum Marsh.). We conducted regeneration surveys at 2, 5, 10, and 15 years after harvest. Overall, group selection and patch cuttings were successful in regenerating the target species. Yellow birch, for instance, showed a mean stocking around 60% and a mean sapling density around 3400 stems ha−1 after 15 years. We compared several variables for measuring regeneration in early years, and found that the relative abundance, the stocking based on one stem per sampling unit, and the mean maximum height were good predictors of the relative presence of yellow birch and sugar maple in 15-year-old canopy openings. Using smaller sampling units (6.25 m2 rather than 25 m2) and waiting until year 5 may be more useful for making such predictions. In addition, there was an important turnover in vertical dominance in these openings. Non-commercial woody competitors were frequently dominant in early years but were often replaced by commercial hardwoods, notably yellow birch. We propose certain thresholds for assessing the success of post-harvest regeneration and for evaluating the need for a cleaning treatment.
Keywords: Guillemette_Francois

Changes in growth dominance after partial cuts in even- and uneven-aged northern hardwood stands - Lemire, Caroline; Bédard, Steve; Guillemette, François; Pothier, David (Forest Ecology and Management, 2020)
Keywords: Guillemette_Francois

Reviews and syntheses: Recent advances in microwave remote sensing in support of terrestrial carbon cycle science in Arctic–boreal regions - Mavrovic, Alex; Sonnentag, Oliver; Lemmetyinen, Juha; Baltzer, Jennifer L.; Kinnard, Christophe; Roy, Alexandre (Biogeosciences, 2023)
Abstract. Spaceborne microwave remote sensing (300 MHz–100 GHz) provides a valuable method for characterizing environmental changes, especially in Arctic–boreal regions (ABRs) where ground observations are generally spatially and temporally scarce. Although direct measurements of carbon fluxes are not feasible, spaceborne microwave radiometers and radar can monitor various important surface and near-surface variables that affect terrestrial carbon cycle processes such as respiratory carbon dioxide (CO2) fluxes; photosynthetic CO2 uptake; and processes related to net methane (CH4) exchange including CH4 production, transport and consumption. Examples of such controls include soil moisture and temperature, surface freeze–thaw cycles, vegetation water storage, snowpack properties and land cover. Microwave remote sensing also provides a means for independent aboveground biomass estimates that can be used to estimate aboveground carbon stocks. The microwave data record spans multiple decades going back to the 1970s with frequent (daily to weekly) global coverage independent of atmospheric conditions and solar illumination. Collectively, these advantages hold substantial untapped potential to monitor and better understand carbon cycle processes across ABRs. Given rapid climate warming across ABRs and the associated carbon cycle feedbacks to the global climate system, this review argues for the importance of rapid integration of microwave information into ABR terrestrial carbon cycle science.
Keywords: Kinnard_Christophe

Historical Trends and Projections of Snow Cover over the High Arctic: A Review - Mohammadzadeh Khani, Hadi; Kinnard, Christophe; Lévesque, Esther (Water, 2022)
Snow is the dominant form of precipitation and the main cryospheric feature of the High Arctic (HA) covering its land, sea, lake and river ice surfaces for a large part of the year. The snow cover in the HA is involved in climate feedbacks that influence the global climate system, and greatly impacts the hydrology and the ecosystems of the coldest biomes of the Northern Hemisphere. The ongoing global warming trend and its polar amplification is threatening the long-term stability of the snow cover in the HA. This study presents an extensive review of the literature on observed and projected snow cover conditions in the High Arctic region. Several key snow cover metrics were reviewed, including snowfall, snow cover duration (SCD), snow cover extent (SCE), snow depth (SD), and snow water equivalent (SWE) since 1930 based on in situ, remote sensing and simulations results. Changes in snow metrics were reviewed and outlined from the continental to the local scale. The reviewed snow metrics displayed different sensitivities to past and projected changes in precipitation and air temperature. Despite the overall increase in snowfall, both observed from historical data and projected into the future, some snow cover metrics displayed consistent decreasing trends, with SCE and SCD showing the most widespread and steady decreases over the last century in the HA, particularly in the spring and summer seasons. However, snow depth and, in some regions SWE, have mostly increased; nevertheless, both SD and SWE are projected to decrease by 2030. By the end of the century, the extent of Arctic spring snow cover will be considerably less than today (10–35%). Model simulations project higher winter snowfall, higher or lower maximum snow depth depending on regions, and a shortened snow season by the end of the century. The spatial pattern of snow metrics trends for both historical and projected climates exhibit noticeable asymmetry among the different HA sectors, with the largest observed and anticipated changes occurring over the Canadian HA.
Keywords: Kinnard_Christophe

Impact of forcing on sublimation simulations for a high mountain catchment in the semiarid Andes - Réveillet, Marion; MacDonell, Shelley; Gascoin, Simon; Kinnard, Christophe; Lhermitte, Stef; Schaffer, Nicole (The Cryosphere, 2020)
Abstract. In the semiarid Andes of Chile, farmers and industry in the cordillera lowlands depend on water from snowmelt, as annual rainfall is insufficient to meet their needs. Despite the importance of snow cover for water resources in this region, understanding of snow depth distribution and snow mass balance is limited. Whilst the effect of wind on snow cover pattern distribution has been assessed, the relative importance of melt versus sublimation has only been studied at the point scale over one catchment. Analyzing relative ablation rates and evaluating uncertainties are critical for understanding snow depth sensitivity to variations in climate and simulating the evolution of the snowpack over a larger area and over time. Using a distributed snowpack model (SnowModel), this study aims to simulate melt and sublimation rates over the instrumented watershed of La Laguna (513 km2, 3150–5630 m a.s.l., 30∘ S, 70∘ W), during two hydrologically contrasting years (i.e., dry vs. wet). The model is calibrated and forced with meteorological data from nine Automatic Weather Stations (AWSs) located in the watershed and atmospheric simulation outputs from the Weather Research and Forecasting (WRF) model. Results of simulations indicate first a large uncertainty in sublimation-to-melt ratios depending on the forcing as the WRF data have a cold bias and overestimate precipitation in this region. These input differences cause a doubling of the sublimation-to-melt ratio using WRF forcing inputs compared to AWS. Therefore, the use of WRF model output in such environments must be carefully adjusted so as to reduce errors caused by inherent bias in the model data. For both input datasets, the simulations indicate a similar sublimation fraction for both study years, but ratios of sublimation to melt vary with elevation as melt rates decrease with elevation due to decreasing temperatures. Finally results indicate that snow persistence during the spring period decreases the ratio of sublimation due to higher melt rates.
Keywords: Kinnard_Christophe

A new interpolation method to resolve under-sampling of UAV-lidar snow depth observations in coniferous forests - Dharmadasa, Vasana; Kinnard, Christophe; Baraër, Michel (Cold Regions Science and Technology, 2024)
Keywords: Baraer_Michel; Kinnard_Christophe

Global change on the Blue Planet - Bourbonnais, Annie; Ho, Sze Ling; Kinnard, Christophe; Lenaerts, Jan T. M.; Sugiyama, Shin; Altabet, Mark (Communications Earth & Environment, 2021)
Keywords: Kinnard_Christophe

Association between Beverage Consumption and Sleep Quality in Adolescents - Vézina-Im, Lydi-Anne; Beaulieu, Dominique; Turcotte, Stéphane; Turcotte, Anne-Frédérique; Delisle-Martel, Joannie; Labbé, Valérie; Lessard, Lily; Gingras, Mariane (Nutrients, 2024)
The objective of this study was to verify if the consumption of different beverages (such as water, 100% pure fruit juice, and sugar-sweetened beverages (SSBs)) is associated with adolescents’ sleep quality. French-speaking adolescents were recruited in person and online throughout the province of Québec (Canada) from the end of March to early July 2023. Beverage consumption and sleep quality were measured using French versions of validated questionnaires specifically designed for adolescents. A total of 218 adolescents (14–17 years; 55.5% female) completed the online survey. Among caffeinated SSBs, energy drink (rs = −0.16; p = 0.0197) and sugar-sweetened coffee (rs = −0.33; p < 0.0001) intake was correlated with adolescents’ sleep quality. Energy drink consumption (β = −0.0048; p = 0.0005) and being male (β = 0.6033; p < 0.0001) were associated with adolescents’ sleep quality. There was an interaction between sugar-sweetened coffee intake and biological sex that was associated with adolescents’ sleep quality (p = 0.0053). Sugar-sweetened coffee consumption was correlated with adolescent girls’ abilities to go to bed (rs = −0.21; p = 0.0203) and fall asleep (rs = −0.28; p = 0.0020), while in boys, it was only significantly correlated with their abilities to go to bed (rs = −0.27; p = 0.0069). Public health interventions aimed at adolescent boys should primarily target lowering energy drink consumption, while those aimed at girls should prioritize sugar-sweetened coffee intake to possibly improve their sleep quality.
Keywords: FRQ_S; Lessard_Lily

Artefacts of disaster risk reduction: conceptualizing bottom-up initiatives of climate action in informal settlements - Lizarralde, Gonzalo; Herazo, Benjamín; Smith, David; Bornstein, Lisa; Gould, Kevin; Monsalve, Elsa; Ordoñez, Nicolás; López, Adriana; López, Oswaldo; Burdiles, Roberto; Araneda, Claudio; Olivera, Andrés (Disaster Prevention and Management: An International Journal, 2024)
Purpose Disaster risk reduction is of prime importance in informal settlements in the Global South, where several forms of vulnerability coexist. Policy and official programmes, however, rarely respond to the needs and expectations of citizens and local leaders living in these settlements. Even though these agents constantly attempt to reduce risks in their own way, we know very little about their activities, motivations and effective impact on risk reduction. Here we seek to conceptualize bottom-up initiatives to better grasp their origins, limitations and success. Design/methodology/approach Through a four-year action-research project in Colombia, Cuba and Chile, we theorize about the production of change by local agents. Through detailed case studies we explored the activism of 17 local leaders. Through narrative analysis we studied their motivations and explanations. Finally, by documenting 22 initiatives, we revealed effective changes in space. Findings In the face of risk and disasters, residents and leaders in informal settings engaged in symbolic, physical and social spaces of interaction. Their actions were guided by trust, emotions, time cycles and activism. Local agency was justified by narratives about risk and climate change that differ from those of authorities and scholars. Research limitations/implications There is still limited understanding of bottom-up initiatives in informal settings. It is crucial to conceptualize their origins, limitations and success. The focus on three specific countries necessitates further research for broader applicability and understanding. Practical implications A better comprehension of bottom-up actions is crucial for informing policies and programmes aimed at reducing risk in informal settings. Stakeholders must recognize the political, social and cultural roles of these actions for more impactful climate action. Originality/value We borrow Simon’s concept of “artefact” to introduce the notion of “Artefacts of Disaster Risk Reduction”, providing insights into the multifaceted nature of bottom-up initiatives. We also emphasize the simultaneous political and phenomenological character of these actions, contributing to a deeper understanding of their origins and impact.
Keywords: Infolettre; Infolettre_Ete_2024; Lizarralde_Gonzalo

The problem of doing more: success and paradoxes in scaling up informal initiatives for disaster risk reduction and climate action - Lizarralde, Gonzalo; Bornstein, Lisa; Herazo, Benjamin; Burdiles, Roberto; Araneda, Claudio; Páez Martínez, Holmes; Diaz, Julia Helena; Fauveaud, Gabriel; Olivera, Andrés; Gonzalez, Gonzalo; López, Oswaldo; López, Adriana; et al. (Canadian Journal of Development Studies / Revue canadienne d'études du développement, 2022)
Keywords: Lizarralde_Gonzalo

Policies of Exclusion: The Case of Syrian Refugees in Lebanon - Kikano, Faten; Fauveaud, Gabriel; Lizarralde, Gonzalo (Journal of Refugee Studies, 2021)
Abstract When the Syrian war erupted in 2011, the Lebanese government withdrew from managing the influx of Syrian refugees. Three years later, Lebanon’s Council of Ministers set new regulations for Syrians with the purpose of reducing access to territory and persuading refugees to leave the country. This article analyses the reasons for and the outcomes of Lebanon’s response to the refugee crisis before and after 2014. It then examines, through a qualitative exploratory approach and based on two longitudinal case studies, the impact of Lebanese regulations. In both cases, the so-called ‘temporary gatherings’ became permanent settlements beyond the government’s control. The government’s strategy backfired: in attempting to avoid ghettos, it created them. We conclude that when refugee situations become protracted, most efforts aimed at excluding refugees fail. Excluding refugees increases their vulnerability and reduces their chances of repatriation or resettlement. To prevent this, we argue that hosting policies must lead to the temporary integration of refugees within urban systems and public institutions.
Keywords: Lizarralde_Gonzalo

Maladaptation, fragmentation, and other secondary effects of centralized post-disaster urban planning: The case of the 2011 “cascading” disaster in Japan - Kondo, Tamiyo; Lizarralde, Gonzalo (International Journal of Disaster Risk Reduction, 2021)
Keywords: Lizarralde_Gonzalo

City profile: Canaan, Haiti - A new post disaster city - Petter, Anne-Marie; Labbé, Danielle; Lizarralde, Gonzalo; Goulet, Jean (Cities, 2020)
Keywords: Lizarralde_Gonzalo

The language of risk and the risk of language: Mismatches in risk response in Cuban coastal villages - Aragón-Duran, Ernesto; Lizarralde, Gonzalo; González-Camacho, Gonzalo; Olivera-Ranero, Andrés; Bornstein, Lisa; Herazo, Benjamin; Labbé, Danielle (International Journal of Disaster Risk Reduction, 2020)
Keywords: Lizarralde_Gonzalo

Numerical investigation of the scour around a diamond- and square-shaped pile in a narrow channel - Hurtado-Herrera, Mario; Uh Zapata, Miguel; Hammouti, Abdelkader; Pham Van Bang, Damien; Zhang, Wei; Nguyen, Kim Dan (Ocean Engineering, 2024)
Keywords: PhamVanBang_Damien

Bathymetric data integration approach to study bedforms in the estuary of the Saint‐Lawrence River - Noman, Juzer; Cassol, Willian Ney; Daniel, Sylvie; Pham Van Bang, Damien (Frontiers in Remote Sensing, 2023)
The identification of bedforms has an important role in the study of seafloor morphology. The presence of these dynamic structures on the seafloor represents a hazard for navigation. They also influence the hydrodynamic simulation models used in the context, for example, of coastal flooding. Generally, multiBeam EchoSounders (MBES) are used to survey these bedforms. Unfortunately, the coverage of the MBES is limited to small areas per survey. Therefore, the analysis of large areas of interest (like navigation channels) requires the integration of different datasets acquired over overlapping areas at different times. The presence of spatial and temporal inconsistencies between these datasets may significantly affect the study of bedforms, which are subject to many natural processes (e.g. tides; flow). This paper proposes a novel approach to integrate multisource bathymetric datasets to study bedforms. The proposed approach is based on consolidating multisource datasets and applying the Empirical Bayesian Kriging interpolation for the creation of a multisource Digital Bathymetric Model (DBM). It has been designed to be adapted for estuarine areas with a high dynamism of the seafloor, characteristic of the fluvio-marine regime of the Estuary of the Saint-Lawrence River. This area is distinguished by a high tidal cycle and the presence of fields of dunes. The study involves MBES data that was acquired daily over a field of dunes in this area over the span of four days for the purpose of monitoring the morphology and migration of dunes. The proposed approach performs well with a resulting surface with a reduced error relative to the original data compared to existing approaches and the conservation of the dune shape through the integration of the data sets despite the highly dynamic fluvio-marine environments.
Keywords: Infolettre; Infolettre_Octobre_2023; PhamVanBang_Damien

Deformation of Spartina patens and Spartina alterniflora stems under irregular wave action - Markov, Acacia; Stolle, Jacob; Henteleff, Ross; Nistor, Ioan; Pham Van Bang, Damien; Murphy, Enda; Cornett, Andrew (Coastal Engineering Journal, 2023)
Keywords: PhamVanBang_Damien

Numerical Study of the Flow and Blockage Ratio of Cylindrical Pier Local Scour - Hurtado-Herrera, Mario; Zhang, Wei; Hammouti, Abdelkader; Pham Van Bang, Damien; Nguyen, Kim Dan (Applied Sciences, 2023)
A three-dimensional large eddy simulation model is used to simulate the turbulent flow dynamics around a circular pier in live-bed and clear-water scour conditions. The Navier–Stokes equations are transformed into a σ-coordinate system and solved using a second-order unstructured triangular finite-volume method. We simulate the bed evolution by solving the Exner-Polya equation assisted by a sand-slide model as a correction method. The bedload transport rate is based on the model of Engelund and Fredsœ. The model was validated for live-bed conditions in a wide channel and clear-water conditions in a narrow channel against the experimental data found in the literature. The in-house model NSMP3D can successfully produce both the live-bed and clear-water scouring throughout a stable long-term simulation. The flow model was used to study the effects of the blockage ratio in the flow near the pier in clear-water conditions, particularly the contraction effect at the zone where the scour hole starts to form. The scour depth in the clear water simulations is generally deeper than the live-bed simulations. In clear-water, the results show that the present model is able to qualitatively and quantitatively capture the hydrodynamic and morphodynamic processes near the bed. In comparison to the wide channel situation, the simulations indicate that the scour rate is faster in the narrow channel case.
Keywords: PhamVanBang_Damien

Two-Phase Flow Modeling for Bed Erosion by a Plane Jet Impingement - Pham Van Bang, Damien; Uh Zapata, Miguel; Gauthier, Georges; Gondret, Philippe; Zhang, Wei; Nguyen, Kim Dan (Water, 2022)
This paper presents experimental and numerical studies on the erosion of a horizontal granular bed by a two-dimensional plane vertical impinging jet to predict the eroded craters’ size scaling (depth and width). The simulations help understand the microscopic processes that govern erosion in this complex flow. A modified jet-bed distance, accounting for the plane jet virtual origin, is successfully used to obtain a unique relationship between the crater size and a local Shields parameter. This work develops a two-phase flow numerical model to reproduce the experimental results. The numerical techniques are based on a finite volume formulation to approximate spatial derivatives, a projection technique to calculate the pressure and velocity for each phase, and a staggered grid to avoid spurious oscillations. Different options for the sediment’s solid-to-liquid transition during erosion are proposed, tested, and discussed. One model is based on unified equations of continuum mechanics, others on modified closure equations for viscosity or momentum transfer. A good agreement between the numerical solutions and the experimental measurements is obtained.
Keywords: PhamVanBang_Damien

Numerical Study on Measures for Protecting the Go-Cong Coastlines (Vietnam) from Erosion - San, Dinh Cong; Duong, Nguyen Binh; Phong, Nguyen Cong; Tu, Le Xuan; Pham-Van-Bang, Damien; Guillou, Sylvain; Nguyen, Kim Dan (Water, 2022)
Every year, in the Vietnam Mekong Delta Coastal Zone (VMDCZ), erosions cause approximately 300 ha of agricultural land loss. Therefore, measures for shoreline protection are urgently needed. This paper discusses the impacts of protection measures in the Go-Cong Coastal Zone to prevent erosion/accretion processes, predicted by two numerical models, MIKE21-FM and TELEMAC-2D. Hard and soft measures have been proposed using breakwaters and sandbars, respectively. The simulations show that the erosion/accretion trends provided by both models are similar. For breakwaters, MIKE21-FM provides less accretion than TELEMAC-2D in areas extending over 300 m and 500 m from shorelines. However, for sandbars, MIKE21-FM shows higher accretion within areas extending over 500 m but less than 300 m. Sandbars cause higher accretion in a larger area, extending over 1000 m offshore. The simulation results allow us to propose two alternative measures: (1) a row of several breakwater units will be implanted at 300 m offshore. The length of each unit is 600 m, with a gap between two neighbouring units of 70 m and a crest elevation of 2.2 m above mean sea level (MSL). (2) A row of sandbar units will be posed at 500 m offshore, with a unit length of 1000 m and a gap between the two neighbouring units of 200 m. The crest elevation is fixed at MSL.
Keywords: PhamVanBang_Damien

Three-Dimensional Hydrostatic Curved Channel Flow Simulations Using Non-Staggered Triangular Grids - Zhang, Wei; Uh Zapata, Miguel; Pham Van Bang, Damien; Nguyen, Kim Dan (Water, 2022)
Non-staggered triangular grids have many advantages in performing river or ocean modeling with the finite-volume method. However, horizontal divergence errors may occur, especially in large-scale hydrostatic calculations with centrifugal acceleration. This paper proposes an unstructured finite-volume method with a filtered scheme to mitigate the divergence noise and avoid further influencing the velocities and water elevation. In hydrostatic pressure calculations, we apply the proposed method to three-dimensional curved channel flows. Approximations reduce the numerical errors after filtering the horizontal divergence operator, and the approximation is second-order accurate. Numerical results for the channel flow accurately calculate the velocity profile and surface elevation at different Froude numbers. Moreover, secondary flow features such as the vortex pattern and its movement along the channel sections are also well captured.
Keywords: PhamVanBang_Damien

Behavior of variable density munitions under dam break forcing - Idowu, Temitope; Gangadharan, Manoj; Chapman, Emily; Puleo, Jack; Stolle, Jacob; Bang, Damien Pham van (Coastal Engineering Proceedings, 2022)
Munitions or Unexploded Ordnance (UXO) are ammunitions belonging to a larger family of explosives from past military activities. Sea disposal of munitions was a common practice from the late 1800s to 1970 when international conventions put an end to the practice. The exact quantity of munitions dumped into the Oceans globally is unknown due to sparse documentation but conservative estimates of known records stand at 1.6 million tons (Wilkinson, 2017). After decades underwater, some munitions have resurfaced in the nearshore, presumably washed onshore or exhumed by high-energy wave action. Extreme events could be major causes of migration and exposure of UXO in the nearshore. The quantification of variable density munitions behavior in the swash zone remains poorly understood. Biofouling, encrustation, and corrosion can alter the density of the underwater munitions, which consequently impacts the behavior of the munitions in the swash zone. Hence, this experimental study aimed to quantify the behavior of variable density munitions in the swash zone under dam-break scenarios. The findings of the study create more insights into the behavior of variable density munitions in the swash zone and can also serve as validation data for probabilistic models on munitions behavior in the swash zone under extreme events.
Keywords: PhamVanBang_Damien

Two-phase experimental and numerical studies on scouring at the toe of vertical seawall - Uh Zapata, M.; Zhang, W.; Marois, L.; Hammouti, A.; Pham Van Bang, D.; Nguyen, K.D. (European Journal of Mechanics - B/Fluids, 2022)
Keywords: PhamVanBang_Damien

An unstructured finite volume method based on the projection method combined momentum interpolation with a central scheme for three-dimensional nonhydrostatic turbulent flows - Zhang, Wei; Uh Zapata, Miguel; Bai, Xin; Pham Van Bang, Damien; Nguyen, Kim Dan (European Journal of Mechanics - B/Fluids, 2020)
Keywords: PhamVanBang_Damien

Three-dimensional simulation of horseshoe vortex and local scour around a vertical cylinder using an unstructured finite-volume technique - Zhang, Wei; Uh Zapata, Miguel; Bai, Xin; Pham-Van-Bang, Damien; Nguyen, Kim Dan (International Journal of Sediment Research, 2020)
Keywords: PhamVanBang_Damien

Seasonal Variation Of Wave Attenuation Capacity Of Canadian Saltmarsh Vegetation - Caldera, Ganga; Stolle, Jacob; Bang, Damien Pham Van; Murphy, Enda; Knox, Paul (CoastLab 2024: Physical Modelling in Coastal Engineering and Science, 2024)
Nature-based Solutions (NbS) for coastal protection have been widely recognized as sustainable, economical, and eco-friendly alternatives to conventional grey structures, particularly under the threat of climate change (Temmerman et al., 2013). Living shorelines are a form of NbS, which incorporate natural elements (such as saltmarshes) that provide flood and erosion risk management benefits. Climate change impacts, such as rising sea levels and reducing sea-ice cover (Savard et al., 2016), are increasingly motivating communities in Canada to consider incorporating living shorelines in coastal protection schemes. The efficacy of wave energy dissipation by vegetation depends on both hydrodynamic conditions and plant characteristics. However, plant parameters, such as standing biomass exhibit seasonal fluctuations, leading to corresponding variations in attenuation capacity (Schulze et al., 2019). Hence, the design of NbS utilizing saltmarsh vegetation must account for seasonal variations to ensure sustained efficacy, especially within the context of Canadian regional climates, which are typically characterized by extended, stormy winters and shorter summer seasons. Few studies have quantified wave attenuation by real saltmarsh vegetation in large-scale laboratory facilities (Möller et al., 2014; Maza et al., 2015; Ghodoosipour et al., 2022), particularly for species native to the east coast of Canada. There is a knowledge gap on how seasonality affects wave attenuation by saltmarsh vegetation and how attenuation varies from the lower marsh to the higher marsh depending on species-specific plant traits. Research is needed to bridge this gap and develop technical guidance for the design of performant living shorelines in Canada.
Keywords: PhamVanBang_Damien

Wave attenuation of saltmarsh vegetation under storm conditions - Caldera, Ganga; Stolle, Jacob; Bang, Damien Pham Van; Cornett, Andrew; Murphy, Enda; Nistor, Ioan (Coastal Engineering Proceedings, 2022)
Nature-based solutions (NbS) for coastal protection has recently gained increased attention worldwide as a sustainable, economical and eco-friendly alternative to conventional grey structures, particularly under the threat of climate change (Temmerman et al. 2013). Wave energy dissipation by vegetation can be parameterized by the total horizontal force acting on the plant; expressed using a Morison-type equation considering only the form drag component (Dalrymple et al. 1984). Modelling wave-vegetation interaction is challenging in a laboratory environment (Lara et al. 2016) and it is difficult to accomplish a realistic representation of a plant’s biomechanical behavior and geometry using plant mimics or surrogates. Few studies have modelled real saltmarsh vegetation in large scale laboratory facilities (Moller et al. 2014; Maza et al. 2015) and quantified wave attenuation, particularly for engineered living shorelines (Maryland DoE, 2013). Further research is needed, particularly in the Canadian context, to investigate the capacity of different saltmarsh species to effectively attenuate waves and wave runup under storm conditions, to examine the plant’s drag coefficient and to bridge the gap to develop technical design specifications for the detailed design of living shorelines.
Keywords: PhamVanBang_Damien

Using Rocking Frequencies of Bridge Piers for Scour Monitoring - Boujia, Nissrine; Schmidt, Franziska; Chevalier, Christophe; Siegert, Dominique; Pham Van Bang, Damien (Structural Engineering International, 2021)
Keywords: PhamVanBang_Damien

Distributed Optical Fiber-Based Approach for Soil–Structure Interaction - Boujia, Nissrine; Schmidt, Franziska; Chevalier, Christophe; Siegert, Dominique; Pham Van Bang, Damien (Sensors, 2020)
Scour is a hydraulic risk threatening the stability of bridges in fluvial and coastal areas. Therefore, developing permanent and real-time monitoring techniques is crucial. Recent advances in strain measurements using fiber optic sensors allow new opportunities for scour monitoring. In this study, the innovative optical frequency domain reflectometry (OFDR) was used to evaluate the effect of scour by performing distributed strain measurements along a rod under static lateral loads. An analytical analysis based on the Winkler model of the soil was carefully established and used to evaluate the accuracy of the fiber optic sensors and helped interpret the measurements results. Dynamic tests were also performed and results from static and dynamic tests were compared using an equivalent cantilever model.
Keywords: PhamVanBang_Damien

Impacts of high precipitation on the energy and water budgets of a humid boreal forest - Isabelle, Pierre-Erik; Nadeau, Daniel F.; Anctil, François; Rousseau, Alain N.; Jutras, Sylvain; Music, Biljana (Agricultural and Forest Meteorology, 2020)
Keywords: Ouvrage_Collectif_Numéro1; Rousseau_Alain

Quantitative assessment on basin-scale hydrological services of wetlands - Wu, Yanfeng; Zhang, Guangxin; Rousseau, Alain N. (Science China Earth Sciences, 2020)

Quantifying streamflow regulation services of wetlands with an emphasis on quickflow and baseflow responses in the Upper Nenjiang River Basin, Northeast China - Wu, Yanfeng; Zhang, Guangxin; Rousseau, Alain N.; Xu, Y. Jun (Journal of Hydrology, 2020)
Keywords: Rousseau_Alain

Extension of a Monolayer Energy-Budget Degree-Day Model to a Multilayer One - Augas, Julien; Foulon, Etienne; Rousseau, Alain N.; Baraër, Michel (Water, 2024)
This paper presents the extension of the monolayer snow model of a semi-distributed hydrological model (HYDROTEL) to a multilayer model that considers snow to be a combination of ice and air, while accounting for freezing rain. For two stations in Yukon and one station in northern Quebec, Canada, the multilayer model achieves high performances during calibration periods yet similar to the those of the monolayer model, with KGEs of up to 0.9. However, it increases the KGE values by up to 0.2 during the validation periods. The multilayer model provides more accurate estimations of maximum SWE and total spring snowmelt dates. This is due to its increased sensitivity to thermal atmospheric conditions. Although the multilayer model improves the estimation of snow heights overall, it exhibits excessive snow densities during spring snowmelt. Future research should aim to refine the representation of snow densities to enhance the accuracy of the multilayer model. Nevertheless, this model has the potential to improve the simulation of spring snowmelt, addressing a common limitation of the monolayer model.
Keywords: Baraer_Michel; Rousseau_Alain

Deriving synthetic rating curves from a digital elevation model to delineate the inundated areas of small watersheds - Gordon, Camila A.; Foulon, Etienne; Rousseau, Alain N. (Journal of Hydrology: Regional Studies, 2023)
Keywords: Infolettre; Infolettre_Janvier_2024; Rousseau_Alain

What is the Trade-Off between Snowpack Stratification and Simulated Snow Water Equivalent in a Physically-Based Snow Model? - Augas, Julien; Abbasnezhadi, Kian; Rousseau, Alain N.; Baraer, Michel (Water, 2020)
In Nordic watersheds, estimation of the dynamics of snow water equivalent (SWE) represents a major step toward a satisfactory modeling of the annual hydrograph. For a multilayer, physically-based snow model like MASiN (Modèle Autonome de Simulation de la Neige), the number of modeled snow layers can affect the accuracy of the simulated SWE. The objective of this study was to identify the maximum number of snow layers (MNSL) that would define the trade-off between snowpack stratification and SWE modeling accuracy. Results indicated that decreasing the MNSL reduced the SWE modeling accuracy since the thermal energy balance and the mass balance were less accurately resolved by the model. Nevertheless, from a performance standpoint, SWE modeling can be accurate enough with a MNSL of two (2), with a substantial performance drop for a MNSL value of around nine (9). Additionally, the linear correlation between the values of the calibrated parameters and the MNSL indicated that reducing the latter in MASiN increased the fresh snow density and the settlement coefficient, while the maximum radiation coefficient decreased. In this case, MASiN favored the melting process, and thus the homogenization of snow layers occurred from the top layers of the snowpack in the modeling algorithm.
Keywords: Baraer_Michel; Rousseau_Alain

A WCSPH Particle Shifting Strategy for Simulating Violent Free Surface Flows - Krimi, Abdelkader; Jandaghian, Mojtaba; Shakibaeinia, Ahmad (Water, 2020)
In this work, we develop an enhanced particle shifting strategy in the framework of weakly compressible δ+-SPH method. This technique can be considered as an extension of the so-called improved particle shifting technology (IPST) proposed by Wang et al. (2019). We introduce a new parameter named “ϕ” to the particle shifting formulation, on the one hand to reduce the effect of truncated kernel support on the formulation near the free surface region, on the other hand, to deal with the problem of poor estimation of free surface particles. We define a simple criterion based on the estimation of particle concentration to limit the error’s accumulation in time caused by the shifting in order to achieve a long time violent free surface flows simulation. We propose also an efficient and simple concept for free surface particles detection. A validation of accuracy, stability and consistency of the presented model was shown via several challenging benchmarks.
Keywords: Ahmad_Shakibaeinia

Two‐ and three‐dimensional multiphase mesh‐free particle modeling of transitional landslide with μ ( I ) rheology - Jafari Nodoushan, Ehsan; Tajnesaie, Mohanna; Shakibaeinia, Ahmad (International Journal for Numerical Methods in Fluids, 2024)
Abstract Landslides, which are the sources of most catastrophic natural disasters, can be subaerial (dry), submerged (underwater), or semi‐submerged (transitional). Semi‐submerged or transitional landslides occur when a subaerial landslide enters water and turns to submerged condition. Predicting the behavior of such a highly dynamic multi‐phase granular flow system is challenging, mainly due to the water entry effects, such as wave impact and partial saturation (and resulted cohesion). The mesh‐free particle methods, such as the moving particle semi‐implicit (MPS) method, have proven their capabilities for the simulation of the highly dynamic multiphase systems. This study develops and evaluates a numerical model, based on the MPS particle method in combination with the μ ( I ) rheological model, to simulate the morphodynamic of the granular mass in semi‐submerged landslides in two and three dimensions. An algorithm is developed to consider partial saturation (and resulting cohesion) during the water entry. Comparing the numerical results with the experimental measurements shows the ability of the proposed model to accurately reproduce the morphological evolution of the granular mass, especially at the moment of water entry.
Keywords: Ahmad_Shakibaeinia; Infolettre; Infolettre_Fevrier_2024

Experimental and numerical investigations of dam break flow over dry and wet beds - Garoosi, Faroogh; Nicole Mellado-Cusicahua, Andrea; Shademani, Maryam; Shakibaeinia, Ahmad (International Journal of Mechanical Sciences, 2022)
Keywords: Ahmad_Shakibaeinia; Infolettre; Infolettre_Janvier_2022; Site_internet_RIISQ

A fully Lagrangian DEM-MPS mesh-free model for ice-wave dynamics - Amaro, Rubens Augusto; Mellado-Cusicahua, Andrea; Shakibaeinia, Ahmad; Cheng, Liang-Yee (Cold Regions Science and Technology, 2021)
Keywords: Ahmad_Shakibaeinia

Enhanced weakly-compressible MPS method for violent free-surface flows: Role of particle regularization techniques - Jandaghian, Mojtaba; Krimi, Abdelkader; Zarrati, Amir Reza; Shakibaeinia, Ahmad (Journal of Computational Physics, 2021)
Keywords: Ahmad_Shakibaeinia

An improved high-order ISPH method for simulation of free-surface flows and convection heat transfer - Garoosi, Faroogh; Shakibaeinia, Ahmad (Powder Technology, 2020)
Keywords: Ahmad_Shakibaeinia

Numerical simulation of free-surface flow and convection heat transfer using a modified Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) method - Garoosi, Faroogh; Shakibaeinia, Ahmad (International Journal of Mechanical Sciences, 2020)
Keywords: Ahmad_Shakibaeinia

An enhanced weakly-compressible MPS method for free-surface flows - Jandaghian, M.; Shakibaeinia, A. (Computer Methods in Applied Mechanics and Engineering, 2020)
Keywords: Ahmad_Shakibaeinia

Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models - Arsenault, Richard; Martel, Jean-Luc; Brunet, Frédéric; Brissette, François; Mai, Juliane (Hydrology and Earth System Sciences, 2023)
Abstract. This study investigates the ability of long short-term memory (LSTM) neural networks to perform streamflow prediction at ungauged basins. A set of state-of-the-art, hydrological model-dependent regionalization methods are applied to 148 catchments in northeast North America and compared to an LSTM model that uses the exact same available data as the hydrological models. While conceptual model-based methods attempt to derive parameterizations at ungauged sites from other similar or nearby catchments, the LSTM model uses all available data in the region to maximize the information content and increase its robustness. Furthermore, by design, the LSTM does not require explicit definition of hydrological processes and derives its own structure from the provided data. The LSTM networks were able to clearly outperform the hydrological models in a leave-one-out cross-validation regionalization setting on most catchments in the study area, with the LSTM model outperforming the hydrological models in 93 % to 97 % of catchments depending on the hydrological model. Furthermore, for up to 78 % of the catchments, the LSTM model was able to predict streamflow more accurately on pseudo-ungauged catchments than hydrological models calibrated on the target data, showing that the LSTM model's structure was better suited to convert the meteorological data and geophysical descriptors into streamflow than the hydrological models even calibrated to those sites in these cases. Furthermore, the LSTM model robustness was tested by varying its hyperparameters, and still outperformed hydrological models in regionalization in almost all cases. Overall, LSTM networks have the potential to change the regionalization research landscape by providing clear improvement pathways over traditional methods in the field of streamflow prediction in ungauged catchments.
Keywords: Brunet_Alain; Infolettre; Infolettre_Fevrier_2023

Impact of Natural Disasters on Household Income and Expenditure Inequality in China - Wang, Weiwei; Zhao, Yifan (Sustainability, 2023)
Natural disasters have been demonstrated to cause devastating effects on economic and social development in China, but little is known about the relationship between natural disasters and income at the household level. This study explores the impact of natural disasters on household income, expenditure, and inequality in China as the first study of this nature for the country. The empirical analysis is conducted based on a unique panel dataset that contains six waves of the Chinese Household Income Project (CHIP) survey data over the 1988–2018 period, data on natural disasters, and other social and economic status of households. By employing the fixed effects models, we find that disasters increase contemporaneous levels of income inequality, and disasters that occurred in the previous year significantly increase expenditure inequality. Natural disasters increase operating income inequality but decrease transfer income inequality. Poor households are found to be more vulnerable to disasters and suffer significant income losses. However, there is no evidence to suggest that natural disasters significantly reduce the income of upper- and middle-income groups. These findings have important implications for policies aimed at poverty alleviation and revenue recycling, as they can help improve economic justice and enhance resilience to natural disasters.

Risk assessment of drinking water intake contamination from agricultural activities using a Bayesian network - Kammoun, Raja; McQuaid, Natasha; Lessard, Vincent; Goitom, Eyerusalem Adhanom; Prévost, Michèle; Bichai, Françoise; Dorner, Sarah (PLOS Water, 2023)
Agricultural activities can result in the contamination of surface runoff with pathogens, pesticides, and nutrients. These pollutants can enter surface water bodies in two ways: by direct discharge into surface waters or by infiltration and recharge into groundwater, followed by release to surface waters. Lack of financial resources makes risk assessment through analysis of drinking water pollutants challenging for drinking water suppliers. Inability to identify agricultural lands with a high-risk level and implement action measures might lead to public health issues. As a result, it is essential to identify hazards and conduct risk assessments even with limited data. This study proposes a risk assessment model for agricultural activities based on available data and integrating various types of knowledge, including expert and literature knowledge, to estimate the levels of hazard and risk that different agricultural activities could pose to the quality of withdrawal waters. To accomplish this, we built a Bayesian network with continuous and discrete inputs capturing raw water quality and land use upstream of drinking water intakes (DWIs). This probabilistic model integrates the DWI vulnerability, threat exposure, and threats from agricultural activities, including animal and crop production inventoried in drainage basins. The probabilistic dependencies between model nodes are established through a novel adaptation of a mixed aggregation method. The mixed aggregation method, a traditional approach used in ecological assessments following a deterministic framework, involves using fixed assumptions and parameters to estimate ecological outcomes in a specific case without considering inherent randomness and uncertainty within the system. After validation, this probabilistic model was used for four water intakes in a heavily urbanized watershed with agricultural activities in the south of Quebec, Canada. The findings imply that this methodology can assist stakeholders direct their efforts and investments on at-risk locations by identifying agricultural areas that can potentially pose a risk to DWIs.
Keywords: Dorner_Sarah

Ambidexterity capacities for a recovery culture: Combination of logics and emergence of new practices - Normandin, Julie-Maude; Therrien, Marie-Christine; Baril, Geneviève; Daoust Gauthier, Marie (International Journal of Disaster Risk Reduction, 2022)
Keywords: Infolettre; Infolettre_Septembre_2022; Site_internet_RIISQ

How African Nova Scotians envision culturally relevant and sustaining pedagogy as civic repair - Jean-Pierre, Johanne (British Journal of Sociology of Education, 2021)

Modelling nutrient dynamics in cold agricultural catchments: A review - Costa, Diogo; Baulch, Helen; Elliott, Jane; Pomeroy, John; Wheater, Howard (Environmental Modelling & Software, 2020)

Insights from socio-hydrological modeling to design sustainable wastewater reuse strategies for agriculture at the watershed scale - Jeong, Hanseok; Bhattarai, Rabin; Adamowski, Jan; Yu, David J. (Agricultural Water Management, 2020)

A dual isotopic framework for identifying nitrate sources in surface runoff in a small agricultural watershed, northeast China - Sui, Yuanyuan; Ou, Yang; Yan, Baixing; Rousseau, Alain N.; Fang, Yunting; Geng, Runzhe; Wang, Lixia; Ye, Nan (Journal of Cleaner Production, 2020)
Keywords: Rousseau_Alain

Spatial–temporal variability of seasonal daily minimum flows in southern Quebec: synthesis on the impacts of climate, agriculture and wetlands - Assani, Ali; Zeroual, Ayoub; Kinnard, Christophe; Roy, Alexandre (Hydrology Research, 2022)
Abstract This study compares the impacts of climate, agriculture and wetlands on the spatio-temporal variability of seasonal daily minimum flows during the period 1930–2019 in 17 watersheds of southern Quebec (Canada). In terms of spatial variability, correlation analysis revealed that seasonal daily minimum flows were mainly negatively correlated with the agricultural surface area in watersheds in spring, summer and fall. In winter, these flows were positively correlated with the wetland surface area and March temperatures but negatively correlated with snowfall. During all four seasons, spatial variability was characterized by higher daily minimum flow values on the north shore (smaller agricultural surface area and larger wetland surface area) than those on the south shore. As for temporal variability, the application of six tests of the long-term trend analysis showed that most agricultural watersheds are characterized by a significant increase in flows during the four seasons due to the reduction in agricultural area, thus favoring water infiltration, and increased rainfall in summer and fall. On the other hand, the reduction in the snowfall resulted in a reduction in summer daily minimum flows observed in several less agricultural watersheds.
Keywords: Kinnard_Christophe

Effects of plants and biochar on the performance of treatment wetlands for removal of the pesticide chlorantraniliprole from agricultural runoff - Abas, Khalil; Brisson, Jacques; Amyot, Marc; Brodeur, Jacques; Storck, Veronika; Montiel-León, Juan Manuel; Duy, Sung Vo; Sauvé, Sébastien; Kõiv-Vainik, Margit (Ecological Engineering, 2022)

Impacts of Agricultural Areas on Spatio-Temporal Variability of Daily Minimum Extreme Flows during the Transitional Seasons (Spring and Fall) in Southern Quebec - Assani, Ali Arkamose; Zeroual, Ayoub; Roy, Alexandre; Kinnard, Christophe (Water, 2021)
Several statistical methods were used to analyze the spatio-temporal variability of daily minimum extreme flows (DMEF) in 17 watersheds—divided into three homogenous hydroclimatic regions of southern Quebec—during the transitional seasons (spring and fall), during the 1930–2019 period. Regarding spatial variability, there was a clear difference between the south and north shores of the St. Lawrence River, south of 47° N. DMEF were lower in the more agricultural watersheds on the south shore during transitional seasons compared to those on the north shore. A correlation analysis showed that this difference in flows was mainly due to more agricultural areas ((larger area (>20%) on the south than on the north shore (<5%)). An analysis of the long-term trend of these flows showed that the DMEF of south-shore rivers have increased significantly since the 1960s, during the fall (October to December), due to an increase in rainfall and a reduction in cultivated land, which increased the infiltration in the region. Although there was little difference between the two shores in the spring (April to June), we observed a decrease in minimum extreme flows in half (50%) of the south-shore rivers located north of 47° N.
Number: 24 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Infolettre; Infolettre_Janvier_2022; Kinnard_Christophe; Site_internet_RIISQ

Preconception and prenatal maternal stress are associated with broad autism phenotype in young adults: Project Ice Storm - Li, Xinyuan; Laplante, David P.; Elgbeili, Guillaume; King, Suzanne (Journal of Developmental Origins of Health and Disease, 2023)
Studies show associations between prenatal maternal stress (PNMS) and child autism, with little attention paid to PNMS and autism in young adulthood. The broad autism phenotype (BAP), encompassing sub-clinical levels of autism, includes aloof personality, pragmatic language impairment and rigid personality. It remains unclear whether different aspects of PNMS explain variance in different BAP domains in young adult offspring. We recruited women who were pregnant during, or within 3 months of, the 1998 Quebec ice storm crisis, and assessed three aspects of their stress (i.e., objective hardship, subjective distress and cognitive appraisal). At age 19, the young adult offspring (n = 33, 22F / 11M) completed a BAP self-report. Linear and logistic regressions were implemented to examine associations between PNMS and BAP traits. Up to 21.4% of the variance in BAP total score and in BAP three domains tended to be explained by at least one aspect of maternal stress, For example, 16.8% of the variance in aloof personality tended to be explained by maternal objective hardship; 15.1% of the variance in pragmatic language impairment tended to be explained by maternal subjective distress; 20.0% of the variance in rigid personality tended to be explained by maternal objective hardship and 14.3% by maternal cognitive appraisal. Given the small sample size, the results should be interpreted with caution. In conclusion, this small prospective study suggests that different aspects of maternal stress could have differential effects on different components of BAP traits in young adults.
Keywords: Infolettre; Infolettre_Ete_2023

Statistical Damage Constitutive Model for Anhydrite Rock under Freeze–Thaw Cycles Considering the Residual Strength and Postpeak Stress Dropping Rate - Hou, Chao; Jin, Xiaoguang; He, Jie; Li, Hanlin (International Journal of Geomechanics, 2023)
Keywords: Infolettre; Infolettre_Avril_2023; Infolettre_Mai_2023

Atypical brain structure and function in young adults exposed to disaster‐related prenatal maternal stress: Project Ice Storm - Li, Xinyuan; Qureshi, Muhammad Naveed Iqbal; Laplante, David P.; Elgbeili, Guillaume; Jones, Sherri Lee; Long, Xiangyu; Paquin, Vincent; Bezgin, Gleb; Lussier, Firoza; King, Suzanne; Rosa‐Neto, Pedro (Journal of Neuroscience Research, 2023)
Abstract Studies have shown that prenatal maternal stress (PNMS) affects brain structure and function in childhood. However, less research has examined whether PNMS effects on brain structure and function extend to young adulthood. We recruited women who were pregnant during or within 3 months following the 1998 Quebec ice storm, assessed their PNMS, and prospectively followed‐up their children. T1‐weighted magnetic resonance imaging (MRI) and resting‐state functional MRI were obtained from 19‐year‐old young adults with ( n = 39) and without ( n = 65) prenatal exposure to the ice storm. We examined between‐group differences in gray matter volume (GMV), surface area (SA), and cortical thickness (CT). We used the brain regions showing between‐group GMV differences as seeds to compare between‐group functional connectivity. Within the Ice Storm group, we examined (1) associations between PNMS and the atypical GMV, SA, CT, and functional connectivity, and (2) moderation by timing of exposure. Primarily, we found that, compared to Controls, the Ice Storm youth had larger GMV and higher functional connectivity of the anterior cingulate cortex, the precuneus, the left occipital pole, and the right hippocampus; they also had larger CT, but not SA, of the left occipital pole. Within the Ice Storm group, maternal subjective distress during preconception and mid‐to‐late pregnancy was associated with atypical left occipital pole CT. These results suggest the long‐lasting impact of disaster‐related PNMS on child brain structure and functional connectivity. Our study also indicates timing‐specific effects of the subjective aspect of PNMS on occipital thickness.
Keywords: Infolettre; Infolettre_Octobre_2023

Using Exploratory Structural Equation Modeling (ESEM) to Examine the Internal Structure of Posttraumatic Stress Disorder Symptoms - Fresno, Andrés; Arias, Víctor; Núñez, Daniel; Spencer, Rosario; Ramos, Nadia; Espinoza, Camila; Bravo, Patricia; Arriagada, Jessica; Brunet, Alain (The Spanish Journal of Psychology, 2020)
Abstract Several studies have reported the factor structure of posttraumatic stress disorder (PTSD) using confirmatory factor analysis (CFA). The results show models with different number of factors, high correlations between factors, and symptoms that belong to different factors in different models without affecting the fit index. These elements could suppose the existence of considerable item cross-loading, the overlap of different factors or even the presence of a general factor that explains the items common source of variance. The aim is to provide new evidence regarding the factor structure of PTSD using CFA and exploratory structural equation modeling (ESEM). In a sample of 1,372 undergraduate students, we tested six different models using CFA and two models using ESEM and ESEM bifactor analysis. Trauma event and past-month PTSD symptoms were assessed with Life Events Checklist for DSM-5 (LEC–5) and PTSD Checklist for DSM-5 (PCL–5). All six tested CFA models showed good fit indexes (RMSEA = .051–.056, CFI = .969–.977, TLI = .965–.970), with high correlations between factors ( M = .77, SD = .09 to M = .80, SD = .09). The ESEM models showed good fit indexes (RMSEA = .027–.036, CFI = .991–.996, TLI = .985–.992). These models confirmed the presence of cross-loadings on several items as well as loads on a general factor that explained 76.3% of the common variance. The results showed that most of the items do not meet the assumption of dimensional exclusivity, showing the need to expand the analysis strategies to study the symptomatic organization of PTSD.
Keywords: Brunet_Alain

Nanoplastics in Water: Artificial Intelligence-Assisted 4D Physicochemical Characterization and Rapid In Situ Detection - Wang, Zi; Pal, Devendra; Pilechi, Abolghasem; Ariya, Parisa A. (Environmental Science & Technology, 2024)

Contributions of climate, elevated atmospheric CO2 concentration and land surface changes to variation in water use efficiency in Northwest China - Yang, Linshan; Feng, Qi; Wen, Xiaohu; Barzegar, Rahim; Adamowski, Jan F; Zhu, Meng; Yin, Zhenliang (CATENA, 2022)

Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies - Tarek, Mostafa; Brissette, François; Arsenault, Richard (Hydrology and Earth System Sciences, 2021)
Abstract. Climate change impact studies require a reference climatological dataset providing a baseline period to assess future changes and post-process climate model biases. High-resolution gridded precipitation and temperature datasets interpolated from weather stations are available in regions of high-density networks of weather stations, as is the case in most parts of Europe and the United States. In many of the world's regions, however, the low density of observational networks renders gauge-based datasets highly uncertain. Satellite, reanalysis and merged product datasets have been used to overcome this deficiency. However, it is not known how much uncertainty the choice of a reference dataset may bring to impact studies. To tackle this issue, this study compares nine precipitation and two temperature datasets over 1145 African catchments to evaluate the dataset uncertainty contribution to the results of climate change studies. These deterministic datasets all cover a common 30-year period needed to define the reference period climate. The precipitation datasets include two gauge-only products (GPCC and CPC Unified), two satellite products (CHIRPS and PERSIANN-CDR) corrected using ground-based observations, four reanalysis products (JRA55, NCEP-CFSR, ERA-I and ERA5) and one merged gauged, satellite and reanalysis product (MSWEP). The temperature datasets include one gauged-only (CPC Unified) product and one reanalysis (ERA5) product. All combinations of these precipitation and temperature datasets were used to assess changes in future streamflows. To assess dataset uncertainty against that of other sources of uncertainty, the climate change impact study used a top-down hydroclimatic modeling chain using 10 CMIP5 (fifth Coupled Model Intercomparison Project) general circulation models (GCMs) under RCP8.5 and two lumped hydrological models (HMETS and GR4J) to generate future streamflows over the 2071–2100 period. Variance decomposition was performed to compare how much the different uncertainty sources contribute to actual uncertainty. Results show that all precipitation and temperature datasets provide good streamflow simulations over the reference period, but four precipitation datasets outperformed the others for most catchments. They are, in order, MSWEP, CHIRPS, PERSIANN and ERA5. For the present study, the two-member ensemble of temperature datasets provided negligible levels of uncertainty. However, the ensemble of nine precipitation datasets provided uncertainty that was equal to or larger than that related to GCMs for most of the streamflow metrics and over most of the catchments. A selection of the four best-performing reference datasets (credibility ensemble) significantly reduced the uncertainty attributed to precipitation for most metrics but still remained the main source of uncertainty for some streamflow metrics. The choice of a reference dataset can therefore be critical to climate change impact studies as apparently small differences between datasets over a common reference period can propagate to generate large amounts of uncertainty in future climate streamflows.

Climate change and the nonlinear impact of precipitation anomalies on income inequality - Palagi, Elisa; Coronese, Matteo; Lamperti, Francesco; Roventini, Andrea (Proceedings of the National Academy of Sciences, 2022)
Climate anomalies, such as floods and droughts, as well as gradual temperature changes have been shown to adversely affect economies and societies. Although studies find that climate change might increase global inequality by widening disparities across countries, its effects on within-country income distribution have been little investigated, as has the role of rainfall anomalies. Here, we show that extreme levels of precipitation exacerbate within-country income inequality. The strength and direction of the effect depends on the agricultural intensity of an economy. In high-agricultural-intensity countries, climate anomalies that negatively impact the agricultural sector lower incomes at the bottom end of the distribution and generate greater income inequality. Our results indicate that a 1.5-SD increase in precipitation from average values has a 35-times-stronger impact on the bottom income shares for countries with high employment in agriculture compared to countries with low employment in the agricultural sector. Projections with modeled future precipitation and temperature reveal highly heterogeneous patterns on a global scale, with income inequality worsening in high-agricultural-intensity economies, particularly in Africa. Our findings suggest that rainfall anomalies and the degree of dependence on agriculture are crucial factors in assessing the negative impacts of climate change on the bottom of the income distribution.

A temporal downscaling approach for sub-daily gridded extreme rainfall intensity estimation under climate change - Requena, Ana I.; Nguyen, Truong-Huy; Burn, Donald H.; Coulibaly, Paulin; Nguyen, Van-Thanh-Van (Journal of Hydrology: Regional Studies, 2021)

Beyond fear: The role of emotions in disaster risk reduction in the face of climate change - Lizarralde, Gonzalo; Lajoie, Steffen; Gould, Kevin; Araneda, Claudio; Cruz-Panesso, Ilian; Diaz, Julia Helena; Monsalve, Elsa; Burdiles, Roberto; Herazo, Benjamin; Páez, Holmes; Valladares, Arturo; Bornstein, Lisa; et al. (Emotion, Space and Society, 2025)
Keywords: Infolettre; Infolettre_Decembre_2024

Does climate change cause disasters? How citizens, academics, and leaders explain climate-related risk and disasters in Latin America and the Caribbean - Lizarralde, Gonzalo; Bornstein, Lisa; Robertson, Mélanie; Gould, Kevin; Herazo, Benjamín; Petter, Anne-Marie; Páez, Holmes; Díaz, Julia Helena; Olivera, Andrés; González, Gonzalo; López, Oswaldo; López, Adriana; et al. (International Journal of Disaster Risk Reduction, 2021)
Keywords: Lizarralde_Gonzalo

Climate Change and Rainfall Intensity–Duration–Frequency Curves: Overview of Science and Guidelines for Adaptation - Martel, Jean-Luc; Brissette, François P.; Lucas-Picher, Philippe; Troin, Magali; Arsenault, Richard (Journal of Hydrologic Engineering, 2021)

We said, they said: the politics of conceptual frameworks in disasters and climate change in Colombia and Latin America - Lizarralde, Gonzalo; Páez, Holmes; Lopez, Adriana; Lopez, Oswaldo; Bornstein, Lisa; Gould, Kevin; Herazo, Benjamin; Muñoz, Lissette (Disaster Prevention and Management: An International Journal, 2020)
Purpose Few people living in informal settlements in the Global South spontaneously claim that they are “resilient” or “adapting” to disaster risk or climate change. Surely, they often overcome multiple challenges, including natural hazards exacerbated by climate change. Yet their actions are increasingly examined through the framework of resilience, a notion developed in the North, and increasingly adopted in the South. To what extent eliminate’ do these initiatives correspond to the concepts that scholars and authorities place under the resilience framework? Design/methodology/approach Three longitudinal case studies in Yumbo, Salgar and San Andrés (Colombia) serve to investigate narratives of disaster risks and responses to them. Methods include narrative analysis from policy and project documents, presentations, five workshops, six focus groups and 24 interviews. Findings The discourse adopted by most international scholars and local authorities differs greatly from that used by citizens to explain risk and masks the politics involved in disaster reduction and the search for social justice. Besides, narratives of social change, aspirations and social status are increasingly masked in disaster risk explanations. Tensions are also concealed, including those regarding the winners and losers of interventions and the responsibilities for disaster risk reduction. Originality/value Our findings confirm previous results that have shown that the resilience framework contributes to “depoliticize” the analysis of risk and serves to mask and dilute the responsibility of political and economic elites in disaster risk creation. But they also show that resilience fails to explain the type of socioeconomic change that is required to reduce vulnerabilities in Latin America.
Keywords: Lizarralde_Gonzalo

Welfare in the 21st century: Increasing development, reducing inequality, the impact of climate change, and the cost of climate policies - Lomborg, Bjorn (Technological Forecasting and Social Change, 2020)

How children make sense of climate change: A descriptive qualitative study of eco-anxiety in parent-child dyads - Léger-Goodes, Terra; Malboeuf-Hurtubise, Catherine; Hurtubise, Karen; Simons, Kyra; Boucher, Amélie; Paradis, Pier-Olivier; Herba, Catherine M.; Camden, Chantal; Généreux, Mélissa (PLOS ONE, 2023)
The climate crisis not only has significant impacts on biodiversity and the physical health of humans, but its ramifications are also affecting people’s mental health. Eco-anxiety, or the emotions that emerge with the awareness of climate change and the apprehension of its detrimental effects, has been investigated in adults and adolescents, but much less attention has been given to the impacts on children’s mental health and well-being. Initial evidence confirms that youth are significantly concerned about climate change, but few studies have investigated the resulting emotional responses of children and the role of their parents in tempering these, especially using qualitative methodologies. The present study used a descriptive qualitative design with a convenience sample of parents and child dyads, assessed separately. Children’s ( n = 15, ages 8–12 years) experiences were explored using semi-structured interviews and their parents’ ( n = 12) perceptions were captured using a survey with closed and open-ended questions. A reflexive thematic analysis was used to analyze the interview data, and content analysis was used to investigate parent-child experiences. Three themes emerged from the thematic analysis: 1. children’s understanding of climate change, 2. their emotional reaction to climate change, and 3. their coping mechanisms to deal with these emotions. The comparative content analysis revealed that parents who were aware that their children had concerns about climate change, had children who used more adaptive coping mechanisms. The results of this qualitative study contribute to a better understanding of children’s emotional experience of the awareness of climate change in Canada and how they cope with these emotions. Furthermore, the results provide insight into the role parents might play in helping their children cope with their feelings.
Keywords: Généreux_Mélissa

Changes in extreme precipitation indices across Algeria climate zones - Hamitouche, Yasmine; Zeroual, Ayoub; Meddi, Mohamed; Assani, Ali Arkamose; Alkama, Ramdane (International Journal of Climatology, 2024)
Abstract Extreme precipitation events can have a significant impact on the environment, agriculture, economy and safety, making close monitoring of their short‐ and long‐term trends essential for the development of effective mitigation and adaptation strategies. In this study, we analysed 16 in situ observation datasets from four different climate zones in Algeria, spanning from 1969 to 2021. The trend analysis was conducted using the original Mann–Kendall test and seven modified tests to eliminate the effects of short‐term persistence. Our findings reveal a significant increasing trend of extreme precipitation variability for most stations in the Warm Mediterranean climate zone, except for the Consecutive dry days index, which showed a negative trend for the same zone, while stations in the Cold/Warm semi‐arid climate and Cold desert climate (Bwk) zones showed a decreasing trend. Additionally, all index series with significant long‐term trends were affected by a significant shift in their means, which was confirmed by both the Lombard and Pettitt tests. However, when we used the modified MPT and the test eliminating the effects of long‐term persistence, the significance of the shifts and the trend decreased. Our results suggest that while extreme precipitation events have been increasing in some parts of Algeria; the trend may not be statistically significant in the long‐run, indicating the necessity of revisiting and refreshing the findings of previous studies for a more current perspective.
Keywords: Infolettre; Infolettre_Ete_2024; Site_internet_RIISQ

Risk perception—A lens for understanding adaptive behaviour in the age of climate change? Narratives from the Global South - Dhar, Tapan; Bornstein, Lisa; Lizarralde, Gonzalo; Nazimuddin, S.M. (International Journal of Disaster Risk Reduction, 2023)
Keywords: Infolettre; Infolettre_Septembre_2023; Lizarralde_Gonzalo

The archaeology of climate change: The case for cultural diversity - Burke, Ariane; Peros, Matthew C.; Wren, Colin D.; Pausata, Francesco S. R.; Riel-Salvatore, Julien; Moine, Olivier; De Vernal, Anne; Kageyama, Masa; Boisard, Solène (Proceedings of the National Academy of Sciences, 2021)
Anthropogenic climate change is currently driving environmental transformation on a scale and at a pace that exceeds historical records. This represents an undeniably serious challenge to existing social, political, and economic systems. Humans have successfully faced similar challenges in the past, however. The archaeological record and Earth archives offer rare opportunities to observe the complex interaction between environmental and human systems under different climate regimes and at different spatial and temporal scales. The archaeology of climate change offers opportunities to identify the factors that promoted human resilience in the past and apply the knowledge gained to the present, contributing a much-needed, long-term perspective to climate research. One of the strengths of the archaeological record is the cultural diversity it encompasses, which offers alternatives to the solutions proposed from within the Western agro-industrial complex, which might not be viable cross-culturally. While contemporary climate discourse focuses on the importance of biodiversity, we highlight the importance of cultural diversity as a source of resilience.

Evaluation of the Impact of Climate Change on Runoff Generation in an Andean Glacier Watershed - Escanilla-Minchel, Rossana; Alcayaga, Hernán; Soto-Alvarez, Marco; Kinnard, Christophe; Urrutia, Roberto (Water, 2020)
Excluding Antarctica and Greenland, 3.8% of the world’s glacier area is concentrated in Chile. The country has been strongly affected by the mega drought, which affects the south-central area and has produced an increase in dependence on water resources from snow and glacier melting in dry periods. Recent climate change has led to an elevation of the zero-degree isotherm, a decrease in solid-state precipitation amounts and an accelerated loss of glacier and snow storage in the Chilean Andes. This situation calls for a better understanding of future water discharge in Andean headwater catchments in order to improve water resources management in glacier-fed populated areas. The present study uses hydrological modeling to characterize the hydrological processes occurring in a glacio-nival watershed of the central Andes and to examine the impact of different climate change scenarios on discharge. The study site is the upper sub-watershed of the Tinguiririca River (area: 141 km2), of which nearly 20% is covered by Universidad Glacier. The semi-distributed Snowmelt Runoff Model + Glacier (SRM+G) was forced with local meteorological data to simulate catchment runoff. The model was calibrated on even years and validated on odd years during the 2008–2014 period and found to correctly reproduce daily runoff. The model was then forced with downscaled ensemble projected precipitation and temperature series under the RCP 4.5 and RCP 8.5 scenarios, and the glacier adjusted using a volume-area scaling relationship. The results obtained for 2050 indicate a decrease in mean annual discharge (MAD) of 18.1% for the lowest emission scenario and 43.3% for the most pessimistic emission scenario, while for 2100 the MAD decreases by 31.4 and 54.2%, respectively, for each emission scenario. Results show that decreasing precipitation lead to reduced rainfall and snowmelt contributions to discharge. Glacier melt thus partly buffers the drying climate trend, but our results show that the peak water occurs near 2040, after which glacier depletion leads to reducing discharge, threatening the long-term water resource availability in this region.
Keywords: Kinnard_Christophe

Integrated assessment of localized SSP–RCP narratives for climate change adaptation in coupled human-water systems - Alizadeh, Mohammad Reza; Adamowski, Jan; Inam, Azhar (Science of The Total Environment, 2022)

Impacts of climate change on the hydrology of northern midlatitude cold regions - Aygün, Okan; Kinnard, Christophe; Campeau, Stéphane (Progress in Physical Geography: Earth and Environment, 2020)
Cold region hydrology is conditioned by distinct cryospheric and hydrological processes. While snowmelt is the main contributor to both surface and subsurface flows, seasonally frozen soil also influences the partition of meltwater and rain between these flows. Cold regions of the Northern Hemisphere midlatitudes have been shown to be sensitive to climate change. Assessing the impacts of climate change on the hydrology of this region is therefore crucial, as it supports a significant amount of population relying on hydrological services and subjected to changing hydrological risks. We present an exhaustive review of the literature on historical and projected future changes on cold region hydrology in response to climate change. Changes in snow, soil, and streamflow key metrics were investigated and summarized at the hemispheric scale, down to the basin scale. We found substantial evidence of both historical and projected changes in the reviewed hydrological metrics. These metrics were shown to display different sensitivities to climate change, depending on the cold season temperature regime of a given region. Given the historical and projected future warming during the 21st century, the most drastic changes were found to be occurring over regions with near-freezing air temperatures. Colder regions, on the other hand, were found to be comparatively less sensitive to climate change. The complex interactions between the snow and soil metrics resulted in either colder or warmer soils, which led to increasing or decreasing frost depths, influencing the partitioning rates between the surface and subsurface flows. The most consistent and salient hydrological responses to both historical and projected climate change were an earlier occurrence of snowmelt floods, an overall increase in water availability and streamflow during winter, and a decrease in water availability and streamflow during the warm season, which calls for renewed assessments of existing water supply and flood risk management strategies.
Keywords: Kinnard_Christophe

Investigation of the Multi-Scale Deterioration Mechanisms of Anhydrite Rock Exposed to Freeze–Thaw Environment - Jin, Xiaoguang; Hou, Chao; He, Jie; Dias, Daniel (Materials, 2024)
The deterioration of anhydrite rock exposed to a freeze–thaw environment is a complex process. Therefore, this paper systematically investigated the physical and mechanical evolutions of freeze–thawed anhydrite rock through a series of multi-scale laboratory tests. Meanwhile, the correlation between pore structure and macroscopic mechanical parameters was discussed, and the deterioration mechanisms of anhydrite rock under freeze–thaw cycles were revealed. The results show that with the increase in freeze–thaw processes, the mechanical strength, elastic modulus, cohesion, proportions of micropores (r ≤ 0.1 μm), and PT-Ipore throat (0–0.1 μm) decrease exponentially. In comparison, the mass variation, proportions of mesopores (0.1 μm < r < 1 μm), macropores (r ≥ 1 μm), and PT-II pore throat (0.1–4 μm) increase exponentially. After 120 cycles, the mean porosity increases by 66.27%, and there is a significant honeycomb and pitted surface phenomenon. Meanwhile, as the freeze–thaw cycles increase, the frost resistance coefficient decreases, while the damage variable increases. The correlation analysis between pore structure and macroscopic mechanical parameters shows that macropores play the most significant role in the mechanical characteristic deterioration of freeze–thawed anhydrite rock. Finally, it is revealed that the water–rock expansion and water dissolution effects play a crucial role in the multi-scale damage of anhydrite rock under the freeze–thaw environment.
Keywords: Infolettre; Infolettre_Fevrier_2024

Fine‐scale environment control on ground surface temperature and thaw depth in a High Arctic tundra landscape - Khani, Hadi Mohammadzadeh; Kinnard, Christophe; Gascoin, Simon; Lévesque, Esther (Permafrost and Periglacial Processes, 2023)
Abstract Surface conditions are known to mediate the impacts of climate warming on permafrost. This calls for a better understanding of the environmental conditions that control the thermal regime and the depth of the active layer, especially within heterogeneous tundra landscapes. This study analyzed the spatial relationships between thaw depths, ground surface temperature (GST), and environmental conditions in a High Arctic tundra environment at Bylot Island, Nunavut, Canada. Measurements were distributed within the two dominant landforms, namely earth hummocks and low‐center polygons, and across a topographic gradient. Our results revealed that GST and thaw depth were highly heterogeneous, varying by up to 3.7°C and by more than 20 cm over short distances (<1 m) within periglacial landforms. This microscale variability sometimes surpassed the variability at the hillslope scale, especially in summer. Late‐winter snowpack thickness was found to be the prime control on the spatial variability in winter soil temperatures due to the highly heterogeneous snow cover induced by blowing snow, and this thermal effect carried over into summer. However, microtopography was the predominant driver of the spatial variability in summer GST, followed by altitude and moss thickness. In contrast, the spatial variability in thaw depth was influenced predominantly by variations in moss thickness. Hence, summer microclimate conditions dominated active layer development, but a thicker snowpack favored soil cooling in the following summer, due to the later disappearance of snow cover. These results enhance our understanding of High Arctic tundra environments and highlight the complexity of considering surface feedback effects in future projections of permafrost states within heterogeneous tundra landscapes.
Keywords: Kinnard_Christophe

Evaluating Operational Risk in Environmental Modeling: Assessment of Reliability and Sharpness for Ensemble Selection - Pokorny, Scott; Stadnyk, Tricia A.; Ali, Genevieve (Journal of Hydrologic Engineering, 2023)

Ice Nucleation of Pharmaceutical and Synthetic Organic Emerging Contaminants: The Impact of Selected Environmental Conditions - Kaur, Japandeep; Ganguly, Mainak; Rangel-Alvardo, Rodrigo; Pal, Devendra; Hall, Ryan; Ariya, Parisa A. (ACS Earth and Space Chemistry, 2022)

Risks and the Anthropocene: Alternative Views on the Environmental Emergency - Rebotier, J (Wiley, 2022)
Keywords: Nobert_Sebastien

Hydrological behaviour of an ice‐layered snowpack in a non‐mountainous environment - Paquotte, Andrea; Baraer, Michel (Hydrological Processes, 2022)
Abstract The increased frequency of mild rain‐on‐snow (R.O.S.) events in cold regions associated with climate change is projected to affect snowpack structure and hydrological behaviour. The ice layers that form in a cold snowpack when R.O.S. events occur have been shown to influence flowthrough processes and liquid water retention, with consequences for winter floods, groundwater recharge, and water resources management. This study explores interconnections between meteorological conditions, ice layer formation, and lateral flows during R.O.S. events throughout the 2018–2019 winter in meridional Quebec, Canada. Automated hydro‐meteorological measurements, such as water availability for runoff, snow water equivalent, and snowpit observations, are used to compute water and energy balances, making it possible to characterize a snowpack's internal conditions and flowthrough regimes. For compatibility assessment, water and energy balances‐based flowthrough scenarios are then compared to different hydro‐meteorological variables', such as water table or streamlet water levels. The results show an association between highly variable meteorological conditions, frequent R.O.S. events, and ice layer formation. Lateral flows were mainly observed during the early stage of the ablation period. The hydrologically significant lateral flows observed in the study are associated with winter conditions that are predicted to become more frequent in a changing climate, stressing the need for further evaluation of their potential impact at the watershed scale.
Keywords: Baraer_Michel; Infolettre; Infolettre_Ete_2023

Evaluating the Ubiquity of Thresholds in Rainfall‐Runoff Response Across Contrasting Environments - Ross, Cody A.; Ali, Geneviève A.; Spence, Christopher; Courchesne, François (Water Resources Research, 2021)
Abstract Thresholds in precipitation‐runoff relationships have been observed in numerous studies using scatter plots comparing meteorological factors and hydrologic response metrics. Most thresholds reported in the literature have been identified from relationships between meteorological factors that quantify volumes or depths of water (e.g., total event rainfall) and metrics capturing hydrologic response magnitude (e.g., runoff ratio), with a strong emphasis on hillslopes and catchments in temperate humid environments. Knowledge gaps, however, remain regarding the ubiquity of hydrologic thresholds across different climatic environments and different meteorological factors that affect different response metrics. This study therefore aimed to evaluate relationships for a wide range of meteorological factors and response metrics derived from event‐scale rainfall‐runoff analysis for 21 sites spanning seven contrasting geographic areas. Specifically, meteorological factors quantifying rainfall depth, rainfall intensity, and hydrologic abstractions related to evapotranspiration were considered, along with response metrics that describe response timing and response magnitude, leading to 4,557 relationships being evaluated. While rainfall depth thresholds were observed for most sites, rainfall intensity thresholds were also observed. Additionally, threshold behavior was shown to be sensitive to antecedent conditions over specific durations of time preceding a rainfall‐runoff event. The large number of relationships evaluated in this study allowed for the development of a typology of threshold dynamics and the formulation of hypotheses about dominant hydrological processes. This typology may not only promote standardized threshold descriptions but also make intersite comparisons of nonlinear rainfall‐runoff behavior easier. , Key Points While water volume thresholds dominate the literature, rainfall intensity thresholds were observed even at sites with humid climates Threshold behavior is sensitive to antecedent conditions over specific durations of time preceding a rainfall‐runoff event A newly proposed typology of threshold dynamics may be used toward standardized threshold descriptions and intersite comparisons

Cumulative Effects of Watershed Disturbances and Run-of-river Dams on Mercury Cycling: Case Study and Recommendations for Environmental Managers - Amyot, M.; Bilodeau, F.; Tremblay, A.; Planas, D.; Walsh, D.; Ponton, D. E. (Environmental Management, 2024)
Abstract Run-of-river power plants (ROR) represent the majority of hydroelectric plants worldwide. Their environmental impacts are not well documented and are believed to be limited, particularly regarding the contamination of food webs by methylmercury (MeHg), a neurotoxin. RORs are typically installed in small rivers where combined effects of watershed disturbances with dam construction can complicate environmental management. We report a multi-year case study on the Saint-Maurice River (Canada) where an unpredicted temporary increase in MeHg accumulation in predator fish was observed after the construction of two ROR plants. The associated pondages acted as sedimentation basins for mercury (Hg) and organic matter from a watershed disturbed by a forest fire and by logging. This fresh organic carbon likely fueled microbial MeHg production. Hg methylation was more associated with environmental conditions than to the presence of Hg, and main methylating microbial groups were identified. A constructed wetland was a site of significant Hg methylation but was not the main source of the fish Hg increase. Organic carbon degradation was the main driver of MeHg accumulation at the base of the food chain whereas trophic levels explained the variations at the top of the food chain. Overall, carbon cycling was a key driver of Hg dynamics in this system, and ROR plants can cause temporary (ca. 12 years) Hg increase in food webs when developed in disturbed watersheds, although this increase is smaller than for large reservoirs. Recommendations for future ROR construction are to establish a good environmental monitoring plan with initial high temporal resolution and to consider recent and potential watershed disturbances in the plan.

Experimental and Numerical Simulation Investigation of the Mechanical Properties of Anhydrite Rock Under Freeze–Thaw Environment - Hou, Chao; Jin, Xiaoguang; Zhai, Shengtian; He, Jie; Lei, Ruide; Dias, Daniel (Geotechnical and Geological Engineering, 2024)
To study the mechanical and cracking modes of anhydrite rock under the freeze–thaw weathering process, the physico-mechanical characteristics and morphology evolutions of anhydrite samples were determined by a series of laboratory tests. Then, a numerical simulation model was established through the PFC2D program, and the types and number of cracks during the uniaxial compression conditions were analyzed. Finally, the distribution of maximum principal stress and shear stress was revealed. The results indicate that as the number of freeze–thaw cycles increases, there is a growth in the mass loss rate and macroscopic damage variables while the uniaxial compression strength and elastic modulus decrease exponentially. Under uniaxial compression stress, the proportion of tensile cracks in the anhydrite model is the highest, followed by tensile shear cracks and compressive shear cracks. As the number of freeze–thaw cycles increases, the proportion of tensile cracks increases exponentially, while the proportion of tensile shear cracks and compressive shear cracks decreases exponentially. Furtherly, it is found that the maximum principal stress and maximum shear stress extreme values decrease exponentially with the increase of freeze–thaw cycles. For example, after 120 cycles, the maximum shear stress at the peak stress point decreased by 47.3%. The research results will promote the comprehension of anhydrite rock geotechnical engineering disaster mechanisms in cold regions.
Keywords: Infolettre; Infolettre_Mai_2024

Topographic and vegetation controls of the spatial distribution of snow depth in agro-forested environments by UAV lidar - Dharmadasa, Vasana; Kinnard, Christophe; Baraër, Michel (The Cryosphere, 2023)
Abstract. Accurate knowledge of snow depth distributions in forested regions is crucial for applications in hydrology and ecology. In such a context, understanding and assessing the effect of vegetation and topographic conditions on snow depth variability is required. In this study, the spatial distribution of snow depth in two agro-forested sites and one coniferous site in eastern Canada was analyzed for topographic and vegetation effects on snow accumulation. Spatially distributed snow depths were derived by unmanned aerial vehicle light detection and ranging (UAV lidar) surveys conducted in 2019 and 2020. Distinct patterns of snow accumulation and erosion in open areas (fields) versus adjacent forested areas were observed in lidar-derived snow depth maps at all sites. Omnidirectional semi-variogram analysis of snow depths showed the existence of a scale break distance of less than 10 m in the forested area at all three sites, whereas open areas showed comparatively larger scale break distances (i.e., 11–14 m). The effect of vegetation and topographic variables on the spatial variability in snow depths at each site was investigated with random forest models. Results show that the underlying topography and the wind redistribution of snow along forest edges govern the snow depth variability at agro-forested sites, while forest structure variability dominates snow depth variability in the coniferous environment. These results highlight the importance of including and better representing these processes in physically based models for accurate estimates of snowpack dynamics.
Keywords: Baraer_Michel; Kinnard_Christophe

Greening the color line: historicizing water infrastructure redevelopment and environmental justice in the St. Louis metropolitan region - Heck, Sarah (Journal of Environmental Policy & Planning, 2021)

Using the ecosystem serviceshed concept in conservation planning for more equitable outcomes - Goyette, Jean-Olivier; Mendes, Poliana; Cimon-Morin, Jérôme; Dupras, Jérôme; Pellerin, Stéphanie; Rousseau, Alain N.; Poulin, Monique (Ecosystem Services, 2024)
Keywords: Infolettre; Infolettre_Avril_2024

International Guidelines on Natural and Nature-Based Features - Bridges, Todd; Simm, Jonathan; King, Jeffrey (Science and practice for an uncertain future, 2021)

Evaluating the impact of the Central Chile Mega Drought on debris cover, broadband albedo, and surface drainage system of a Dry Andes glacier - Podgórski, Julian; Pętlicki, Michał; Fernández, Alfonso; Urrutia, Roberto; Kinnard, Christophe (Science of The Total Environment, 2023)
Keywords: Kinnard_Christophe

How extreme are flood peak distributions? A quasi-global analysis of daily discharge records - Zaerpour, Masoud; Papalexiou, Simon Michael; Pietroniro, Alain; Nazemi, Ali (Journal of Hydrology, 2024)
Keywords: Infolettre; Infolettre_Avril_2024

Understanding Uncertainty in Probabilistic Floodplain Mapping in the Time of Climate Change - Zahmatkesh, Zahra; Han, Shasha; Coulibaly, Paulin (Water, 2021)
An integrated framework was employed to develop probabilistic floodplain maps, taking into account hydrologic and hydraulic uncertainties under climate change impacts. To develop the maps, several scenarios representing the individual and compounding effects of the models’ input and parameters uncertainty were defined. Hydrologic model calibration and validation were performed using a Dynamically Dimensioned Search algorithm. A generalized likelihood uncertainty estimation method was used for quantifying uncertainty. To draw on the potential benefits of the proposed methodology, a flash-flood-prone urban watershed in the Greater Toronto Area, Canada, was selected. The developed floodplain maps were updated considering climate change impacts on the input uncertainty with rainfall Intensity–Duration–Frequency (IDF) projections of RCP8.5. The results indicated that the hydrologic model input poses the most uncertainty to floodplain delineation. Incorporating climate change impacts resulted in the expansion of the potential flood area and an increase in water depth. Comparison between stationary and non-stationary IDFs showed that the flood probability is higher when a non-stationary approach is used. The large inevitable uncertainty associated with floodplain mapping and increased future flood risk under climate change imply a great need for enhanced flood modeling techniques and tools. The probabilistic floodplain maps are beneficial for implementing risk management strategies and land-use planning.

Housing Market Response to New Flood Risk Information and the Impact on Poor Tenant - Yi, Donggyu; Choi, Hyundo (The Journal of Real Estate Finance and Economics, 2020)
Keywords: Ouvrage_Collectif_Numéro1

Towards sustainable agricultural landscapes: Lessons from an interdisciplinary research-based framework applied to the Saint Lawrence floodplain - Watson, Christopher J; Mazzei, Renata; Bourgeois, Bérenger; Smedbol, Élise; Guiraud, Noé; Félix-Faure, Jim; Damar, Hada; Tremblay, Maxime; Bordeleau, Pierre-Andé; Vaillancourt, Mathieu; Bertolo, Andrea; Cabana, Gilbert; et al. (Basic and Applied Ecology, 2024)
Keywords: Infolettre; Infolettre_Octobre_2024

Can the combining of wetlands with reservoir operation reduce the risk of future floods and droughts? - Wu, Yanfeng; Sun, Jingxuan; Hu, Boting; Xu, Y. Jun; Rousseau, Alain N.; Zhang, Guangxin (Hydrology and Earth System Sciences, 2023)
Wetlands and reservoirs are important water flow and storage regulators in a river basin; therefore, they can play a crucial role in mitigating flood and hydrological drought risks. Despite the advancement of river basin theory and modeling, our knowledge is still limited about the extent to which these two regulators could perform such a role, especially under future climate extremes. To improve our understanding, we first coupled wetlands and reservoir operations into a semi-spatially explicit hydrological model and then applied it in a case study involving a large river basin in northeast China. The projection of future floods and hydrological droughts was performed using the hydrological model during different periods (near future: 2026–2050, middle century: 2051–2075, and end century: 2076–2100) under five future climate change scenarios. We found that the risk of future floods and hydrological droughts can vary across different periods – in particular, it will experience relatively large increases and slight decreases. This large river basin will experience flood events of longer duration, with larger peak flows and volume, and of enhanced flashiness compared to the historical period. Simultaneously, the hydrological droughts will be much more frequent, with longer durations and more serious deficits. Therefore, the risk of floods and droughts will, overall, increase further under future climate change even under the combined influence of reservoirs and wetlands. These findings highlight the hydrological regulation function of wetlands and reservoirs and attest that the combining of wetlands with reservoir operation cannot fully eliminate the increasing future flood and drought risks. To improve a river basin's resilience to the risks of future climate change, we argue that the implementation of wetland restoration and the development of accurate forecasting systems for effective reservoir operation are of great importance. Furthermore, this study demonstrated a wetland–reservoir integrated modeling and assessment framework that is conducive to risk assessment of floods and hydrological droughts and that can be used for other river basins in the world.
Publisher: Copernicus GmbH
Keywords: Infolettre; Infolettre_Septembre_2023; Rousseau_Alain

Understanding the shift toward a risk-based approach in flood risk management, a comparative case study of three Italian rivers - Vitale, Corinne (Environmental Science & Policy, 2023)

Inequitable patterns of US flood risk in the Anthropocene - Wing, Oliver E. J.; Lehman, William; Bates, Paul D.; Sampson, Christopher C.; Quinn, Niall; Smith, Andrew M.; Neal, Jeffrey C.; Porter, Jeremy R.; Kousky, Carolyn (Nature Climate Change, 2022)
Abstract Current flood risk mapping, relying on historical observations, fails to account for increasing threat under climate change. Incorporating recent developments in inundation modelling, here we show a 26.4% (24.1–29.1%) increase in US flood risk by 2050 due to climate change alone under RCP4.5. Our national depiction of comprehensive and high-resolution flood risk estimates in the United States indicates current average annual losses of US$32.1 billion (US$30.5–33.8 billion) in 2020’s climate, which are borne disproportionately by poorer communities with a proportionally larger White population. The future increase in risk will disproportionately impact Black communities, while remaining concentrated on the Atlantic and Gulf coasts. Furthermore, projected population change (SSP2) could cause flood risk increases that outweigh the impact of climate change fourfold. These results make clear the need for adaptation to flood and emergent climate risks in the United States, with mitigation required to prevent the acceleration of these risks.

Quantifying changes in floods under different bathymetry conditions for a lake setting - Tilano, Sergio Andrés Redondo; Boucher, Marie-Amélie; Lacey, Jay; Parent, Jérémy (Canadian Journal of Civil Engineering, 2024)
Floods can cause extensive damage proportional to their magnitude, depending on the watershed hydrology and terrain characteristics. Flood studies generally assume bathymetry as steady, while in reality it is constantly changing due to sediment transport. This study seeks to quantify the impact of different lake bathymetry conditions on flood dynamics. The Hydrotel and Telemac2D models are used to simulate floods for a lake with bathymetries from multiple year surveys. The bathymetries differ in bed elevation due to sediment accumulation and/or remobilisation. Results show that bathymetric differences produce a more noticeable effect for moderate flows than for maximum flows. During moderate flows, shallower bathymetries induce higher water levels and larger water extents. For peak flows, differences in water levels and extent are practically negligible for the different bathymetries tested. Higher water levels during moderate flows could produce longer flooding times and affect the community’s perception of flood impacts.
Keywords: Infolettre; Infolettre_Septembre_2024

Establishment of reed canarygrass ( Phalaris arundinacea ) in the context of floodplain restoration: impact of companion plant and sowing rate - Vaillancourt, Mathieu; Čapkun-Huot, Catherine; Jean Jacques, Samuel; Bourgeois, Bérenger; Poulin, Monique (Botany, 2024)
Habitat loss and degradation is a leading cause of the current biodiversity crisis. In the lake Saint-Pierre floodplain, agricultural intensification has led to the loss of substantial spawning and rearing areas for the yellow perch ( Perca flavescens Mitchill). Restoring perennial vegetation cover is key to ensure the persistence of the population, but the floodplain conditions limit our ability to do so. In this study, we tested the impact of companion plants ( Avena sativa L., Lolium multiflorum L.) and sowing rate on the establishment success of reed canarygrass ( Phalaris arundinacea L.; RCG) in year 2. RCG tolerates a wide range of environmental conditions and can provide the plant cover essential to the reproduction of yellow perch. We hypothesized that companion plants would reduce weed pressure and in turn improve RCG establishment, and that increasing the sowing rate would improve the establishment success. Contrary to our expectations, using companion plants generally reduced the cover and biomass of RCG. It also led to increased weed prevalence in most treatments. In addition, sowing at high rates did not impact RCG cover and biomass. Sowing RCG alone appears to be the most effective option to establish perennial vegetation supporting the recovery of the yellow perch population.
Keywords: Infolettre; Infolettre_Mai_2024

Quantifying flood risks during monsoon and post-monsoon seasons: An integrated framework for resource-constrained coastal regions - Thakur, Dev Anand; Mohanty, Mohit Prakash; Mishra, Ashok; Karmakar, Subhankar (Journal of Hydrology, 2024)

Cooperation in flood risk management: understanding the role of strategic planning in two Austrian policy instruments - Thaler, Thomas; Nordbeck, Ralf; Löschner, Lukas; Seher, Walter (Environmental Science & Policy, 2020)

Are periodic (intra-annual) tangential bands of vessels in diffuse-porous tree species the equivalent of flood rings in ring-porous species? Reproducibility and cause - Tardif, Jacques C.; Dickson, Heather; Conciatori, France; Nolin, Alexandre Florent; Bergeron, Yves (Dendrochronologia, 2021)
Keywords: Site_internet_RIISQ

Risk-based shelter network design in flood-prone areas: An application to Haiti - Sharbaf, Maedeh; Bélanger, Valérie; Cherkesly, Marilène; Rancourt, Marie-Ève; Toglia, Giovanni Michele (Omega, 2025)
Keywords: Infolettre; Infolettre_Novembre_2024

Dynamics of household welfare change and analysis of coping strategies during floods: an empirical investigation - Senapati, Sibananda (International Journal of Social Economics, 2024)
Purpose This study aims to understand the socioeconomic impact of flood events on households, especially household welfare in terms of changes in consumption and coping strategies to deal with flood risk. This study is based on Bihar, one of the most frequently flood-affected, most populous and economically backward states in India. Design/methodology/approach Primary data were collected from 700 households in the seven most frequently flood-affected districts in Bihar. A total of 100 individuals from each district were randomly selected from flood-affected villages. Based on a detailed literature review, an econometric (probit) model was developed to test the null hypothesis of the availability of consumption insurance, and the multivariate probability approach was used to analyze the various coping strategies of these households. Findings The results of this study suggest that flood-affected households maintain their consumption by overcoming various losses, including income, house damage and livestock loss. Households depend on financial transfers, borrowings and relief, and migrate to overcome losses. Borrowing could be an extra burden as the government compensates for house damage and crop loss late to the affected households. Again, there is no compensation to overcome livelihood loss and deal with occurrences of post-flood diseases, which further emphasizes the policy implications of strengthening the health infrastructure in the state and generating alternative livelihood opportunities. Originality/value This study discusses flood risk in terms of changes in household welfare, identifies the most effective risk-coping capabilities of rural communities and contributes to the shortcomings of the government insurance and relief model. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-07-2023-0569

A comprehensive review of AI-based methods used for forecasting ice jam floods occurrence, severity, timing, and location - Salimi, Amirhossein; Ghobrial, Tadros; Bonakdari, Hossein (Cold Regions Science and Technology, 2024)
Keywords: Infolettre; Infolettre_Octobre_2024

Integrating climate change induced flood risk into future population projections - Shu, Evelyn G.; Porter, Jeremy R.; Hauer, Mathew E.; Sandoval Olascoaga, Sebastian; Gourevitch, Jesse; Wilson, Bradley; Pope, Mariah; Melecio-Vazquez, David; Kearns, Edward (Nature Communications, 2023)
Abstract Flood exposure has been linked to shifts in population sizes and composition. Traditionally, these changes have been observed at a local level providing insight to local dynamics but not general trends, or at a coarse resolution that does not capture localized shifts. Using historic flood data between 2000-2023 across the Contiguous United States (CONUS), we identify the relationships between flood exposure and population change. We demonstrate that observed declines in population are statistically associated with higher levels of historic flood exposure, which may be subsequently coupled with future population projections. Several locations have already begun to see population responses to observed flood exposure and are forecasted to have decreased future growth rates as a result. Finally, we find that exposure to high frequency flooding (5 and 20-year return periods) results in 2-7% lower growth rates than baseline projections. This is exacerbated in areas with relatively high exposure to frequent flooding where growth is expected to decline over the next 30 years.

Large and inequitable flood risks in Los Angeles, California - Sanders, Brett F.; Schubert, Jochen E.; Kahl, Daniel T.; Mach, Katharine J.; Brady, David; AghaKouchak, Amir; Forman, Fonna; Matthew, Richard A.; Ulibarri, Nicola; Davis, Steven J. (Nature Sustainability, 2022)

Flood impact on income inequality in the Itapocu River basin, Brazil - Silva Araújo, Rafael; Ohara, Miho; Miyamoto, Mamoru; Takeuchi, Kuniyoshi (Journal of Flood Risk Management, 2022)
Abstract Disasters worldwide tend to affect the poorest more severely and increase inequality. Brazil is one of the countries with high income‐inequality rates and has unplanned urbanization issues and an extensive disaster risk profile with little knowledge on how those disasters affect people's welfare. Thus, disasters often hit the poorest hardest, increasing the country's income inequality and poverty rates. This study proposes a method to assess the impact of floods on households spatially based on their income levels by conducting flood analysis and income analysis. The method is applied to the Itapocu River basin (IRB) located in Santa Catarina State, Brazil. The flood is assessed by conducting rainfall analysis and hydrological simulation and generating flood inundation maps. The income is evaluated using downloaded 2010 census data and a dasymetric approach. Flood and income information is combined to analyze flood‐impacted households by income level and flood return period. The results confirm the initial assumption that flood events in the IRB are more likely to affect the lowest‐income households rather than the highest‐income levels, thus, increasing the income inequality.

GIS derived synthetic rating curves and HAND model to support on-the-fly flood mapping - Scriven, Blair William Gerald; McGrath, Heather; Stefanakis, Emmanuel (Natural Hazards, 2021)
Abstract A timely and cost-effective method of creating inundation maps could assist first responders in allocating resources and personnel in the event of a flood or in preparation of a future disaster. The Height Above Nearest Drainage (HAND) model could be implemented into an on-the-fly flood mapping application for a Canada-wide service. The HAND model requires water level (m) data inputs while many sources of hydrological data in Canada only provide discharge (m 3 /sec) data. Synthetic rating curves (SRCs), created using river geometry/characteristics and the Manning’s formula, could be utilized to provide an approximate water level given a discharge input. A challenge with creating SRCs includes representing how multiple different land covers will slow impact flow due to texture and bulky features (i.e., smooth asphalt versus rocky river channel); this relates to the roughness coefficient ( n ). In our study, two methods of representing multiple n values were experimented with (a weighted method and a minimum-median method) and were compared to using a fixed n method. A custom ArcGIS tool, Canadian Estimator of Ratings Curves using HAND and Discharge (CERC-HAND-D), was developed to create SRCs using all three methods. Control data were sourced from gauge stations across Canada in the form of rating curves. Results indicate that in areas with medium to medium–high river gradients (S > 0.002 m/m) or with river reaches under 5 km, the CERC-HAND-D tool creates more accurate SRCs (NRMSE = 3.7–8.8%, Percent Bias = −7.8%—9.4%), with the minimum-median method being the preferred n method.

Emerging strategies for addressing flood-damage modeling issues: A review - Redondo-Tilano, Sergio Andrés; Boucher, Marie-Amélie; Lacey, Jay (International Journal of Disaster Risk Reduction, 2025)
Keywords: Infolettre; Infolettre_Fevrier_2025

Do Areas Affected by Flood Disasters Attract Lower-Income and Less Creditworthy Homeowners? - Ratnadiwakara, Dimuthu; Venugopal, Buvaneshwaran (Journal of Housing Research, 2020)

Sensitivity of various topographic data in flood management: Implications on inundation mapping over large data-scarce regions - Prakash Mohanty, Mohit; Nithya, S.; Nair, Akhilesh S.; Indu, J.; Ghosh, Subimal; Mohan Bhatt, Chandra; Srinivasa Rao, Goru; Karmakar, Subhankar (Journal of Hydrology, 2020)

Spatial Spillovers in the Pricing of Flood Risk: Insights from the Housing Market - Pommeranz, Carolin; Steininger, Bertram I. (Journal of Housing Research, 2020)
Keywords: Ouvrage_Collectif_Numéro1

Regional flood frequency analysis based on peaks-over-threshold approach: A case study for South-Eastern Australia - Pan, Xiao; Rahman, Ataur; Haddad, Khaled; Ouarda, Taha B.M.J.; Sharma, Ashish (Journal of Hydrology: Regional Studies, 2023)
Keywords: Infolettre; Infolettre_Septembre_2023

Designing policy instruments for regional floodplain management in Austria: the role of effectiveness and legitimacy - Nordbeck, Ralf; Löschner, Lukas; Seher, Walter (Journal of Environmental Policy & Planning, 2022)

Peaks-over-threshold model in flood frequency analysis: a scoping review - Pan, Xiao; Rahman, Ataur; Haddad, Khaled; Ouarda, Taha B. M. J. (Stochastic Environmental Research and Risk Assessment, 2022)
Abstract In flood frequency analysis (FFA), annual maximum (AM) model is widely adopted in practice due to its straightforward sampling process. However, AM model has been criticized for its limited flexibility. FFA using peaks-over-threshold (POT) model is an alternative to AM model, which offers several theoretical advantages; however, this model is currently underemployed internationally. This study aims to bridge the current knowledge gap by conducting a scoping review covering several aspects of the POT approach including model assumptions, independence criteria, threshold selection, parameter estimation, probability distribution, regionalization and stationarity. We have reviewed the previously published articles on POT model to investigate: (a) possible reasons for underemployment of the POT model in FFA; and (b) challenges in applying the POT model. It is highlighted that the POT model offers a greater flexibility compared to the AM model due to the nature of sampling process associated with the POT model. The POT is more capable of providing less biased flood estimates for frequent floods. The underemployment of POT model in FFA is mainly due to the complexity in selecting a threshold (e.g., physical threshold to satisfy independence criteria and statistical threshold for Generalized Pareto distribution – the most commonly applied distribution in POT modelling). It is also found that the uncertainty due to individual variable and combined effects of the variables are not well assessed in previous research, and there is a lack of established guideline to apply POT model in FFA.
Keywords: Infolettre; Infolettre_Avril_2022; Site_internet_RIISQ

Flood Risk Assessment under Climate Change: The Petite Nation River Watershed - Oubennaceur, Khalid; Chokmani, Karem; Gauthier, Yves; Ratte-Fortin, Claudie; Homayouni, Saeid; Toussaint, Jean-Patrick (Climate, 2021)
In Canada, climate change is expected to increase the extreme precipitation events by magnitude and frequency, leading to more intense and frequent river flooding. In this study, we attempt to map the flood hazard and damage under projected climate scenarios (2050 and 2080). The study was performed in the two most populated municipalities of the Petite Nation River Watershed, located in southern Quebec (Canada). The methodology follows a modelling approach, in which climate projections are derived from the Hydroclimatic Atlas of Southern Quebec following two representative concentration pathways (RCPs) scenarios, i.e., RCP 4.5 and RCP 8.5. These projections are used to predict future river flows. A frequency analysis was carried out with historical data of the peak flow (period 1969–2018) to derive different return periods (2, 20, and 100 years), which were then fed into the GARI tool (Gestion et Analyse du Risque d’Inondation). This tool is used to simulate flood hazard maps and to quantify future flood risk changes. Projected flood hazard (extent and depth) and damage maps were produced for the two municipalities under current and for future scenarios. The results indicate that the flood frequencies are expected to show a minor decrease in peak flows in the basin at the time horizons, 2050 and 2080. In addition, the depth and inundation areas will not significantly change for two time horizons, but instead show a minor decrease. Similarly, the projected flood damage changes in monetary losses are projected to decrease in the future. The results of this study allow one to identify present and future flood hazards and vulnerabilities, and should help decision-makers and the public to better understand the significance of climate change on flood risk in the Petite Nation River watershed.
Keywords: Site_internet_RIISQ

Fraxinus nigra flood ring dataset for the study of flood history (1850-2017) of the Driftwood River, northwestern Ontario - Nolin, Alexandre; Tardif, Jacques Clément; Conciatori, France; Bergeron, Yves (2021)
Data include sample replication (N) and flood-ring frequencies (F1, F2) derived from black ash (Fraxinus nigra Marsh.) trees growing in the floodplain of the Driftwood River in northwestern Ontario reported in "Flood ring production modulated by river regulation in eastern boreal Canada" published in "Frontiers in Plant Science - Quantitative Wood Anatomy to Explore Tree Responses to Global Change" by Nolin et al. in 2021c. DriftwoodFR.csv, as in Fig. 4, F1 and F2 flood-rings chronologies per sites and distance class with sample replication (N) to reproduce the flood-ring frequencies. Harricana River F1 and F2 flood ring chronologies from Nolin et al., 2021b are also provided. DriftwoodRW.csv, as in Fig. 5, the mean site chronologies of total ring width with sample replication (N). LAT_LON_Driftwood.kml, the coordinate data for each F. nigra stand sampled on the Driftwood River, including Monteith dam location, in Google Earth format (.kml) meatadatas.txt, a set of self-explanatory instructions and descriptions for data files. All other data are available upon request to the corresponding author at alexandreflorent.nolin@uqat.ca (institutional email), alexandreflorent.nolin@gmail.com (permanent email).
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Fidelity of reanalysis datasets in floodplain mapping: Investigating performance at inundation level over large regions - Mohanty, Mohit Prakash; Simonovic, Slobodan P. (Journal of Hydrology, 2021)

Flood management in India: A focussed review on the current status and future challenges - Mohanty, Mohit Prakash; Mudgil, Sahil; Karmakar, Subhankar (International Journal of Disaster Risk Reduction, 2020)

Smoothed Particle Hydrodynamics Modeling with Advanced Boundary Conditions for Two-Dimensional Dam-Break Floods - Mirauda, Domenica; Albano, Raffaele; Sole, Aurelia; Adamowski, Jan (Water, 2020)
To simulate the dynamics of two-dimensional dam-break flow on a dry horizontal bed, we use a smoothed particle hydrodynamics model implementing two advanced boundary treatment techniques: (i) a semi-analytical approach, based on the computation of volume integrals within the truncated portions of the kernel supports at boundaries and (ii) an extension of the ghost-particle boundary method for mobile boundaries, adapted to free-slip conditions. The trends of the free surface along the channel, and of the impact wave pressures on the downstream vertical wall, were first validated against an experimental case study and then compared with other numerical solutions. The two boundary treatment schemes accurately predicted the overall shape of the primary wave front advancing along the dry bed until its impact with the downstream vertical wall. Compared to data from numerical models in the literature, the present results showed a closer fit to an experimental secondary wave, reflected by the downstream wall and characterized by complex vortex structures. The results showed the reliability of both the proposed boundary condition schemes in resolving violent wave breaking and impact events of a practical dam-break application, producing smooth pressure fields and accurately predicting pressure and water level peaks.

Coastal Flooding Associated with Hurricane Irma in Central Cuba (Ciego de Ávila Province) - Matos-Pupo, Felipe; Peros, Matthew C.; González-De Zayas, Roberto; Valero-Jorge, Alexey; Pérez-López, Osvaldo E.; Álvarez-Taboada, Flor; Sorí, Rogert (Atmosphere, 2023)
Irma was a major hurricane that developed during the 2017 season. It was a category 5 on the Saffir–Simpson Hurricane wind scale. This hurricane caused severe damage in the Caribbean area and the Florida Keys. The social, economic, and environmental impacts, mainly related to coastal flooding, were also significant in Cuba. The maximum limits of coastal flooding caused by this hurricane were determined in this research. Field trips and the use of the GPS supported our work, which focused on both the northern and southern coasts of the Ciego de Ávila province. This work has been critical for improving coastal flooding scenarios related to a strong hurricane, as it has been the first experience according to hurricane data since 1851. Results showed that the Punta Alegre and Júcaro towns were the most affected coastal towns. The locals had never seen similar flooding in these places before. The differences between flood areas associated with Hurricane Irma and previous modeled hazard scenarios were evident (the flooded areas associated with Hurricane Irma were smaller than those modeled for categories 1, 3, and 5 hurricanes). The effects of this hurricane on the most vulnerable coastal settlements, including the impacts on the archeological site “Los Buchillones”, were also assessed.
Keywords: Infolettre; Infolettre_Octobre_2023

Prediction and Classification of Flood Susceptibility Based on Historic Record in a Large, Diverse, and Data Sparse Country - McGrath, Heather; Gohl, Piper Nora (MDPI, 2023)

Accessing the Impact of Meteorological Variables on Machine Learning Flood Susceptibility Mapping - McGrath, Heather; Gohl, Piper Nora (Remote Sensing, 2022)
Machine learning (ML) algorithms have emerged as competent tools for identifying areas that are susceptible to flooding. The primary variables considered in most of these works include terrain models, lithology, river networks and land use. While several recent studies include average annual rainfall and/or temperature, other meteorological information such as snow accumulation and short-term intense rain events that may influence the hydrology of the area under investigation have not been considered. Notably, in Canada, most inland flooding occurs during the freshet, due to the melting of an accumulated snowpack coupled with heavy rainfall. Therefore, in this study the impact of several climate variables along with various hydro-geomorphological (HG) variables were tested to determine the impact of their inclusion. Three tests were run: only HG variables, the addition of annual average temperature and precipitation (HG-PT), and the inclusion of six other meteorological datasets (HG-8M) on five study areas across Canada. In HG-PT, both precipitation and temperature were selected as important in every study area, while in HG-8M a minimum of three meteorological datasets were considered important in each study area. Notably, as the meteorological variables were added, many of the initial HG variables were dropped from the selection set. The accuracy, F1, true skill and Area Under the Curve (AUC) were marginally improved when the meteorological data was added to the a parallel random forest algorithm (parRF). When the model is applied to new data, the estimated accuracy of the prediction is higher in HG-8M, indicating that inclusion of relevant, local meteorological datasets improves the result.

Floodplains in the Anthropocene: A Global Analysis of the Interplay Between Human Population, Built Environment, and Flood Severity - Mazzoleni, M.; Mård, J.; Rusca, M.; Odongo, V.; Lindersson, S.; Di Baldassarre, G. (Water Resources Research, 2021)
Abstract This study presents a global explanatory analysis of the interplay between the severity of flood losses and human presence in floodplain areas. In particular, we relate economic losses and fatalities caused by floods during 1990–2000, with changes in human population and built‐up areas in floodplains during 2000–2015 by exploiting global archives. We found that population and built‐up areas in floodplains increased in the period 2000–2015 for the majority of the analyzed countries, albeit frequent flood losses in the previous period 1990–2000. In some countries, however, population in floodplains decreased in the period 2000–2015, following more severe floods losses that occurred in the period 1975–2000. Our analysis shows that (i) in low‐income countries, population in floodplains increased after a period of high flood fatalities; while (ii) in upper‐middle and high‐income countries, built‐up areas increased after a period of frequent economic losses. In this study, we also provide a general framework to advance knowledge of human‐flood interactions and support the development of sustainable policies and measures for flood risk management and disaster risk reduction. , Key Points We analyzed the interplay between the severity of flood losses and human presence in floodplains using freely available global data sets Despite the frequent flood losses in the period 1990–2000, human presence and built‐up areas in the floodplains increased between 2000 and 2015 In low‐income countries, population in floodplains increased after a period of high flood fatalities

Urban form and structure explain variability in spatial inequality of property flood risk among US counties - Ma, Junwei; Mostafavi, Ali (Communications Earth & Environment, 2024)
Abstract Understanding the relationship between urban form and structure and spatial inequality of property flood risk has been a longstanding challenge in urban planning and emergency management. Here we explore eight urban form and structure features to explain variability in spatial inequality of property flood risk among 2567 US counties. Using datasets related to human mobility and facility distribution, we identify notable variation in spatial inequality of property flood risk, particularly in coastline and metropolitan counties. The results reveal variations in spatial inequality of property flood risk can be explained based on principal components of development density, economic activity, and centrality and segregation. The classification and regression tree model further demonstrates how these principal components interact and form pathways that explain spatial inequality of property flood risk. The findings underscore the critical role of urban planning in mitigating flood risk inequality, offering valuable insights for crafting integrated strategies as urbanization progresses.

Future flood envelope curves for the estimation of design flood magnitudes for highway bridges at river crossings - Maria, Dona; Sushama, Laxmi; Almansour, Husham; Khaliq, Muhammad Naveed; Nguyen, Van-Thanh-Van; Chouinard, Luc (Results in Engineering, 2024)
Keywords: Infolettre; Infolettre_Mai_2024

Strategic use of instruments of land policy for mobilising private land for flood risk management - Löschner, Lukas; Hartmann, Thomas; Priest, Sally; Collentine, Dennis (Environmental Science & Policy, 2021)
Keywords: Ouvrage_Collectif_Numéro1

Prenatal maternal subjective distress predicts higher autistic-like traits in offspring: The Iowa Flood Study - Lapierre, Mylène; Elgbeili, Guillaume; Laplante, David P.; O’Hara, Michael W.; D’Antono, Bianca; King, Suzanne (Development and Psychopathology, 2024)
Abstract Autism spectrum disorder prevalence more than quadrupled in the United States between 2000 and 2020. Ice storm-related prenatal maternal stress (PNMS) predicts autistic-like trait severity in children exposed early in gestation. The objective was to determine the extent to which PNMS influences the severity and trajectory of autistic-like traits in prenatally flood-exposed children at ages 4–7 years and to test moderation by sex and gestational timing. Soon after the June 2008 floods in Iowa, USA, 268 women pregnant during the disaster were assessed for objective hardship, subjective distress, and cognitive appraisal of the experience. When their children were 4, 5½, and 7 years old, mothers completed the Social Communication Questionnaire (SCQ) to assess their children’s autistic-like traits; 137 mothers completed the SCQ for at least one age. The final longitudinal multilevel model showed that the greater the maternal subjective distress, the more severe the child’s autistic-like traits, controlling for objective hardship. The effect of PNMS on rate of change was not significant, and there were no significant main effects or interactions involving sex or timing. Prenatal maternal subjective distress, but not objective hardship or cognitive appraisal, predicted more severe autistic-like traits at age 4, and this effect remained stable through age 7.
Keywords: Infolettre; Infolettre_Novembre_2024

The wider the gap between rich and poor the higher the flood mortality - Lindersson, Sara; Raffetti, Elena; Rusca, Maria; Brandimarte, Luigia; Mård, Johanna; Di Baldassarre, Giuliano (Nature Sustainability, 2023)
Economic inequality is rising within many countries globally, and this can significantly influence the social vulnerability to natural hazards. We analysed income inequality and flood disasters in 67 middle- and high-income countries between 1990 and 2018 and found that unequal countries tend to suffer more flood fatalities. This study integrates geocoded mortality records from 573 major flood disasters with population and economic data to perform generalized linear mixed regression modelling. Our results show that the significant association between income inequality and flood mortality persists after accounting for the per-capita real gross domestic product, population size in flood-affected regions and other potentially confounding variables. The protective effect of increasing gross domestic product disappeared when accounting for income inequality and population size in flood-affected regions. On the basis of our results, we argue that the increasingly uneven distribution of wealth deserves more attention within international disaster-risk research and policy arenas.
Number: 8 Publisher: Nature Publishing Group

Multi-Scale Flood Mapping under Climate Change Scenarios in Hexagonal Discrete Global Grids - Li, Mingke; McGrath, Heather; Stefanakis, Emmanuel (ISPRS International Journal of Geo-Information, 2022)
Among the most prevalent natural hazards, flooding has been threatening human lives and properties. Robust flood simulation is required for effective response and prevention. Machine learning is widely used in flood modeling due to its high performance and scalability. Nonetheless, data pre-processing of heterogeneous sources can be cumbersome, and traditional data processing and modeling have been limited to a single resolution. This study employed an Icosahedral Snyder Equal Area Aperture 3 Hexagonal Discrete Global Grid System (ISEA3H DGGS) as a scalable, standard spatial framework for computation, integration, and analysis of multi-source geospatial data. We managed to incorporate external machine learning algorithms with a DGGS-based data framework, and project future flood risks under multiple climate change scenarios for southern New Brunswick, Canada. A total of 32 explanatory factors including topographical, hydrological, geomorphic, meteorological, and anthropogenic were investigated. Results showed that low elevation and proximity to permanent waterbodies were primary factors of flooding events, and rising spring temperatures can increase flood risk. Flooding extent was predicted to occupy 135–203% of the 2019 flood area, one of the most recent major flooding events, by the year 2100. Our results assisted in understanding the potential impact of climate change on flood risk, and indicated the feasibility of DGGS as the standard data fabric for heterogeneous data integration and incorporated in multi-scale data mining.

The challenge of unprecedented floods and droughts in risk management - Kreibich, Heidi; Van Loon, Anne F.; Schröter, Kai; Ward, Philip J.; Mazzoleni, Maurizio; Sairam, Nivedita; Abeshu, Guta Wakbulcho; Agafonova, Svetlana; AghaKouchak, Amir; Aksoy, Hafzullah; Alvarez-Garreton, Camila; Aznar, Blanca; et al. (Nature, 2022)
Abstract Risk management has reduced vulnerability to floods and droughts globally 1,2 , yet their impacts are still increasing 3 . An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data 4,5 . On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change 3 .

The behavioral turn in flood risk management, its assumptions and potential implications - Kuhlicke, Christian; Seebauer, Sebastian; Hudson, Paul; Begg, Chloe; Bubeck, Philip; Dittmer, Cordula; Grothmann, Torsten; Heidenreich, Anna; Kreibich, Heidi; Lorenz, Daniel F.; Masson, Torsten; Reiter, Jessica; et al. (WIREs Water, 2020)
Abstract Recent policy changes highlight the need for citizens to take adaptive actions to reduce flood‐related impacts. Here, we argue that these changes represent a wider behavioral turn in flood risk management (FRM). The behavioral turn is based on three fundamental assumptions: first, that the motivations of citizens to take adaptive actions can be well understood so that these motivations can be targeted in the practice of FRM; second, that private adaptive measures and actions are effective in reducing flood risk; and third, that individuals have the capacities to implement such measures. We assess the extent to which the assumptions can be supported by empirical evidence. We do this by engaging with three intellectual catchments. We turn to research by psychologists and other behavioral scientists which focus on the sociopsychological factors which influence individual motivations (Assumption 1). We engage with economists, engineers, and quantitative risk analysts who explore the extent to which individuals can reduce flood related impacts by quantifying the effectiveness and efficiency of household‐level adaptive measures (Assumption 2). We converse with human geographers and sociologists who explore the types of capacities households require to adapt to and cope with threatening events (Assumption 3). We believe that an investigation of the behavioral turn is important because if the outlined assumptions do not hold, there is a risk of creating and strengthening inequalities in FRM. Therefore, we outline the current intellectual and empirical knowledge as well as future research needs. Generally, we argue that more collaboration across intellectual catchments is needed, that future research should be more theoretically grounded and become methodologically more rigorous and at the same time focus more explicitly on the normative underpinnings of the behavioral turn. This article is categorized under: Engineering Water > Planning Water Human Water > Water Governance Science of Water > Water Extremes

Floods have become less deadly: an analysis of global flood fatalities 1975–2022 - Jonkman, S. N.; Curran, A.; Bouwer, L. M. (Natural Hazards, 2024)
Abstract Floods are amongst the most frequent disasters in terms of human and economic impacts. This study provides new insights into the frequency of loss of life at the global scale, mortality fractions of the population exposed to floods, and underlying trends. A dataset is compiled based on the EM-DAT disaster database covering the period 1975 until 2022, extending previous studies on this topic. Flood impact data are analysed over spatial, temporal and economic scales, decomposed in various flood types and compared with other natural disasters. Floods are the most frequent natural disasters up to 1000 fatalities, and flash floods lead to the highest mortality fractions per event, i.e. the number of deaths in an event relative to the exposed population. Despite population growth and increasing flood hazards, the average number of fatalities per event has declined over time. Mortality fractions per event have decreased over time for middle- and high-middle-income countries, but increased for low-income countries. This highlights the importance of continuing and expanding risk reduction and adaptation efforts.

A novel explainable PSO-XGBoost model for regional flood frequency analysis at a national scale: Exploring spatial heterogeneity in flood drivers - Kanani-Sadat, Yousef; Safari, Abdolreza; Nasseri, Mohsen; Homayouni, Saeid (Journal of Hydrology, 2024)
Keywords: Infolettre; Infolettre_Ete_2024

Flood Damage and Mortgage Credit Risk: A Case Study of Hurricane Harvey - Kousky, Carolyn; Palim, Mark; Pan, Ying (Journal of Housing Research, 2020)
Keywords: Ouvrage_Collectif_Numéro1

Impacts of climate change on flood volumes over North American catchments - Ionno, Alexandre; Arsenault, Richard; Troin, Magali; Martel, Jean-Luc; Brissette, François (Journal of Hydrology, 2024)

A framework for coastal flood hazard assessment under sea level rise: Application to the Persian Gulf - Irani, Maryam; Naderi, Mohammad Mahdi; Massah Bavani, Ali Reza; Hassanzadeh, Elmira; Moftakhari, Hamed (Journal of Environmental Management, 2024)
Keywords: Infolettre; Infolettre_Janvier_2024

Regionalization of flood magnitudes using the ecological attributes of watersheds - Jabbarian Amiri, Bahman; Baheri, Bahareh; Fohrer, Nicola; Adamowski, Jan Franklin (Geocarto International, 2020)

Turkmen women’s traditional craft skills in post-disaster recovery: the case of the 2019 Northeast floods in Iran - Hassani, Atoosa; Fayazi, Mahmood; Mottaki, Zoheir; Adib, Morteza; Dehbandi, Ramin; Khalili Gheidari, Yasamam; Seraji, Fatemeh (Disaster Prevention and Management: An International Journal, 2025)
Purpose This study investigates why Turkmen women’s traditional handicraft skills have declined and explains how the local, traditional craft skills accelerated the post-flood recovery of Turkmen women in the aftermath of the 2019 Northeast floods in Iran. Design/methodology/approach The research adopts a case study approach, employing reflective thematic analysis. Findings Post-disaster recovery spurred a shift from traditional to modern lifestyles through new housing designs, enhanced female literacy and greater economic participation. However, this transition devalued traditional crafts due to heightened household chores, material scarcity and reduced market demand. Nonetheless, women with craft skills played a pivotal role in household recovery by repairing damaged items and crafting dowries for their daughters, illustrating their contribution to social and economic resilience. Social implications These research findings shed light on the importance of traditional craft skills in enabling the female household member, in particular, to recover from disasters and contribute to the recovery of their households and communities. Originality/value The originality of this study lies in its focus on the specific context of Turkmen women’s traditional craft skills and their role in post-disaster recovery, particularly after the 2019 Northeast floods in Iran. While there is existing research on post-disaster recovery mechanisms, this study uniquely examines the under-researched impact of traditional craft skills on the recovery process, specifically for female household members.
Keywords: Infolettre; Infolettre_Fevrier_2025

Urinary 1H NMR Metabolomic Analysis of Prenatal Maternal Stress Due to a Natural Disaster Reveals Metabolic Risk Factors for Non-Communicable Diseases: The QF2011 Queensland Flood Study - Heynen, Joshua P.; McHugh, Rebecca R.; Boora, Naveenjyote S.; Simcock, Gabrielle; Kildea, Sue; Austin, Marie-Paule; Laplante, David P.; King, Suzanne; Montina, Tony; Metz, Gerlinde A. S. (Metabolites, 2023)
Prenatal stress alters fetal programming, potentially predisposing the ensuing offspring to long-term adverse health outcomes. To gain insight into environmental influences on fetal development, this QF2011 study evaluated the urinary metabolomes of 4-year-old children (n = 89) who were exposed to the 2011 Queensland flood in utero. Proton nuclear magnetic resonance spectroscopy was used to analyze urinary metabolic fingerprints based on maternal levels of objective hardship and subjective distress resulting from the natural disaster. In both males and females, differences were observed between high and low levels of maternal objective hardship and maternal subjective distress groups. Greater prenatal stress exposure was associated with alterations in metabolites associated with protein synthesis, energy metabolism, and carbohydrate metabolism. These alterations suggest profound changes in oxidative and antioxidative pathways that may indicate a higher risk for chronic non-communicable diseases such obesity, insulin resistance, and diabetes, as well as mental illnesses, including depression and schizophrenia. Thus, prenatal stress-associated metabolic biomarkers may provide early predictors of lifetime health trajectories, and potentially serve as prognostic markers for therapeutic strategies in mitigating adverse health outcomes.
Number: 4 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Infolettre; Infolettre_Mai_2023

Building Structural Characterization using Mobile Terrestrial Point Cloud for Flood Risk Anticipation - Haghighatgou, Niloufar (Université Laval, 2022)

A method for automatic identification of openings in buildings facades based on mobile LiDAR point clouds for assessing impacts of floodings - Haghighatgou, Niloufar; Daniel, Sylvie; Badard, Thierry (International Journal of Applied Earth Observation and Geoinformation, 2022)
Keywords: Infolettre; Infolettre_Juillet_2022; Site_internet_RIISQ

Evaluating the suitability of policy instruments for urban flood risk reduction - Henstra, Daniel; Thistlethwaite, Jason; Dordi, Truzaar (Local Environment, 2020)
Keywords: Ouvrage_Collectif_Numéro1

Flood Risk Perception in the Housing Market and the Impact of a Major Flood Event - Hennighausen, Hannah; Suter, Jordan F. (Land Economics, 2020)
Keywords: Ouvrage_Collectif_Numéro1

LiDAR topo‐bathymetry for riverbed elevation assessment: A review of approaches and performance for hydrodynamic modelling of flood plains - Frizzle, Catherine; Trudel, Mélanie; Daniel, Sylvie; Pruneau, Antoine; Noman, Juzer (Earth Surface Processes and Landforms, 2024)
Abstract Topo‐bathymetric LiDAR (TBL) can provide a continuous digital elevation model (DEM) for terrestrial and submerged portions of rivers. This very high horizontal spatial resolution and high vertical accuracy data can be promising for flood plain mapping using hydrodynamic models. Despite the increasing number of papers regarding the use of TBL in fluvial environments, its usefulness for flood mapping remains to be demonstrated. This review of real‐world experiments focusses on three research questions related to the relevance of TBL in hydrodynamic modelling for flood mapping at local and regional scales: (i) Is the accuracy of TBL sufficient? (ii) What environmental and technical conditions can optimise the quality of acquisition? (iii) Is it possible to predict which rivers would be good candidates for TBL acquisition? With a root mean square error (RMSE) of 0.16 m, results from real‐world experiments confirm that TBL provides the required vertical accuracy for hydrodynamic modelling. Our review highlighted that environmental conditions, such as turbidity, overhanging vegetation or riverbed morphology, may prove to be limiting factors in the signal's capacity to reach the riverbed. A few avenues have been identified for considering whether TBL acquisition would be appropriate for a specific river. Thresholds should be determined using geometric or morphological criteria, such as rivers with steep slopes, steep riverbanks, and rivers too narrow or with complex morphologies, to avoid compromising the quality or the extent of the coverage. Based on this review, it appears that TBL acquisition conditions for hydrodynamic modelling for flood mapping should optimise the signal's ability to reach the riverbed. However, further research is needed to determine the percentage of coverage required for the use of TBL as a source of bathymetry in a hydrodynamic model, and whether specific river sections must be covered to ensure model performance for flood mapping.
Keywords: Infolettre; Infolettre_Avril_2024

Urban flooding and the resultant pollution: What French-speaking scientists make of it? - Genouel, Maïlys; Comby, Emeline; Le Lay, Yves-François; Biron, Pascale (Anthropocene, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Temporal and Spatial Amplification of Extreme Rainfall and Extreme Floods in a Warmer Climate - Faghih, Mina; Brissette, François (Journal of Hydrometeorology, 2023)
Abstract This work explores the relationship between catchment size, rainfall duration, and future streamflow increases on 133 North American catchments with sizes ranging from 66.5 to 9886 km2. It uses the outputs from a high spatial (0.11°) and temporal (1-h) resolution single model initial-condition large ensemble (SMILE) and a hydrological model to compute extreme rainfall and streamflow for durations ranging from 1 to 72 h and for return periods of between 2 and 300 years. Increases in extreme precipitation are observed across all durations and return periods. The projected increases are strongly related to duration, frequency, and catchment size, with the shortest durations, longest return periods, and smaller catchments witnessing the largest relative rainfall increases. These increases can be quite significant, with the 100-yr rainfall becoming up to 20 times more frequent over the smaller catchments. A similar duration–frequency–size pattern of increases is also observed for future extreme streamflow, but with even larger relative increases. These results imply that future increases in extreme rainfall will disproportionately impact smaller catchments, and particularly so for impervious urban catchments which are typically small, and whose stormwater drainage infrastructures are designed for long-return-period flows, both being conditions for which the amplification of future flow will be maximized.
Publisher: American Meteorological Society Section: Journal of Hydrometeorology
Keywords: Infolettre; Infolettre_Septembre_2023

Flood Hazard Risk Mapping Using a Pseudo Supervised Random Forest - Esfandiari, Morteza; Abdi, Ghasem; Jabari, Shabnam; McGrath, Heather; Coleman, David (Remote Sensing, 2020)
Devastating floods occur regularly around the world. Recently, machine learning models have been used for flood susceptibility mapping. However, even when these algorithms are provided with adequate ground truth training samples, they can fail to predict flood extends reliably. On the other hand, the height above nearest drainage (HAND) model can produce flood prediction maps with limited accuracy. The objective of this research is to produce an accurate and dynamic flood modeling technique to produce flood maps as a function of water level by combining the HAND model and machine learning. In this paper, the HAND model was utilized to generate a preliminary flood map; then, the predictions of the HAND model were used to produce pseudo training samples for a R.F. model. To improve the R.F. training stage, five of the most effective flood mapping conditioning factors are used, namely, Altitude, Slope, Aspect, Distance from River and Land use/cover map. In this approach, the R.F. model is trained to dynamically estimate the flood extent with the pseudo training points acquired from the HAND model. However, due to the limited accuracy of the HAND model, a random sample consensus (RANSAC) method was used to detect outliers. The accuracy of the proposed model for flood extent prediction, was tested on different flood events in the city of Fredericton, NB, Canada in 2014, 2016, 2018, 2019. Furthermore, to ensure that the proposed model can produce accurate flood maps in other areas as well, it was also tested on the 2019 flood in Gatineau, QC, Canada. Accuracy assessment metrics, such as overall accuracy, Cohen’s kappa coefficient, Matthews correlation coefficient, true positive rate (TPR), true negative rate (TNR), false positive rate (FPR) and false negative rate (FNR), were used to compare the predicted flood extent of the study areas, to the extent estimated by the HAND model and the extent imaged by Sentinel-2 and Landsat satellites. The results confirm that the proposed model can improve the flood extent prediction of the HAND model without using any ground truth training data.

Establishing perennial strips in a cultivated floodplain for habitat restoration: monitoring over 4 years and success drivers - Damar, Hada; Vaillancourt, Mathieu; Bourgeois, Bérenger; Poulin, Monique (Restoration Ecology, 2024)
Floodplains, one of the most biologically diverse and productive ecosystems, are under threat from intensive crop production. Implementing perennial strips alongside agricultural ditches and streams could reduce negative impacts of intensive agriculture and restore wildlife habitats in cultivated floodplains. To successfully set up perennial strips, it is important to understand the parameters that drive their establishment. Here we assessed the establishment success of reed canarygrass (RCG; Phalaris arundinacea ) strips in the lake Saint Pierre (LSP) floodplain, Québec, Canada by monitoring RCG biomass and vegetation height over 4 years and identify the factors driving its establishment. A total of 26 RCG strips across six municipalities of LSP were monitored. Biomass and vegetation height of RCG increased over time to reach an average of 5048 kg/ha in year 4 and 104 cm in year 3 in established strips. The RCG established successfully in 62% of surveyed plots and three environmental parameters explained 61% of this success. Establishment of RCG was most successful when a first rain came right after seeding (<3 days). High clay content and low elevation were associated with establishment failures. Overall, our results highlight the ability of RCG strips to restore dense perennial vegetation cover in cultivated floodplain, thereby providing suitable habitat for fish spawning during spring floods. This study provides significant insight into the drivers of establishment of perennial grass strips in highly constrained cultivated areas such as floodplains.
Keywords: Infolettre; Infolettre_Novembre_2024

A Remote Sensing View of the 2020 Extreme Lake-Expansion Flood Event into the Peace–Athabasca Delta Floodplain—Implications for the Future SWOT Mission - Desrochers, Nicolas M.; Peters, Daniel L.; Siles, Gabriela; Cauvier Charest, Elizabeth; Trudel, Mélanie; Leconte, Robert (Remote Sensing, 2023)
The Peace–Athabasca Delta (PAD) in western Canada is one of the largest inland deltas in the world. Flooding caused by the expansion of lakes beyond normal shorelines occurred during the summer of 2020 and provided a unique opportunity to evaluate the capabilities of remote sensing platforms to map surface water expansion into vegetated landscape with complex surface connectivity. Firstly, multi-source remotely sensed data via satellites were used to create a temporal reconstruction of the event spanning May to September. Optical synthetic aperture radar (SAR) and altimeter data were used to reconstruct surface water area and elevation as seen from space. Lastly, temporal water surface area and level data obtained from the existing satellites and hydrometric stations were used as input data in the CNES Large-Scale SWOT Simulator, which provided an overview of the newly launched SWOT satellite ability to monitor such flood events. The results show a 25% smaller water surface area for optical instruments compared to SAR. Simulations show that SWOT would have greatly increased the spatio-temporal understanding of the flood dynamics with complete PAD coverage three to four times per month. Overall, seasonal vegetation growth was a major obstacle for water surface area retrieval, especially for optical sensors.
Keywords: Infolettre; Infolettre_Avril_2023

Evaluating the Impact of Floods on Housing Price Using a Spatial Matching Difference-In-Differences (SM-DID) Approach - Dubé, Jean; AbdelHalim, Maha; Devaux, Nicolas (2021)
Many applications have relied on the hedonic pricing model (HPM) to measure the willingness-to-pay (WTP) for urban externalities and natural disasters. The classic HPM regresses housing price on a complete list of attributes/characteristics that include spatial or environmental amenities (or disamenities), such as floods, to retrieve the gradients of the market (marginal) WTP for such externalities. The aim of this paper is to propose an innovative methodological framework that extends the causal relations based on a spatial matching difference-in-differences (SM-DID) estimator, and which attempts to calculate the difference between sale price for similar goods within “treated” and “control” groups. To demonstrate the potential of the proposed spatial matching method, the researchers present an empirical investigation based on the case of a flood event recorded in the city of Laval (Québec, Canada) in 1998, using information on transactions occurring between 1995 and 2001. The research results show that the impact of flooding brings a negative premium on the housing price of about 20,000$ Canadian (CAN).
Keywords: Ouvrage_Collectif_Numéro1

Impacts of climate warming on global floods and their implication to current flood defense standards - Chen, Jie; Shi, Xinyan; Gu, Lei; Wu, Guiyang; Su, Tianhua; Wang, Hui-Min; Kim, Jong-Suk; Zhang, Liping; Xiong, Lihua (Journal of Hydrology, 2023)
Keywords: Infolettre; Infolettre_Avril_2024

Using remote sensing to assess how intensive agriculture impacts the turbidity of a fluvial lake floodplain - Clermont, Maxime; Kinnard, Christophe; Dubé-Richard, Daphney; Campeau, Stéphane; Bordeleau, Pierre-André; de Grandpré, Arthur; Ziyad, Jawad; Roy, Alexandre (Journal of Great Lakes Research, 2023)
Keywords: Infolettre; Infolettre_Fevrier_2024; Kinnard_Christophe

Is it the flood, or the disclosure? An inquiry to the impact of flood risk on residential housing prices - Chiang Hsieh, Lin-Han (Land Use Policy, 2021)
Keywords: Ouvrage_Collectif_Numéro1

An assessment of large‐scale flood modelling based on LiDAR data - Choné, Guénolé; Biron, Pascale M.; Buffin‐Bélanger, Thomas; Mazgareanu, Iulia; Neal, Jeff C.; Sampson, Christopher C. (Hydrological Processes, 2021)
Abstract Large‐scale flood modelling approaches designed for regional to continental scales usually rely on relatively simple assumptions to represent the potentially highly complex river bathymetry at the watershed scale based on digital elevation models (DEMs) with a resolution in the range of 25–30 m. Here, high‐resolution (1 m) LiDAR DEMs are employed to present a novel large‐scale methodology using a more realistic estimation of bathymetry based on hydrogeomorphological GIS tools to extract water surface slope. The large‐scale 1D/2D flood model LISFLOOD‐FP is applied to validate the simulated flood levels using detailed water level data in four different watersheds in Quebec (Canada), including continuous profiles over extensive distances measured with the HydroBall technology. A GIS‐automated procedure allows to obtain the average width required to run LISFLOOD‐FP. The GIS‐automated procedure to estimate bathymetry from LiDAR water surface data uses a hydraulic inverse problem based on discharge at the time of acquisition of LiDAR data. A tiling approach, allowing several small independent hydraulic simulations to cover an entire watershed, greatly improves processing time to simulate large watersheds with a 10‐m resampled LiDAR DEM. Results show significant improvements to large‐scale flood modelling at the watershed scale with standard deviation in the range of 0.30 m and an average fit of around 90%. The main advantage of the proposed approach is to avoid the need to collect expensive bathymetry data to efficiently and accurately simulate flood levels over extensive areas.
Keywords: Ouvrage_Collectif_Numéro1; Site_internet_RIISQ

Coping During Pregnancy Following Exposure to a Natural Disaster: The QF2011 Queensland Flood Study - Chen, T.; Laplante, D.P.; Elgbeili, G.; Brunet, A.; Simcock, G.; Kildea, S.; King, S. (Journal of Affective Disorders, 2020)
Keywords: Brunet_Alain

Efficient or Fair? Operationalizing Ethical Principles in Flood Risk Management: A Case Study on the Dutch‐German Rhine - Ciullo, Alessio; Kwakkel, Jan H.; De Bruijn, Karin M.; Doorn, Neelke; Klijn, Frans (Risk Analysis, 2020)
Abstract Flood risk management decisions in many countries are based on decision‐support frameworks which rely on cost‐benefit analyses. Such frameworks are seldom informative about the geographical distribution of risk, raising questions on the fairness of the proposed policies. In the present work, we propose a new decision criterion that accounts for the distribution of risk reduction and apply it to support flood risk management decisions on a transboundary stretch of the Rhine River. Three types of interventions are considered: embankment heightening, making Room for the River, and changing the discharge distribution of the river branches. The analysis involves solving a flood risk management problem according to four alternative formulations, based on different ethical principles. Formulations based on cost optimization lead to very poor performances in some areas for the sake of reducing the overall aggregated costs. Formulations that also include equity criteria have different results depending on how these are defined. When risk reduction is distributed equally, very poor economic performance is achieved. When risk is distributed equally, results are in line with formulations based on cost optimization, while a fairer risk distribution is achieved. Risk reduction measures also differ, with the cost optimization approach strongly favoring the leverage of changing the discharge distribution and the alternative formulations spending more on embankment heightening and Room for the River, to rebalance inequalities in risk levels. The proposed method advances risk‐based decision‐making by allowing to consider risk distribution aspects and their impacts on the choice of risk reduction measures.

Uncertainty sources in flood projections over contrasting hydrometeorological regimes - Castaneda-Gonzalez, Mariana; Poulin, Annie; Romero-Lopez, Rabindranarth; Turcotte, Richard; Chaumont, Diane (Hydrological Sciences Journal, 2022)
Keywords: Infolettre; Infolettre_Fevrier_2023

Monitoring Water Turbidity in a Temperate Floodplain Using UAV: Potential and Challenges - Bussières, Savannah; Kinnard, Christophe; Clermont, Maxime; Campeau, Stéphane; Dubé-Richard, Daphney; Bordeleau, Pierre-André; Roy, Alexandre (Canadian Journal of Remote Sensing, 2022)
Keywords: Kinnard_Christophe

Gridded flood depth estimates from satellite-derived inundations - Bryant, Seth; McGrath, Heather; Boudreault, Mathieu (Natural Hazards and Earth System Sciences, 2022)
Abstract. Canada's RADARSAT missions improve the potential to study past flood events; however, existing tools to derive flood depths from this remote-sensing data do not correct for errors, leading to poor estimates. To provide more accurate gridded depth estimates of historical flooding, a new tool is proposed that integrates Height Above Nearest Drainage and Cost Allocation algorithms. This tool is tested against two trusted, hydraulically derived, gridded depths of recent floods in Canada. This validation shows the proposed tool outperforms existing tools and can provide more accurate estimates from minimal data without the need for complex physics-based models or expert judgement. With improvements in remote-sensing data, the tool proposed here can provide flood researchers and emergency managers accurate depths in near-real time.
Keywords: Infolettre; Infolettre_Juillet_2022; Site_internet_RIISQ

Ratemaking territories and adverse selection for flood insurance - Boudreault, Mathieu; Ojeda, Angelica (Insurance: Mathematics and Economics, 2022)
Keywords: Infolettre; Infolettre_Novembre_2022

Impacts of Ship-Induced Waves along Shorelines during Flooding Events - Bluteau, Cynthia E.; Van Rooijen, Arnold; Matte, Pascal; Dumont, Dany (Journal of Waterway, Port, Coastal, and Ocean Engineering, 2023)
Keywords: Infolettre; Infolettre_Octobre_2023

Public-private flood management: Who should pay and when? - Bouchard St-Amant, Pier-André; Tchokouagueu, Franck Aurelien; Dumais, Guillaume (Heliyon, 2023)

Urban Flood Detection Using TerraSAR-X and SAR Simulated Reflectivity Maps - Baghermanesh, Shadi Sadat; Jabari, Shabnam; McGrath, Heather (Remote Sensing, 2022)
Synthetic Aperture Radar (SAR) imagery is a vital tool for flood mapping due to its capability to acquire images day and night in almost any weather and to penetrate through cloud cover. In rural areas, SAR backscatter intensity can be used to detect flooded areas accurately; however, the complexity of urban structures makes flood mapping in urban areas a challenging task. In this study, we examine the synergistic use of SAR simulated reflectivity maps and Polarimetric and Interferometric SAR (PolInSAR) features in the improvement of flood mapping in urban environments. We propose a machine learning model employing simulated and PolInSAR features derived from TerraSAR-X images along with five auxiliary features, namely elevation, slope, aspect, distance from the river, and land-use/land-cover that are well-known to contribute to flood mapping. A total of 2450 data points have been used to build and evaluate the model over four different areas with different vegetation and urban density. The results indicated that by using PolInSAR and SAR simulated reflectivity maps together with five auxiliary features, a classification overall accuracy of 93.1% in urban areas was obtained, representing a 9.6% improvement over using the five auxiliary features alone.

Conséquences des inondations de 2019 chez les intervenants de première et de deuxième lignes : le point de vue des principaux intéressés - Maltais, Danielle; Hamel, Ariane; Lansard, Anne-Lise (Canadian Social Work Review, 2024)
Keywords: Infolettre; Infolettre_Octobre_2024

Posttraumatic growth and its relationship with posttraumatic stress symptoms following wildfires: A longitudinal study. - Gaboury, Marie-Pier; Belleville, Geneviève; Lebel, Jessica; Ouellet, Marie-Christine; Morin, Charles; Bouchard, Stéphane; Bergeron, Nicolas; Ghosh, Sunita; Campbell, Tavis; MacMaster, Frank P. (Traumatology, 2023)
Keywords: Infolettre; Infolettre_Decembre_2023

Trinity flame retardant with benzimidazole structure towards unsaturated polyester possessing high thermal stability, fire-safety and smoke suppression with in-depth insight into the smoke suppression mechanism - Li, Zhen; Fu, Teng; Guo, De-Ming; Lu, Jia-Hui; He, Jie-Hao; Chen, Li; Li, Wen-Da; Wang, Yu-Zhong (Polymer, 2023)
Keywords: Infolettre; Infolettre_Juin_2023

Impact of the Carbon Cycle on Mercury Dynamics in a River Impacted by Run-Of-The-River Power Plants, Logging and Forest Fire - Amyot, Marc; Ponton, Dominic; Bilodeau, François; Harrisson, Makaila; Leclerc, Maxime; Millera Ferriz, Lise; Lavoie, Raphaël; Storck, Veronika; Planas, Dolors; Poulain, Alexandre; Walsh, David (Goldschmidt Abstracts, 2020)

Défis de l’action intersectorielle et pistes de réflexion pour renforcer la concertation dans les milieux ruraux du Québec en contexte de pandémie - Richard, Julie; Bergeron, Dave A.; Lessard, Lily; Toupin, Isabelle; Ouellet, Nicole; Bédard, Emmanuelle (Global Health Promotion, 2021)
La présente pandémie nécessite le recours aux mécanismes qui favorisent l’action intersectorielle entre les autorités et les partenaires de différents secteurs de la santé et de la société civile pour coordonner et adapter la réponse socio-sanitaire en fonction des particularités des milieux et de l’évolution de la pandémie. Ce commentaire propose de mettre en lumière quelques défis qui se posent actuellement dans la mise en œuvre d’actions intersectorielles dans les milieux ruraux du Québec. Des pistes de réflexion en faveur du renforcement des mécanismes de concertation nécessaires à la gestion de la pandémie sont proposées.
Keywords: Lessard_Lily

Enhancing public transport use: The influence of soft pull interventions - Zarabi, Zahra; Waygood, E. Owen D.; Olsson, Lars; Friman, Margareta; Gousse-Lessard, Anne-Sophie (Transport Policy, 2024)
Keywords: Gousse-Lessard_Anne-Sophie

Adolescents Exposed to Cumulative Natural Disasters: A Comparison Between their Realities in Rural and Urban Areas - Pouliot, Eve; Maltais, Danielle; Gervais, Christine; Tardif-Grenier, Kristel; Simard, Ann-Sophie; Gauthier, Pascal; Maltais-Dufour, Olivia; Hamel, Ariane (Prehospital and Disaster Medicine, 2023)
Introduction: Over the past years, the Outaouais region (Quebec, Canada) and their residents have had to endure no less than five natural disasters (floods, tornadoes). These disasters are likely to have a variety of consequences on the physical and mental health of adolescents, as well as on their personal, family, school and social lives. The experiences of teenagers are also likely to vary depending on whether they live in rural or urban areas. Method: Data were collected via a self-administered questionnaire in February 2022. A total of 1307 teenagers from two high schools participated in the study by completing an online survey. The questionnaire measured various aspects of the youth's mental health using validated tests, such as manifestations of post-traumatic stress, anxiety and depression, as well as the presence of suicidal thoughts and self-harm. Other aspects of the youth's experience were measured, including their level of social support, school engagement, alcohol and drug use, and coping strategies. Results: One third of young students (n=1307) were experiencing depressive symptoms and suicidal thoughts, as well as significant daily stress. More than 25% of the students had moderate or severe anxiety and thoughts of self-harm. These problems were significantly more prevalent among youths with prior exposure to a natural disaster. The study data also revealed that youths living in rural areas had a more worrying profile than those living in urban areas. Conclusion: Similar to other studies (Ran et al., 2015; Stratta et al., 2014), our research data revealed that youths living in rural areas presented a more concerning profile than those residing in urban areas. It therefore seems important, in future studies and services, to focus more specifically on these teenagers to better understand their needs and to develop adapted services more likely to meet them.

Mixture Probability Models with Covariates: Applications in Estimating Risk of Hydroclimatic Extremes - Yousfi, Nawres; El Adlouni, Salaheddine; Papalexiou, Simon Michael; Gachon, Philippe (Journal of Hydrologic Engineering, 2023)
Keywords: Gachon_Philippe

Atmospheric blocking events in the North Atlantic: trends and links to climate anomalies and teleconnections - Wazneh, Hussein; Gachon, Philippe; Laprise, René; de Vernal, Anne; Tremblay, Bruno (Climate Dynamics, 2021)
Atmospheric blockings are generally associated with large-scale high-pressure systems that interrupt west-to-east atmospheric flow in mid and high latitudes. Blockings cause several days of quasi-stationary weather conditions, and therefore can result in monthly or seasonal climate anomalies and extreme weather events on the affected regions. In this paper, the long-term coupled CERA-20C reanalysis data from 1901 to 2010 are used to evaluate the links between blocking events over the North Atlantic north of 35° N, and atmospheric and oceanic modes of climate variability on decadal time scales. This study indicates more frequent and longer lasting blocking events than previous studies using other reanalyses products. A strong relationship was found between North Atlantic blocking events and North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO) and Baffin Island–West Atlantic (BWA) indices, in fall, winter and spring. More blocking events occur during the negative phases of the NAO index and positive phases of the BWA mode. In some situations, the BWA patterns provide clearer links with the North Atlantic blocking occurrence than with the NAO alone. The correlation between the synchronous occurrences of AMO and blocking is generally weak, although it does increase for a lag of about 6–10 years. Convergent cross mapping (CCM) furthermore demonstrates a significant two-way causal effect between blocking occurrences and the NAO and BWA indices. Finally, while we find no significant trends in blocking frequencies over the last 110 years in the Northern Hemisphere, these events become longer lasting in summer and fall, and more intense in spring in the North Atlantic.
Keywords: Gachon_Philippe

Correction to: Atmospheric blocking events in the North Atlantic: trends and links to climate anomalies and teleconnections - Wazneh, Hussein; Gachon, Philippe; Laprise, René; de Vernal, Anne; Tremblay, Bruno (Climate Dynamics, 2021)
The article: Atmospheric blocking events in the North Atlantic: trends and links to climate anomalies and teleconnections, written by Hussein Wazneh, Philippe Gachon, René Laprise, Anne de Vernal, Bruno Tremblay was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 5 January 2021 without open access.
Keywords: Gachon_Philippe

Predicting malaria risk considering vector control interventions under climate change scenarios - Sadoine, Margaux L.; Zinszer, Kate; Liu, Ying; Gachon, Philippe; Fournier, Michel; Dueymes, Guillaume; Dorsey, Grant; Llerena, Ana; Namuganga, Jane Frances; Nasri, Bouchra; Smargiassi, Audrey (Scientific Reports, 2024)
Many studies have projected malaria risks with climate change scenarios by modelling one or two environmental variables and without the consideration of malaria control interventions. We aimed to predict the risk of malaria with climate change considering the influence of rainfall, humidity, temperatures, vegetation, and vector control interventions (indoor residual spraying (IRS) and long-lasting insecticidal nets (LLIN)). We used negative binomial models based on weekly malaria data from six facility-based surveillance sites in Uganda from 2010–2018, to estimate associations between malaria, environmental variables and interventions, accounting for the non-linearity of environmental variables. Associations were applied to future climate scenarios to predict malaria distribution using an ensemble of Regional Climate Models under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Predictions including interaction effects between environmental variables and interventions were also explored. The results showed upward trends in the annual malaria cases by 25% to 30% by 2050s in the absence of intervention but there was great variability in the predictions (historical vs RCP 4.5 medians [Min–Max]: 16,785 [9,902–74,382] vs 21,289 [11,796–70,606]). The combination of IRS and LLIN, IRS alone, and LLIN alone would contribute to reducing the malaria burden by 76%, 63% and 35% respectively. Similar conclusions were drawn from the predictions of the models with and without interactions between environmental factors and interventions, suggesting that the interactions have no added value for the predictions. The results highlight the need for maintaining vector control interventions for malaria prevention and control in the context of climate change given the potential public health and economic implications of increasing malaria in Uganda.
Keywords: Gachon_Philippe

Differential Influence of Environmental Factors on Malaria Due to Vector Control Interventions in Uganda - Sadoine, Margaux L.; Smargiassi, Audrey; Liu, Ying; Gachon, Philippe; Fournier, Michel; Dueymes, Guillaume; Namuganga, Jane Frances; Dorsey, Grant; Nasri, Bouchra; Zinszer, Kate (International Journal of Environmental Research and Public Health, 2023)
Background: Few studies have explored how vector control interventions may modify associations between environmental factors and malaria. Methods: We used weekly malaria cases reported from six public health facilities in Uganda. Environmental variables (temperature, rainfall, humidity, and vegetation) were extracted from remote sensing sources. The non-linearity of environmental variables was investigated, and negative binomial regression models were used to explore the influence of indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) on associations between environmental factors and malaria incident cases for each site as well as pooled across the facilities, with or without considering the interaction between environmental variables and vector control interventions. Results: An average of 73.3 weekly malaria cases per site (range: 0–597) occurred between 2010 and 2018. From the pooled model, malaria risk related to environmental variables was reduced by about 35% with LLINs and 63% with IRS. Significant interactions were observed between some environmental variables and vector control interventions. There was site-specific variability in the shape of the environment–malaria risk relationship and in the influence of interventions (6 to 72% reduction in cases with LLINs and 43 to 74% with IRS). Conclusion: The influence of vector control interventions on the malaria–environment relationship need to be considered at a local scale in order to efficiently guide control programs.
Keywords: Gachon_Philippe

Differential impact of environment on malaria due to control interventions in Uganda, 2010-2018 - Sadoine, Margaux; Smargiassi, Audrey; Liu, Ying; Gachon, Philippe; Dueymes, Guillaume; Namuganga, Jane Frances; Dorsey, Grant; Fournier, Michel; Nasri, Bouchra; Zinszer, Kate (ISEE Conference Abstracts, 2022)
Keywords: Gachon_Philippe

The influence of the environment and indoor residual spraying on malaria risk in a cohort of children in Uganda - Sadoine, Margaux L.; Smargiassi, Audrey; Liu, Ying; Gachon, Philippe; Dueymes, Guillaume; Dorsey, Grant; Fournier, Michel; Nankabirwa, Joaniter I.; Rek, John; Zinszer, Kate (Scientific Reports, 2022)
Studies have estimated the impact of the environment on malaria incidence although few have explored the differential impact due to malaria control interventions. Therefore, the objective of the study was to evaluate the effect of indoor residual spraying (IRS) on the relationship between malaria and environment (i.e. rainfall, temperatures, humidity, and vegetation) using data from a dynamic cohort of children from three sub-counties in Uganda. Environmental variables were extracted from remote sensing sources and averaged over different time periods. General linear mixed models were constructed for each sub-counties based on a log-binomial distribution. The influence of IRS was analysed by comparing marginal effects of environment in models adjusted and unadjusted for IRS. Great regional variability in the shape (linear and non-linear), direction, and magnitude of environmental associations with malaria risk were observed between sub-counties. IRS was significantly associated with malaria risk reduction (risk ratios vary from RR = 0.03, CI 95% [0.03–0.08] to RR = 0.35, CI95% [0.28–0.42]). Model adjustment for this intervention changed the magnitude and/or direction of environment-malaria associations, suggesting an interaction effect. This study evaluated the potential influence of IRS in the malaria-environment association and highlighted the necessity to control for interventions when they are performed to properly estimate the environmental influence on malaria. Local models are more informative to guide intervention program compared to national models.
Keywords: Gachon_Philippe

Yellow fever virus outbreak in Brazil under current and future climate - Sadeghieh, Tara; Sargeant, Jan M.; Greer, Amy L.; Berke, Olaf; Dueymes, Guillaume; Gachon, Philippe; Ogden, Nicholas H.; Ng, Victoria (Infectious Disease Modelling, 2021)
Keywords: Gachon_Philippe

Zika virus outbreak in Brazil under current and future climate - Sadeghieh, Tara; Sargeant, Jan M.; Greer, Amy L.; Berke, Olaf; Dueymes, Guillaume; Gachon, Philippe; Ogden, Nicholas H.; Ng, Victoria (Epidemics, 2021)
Keywords: Gachon_Philippe

Assessment of simulations of a polar low with the Canadian Regional Climate Model - Moreno-Ibáñez, Marta; Laprise, René; Gachon, Philippe (PLOS ONE, 2023)
Polar lows (PLs), which are intense maritime polar mesoscale cyclones, are associated with severe weather conditions. Due to their small size and rapid development, PL forecasting remains a challenge. Convection-permitting models are adequate to forecast PLs since, compared to coarser models, they provide a better representation of convection as well as surface and near-surface processes. A PL that formed over the Norwegian Sea on 25 March 2019 was simulated using the convection-permitting Canadian Regional Climate Model version 6 (CRCM6/GEM4, using a grid mesh of 2.5 km) driven by the reanalysis ERA5. The objectives of this study were to quantify the impact of the initial conditions on the simulation of the PL, and to assess the skill of the CRCM6/GEM4 at reproducing the PL. The results show that the skill of the CRCM6/GEM4 at reproducing the PL strongly depends on the initial conditions. Although in all simulations the synoptic environment is favourable for PL development, with a strong low-level temperature gradient and an upper-level through, only the low-level atmospheric fields of three of the simulations lead to PL development through baroclinic instability. The two simulations that best captured the PL represent a PL deeper than the observed one, and they show higher temperature mean bias compared to the other simulations, indicating that the ocean surface fluxes may be too strong. In general, ERA5 has more skill than the simulations at reproducing the observed PL, but the CRCM6/GEM4 simulation with initialisation time closer to the genesis time of the PL reproduces quite well small scale features as low-level baroclinic instability during the PL development phase.
Keywords: Gachon_Philippe

Analysis of the Development Mechanisms of a Polar Low over the Norwegian Sea Simulated with the Canadian Regional Climate Model - Moreno-Ibáñez, Marta; Laprise, René; Gachon, Philippe (Atmosphere, 2023)
Polar lows (PLs) are maritime mesoscale cyclones associated with severe weather. They develop during marine cold air outbreaks near coastlines and the sea ice edge. Unfortunately, our knowledge about the mechanisms leading to PL development is still incomplete. This study aims to provide a detailed analysis of the development mechanisms of a PL that formed over the Norwegian Sea on 25 March 2019 using the output of a simulation with the sixth version of the Canadian Regional Climate Model (CRCM6/GEM4), a convection-permitting model. First, the life cycle of the PL is described and the vertical wind shear environment is analysed. Then, the horizontal wind divergence and the baroclinic conversion term are computed, and a surface pressure tendency equation is developed. In addition, the roles of atmospheric static stability, latent heat release, and surface heat and moisture fluxes are explored. The results show that the PL developed in a forward-shear environment and that moist baroclinic instability played a major role in its genesis and intensification. Baroclinic instability was initially only present at low levels of the atmosphere, but later extended upward until it reached the mid-troposphere. Whereas the latent heat of condensation and the surface heat fluxes also contributed to the development of the PL, convective available potential energy and barotropic conversion do not seem to have played a major role in its intensification. In conclusion, this study shows that a convection-permitting model simulation is a powerful tool to study the details of the structure of PLs, as well as their development mechanisms.
Keywords: Gachon_Philippe

Climate change alone cannot explain boreal caribou range recession in Quebec since 1850 - Morineau, Chloé; Boulanger, Yan; Gachon, Philippe; Plante, Sabrina; St‐Laurent, Martin‐Hugues (Global Change Biology, 2023)
Abstract The contraction of species range is one of the most significant symptoms of biodiversity loss worldwide. While anthropogenic activities and habitat alteration are major threats for several species, climate change should also be considered. For species at risk, differentiating the effects of human disturbances and climate change on past and current range transformations is an important step towards improved conservation strategies. We paired historical range maps with global atmospheric reanalyses from different sources to assess the potential effects of recent climate change on the observed northward contraction of the range of boreal populations of woodland caribou ( Rangifer tarandus caribou ) in Quebec (Canada) since 1850. We quantified these effects by highlighting the discrepancies between different southern limits of the caribou's range (used as references) observed in the past and reconstitutions obtained through the hindcasting of the climate conditions within which caribou are currently found. Hindcasted southern limits moved ~105 km north over time under all reanalysis datasets, a trend drastically different from the ~620 km reported for observed southern limits since 1850. The differences in latitudinal shift through time between the observed and hindcasted southern limits of distribution suggest that caribou range recession should have been only 17% of what has been observed since 1850 if recent climate change had been the only disturbance driver. This relatively limited impact of climate reinforces the scientific consensus stating that caribou range recession in Quebec is mainly caused by anthropogenic drivers (i.e. logging, development of the road network, agriculture, urbanization) that have modified the structure and composition of the forest over the past 160 years, paving the way for habitat‐mediated apparent competition and overharvesting. Our results also call for a reconsideration of past ranges in models aiming at projecting future distributions, especially for endangered species.
Keywords: Gachon_Philippe

Respiratory and Otolaryngology Symptoms Following the 2019 Spring Floods in Quebec - Landaverde, Elsa; Généreux, Mélissa; Maltais, Danielle; Gachon, Philippe (International Journal of Environmental Research and Public Health, 2022)
Background: Although floods may have important respiratory health impacts, few studies have examined this issue. This study aims to document the long-term impacts of the spring floods of 2019 in Quebec by (1) describing the population affected by the floods; (2) assessing the impacts on the respiratory system according to levels of exposure; and (3) determining the association between stressors and respiratory health. Methods: A population health survey was carried out across the six most affected regions 8–10 months post-floods. Data were collected on self-reported otolaryngology (ENT) and respiratory symptoms, along with primary and secondary stressors. Three levels of exposure were examined: flooded, disrupted and unaffected. Results: One in ten respondents declared being flooded and 31.4% being disrupted by the floods. Flooded and disrupted participants reported significantly more ENT symptoms (adjusted odds ratio (aOR): 3.18; 95% CI: 2.45–4.14; aOR: 1.76; 95% CI: 1.45–2.14) and respiratory symptoms (aOR: 3.41; 95% CI: 2.45–4.75; aOR: 1.45; 95% CI: 1.10–1.91) than the unaffected participants. All primary stressors and certain secondary stressors assessed were significantly associated with both ENT and respiratory symptoms, but no “dose–response” gradient could be observed. Conclusion: This study highlights the long-term adverse effects of flood exposure on respiratory health.
Number: 18 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Gachon_Philippe; Généreux_Mélissa; Infolettre; Infolettre_Octobre_2022; Site_internet_RIISQ

The 2023 wildfire season in Québec: an overview of extreme conditions, impacts, lessons learned and considerations for the future - Boulanger, Yan; Arseneault, Dominique; Bélisle, Annie Claude; Bergeron, Yves; Boucher, Jonathan; Boucher, Yan; Danneyrolles, Victor; Erni, Sandy; Gachon, Philippe; Girardin, Martin P.; Grant, Eliane; Grondin, Pierre; et al. (Canadian Journal of Forest Research, 2024)
The 2023 wildfire season in Québec set records due to extreme warm and dry conditions, burning 4.5 million hectares and indicating persistent and escalating impacts associated with climate change. This study reviews the unusual weather conditions that led to the fires, discussing their extensive impacts on the forest sector, fire management, boreal caribou habitats, and particularly the profound effects on First Nation communities. The wildfires led to significant declines in forest productivity and timber supply, overwhelming fire management resources, and necessitating widespread evacuations. First Nation territories were dramatically altered, facing severe air quality issues and disruptions. While caribou impacts were modest across the province, the broader ecological, economical, and social repercussions were considerable. To mitigate future extreme wildfire seasons, the study suggests changes in forest management practices to increase forest resilience and resistance, adapting industrial structures to changes in wood type harvested, and enhancing fire suppression and risk management strategies. It calls for a comprehensive, unified approach to risk management that incorporates the lessons learned from the 2023 fire season and accounts for ongoing climate change. The studyunderscores the urgent need for detailed planning and proactive measures to reduce the growing risks and impacts of wildfires in a changing climate.
Keywords: Gachon_Philippe; Guillemette_Francois

Natural disasters and risk aversion - Bourdeau-Brien, Michael; Kryzanowski, Lawrence (Journal of Economic Behavior & Organization, 2020)
Keywords: Bourdeau-Brien_Michael; Ouvrage_Collectif_Numéro1

Soil and water bioengineering in cold rivers: A biogeomorphological perspective - Prugne, Matthieu; Corenblit, Dov; Boivin, Maxime; Evette, André; Buffin-Bélanger, Thomas (Ecological Engineering, 2024)
Keywords: Boivin_Maxime

Dynamiques hydrogéomorphologiques historiques et actuelles d'une rivière perturbée par les activités de la drave et analyse des impacts d'un démantèlement de barrage - Bouchard, Marianne; Boivin, Maxime (Canadian Geographies / Géographies canadiennes, 2023)
Résumé Au Québec, la dynamique fluviale de la rivière des Escoumins a été perturbée par l'industrie forestière pendant plus d'un siècle. Un barrage a notamment été construit près de l'embouchure en 1846, puis démantelé en 2013. Ces perturbations ont entraîné des répercussions importantes sur l'équilibre du cours d'eau et sur l'habitat du saumon atlantique. Cette étude propose donc de caractériser la dynamique fluviale de la rivière des Escoumins et d'analyser les impacts du démantèlement du barrage dans une perspective de restauration des processus hydrogéomorphologiques et d'amélioration de l'habitat du saumon atlantique. Les résultats suggèrent que la trajectoire de la rivière a évolué différemment en fonction du style fluvial et de la composition granulométrique de chacun de ses segments homogènes. Toutefois, ce sont les activités de la drave et le démantèlement du barrage qui semblent avoir été les facteurs de contrôle les plus importants sur l'évolution de la trajectoire du cours d'eau. Le démantèlement a notamment permis la restauration de processus hydrogéomorphologiques et la libre circulation des salmonidés. Une meilleure procédure entourant le démantèlement des barrages et leur suivi devrait donc être mise en place au Canada afin de favoriser cette pratique . , Abstract In Quebec, the fluvial dynamics of the Escoumins River have been disturbed by the forestry industry for over a century. Most specifically, a dam was built near the mouth of the river in 1846 and dismantled in 2013. These disturbances had significant repercussions on the equilibrium of the river and Atlantic salmon habitat. This study therefore proposes to characterize the fluvial dynamics of the Escoumins River and to analyze the impacts of the dam dismantling from the perspective of restoring hydrogeomorphological processes and improving Atlantic salmon habitat. The results suggest that the trajectory of the river evolved differently depending on the fluvial style and the grain size composition of each of its homogeneous segments. However, log drive activities in river and dam removal appear to have been the most important controlling factors on the evolution of the stream trajectory. The dismantling notably allowed the restoration of hydrogeomorphological processes and the free movement of salmonids. A better procedure for dam removal and monitoring should be put in place in Canada to encourage this practice . , Messages clés Les activités de la drave et le démantèlement du barrage ont fortement affecté la trajectoire hydrogéomorphologique de la rivière des Escoumins, au Québec. Un démantèlement de barrage permet une restauration globale de l'écosystème fluvial et de ses processus hydrogéomorphologiques en plus d'améliorer les habitats disponibles pour les espèces aquatiques. Le démantèlement des barrages désuets ou désaffectés doit être considéré pour la restauration des écosystèmes fluviaux et une meilleure procédure entourant cette pratique doit être mise en place au Canada.
Keywords: Boivin_Maxime

Detection of Management Practices and Cropping Phases in Wild Lowbush Blueberry Fields Using Multispectral UAV Data - Marty, Charles; Khare, Siddhartha; Rossi, Sergio; Lafond, Jean; Boivin, Maxime; Paré, Maxime C. (Canadian Journal of Remote Sensing, 2022)
Keywords: Boivin_Maxime

Japanese knotweed increases soil erosion on riverbanks - Matte, Rébecca; Boivin, Maxime; Lavoie, Claude (River Research and Applications, 2022)
Abstract For years, Japanese knotweed ( Reynoutria japonica ) has been suspected of accelerating riverbank erosion, despite a lack of convincing evidence. The stems of this invasive plant die back following the first autumn frosts, leaving the soil unprotected during winter and spring floods. In Québec (Canada), riverbank erosion may also be accentuated by ice during mechanical ice breakups. The objective of this study was to evaluate the influence of knotweed on riverbank erosion along a river invaded by the species, within a context of floods with ice. The elevation along 120 cross‐sectional riverbank profiles, occupied or not by knotweed, was measured before and after the spring flood of 2019. On average, riverbanks occupied by knotweed had nearly 3 cm more soil erosion than riverbanks without knotweed, a statistically significant difference. Stem density also influenced erosion: the higher the density, the greater the soil loss. Certain riverside conditions, such as the slope of the riverbank or being located on an islet, interacted with knotweed, further accentuating erosion. Soil losses measured between November 2018 and May–June 2019 were particularly pronounced, but the spring flood was also exceptional, with a recurrence interval close to 50 years. On the other hand, soil loss from rivers invaded by knotweed can be expected to increase over time, as this invasive species spreads rapidly in riparian habitats.
Keywords: Boivin_Maxime; Infolettre; Infolettre_Janvier_2022; Site_internet_RIISQ

Can the Morphological Quality Index (MQI) be used to determine the ecological status of lowland rivers? - Lemay, Johnathan; Biron, Pascale M.; Boivin, Maxime; Stämpfli, Nicolas; Foote, Kyleisha (Geomorphology, 2021)
Keywords: Boivin_Maxime

Overview of Retrogressive Landslide Risk Analysis in Sensitive Clay Slope - Richer, Blanche; Saeidi, Ali; Boivin, Maxime; Rouleau, Alain (Geosciences, 2020)
Sensitive clays are known for producing retrogressive landslides, also called spread or flowslides. The key characteristics associated with the occurrence of these landslides on a sensitive clay slope must be assessed, and the potential retrogressive distance must be evaluated. Common risk analysis methods include empirical methods for estimating the distance of potential retrogression, analytical limit equilibrium methods, numerical modelling methods using the strength reduction technique, and the integration of a progressive failure mechanism into numerical methods. Methods developed for zoning purposes in Norway and Quebec provide conservative results in most cases, even if they don’t cover the worst cases scenario. A flowslide can be partially analysed using analytical limit equilibrium methods and numerical methods having strength reduction factor tools. Numerical modelling of progressive failure mechanisms using numerical methods can define the critical parameters of spread-type landslides, such as critical unloading and the retrogression distance of the failure. Continuous improvements to the large-deformation numerical modeling approach allow its application to all types of sensitive clay landslides.
Keywords: Boivin_Maxime

Finding the Voice of the River: Beyond Restoration and ManagementFinding the Voice of the River: Beyond Restoration and ManagementGary J.Brierley. Cham, Switzerland: Palgrave Pivot, 2020. xviii and 179 pp., references, index. $59.99 hardcover (ISBN 978-3-030-27067-4), $44.99 electronic (ISBN 978-3-030-27068-1).: Gary J. Brierley. Cham, Switzerland: Palgrave Pivot, 2020. xviii and 179 pp., references, index. $59.99 hardcover (ISBN 978-3-030-27067-4), $44.99 electronic (ISBN 978-3-030-27068-1). - Tooth, Stephen (The AAG Review of Books, 2023)
Keywords: Ouvrage_Collectif_Numéro1

Switzerland’s transition from flood defence to flood-adapted land use–A policy coordination perspective - Löschner, Lukas; Nordbeck, Ralf (Land Use Policy, 2020)

Large Scale Flood Risk Mapping in Data Scarce Environments: An Application for Romania - Albano, Raffaele; Samela, Caterina; Crăciun, Iulia; Manfreda, Salvatore; Adamowski, Jan; Sole, Aurelia; Sivertun, Åke; Ozunu, Alexandru (Water, 2020)
Large-scale flood risk assessment is essential in supporting national and global policies, emergency operations and land-use management. The present study proposes a cost-efficient method for the large-scale mapping of direct economic flood damage in data-scarce environments. The proposed framework consists of three main stages: (i) deriving a water depth map through a geomorphic method based on a supervised linear binary classification; (ii) generating an exposure land-use map developed from multi-spectral Landsat 8 satellite images using a machine-learning classification algorithm; and (iii) performing a flood damage assessment using a GIS tool, based on the vulnerability (depth–damage) curves method. The proposed integrated method was applied over the entire country of Romania (including minor order basins) for a 100-year return time at 30-m resolution. The results showed how the description of flood risk may especially benefit from the ability of the proposed cost-efficient model to carry out large-scale analyses in data-scarce environments. This approach may help in performing and updating risk assessments and management, taking into account the temporal and spatial changes in hazard, exposure, and vulnerability.

A participatory system dynamics modeling approach to facilitate collaborative flood risk management: A case study in the Bradano River (Italy) - Perrone, Antonio; Inam, Azhar; Albano, Raffaele; Adamowski, Jan; Sole, Aurelia (Journal of Hydrology, 2020)

Use of digital elevation models for flood susceptibility assessment via a hydrogeomorphic approach: A case study of the Basento River in Italy - Albano, Raffaele; Adamowski, Jan (Natural Hazards, 2025)
Abstract Floods are the most common and threatening natural risk for many countries in the world. Flood risk mapping is therefore of great importance for managing socio-economic and environmental impacts. Several researchers have proposed low-complexity and cost-effective flood mapping solutions that are useful for data scarce environments or at large-scale. Among these approaches, a line of recent research focuses on hydrogeomorphic methods that, due to digital elevation models (DEMs), exploit the causality between past flood events and the hydraulic geometry of floodplains. This study aims to compare the use of freely-available DEMs to support an advanced hydrogeomorphic method, Geomorphic Flood Index (GFI), to map flood-prone areas of the Basento River basin (Italy). The five selected DEMs are obtained from different sources, are characterized by different resolutions, spatial coverage, acquisition process, processing and validation, etc., and include: (i) HydroSHEDS v.1.1 (resolution 3 arc-seconds), hydrologically conditioned, derived primarily from STRM (NASA) and characterized by global coverage; (ii) ASTER GDEM v.3 with a res. of around 30 m (source: METI and NASA) and global coverage; (iii) EU-DEM v. 1.1 (res. 1 arc-second), Pan-European and combining SRTM and ASTER GDEM, customized to obtain a consistency with the EU-Hydro and screened to remove artefacts (source: Copernicus Land Monitoring Service); (iv) TinItaly DEM v. 1.1, (res. 10 m-cell size grid) and produced and distributed by INGV with coverage of the entire Italian territory; (v) Laser Scanner DEM with high resolution (5 m cell size grid) produced on the basis of Ground e Model Keypoint and available as part of the RSDI geoportal of the Basilicata Region with coverage at the regional administrative level. The effects of DEMs on the performance of the GFI calibration on the main reach of the Basento River, and its validation on one of its mountain tributaries (Gallitello Creek), were evaluated with widely accepted statistical metrics, i.e., the Area Under the Receiver Operating Characteristics (ROC) curve (AUC), Accuracy, Sensitivity and Specificity. Results confirmed the merits of the GFI in flood mapping using simple watershed characteristics and showed high Accuracy (AUC reached a value over 0.9 in all simulations) and low dependency on changes in the adopted DEMs and standard flood maps (1D and 2D hydraulic models or three return periods). The EU-DEM was identified as the most suitable data source for supporting GFI mapping with an AUC > 0.97 in the calibration phase for the main river reach. This may be due in part to its appropriate resolution for hydrological application but was also due to its customized pre-processing that supported an optimal description of the river network morphology. Indeed, EU-DEM obtained the highest performances (e.g., Accuracy around 98%) even in the validation phase where better results were expected from the high-resolution DEM (due to the very small size of Gallitello Creek cross-sections). For other DEMs, GFI generally showed an increase in metrics performance when, in the calibration phase, it neglected the floodplains of the river delta, where the standard flood map is produced using a 2D hydraulic model. However, if the DEMs were hydrologically conditioned with a relatively simple algorithm that forced the stream flow in the main river network, the GFI could be applied to the whole Basento watershed, including the delta, with a similar performance.
Keywords: Infolettre; Infolettre_Fevrier_2025

Flood scenario spatio-temporal mapping via hydrological and hydrodynamic modelling and a remote sensing dataset: A case study of the Basento river (Southern Italy) - Albano, Raffaele; Limongi, Carmine; Dal Sasso, Silvano Fortunato; Mancusi, Leonardo; Adamowski, Jan (International Journal of Disaster Risk Reduction, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

A 3D Numerical Study on the Tidal Asymmetry, Residual Circulation and Saline Intrusion in the Gironde Estuary (France) - Pham Van Bang, Damien; Phan, Ngoc Vinh; Guillou, Sylvain; Nguyen, Kim Dan (Water, 2023)
A full 3D numerical model is used for studying tidal asymmetry, estuarine circulation, and saline intrusion in the Gironde estuary. The model is calibrated and verified using the data measured during two field surveys in the Gironde estuary. Harmonic analysis of numerical results is proposed to understand how the superposition of M2, M4 and M6 components generate a complex estuarine circulation and salinity intrusion in the Gironde estuary. The numerical results show that the M6 component plays a significant role as important as the M4 one in modifying the nature of tidal asymmetry, especially in the Gironde upper estuary. In this case, the use of the phase lag between M2 and M4, neglecting M6, to predict the tidal asymmetry nature could produce errors. The effect of asymmetrical tides on saline intrusion and residual circulation is specifically discussed here.
Keywords: PhamVanBang_Damien

Urban flood risk and green infrastructure: Who is exposed to risk and who benefits from investment? A case study of three U.S. Cities - Pallathadka, Arun; Sauer, Jason; Chang, Heejun; Grimm, Nancy B. (Landscape and Urban Planning, 2022)

County-scale flood risk assessment of properties and associated population in the United States - Srivastava, Shivendra; Gerdes, Tyler; Roy, Tirthankar (Natural Hazards, 2024)

A rasterized building footprint dataset for the United States - Heris, Mehdi P.; Foks, Nathan Leon; Bagstad, Kenneth J.; Troy, Austin; Ancona, Zachary H. (Scientific Data, 2020)
Abstract Microsoft released a U.S.-wide vector building dataset in 2018. Although the vector building layers provide relatively accurate geometries, their use in large-extent geospatial analysis comes at a high computational cost. We used High-Performance Computing (HPC) to develop an algorithm that calculates six summary values for each cell in a raster representation of each U.S. state, excluding Alaska and Hawaii: (1) total footprint coverage, (2) number of unique buildings intersecting each cell, (3) number of building centroids falling inside each cell, and area of the (4) average, (5) smallest, and (6) largest area of buildings that intersect each cell. These values are represented as raster layers with 30 m cell size covering the 48 conterminous states. We also identify errors in the original building dataset. We evaluate precision and recall in the data for three large U.S. urban areas. Precision is high and comparable to results reported by Microsoft while recall is high for buildings with footprints larger than 200 m2 but lower for progressively smaller buildings.
Keywords: Ouvrage_Collectif_Numéro1

Climate indices to characterize climatic changes across southern Canada - Wazneh, Hussein; Arain, M. Altaf; Coulibaly, Paulin (Meteorological Applications, 2020)
Abstract The present study analyses the impacts of past and future climate change on extreme weather events for southern parts of Canada from 1981 to 2100. A set of precipitation and temperature‐based indices were computed using the downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) multi‐model ensemble projections at 8 km resolution over the 21st Century for two representative concentration pathway (RCP) scenarios: RCP4.5 and RCP8.5. The results show that this region is expected to experience stronger warming and a higher increase in precipitation extremes in future. Generally, projected changes in minimum temperature will be greater than changes in maximum temperature, as shown by respective indices. A decrease in frost days and an increase in warm nights will be expected. By 2100 there will be no cool nights and cool days. Daily minimum and maximum temperatures will increase by 12 and 7°C, respectively, under the RCP8.5 scenario, when compared with the reference period 1981–2000. The highest warming in minimum temperature and decrease in cool nights and days will occur in Ontario and Quebec provinces close to the Great Lakes and Hudson Bay. The highest warming in maximum temperature will occur in the southern parts of Alberta and Saskatchewan. Annual total precipitation is expected to increase by about 16% and the occurrence of heavy precipitation events by five days. The highest increase in annual total precipitation will occur in the northern parts of Ontario and Quebec and in western British Columbia.

Individual and environmental correlates of tap water consumption among adolescents in Canada - Vézina-Im, Lydi-Anne; Beaulieu, Dominique; Turcotte, Stéphane; Turcotte, Anne-Frédérique; Lessard, Lily; Delisle-Martel, Joannie; Boucher, Danielle; Labbé, Valérie; Gingras, Mariane (Appetite, 2024)
Keywords: Lessard_Lily

Monitoring the evolution of individuals’ flood-related adaptive behaviors over time: two cross-sectional surveys conducted in the Province of Quebec, Canada - Valois, Pierre; Tessier, Maxime; Bouchard, David; Talbot, Denis; Morin, Alexandre J. S.; Anctil, François; Cloutier, Geneviève (BMC Public Health, 2020)
Abstract Climate change is predicted to increase the frequency and intensity of floods in the province of Quebec, Canada. Therefore, in 2015, to better monitor the level of adaptation to flooding of Quebec residents living in or near a flood-prone area, the Quebec Observatory of Adaptation to Climate Change developed five indices of adaptation to flooding, according to the chronology of events. The present study was conducted 4 years later and is a follow-up to the 2015 one. Two independent samples of 1951 (2015) and 974 (2019) individuals completed a questionnaire on their adoption (or non-adoption) of flood adaptation behaviors, their perception of the mental and physical impacts of flooding, and their knowledge of the fact that they lived in a flood-prone area. The results of the study demonstrated the measurement invariance of the five indices across two different samples of people over time, ensuring that the differences (or absence of differences) observed in flood-related adaptive behaviors between 2015 and 2019 were real and not due to measurement errors. They also showed that, overall, Quebeckers’ flood-related adaptive behaviors have not changed considerably since 2015, with adaptation scores being similar in 2019 for four of the five flood indices. Moreover, the results indicated an increase in self-reported physical and mental health issues related to past flooding events, as well as a larger proportion of people having consulted a health professional because of these problems. Thus, this study provides a better understanding of flood adaptation in Quebec over the past 4 years and confirms that the five adaptive behavior indices developed in 2015 are appropriate tools for monitoring changes in flood adaptation in the province. Finally, our results showed that little has changed in Quebeckers’ adoption of adaptive behaviors, highlighting the need for awareness raising in order to limit the impacts that climate change will have on the population.

Assessment of the Potential Hydrological Impacts of Climate Change in Quebec—Canada, a Refined Neutral Approach - Valencia Giraldo, Marinela Del Carmen; Ricard, Simon; Anctil, François (Water, 2023)
There is currently much discussion as to whether probabilistic (top–down) or possibilistic (bottom–up) approaches are the most appropriate to estimate potential future climate impacts. In a context of deep uncertainty, such as future climate, bottom-up approaches aimed at assessing the sensitivity and vulnerability of systems to changes in climate variables have been gaining ground. A refined framework is proposed here (in terms of coherence, structure, uncertainty, and results analysis) that adopts the scenario–neutral method of the bottom–up approach, but also draws on some elements of the top–down approach. What better guides the task of assessing the potential hydroclimatological impacts of changing climatic conditions in terms of the sensitivity of the systems, differential analysis of climatic stressors, paths of change, and categorized response of the scenarios: past, changing, compensatory, and critical condition. The results revealed a regional behavior (of hydroclimatology, annual water balances, and snow) and a differential behavior (of low flows). We find, among others, the plausible scenario in which increases in temperature and precipitation would generate the same current mean annual flows, with a reduction of half of the snow, a decrease in low flows (significant, but differentiated between basins), and a generalized increase in dry events.

2 °C vs. High Warming: Transitions to Flood-Generating Mechanisms across Canada - Teufel, Bernardo; Sushama, Laxmi (Water, 2021)
Fluvial flooding in Canada is often snowmelt-driven, thus occurs mostly in spring, and has caused billions of dollars in damage in the past decade alone. In a warmer climate, increasing rainfall and changing snowmelt rates could lead to significant shifts in flood-generating mechanisms. Here, projected changes to flood-generating mechanisms in terms of the relative contribution of snowmelt and rainfall are assessed across Canada, based on an ensemble of transient climate change simulations performed using a state-of-the-art regional climate model. Changes to flood-generating mechanisms are assessed for both a late 21st century, high warming (i.e., Representative Concentration Pathway 8.5) scenario, and in a 2 °C global warming context. Under 2 °C of global warming, the relative contribution of snowmelt and rainfall to streamflow peaks is projected to remain close to that of the current climate, despite slightly increased rainfall contribution. In contrast, a high warming scenario leads to widespread increases in rainfall contribution and the emergence of hotspots of change in currently snowmelt-dominated regions across Canada. In addition, several regions in southern Canada would be projected to become rainfall dominated. These contrasting projections highlight the importance of climate change mitigation, as remaining below the 2 °C global warming threshold can avoid large changes over most regions, implying a low likelihood that expensive flood adaptation measures would be necessary.

Flood rings, earlywood vessels and hydrological signal in Fraxinus pennsylvanica trees growing along the central Assiniboine river floodplain, southcentral Canada - Tardif, Jacques C.; Conciatori, France; Smith, David L. (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2023)

Identification of flood seasonality and drivers across Canada - Singh, Jitendra; Ghosh, Subimal; Simonovic, Slobodan P.; Karmakar, Subhankar (Hydrological Processes, 2021)
Abstract Floods are the most frequently occurring natural hazard in Canada. An in‐depth understanding of flood seasonality and its drivers at a national scale is essential. Here, a circular, statistics‐based approach is implemented to understand the seasonality of annual‐maximum floods (streamflow) and to identify their responsible drivers across Canada. Nearly 80% and 70% of flood events were found to occur during spring and summer in eastern and western watersheds across Canada, respectively. Flooding in the eastern and western watersheds was primarily driven by snowmelt and extreme precipitation, respectively. This observation suggests that increases in temperature have led to early spring snowmelt‐induced floods throughout eastern Canada. Our results indicate that precipitation (snowmelt) variability can exert large controls on the magnitude of flood peaks in western (eastern) watersheds in Canada. Further, the nonstationarity of flood peaks is modelled to account for impact of the dynamic behaviour of the identified flood drivers on extreme‐flood magnitude by using a cluster of 74 generalized additive models for location scale and shape models, which can capture both the linear and nonlinear characteristics of flood‐peak changes and can model its dependence on external covariates. Using nonstationary frequency analysis, we find that increasing precipitation and snowmelt magnitudes directly resulted in a significant increase in 50‐year streamflow. Our results highlight an east–west asymmetry in flood seasonality, indicating the existence of a climate signal in flood observations. The understating of flood seasonality and flood responses under the dynamic characteristics of precipitation and snowmelt extremes may facilitate the predictability of such events, which can aid in predicting and managing their impacts.

Managing residual flood risk behind levees: Comparing USA , France, and Quebec (Canada) - Serra‐Llobet, Anna; Tourment, Rémy; Montané, Antonin; Buffin‐Belanger, Thomas (Journal of Flood Risk Management, 2022)
Abstract Although hydraulic infrastructure such as levees remain important for flood risk management in the USA, France, and Quebec (Canada), there is increasing emphasis on nonstructural measures, such as regulatory flood maps, to reduce exposure and vulnerability, for example, preventing people from building in high hazard areas. One key concept related to areas protected by levees is that of “residual risk”, that is, the risk from floods greater than the design standard of the levees (levee overtopping) and from levee breach. In this article, we review the legislative framework for regulatory flood maps in the USA, France, and Quebec (Canada) and compare how residual risk behind protective structures is taken into account (or not) in regulatory flood maps. We find big differences in how the USA, France and Canada manage residual risk behind the levees. While in France the area behind levees is part of the regulatory flood prone area, and land use restrictions, building codes, emergency measures and risk communication are mandatory, in the USA the area behind levees is only shown as part of the regulatory flood prone area if the levee is not accredited. In Quebec, regulatory flood maps in general follow the French approach with a few exceptions.
Keywords: Infolettre; Infolettre_Avril_2022

Advancing Spatial Drought Forecasts by Integrating an Improved Outlier Robust Extreme Learning Machine with Gridded Data: A Case Study of the Lower Mainland Basin, British Columbia, Canada - Salimi, Amirhossein; Noori, Amir; Ebtehaj, Isa; Ghobrial, Tadros; Bonakdari, Hossein (Sustainability, 2024)
Droughts have extensive consequences, affecting the natural environment, water quality, public health, and exacerbating economic losses. Precise drought forecasting is essential for promoting sustainable development and mitigating risks, especially given the frequent drought occurrences in recent decades. This study introduces the Improved Outlier Robust Extreme Learning Machine (IORELM) for forecasting drought using the Multivariate Standardized Drought Index (MSDI). For this purpose, four observation stations across British Columbia, Canada, were selected. Precipitation and soil moisture data with one up to six lags are utilized as inputs, resulting in 12 variables for the model. An exhaustive analysis of all potential input combinations is conducted using IORELM to identify the best one. The study outcomes emphasize the importance of incorporating precipitation and soil moisture data for accurate drought prediction. IORELM shows promising results in drought classification, and the best input combination was found for each station based on its results. While high Area Under Curve (AUC) values across stations, a Precision/Recall trade-off indicates variable prediction tendencies. Moreover, the F1-score is moderate, meaning the balance between Precision, Recall, and Classification Accuracy (CA) is notably high at specific stations. The results show that stations near the ocean, like Pitt Meadows, have higher predictability up to 10% in AUC and CA compared to inland stations, such as Langley, which exhibit lower values. These highlight geographic influence on model performance.
Keywords: Infolettre; Infolettre_Mai_2024

A 600‐year marine record associated with the dynamics of the eastern Penny Ice Cap (Baffin Island, Nunavut, Canada) - Rodríguez‐Cuicas, María‐Emilia; Montero‐Serrano, Jean‐Carlos; St‐Onge, Guillaume; Normandeau, Alexandre (Journal of Quaternary Science, 2023)
ABSTRACT Two composite sedimentary sequences sampled in the ice‐proximal (12CS) and ice‐distal (02CS) areas of Coronation Fjord (Baffin Island, Nunavut, Canada) were investigated in order to reconstruct the effect of climate variability on 600 years of changes in sediment transfer from the eastern Penny Ice Cap (PIC). Detrital proxies, and physical and sedimentological analyses revealed that glacial meltwater discharges led to frequent rapidly deposited layers (RDLs) in ice‐proximal settings. RDLs in ice‐distal settings involved the sudden release of a large quantity of sediment‐laden water during floods probably originating from adjacent fjords with large sandur deltas. Laminated sediments with ice‐rafted debris throughout the Little Ice Age interval in the ice‐proximal environment suggest that colder conditions promoted glacier growth, leading to successive episodes of turbid hyperpycnal meltwater plumes and iceberg calving in Coronation Fjord. Since 1850 ce , the accelerated Coronation retreat in response to modern warming has led to increased sedimentation rates, abrupt mineralogical and grain size proxy variations and more frequent RDLs. Similar trends between the detrital proxies of the ice‐proximal core and Atlantic Multidecadal Oscillation record and Arctic surface air temperature suggest high connectivity between atmospheric and sea surface temperature variations and PIC dynamics over the last 600 years.
Keywords: Infolettre; Infolettre_Juin_2023

Influence of local versus national datasets on seismic loss estimates: A case study for residential buildings in the metropolitan area of Montreal, Canada - Rosset, Philippe; Zhu, Huanru; Chouinard, Luc; Sirous, Navid; Rimando, Jeremy; Peace, Alexander; Goda, Katsuichiro (International Journal of Disaster Risk Reduction, 2024)
Keywords: Infolettre; Infolettre_Mai_2024

Development of tree recruitment models for 10 species groups in the sugar maple-dominated mixed forests of eastern Canada - Rijal, Baburam; Power, Hugues; Auger, Isabelle; Guillemette, François; Bédard, Steve; Schneider, Robert (Canadian Journal of Forest Research, 2023)
Individual tree recruitment is an important element needed to understand stand dynamics, as it influences both stand composition and productivity. Forest growth simulators usually include recruitment models. The quality of recruitment predictions can have long-term impacts on estimations of forest growth, ecosystem health and the commercial utility of managed forests. The main objective of this study was to develop a recruitment model for commercial-size trees (i.e., trees with a diameter at breast height > 9 cm) of 10 species groups using different dendrometric and environmental variables. The resulting model will be included in a growth simulator used to support forest management planning. We hypothesized that accounting for sapling density as a covariate would improve the recruitment model's predictive performance. Using empirical data from periodically measured permanent sample plots (1982–2019) located throughout the managed mixed hardwood forests of Quebec, we constructed models with and without sapling-related covariates and compared them on the basis of cross-validation model performance statistics. Our results show that including sapling density significantly improved model performance. From this, we conclude that adding sapling density as a covariate can significantly improve a recruitment model's predictive power for eastern mixed hardwood forests.
Keywords: Guillemette_Francois

Climatological context of the mid-November 2021 floods in the province of British Columbia, Canada - Richards-Thomas, Tamar S.; Déry, Stephen J.; Stewart, Ronald E.; Thériault, Julie M. (Weather and Climate Extremes, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Coupling a peatland hydrological model with a snowmelt module in order to model the snowmelt runoff in a boreal ombrotrophic peatland in eastern Québec (Canada) - Riahi, Khawla; St-Hilaire, André; Bourgault, Marc-André; Taillardat, Pierre; Prijac, Antonin; Garneau, Michelle (Canadian Journal of Civil Engineering, 2024)
Peatlands are relatively common in the province of Quebec (Canada) where they occupy about 12% of the surface. The hydrology of peatlands remains insufficiently documented, more specifically during the spring period where data are currently lacking in many regions, including in the Quebec boreal territory. The paucity of spring data are due to snowmelt that causes flooding in peatlands and along rivers, which makes hydrometry complicated during this period of the year. In this paper, the Peatland Hydrological Impact Model (PHIM) was coupled with a snowmelt module (CemaNeige) to simulate spring flows in an ombrotrophic peatland located in the Romaine River watershed (Quebec). Discharge data from two summer seasons (2019 and 2020) were used to calibrate the hydrological model. Despite the relatively short time series, the results show a good performance. The simulated spring flows resulting from the PHIM + CemaNeige combination are of the right order of magnitude.
Keywords: Infolettre; Infolettre_Fevrier_2025

Field monitoring of river ice processes in the vicinity of ice control structures in the province of Quebec, Canada - Pourshahbaz, Hanif; Ghobrial, Tadros; Shakibaeinia, Ahmad (Canadian Journal of Civil Engineering, 2023)
Over the past decades, a variety of ice control structures (ICSs) have been designed and built, but to date, there has been no systematic evaluation of the effectiveness of these structures. To achieve this objective, first an understanding of the interaction between different ice processes and the ICSs must be established. For this purpose, a total of four ICSs located in the province of Québec were monitored during the 2021–2022 winter. The results showed that the ice jam holding time could vary from 1.5 to 68.5 h. The release of the jam was mechanically driven when the ratio of release to initiation Froude number was higher than one and was thermally driven when this ratio was lower than one, and the water temperature increased between initiation and release. Also, as the ratio of the total pier spacing to upstream river width increased, the holding time decreased.
Keywords: Ahmad_Shakibaeinia; Infolettre; Infolettre_Octobre_2023

Hydrothermal impacts of water release on early life stages of white sturgeon in the Nechako river, B.C. Canada - Oyinlola, Muhammed A.; Khorsandi, Mostafa; Penman, Rachael; Earhart, Madison L.; Arsenault, Richard; Brauner, Colin J.; St-Hilaire, Andre (Journal of Thermal Biology, 2023)

Short-duration precipitation extremes over Canada in a warmer climate - Oh, Seok-Geun; Sushama, Laxmi (Climate Dynamics, 2020)
Short-duration precipitation extremes are widely used in the design of engineering infrastructure systems and they also lead to high impact flash flood events and landslides. Better understanding of these events in a changing climate is therefore critical. This study assesses characteristics of short-duration precipitation extremes of 1-, 3-, 6- and 12-h durations in terms of the precipitation-temperature (P–T) relationship in current and future climates for ten Canadian climatic regions using the limited area version of the global environment multiscale (GEM) model. The GEM simulations, driven by ERA-Interim reanalysis and two coupled global climate models (CanESM2 and MPI-ESM), reproduce the general observed regional P–T relationship characteristics in current climate (1981–2010), such as sub-CC (Clausius–Clapeyron) and CC scalings for the coastal and northern, and inland regions, respectively, albeit with some underestimation. Analysis of the transient climate change simulations suggests important shifts and/or extensions of the P–T curve to higher temperature bins in future climate (2071–2100) for RCP4.5 and 8.5 scenarios, particularly for 1-h duration. Analysis of the spatial patterns of dew point depression (temperature minus dew point temperature) and convective available potential energy (CAPE) corresponding to short-duration precipitation extremes for different temperature bins show their changing relative importance from low to high temperature bins. For the low-temperature bins, short-duration precipitation extremes are largely due to high relative humidity, while for high-temperature bins, strong convection due to atmospheric instability brought by surface warming is largely responsible. The analysis thus addresses some of the key knowledge gaps related to the behavior of P–T relationship and associated mechanisms for the Canadian regions.

A 247‐year tree‐ring reconstruction of spring temperature and relation to spring flooding in eastern boreal Canada - Nolin, Alexandre Florent; Girardin, Martin Philippe; Tardif, Jacques Clément; Guo, Xiao Jing; Conciatori, France; Bergeron, Yves (International Journal of Climatology, 2022)
Abstract Few records of spring paleoclimate are available for boreal Canada, as biological proxies recording the beginning of the warm season are uncommon. Given the spring warming observed during the last decades, and its impact on snowmelt and hydrological processes, searching for spring climate proxies is receiving increasing attention. Tree‐ring anatomical features and intra‐annual widths were used to reconstruct the regional March to May mean air temperature from 1770 to 2016 in eastern boreal Canada. Nested principal component regressions calibrated on 116 years of gridded temperature data were developed from one Fraxinus nigra and 10 Pinus banksiana sites. The reconstruction indicated three distinct phases in spring temperature variability since 1770. Ample phases of multi‐decadal warm and cold springs persisted until the end of the Little Ice Age (1850–1870 CE) and were gradually replaced since the 1940s by decadal to interannual variability associated with an increase in the frequency and magnitude of warm springs. Significant correlations with other paleotemperature records, gridded snow cover extent and runoff support that historical high flooding were associated with late, cold springs with heavy snow cover. Most of the high magnitude spring floods reconstructed for the nearby Harricana River also coincided with the lowest reconstructed spring temperature per decade. However, the last 40 years of observed and reconstructed mean spring temperature showed a reduction in the number of extreme cold springs contrasting with the last few decades of extreme flooding in the eastern Canadian boreal region. This result indicates that warmer late spring mean temperatures on average may contribute, among other factors, to advance the spring break‐up and to likely shift the contribution of snow to rain in spring flooding processes.
Keywords: Infolettre; Infolettre_Avril_2022

Spatial coherency of the spring flood signal among major river basins of eastern boreal Canada inferred from flood rings - Nolin, A.F.; Tardif, J.C.; Conciatori, F.; Bergeron, Y. (Journal of Hydrology, 2021)
Keywords: Site_internet_RIISQ

Multi-century tree-ring anatomical evidence reveals increasing frequency and magnitude of spring discharge and floods in eastern boreal Canada - Nolin, Alexandre Florent; Tardif, Jacques Clément; Conciatori, France; Kames, Susanne; Meko, David M.; Bergeron, Yves (Global and Planetary Change, 2021)
Keywords: Site_internet_RIISQ

Pinus banksiana and Fraxinus nigra dataset for the study of spring temperature in eastern boreal Canada - Nolin, Alexandre; Girardin, Martin Philippe; Tardif, Jacques Clément; Guo, Xiao Jing; Conciatori, France; Bergeron, Yves (2021)
Data include tree-ring widths and wood anatomical chronologies of Pinus banksiana and Fraxinus nigra trees growing in eastern boreal Canada, as well as the reconstructed spring mean temperature, reported in "A 247-years tree-ring reconstruction of spring temperature and relation to spring flooding in eastern boreal Canada" published in "International journal of Climatology" by Nolin et al., 2021. PIBA_FRNI_Chronos.csv, the tree-ring widths and wood anatomical chronologies (1706-2017) used in this study (species and sites are coded as in Table 1); PIBA_FRNI_SampDepth.csv, the annual replication of samples used to produce each chronologies (1706-2017); PIBA_FRNI_RecSpringTemp.csv, the reconstructed mean spring temperature (1770 to 2016) LAT_LON_SpringTemp.kml, the coordinate data for each sampling site: metadatas.txt, a set of self-explanatory instructions and descriptions for data files. All other data are available upon request to the corresponding author at alexandreflorent.nolin@uqat.ca (institutional email), alexandreflorent.nolin@gmail.com (permanent email).

Fraxinus nigra tree-ring dataset for flood history study among major river basins near the Lake Duparquet, eastern boreal Canada. - Nolin, Alexandre; Tardif, Jacques C.; Conciatori, France; Bergeron, Yves (2021)
Data include flood ring (F1, F2) and earlywood vessel chronologies (MVA, N) derived from black ash (Fraxinus nigra Marsh.) trees growing in eastern boreal Canada near Lake Duparquet (Quebec) reported in "Spatial coherence of the spring flood signal among major river basins of eastern boreal Canada inferred from flood rings" published in "Journal of Hydrology" by Nolin et al. in 2021. F1_F2_chrono.csv, as in Figure 3, the F1 and F2 flood-ring chronologies per sites (sites are coded as in Table 1) with sample replication (n); LAT_LON.kml, the coordinate data for each site and sampled tree; MVA_N_chrono.csv, as in Figure 5, the MVA and N chronologies per river basins (river basins are coded as in Table 1); REC1.csv, the reconstruction of the Harricana River spring discharge from 1771 to 2016 reported in "Multi-century tree-ring anatomical evidence reveals increasing frequency and magnitude of spring discharge and floods in eastern boreal Canada" published in "Global and Planetary Change" by Nolin et al. 2021. metadatas.txt, a set of self-explanatory instructions and descriptions for data files. All other data are available upon request to the corresponding author at alexandreflorent.nolin@uqat.ca (institutional email), alexandreflorent.nolin@gmail.com (permanent email).

Observed and projected trends in spring flood discharges for the Upper Harricana River, eastern boreal Canada - Nolin, A.F.; Girardin, M.P.; Adamowski, J.F.; Barzegar, R.; Boucher, M.-A.; Tardif, J.C.; Bergeron, Y. (Journal of Hydrology: Regional Studies, 2023)

Detection of prevalent SARS-CoV-2 variant lineages in wastewater and clinical sequences from cities in Québec, Canada - N’Guessan, Arnaud; Tsitouras, Alexandra; Sanchez-Quete, Fernando; Goitom, Eyerusalem; Reiling, Sarah J.; Galvez, Jose Hector; Nguyen, Thanh Luan; Loan Nguyen, Ha Thanh; Visentin, Flavia; Hachad, Mounia; Krylova, Kateryna; Matthews, Sara; et al. (2022)
ABSTRACT Wastewater-based epidemiology has emerged as a promising tool to monitor pathogens in a population, particularly when clinical diagnostic capacities become overwhelmed. During the ongoing COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), several jurisdictions have tracked viral concentrations in wastewater to inform public health authorities. While some studies have also sequenced SARS-CoV-2 genomes from wastewater, there have been relatively few direct comparisons between viral genetic diversity in wastewater and matched clinical samples from the same region and time period. Here we report sequencing and inference of SARS-CoV-2 mutations and variant lineages (including variants of concern) in 936 wastewater samples and thousands of matched clinical sequences collected between March 2020 and July 2021 in the cities of Montreal, Quebec City, and Laval, representing almost half the population of the Canadian province of Quebec. We benchmarked our sequencing and variant-calling methods on known viral genome sequences to establish thresholds for inferring variants in wastewater with confidence. We found that variant frequency estimates in wastewater and clinical samples are correlated over time in each city, with similar dates of first detection. Across all variant lineages, wastewater detection is more concordant with targeted outbreak sequencing than with semi-random clinical swab sampling. Most variants were first observed in clinical and outbreak data due to higher sequencing rate. However, wastewater sequencing is highly efficient, detecting more variants for a given sampling effort. This shows the potential for wastewater sequencing to provide useful public health data, especially at places or times when sufficient clinical sampling is infrequent or infeasible.
Keywords: Dorner_Sarah

Flood frequency analysis at ungauged catchments with the GAM and MARS approaches in the Montreal region, Canada - Msilini, Amina; Charron, Christian; Ouarda, Taha B. M. J.; Masselot, Pierre (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2022)
Keywords: Infolettre; Infolettre_Avril_2022; Site_internet_RIISQ

Detection of trends in flood magnitude and frequency in Canada - Mostofi Zadeh, Shabnam; Burn, Donald H.; O’Brien, Nicole (Journal of Hydrology: Regional Studies, 2020)

Drivers of rare earth elements (REEs) and radionuclides in changing subarctic (Nunavik, Canada) surface waters near a mining project - Marginson, H.; MacMillan, G.A.; Wauthy, M.; Sicaud, E.; Gérin-Lajoie, J.; Dedieu, J.-P.; Amyot, M. (Journal of Hazardous Materials, 2024)

Will Evolving Climate Conditions Increase the Risk of Floods of the Large U.S.‐Canada Transboundary Richelieu River Basin? - Lucas‐Picher, Philippe; Lachance‐Cloutier, Simon; Arsenault, Richard; Poulin, Annie; Ricard, Simon; Turcotte, Richard; Brissette, François (JAWRA Journal of the American Water Resources Association, 2021)
Abstract In spring 2011, an unprecedented flood hit the complex eastern United States (U.S.)–Canada transboundary Lake Champlain–Richelieu River (LCRR) Basin, destructing properties and inducing negative impacts on agriculture and fish habitats. The damages, covered by the Governments of Canada and the U.S., were estimated to C$90M. This natural disaster motivated the study of mitigation measures to prevent such disasters from reoccurring. When evaluating flood risks, long‐term evolving climate change should be taken into account to adopt mitigation measures that will remain relevant in the future. To assess the impacts of climate change on flood risks of the LCRR basin, three bias‐corrected multi‐resolution ensembles of climate projections for two greenhouse gas concentration scenarios were used to force a state‐of‐the‐art, high‐resolution, distributed hydrological model. The analysis of the hydrological simulations indicates that the 20‐year return period flood (corresponding to a medium flood) should decrease between 8% and 35% for the end of the 21st Century (2070–2099) time horizon and for the high‐emission scenario representative concentration pathway (RCP) 8.5. The reduction in flood risks is explained by a decrease in snow accumulation and an increase in evapotranspiration expected with the future warming of the region. Nevertheless, due to the large climate inter‐annual variability, short‐term flood probabilities should remain similar to those experienced in the recent past.

Development of a mapping approach encompassing most fluvial processes: Lessons learned from the freedom space for rivers concept in Quebec (Canada) - Massé, Simon; Demers, Sylvio; Besnard, Clément; Buffin‐Bélanger, Thomas; Biron, Pascale M.; Choné, Guénolé; Massey, William (River Research and Applications, 2020)
Abstract The consensus around the need for a shift in river management approaches to include more natural processes is steadily growing amongst scientists, practitioners, and governmental agencies. The freedom space for rivers concept promotes the delineation of a single space that integrates multiple fluvial dynamics such as floods, lateral migration, channel avulsions, and riparian wetlands connectivity. The objective of this research is to assess the validity of the hydrogeomorphological approach to delineate the freedom space for an extensive sampling of river reaches, covering 167 km, in contrasting watersheds in Quebec (Canada). Comparative analysis was conducted on the relative importance of erosion and flood processes on the freedom space delineation for various fluvial types. Semiautomated tools based on light detection and ranging (LiDAR) digital elevation models were also tested on an additional 274 km of watercourses to facilitate freedom space mapping over extensive zones and for highly dynamics environments such as alluvial fans. In the studied reaches, flood and erosion processes occur respectively, on average, in a space equivalent to 2.6 and 20.6 channel widths. In unconfined landscapes, flood processes represent an area up to almost four times the area of erosion processes expected in a 50‐year period. In partly confined and confined environments, erosion processes are more likely to exceed flooding zone, and therefore need to be integrated in the mapping. This study helps better determine the conditions for which the full methodology of freedom space mapping is required or where semiautomated methods can be used. It provides useful guidelines for the implementation of the freedom space approach.
Keywords: Ouvrage_Collectif_Numéro1

Precipitation Extremes and Their Links with Regional and Local Temperatures: A Case Study over the Ottawa River Basin, Canada - Llerena, Ana; Gachon, Philippe; Laprise, René (Atmosphere, 2023)
In the context of global warming, the Clausius–Clapeyron (CC) relationship has been widely used as an indicator of the evolution of the precipitation regime, including daily and sub-daily extremes. This study aims to verify the existence of links between precipitation extremes and 2 m air temperature for the Ottawa River Basin (ORB, Canada) over the period 1981–2010, applying an exponential relationship between the 99th percentile of precipitation and temperature characteristics. Three simulations of the Canadian Regional Climate Model version 5 (CRCM5), at three different resolutions (0.44°, 0.22°, and 0.11°), one simulation using the recent CRCM version 6 (CRCM6) at “convection-permitting” resolution (2.5 km), and two reanalysis products (ERA5 and ERA5-Land) were used to investigate the CC scaling hypothesis that precipitation increases at the same rate as the atmospheric moisture-holding capacity (i.e., 6.8%/°C). In general, daily precipitation follows a lower rate of change than the CC scaling with median values between 2 and 4%/°C for the ORB and with a level of statistical significance of 5%, while hourly precipitation increases faster with temperature, between 4 and 7%/°C. In the latter case, rates of change greater than the CC scaling were even up to 10.2%/°C for the simulation at 0.11°. A hook shape is observed in summer for CRCM5 simulations, near the 20–25 °C temperature threshold, where the 99th percentile of precipitation decreases with temperature, especially at higher resolution with the CRCM6 data. Beyond the threshold of 20 °C, it appears that the atmospheric moisture-holding capacity is not the only determining factor for generating precipitation extremes. Other factors need to be considered, such as the moisture availability at the time of the precipitation event, and the presence of dynamical mechanisms that increase, for example, upward vertical motion. As mentioned in previous studies, the applicability of the CC scaling should not be generalised in the study of precipitation extremes. The time and spatial scales and season are also dependent factors that must be taken into account. In fact, the evolution of precipitation extremes and temperature relationships should be identified and evaluated with very high spatial resolution simulations, knowing that local temperature and regional physiographic features play a major role in the occurrence and intensity of precipitation extremes. As precipitation extremes have important effects on the occurrence of floods with potential deleterious damages, further research needs to explore the sensitivity of projections to resolution with various air temperature and humidity thresholds, especially at the sub-daily scale, as these precipitation types seem to increase faster with temperature than with daily-scale values. This will help to develop decision-making and adaptation strategies based on improved physical knowledge or approaches and not on a single assumption based on CC scaling.
Number: 7 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Gachon_Philippe; Infolettre; Infolettre_Ete_2023; Infolettre_Septembre_2023; Site_internet_RIISQ

Mechanisms of spring freshet generation in southern Quebec, Canada - Kinnard, Christophe; Nemri, Saida; Assani, Ali (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Modelling glacier mass balance and climate sensitivity in the context of sparse observations: application to Saskatchewan Glacier, western Canada - Kinnard, Christophe; Larouche, Olivier; Demuth, Michael N.; Menounos, Brian (The Cryosphere, 2022)
Abstract. Glacier mass balance models are needed at sites with scarce long-term observations to reconstruct past glacier mass balance and assess its sensitivity to future climate change. In this study, North American Regional Reanalysis (NARR) data were used to force a physically based, distributed glacier mass balance model of Saskatchewan Glacier for the historical period 1979–2016 and assess its sensitivity to climate change. A 2-year record (2014–2016) from an on-glacier automatic weather station (AWS) and historical precipitation records from nearby permanent weather stations were used to downscale air temperature, relative humidity, wind speed, incoming solar radiation and precipitation from the NARR to the station sites. The model was run with fixed (1979, 2010) and time-varying (dynamic) geometry using a multitemporal digital elevation model dataset. The model showed a good performance against recent (2012–2016) direct glaciological mass balance observations as well as with cumulative geodetic mass balance estimates. The simulated mass balance was not very sensitive to the NARR spatial interpolation method, as long as station data were used for bias correction. The simulated mass balance was however sensitive to the biases in NARR precipitation and air temperature, as well as to the prescribed precipitation lapse rate and ice aerodynamic roughness lengths, showing the importance of constraining these two parameters with ancillary data. The glacier-wide simulated energy balance regime showed a large contribution (57 %) of turbulent (sensible and latent) heat fluxes to melting in summer, higher than typical mid-latitude glaciers in continental climates, which reflects the local humid “icefield weather” of the Columbia Icefield. The static mass balance sensitivity to climate was assessed for prescribed changes in regional mean air temperature between 0 and 7 ∘C and precipitation between −20 % and +20 %, which comprise the spread of ensemble Representative Concentration Pathway (RCP) climate scenarios for the mid (2041–2070) and late (2071–2100) 21st century. The climate sensitivity experiments showed that future changes in precipitation would have a small impact on glacier mass balance, while the temperature sensitivity increases with warming, from −0.65 to −0.93 m w.e. a−1 ∘C−1. The mass balance response to warming was driven by a positive albedo feedback (44 %), followed by direct atmospheric warming impacts (24 %), a positive air humidity feedback (22 %) and a positive precipitation phase feedback (10 %). Our study underlines the key role of albedo and air humidity in modulating the response of winter-accumulation type mountain glaciers and upland icefield-outlet glacier settings to climate.
Keywords: Kinnard_Christophe

Current and Projected Distributions of Aedes aegypti and Ae. albopictus in Canada and the U.S. - Khan, Salah Uddin; Ogden, Nicholas H.; Fazil, Aamir A.; Gachon, Philippe H.; Dueymes, Guillaume U.; Greer, Amy L.; Ng, Victoria (Environmental Health Perspectives, 2020)
Keywords: Gachon_Philippe

Using the theory of planned behavior to identify key beliefs underlying flood-related adaptive behaviors in the province of Québec, Canada - Jacob, Johann; Valois, Pierre; Tessier, Maxime; Talbot, Denis; Anctil, François; Cloutier, Geneviève; Renaud, Jean-Sébastien (Journal of Flood Risk Management, 2023)
Given that flooding episodes are occurring at a greater rate due to climate change, individuals must adopt certain adaptation behaviors to prevent or mitigate the anticipated or negative impact of such events. However, few studies have assessed if and how households and individuals have actually taken action in this regard. Because some individual beliefs can be linked to facilitating factors and barriers to action, a better understanding of the adoption of adaptive behaviors requires a combined analysis of individual psychosocial factors. The purpose of this study was to develop a better understanding of the reasons underlying the adoption of behaviors related to structural adaptation to flooding by people living in or near flood-prone areas in the Province of Québec (Canada). Results of a series of structural equation modeling showed that behavioral, normative and control beliefs were all significant predictors of the respondents' intention to adopt structural flood protective behaviors, with normative beliefs being the strongest. By identifying the best psychosocial predictors of the adoption of such behaviors, the results of this study provide valuable insights regarding the most effective factors to be used in public health messages to promote the adoption of behaviors related to structural adaptation to flooding.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfr3.12906
Keywords: Infolettre; Infolettre_Mai_2023

Wastewater Surveillance for SARS-CoV-2 RNA in Canada - Hrudey, Steve E.; Bischel, Heather N.; Charrois, Jeff; Chik, Alex H. S.; Conant, Bernadette; Delatolla, Rob; Dorner, Sarah; Graber, Tyson E.; Hubert, Casey; Isaac-Renton, Judy; Pons, Wendy; Safford, Hannah; et al. (FACETS, 2022)
Wastewater surveillance for SARS-CoV-2 RNA is a relatively recent adaptation of long-standing wastewater surveillance for infectious and other harmful agents. Individuals infected with COVID-19 were found to shed SARS-CoV-2 in their faeces. Researchers around the world confirmed that SARS-CoV-2 RNA fragments could be detected and quantified in community wastewater. Canadian academic researchers, largely as volunteer initiatives, reported proof-of-concept by April 2020. National collaboration was initially facilitated by the Canadian Water Network. Many public health officials were initially skeptical about actionable information being provided by wastewater surveillance even though experience has shown that public health surveillance for a pandemic has no single, perfect approach. Rather, different approaches provide different insights, each with its own strengths and limitations. Public health science must triangulate among different forms of evidence to maximize understanding of what is happening or may be expected. Well-conceived, resourced, and implemented wastewater-based platforms can provide a cost-effective approach to support other conventional lines of evidence. Sustaining wastewater monitoring platforms for future surveillance of other disease targets and health states is a challenge. Canada can benefit from taking lessons learned from the COVID-19 pandemic to develop forward-looking interpretive frameworks and capacity to implement, adapt, and expand such public health surveillance capabilities.
Keywords: Dorner_Sarah

Projected seasonal flooding in Canada under climate change with statistical and machine learning - Grenier, Manuel; Boudreault, Jérémie; Raymond, Sébastien; Boudreault, Mathieu (Journal of Hydrology: Regional Studies, 2024)
Keywords: Infolettre; Infolettre_Mai_2024

Water Level Temporal Variability of Lake Mégantic during the Period 1920–2020 and Its Impacts on the Frequency of Heavy Flooding of the Chaudière River (Quebec, Canada) - Goulet, Samuel; Assani, Ali Arkamose; Roy, Alexandre (Hydrology, 2024)
The objective of this study is to analyze the temporal variability in water levels of Lake Mégantic (27.4 km2) during the period 1920–2020 in relation to anthropogenic and natural factors on the one hand, and its impact on the intensity and frequency of heavy flooding (recurring floods ≥ 10 years) of the Chaudière River of which it is the source, on the other hand. The application of four different Mann–Kendall tests showed a significant decrease in lake water levels during this period. The Lombard test revealed two breaks in the average daily maximum and average water levels, but only one break in the average daily minimum water levels. The first shift, which was smoothed, occurred between 1957 and 1963. It was caused by the demolition in 1956 of the first dam built in 1893 and the significant storage of water in the dams built upstream of the lake between 1956 and 1975. The second shift, which was rather abrupt, occurred between 1990 and 1993. It was caused by the voluntary and controlled lowering of the lake’s water levels in 1993 to increase the surface area of the beaches for recreational purposes. However, despite this influence of anthropogenic factors on this drop in water levels, they are negatively correlated with the global warming climate index. It is therefore a covariation, due to anthropogenic factors whose impacts are exerted at different spatial scales, without a physical causal link. However, the winter daily minimum water levels, whose temporal variability has not been influenced by anthropogenic activities, are positively correlated with the NAO and AO indices, but negatively with PDO. Finally, since the transformation of Lake Mégantic into a reservoir following the construction of the Mégantic dam in 1893 and 1973 to control heavy flooding in the Chaudière River, all recurrent floods ≥ 10 years have completely disappeared in the section of this river located downstream of Lake Mégantic. However, the disappearance of these floods and the drop in water levels of Lake Mégantic have not significantly impacted the stationarity in the flow series of the Chaudière River since 1920.
Keywords: Infolettre; Infolettre_Octobre_2024

A comprehensive field investigation of the dynamic break-up processes on the Chaudière River, Quebec, Canada - Ghobrial, Tadros; Pelchat, Gabriel; Morse, Brian (Hydrology Research, 2023)
Abstract The Chaudière River in Quebec, Canada, is well known for its frequent ice jam flooding events. As part of a larger watershed research program, an extensive field campaign has been carried out during the 2018–2019 and 2019–2020 winter seasons to quantify the spatiotemporal characteristics of the break-up processes along the Chaudière River. The results showed that mid-winter ice jams have formed in the Intermediate Chaudière and persisted until spring break-up. Spring break-ups were initiated in the Upper Chaudière, and then, almost simultaneously, in the Intermediate and Lower Chaudière reaches. The break-up in the Intermediate Chaudière usually lasts longer than the rest of the river since the slope is much milder, and the occurrence of mid-winter ice jams has been seen to delay the ice clearing. A reach-by-reach characterization of the cumulative degree day of thawing and discharge thresholds for the onset of break-up has been identified. During the field campaign, 51 ice jams were documented together with their location, length, date of formation, and the morphological feature triggering jam formation. Break-up patterns, hydrometeorological thresholds of ice mobilization, and ice jam sites identified in this study can serve as a basis for the implementation of an early warning system.
Keywords: Infolettre; Infolettre_Septembre_2023

A geostatistical approach to create a new climate types map at regional scale: case study of New Brunswick, Canada - Fortin, Guillaume; Dubreuil, Vincent (Theoretical and Applied Climatology, 2020)

Morphological and Habitat Quality of Salmonid Streams and their Relationship with Fish-Based Indices in Aotearoa New Zealand and Ontario (Canada) - Foote, Kyleisha J.; Biron, Pascale M.; Grant, James W. A. (Environmental Management, 2024)
Keywords: Infolettre; Infolettre_Janvier_2024

Meteorological control on snow depth evolution and snowpack energy exchanges in an agro-forested environment by a measurement-based approach: A case study in Sainte-Marthe, Eastern Canada - Dharmadasa, Vasana; Kinnard, Christophe; Baraër, Michel (Agricultural and Forest Meteorology, 2024)
Keywords: Baraer_Michel; Kinnard_Christophe

Comparison of Seasonal Flow Rate Change Indices Downstream of Three Types of Dams in Southern Quebec (Canada) - Delisle, Francis; Assani, Ali Arkamose (Water, 2021)
The objective of this study is to use two hydrological indices (coefficients of variation and immoderation) to analyze the impacts of dam management methods on seasonal daily flow rate change downstream of three dams: Manouane (diversion-type management method), Ouareau (natural-type management method) and Matawin (inversion-type management method). The results show that this change is far greater downstream of the Matawin dam (characterized by an inversion-type management method) than downstream of the two other dams. Moreover, downstream of the Matawin dam, this daily flow rate change increases significantly over time, while decreasing downstream of the two other dams and in natural rivers. Lastly, this change is better correlated with climate downstream of the Ouareau dam than downstream of the two other dams. It is positively correlated with winter and spring temperatures as well as summer and fall rain. Contrary commonly accepted hypothesis, this study shows that the impacts of dams generally result in an increase of the seasonal flow rate change in Quebec.

Large-scale flood modelling based on LiDAR data: a case study in the Southwest Miramichi watershed, New Brunswick, Canada - Choné, Guénolé; Mazgareanu, Iulia; Biron, Pascale M.; Buffin-Bélanger, Thomas; Larouche-Tremblay, François; Perry, Brian; Fortin, Maxim (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2024)
Keywords: Infolettre; Infolettre_Decembre_2024

Projected Wind Impact on Abies balsamea (Balsam fir)-Dominated Stands in New Brunswick (Canada) Based on Remote Sensing and Regional Modelling of Climate and Tree Species Distribution - Bourque, Charles P.-A.; Gachon, Philippe; MacLellan, Benjamin R.; MacLellan, James I. (Remote Sensing, 2020)
The paper describes the development of predictive equations of windthrow for five tree species based on remote sensing of wind-affected stands in southwestern New Brunswick (NB). The data characterises forest conditions before, during and after the passing of extratropical cyclone Arthur, July 4–5, 2014. The five-variable logistic function developed for balsam fir (bF) was validated against remote-sensing-acquired windthrow data for bF-stands affected by the Christmas Mountains windthrow event of November 7, 1994. In general, the prediction of windthrow in the area agreed fairly well with the windthrow sites identified by photogrammetry. The occurrence of windthrow in the Christmas Mountains was prominent in areas with shallow soils and prone to localised accelerations in mean and turbulent airflow. The windthrow function for bF was subsequently used to examine the future impact of windthrow under two climate scenarios (RCP’s 4.5 and 8.5) and species response to local changes anticipated with global climate change, particularly with respect to growing degree-days and soil moisture. Under climate change, future windthrow in bF stands (2006–2100) is projected to be modified as the species withdraws from the high-elevation areas and NB as a whole, as the climate progressively warms and precipitation increases, causing the growing environment of bF to deteriorate.
Keywords: Gachon_Philippe

Harmonizing and Extending Fragmented 100 Year Flood Hazard Maps in Canada’s Capital Region Using Random Forest Classification - Bhuiyan, Shelina A.; Bataille, Clement P.; McGrath, Heather (Water, 2022)
With the record breaking flood experienced in Canada’s capital region in 2017 and 2019, there is an urgent need to update and harmonize existing flood hazard maps and fill in the spatial gaps between them to improve flood mitigation strategies. To achieve this goal, we aim to develop a novel approach using machine learning classification (i.e., random forest). We used existing fragmented flood hazard maps along the Ottawa River to train a random forest classification model using a range of flood conditioning factors. We then applied this classification across the Capital Region to fill in the spatial gaps between existing flood hazard maps and generate a harmonized high-resolution (1 m) 100 year flood susceptibility map. When validated against recently produced 100 year flood hazard maps across the capital region, we find that this random forest classification approach yields a highly accurate flood susceptibility map. We argue that the machine learning classification approach is a promising technique to fill in the spatial gaps between existing flood hazard maps and create harmonized high-resolution flood susceptibility maps across flood-vulnerable areas. However, caution must be taken in selecting suitable flood conditioning factors and extrapolating classification to areas with similar characteristics to the training sites. The resulted harmonized and spatially continuous flood susceptibility map has wide-reaching relevance for flood mitigation planning in the capital region. The machine learning approach and flood classification optimization method developed in this study is also a first step toward Natural Resources Canada’s aim of creating a spatially continuous flood susceptibility map across the Ottawa River watershed. Our modeling approach is transferable to harmonize flood maps and fill in spatial gaps in other regions of the world and will help mitigate flood disasters by providing accurate flood data for urban planning.

Landscape and climate conditions influence the hydrological sensitivity to climate change in eastern Canada - Aygün, Okan; Kinnard, Christophe; Campeau, Stéphane; Pomeroy, John W. (Journal of Hydrology, 2022)
Keywords: Kinnard_Christophe

The new ‘surface storage’ concept versus the old ‘sponge effect’ concept: application to the analysis of the spatio-temporal variability of the annual daily maximum flow characteristics in southern Quebec (Canada) - Assani, Ali Arkamose; Zeroual, Ayoub; Kinnard, Christophe; Roy, Alexandre (Journal of Water and Climate Change, 2023)
Abstract This study confronts the new concept of ‘surface storage’ with the old concept of ‘sponge effect’ to explain the spatio-temporal variability of the annual daily maximum flows measured in 17 watersheds of southern Quebec during the period 1930–2019. The new concept takes into account the hydrological impacts of wetlands and other topographic components of the landscape (lakes, depressions, ditches, etc.) while that of the sponge effect only takes into account the hydrological impacts of wetlands. With regard to spatial variability, the area of wetlands and other water bodies is the variable best correlated negatively with the magnitude but positively with the duration of flows. As for the temporal variability, the application of the long-term trend tests revealed a significant increase in the magnitude and, to a lesser extent, the duration of the flows occurring in the watersheds of the north shore characterized by a greater area of wetlands and other water bodies (>5%). This increase is explained by the fact that the storage capacity of these land types, which remains unchanged over time, does not make it possible to store the surplus runoff water brought by the increase in rainfall during the snowmelt season.
Keywords: Infolettre; Infolettre_Septembre_2023; Kinnard_Christophe

Spatiotemporal variability of fall daily maximum flows in southern Quebec (Canada) from 1930 to 2018 - Assani, Ali A. (Journal of Flood Risk Management, 2024)
Abstract Quebec is experiencing a significant increase in summer and fall temperatures and rainfall. This study compares the spatiotemporal variability of maximum daily flows generated by rainfall during the fall season (September–December) in relation to this climatic change and physiographic and land use factors. Analysis of the spatial variability of these maximum flows measured from 1930 to 2018 in 17 watersheds revealed that the magnitude of flows is approximately twice as low on the north shore as it is on the south shore south of 47° N. This difference is explained by three main factors: wetlands (negative correlation) and agricultural (positive correlation) surface area, and summer–fall total precipitation (positive correlation). As for the temporal variability of flows, the different Mann–Kendall statistical tests showed a significant increase in flows due to increased rainfall. The increase of flows was more widespread on the north shore than on the south because the storage capacity of wetlands and other water bodies does not change over time to store excess rainfall. On the south shore, the increase in flows over time is limited due to the significant reduction in agricultural areas since the modernization of agriculture. This reduction favored infiltration to the detriment of runoff.
Keywords: Infolettre; Infolettre_Septembre_2024; Site_internet_RIISQ

Analysis of the impacts of climate change, physiographic factors and land use/cover on the spatiotemporal variability of seasonal daily mean flows in southern Quebec (Canada) - Assani, Ali A. (Applied Water Science, 2024)
Abstract The objective of this study is to compare the spatiotemporal variability of seasonal daily mean flows measured in 17 watersheds, grouped into three homogeneous hydroclimatic regions, during the period 1930–2023 in southern Quebec. With regard to spatial variability, unlike extreme daily flows, seasonal daily mean flows are very poorly correlated with physiographic factors and land use and land cover. In fall, they are not correlated with any physiographic or climatic factor. In winter, they are positively correlated with the rainfall and winter daily mean maximum temperatures. In spring, they are strongly correlated positively with the snowfall but negatively with the spring daily mean maximum temperatures. However, in summer, they are better correlated with forest area and, to a lesser extent, with the rainfall. As for their temporal variability, the application of six different statistical tests revealed a general increase in daily mean flows in winter due to early snowmelt and increased rainfall in fall. In summer, flows decreased significantly in the snowiest hydroclimatic region on the south shore due to the decrease in the snowfall. In spring, no significant change in flows was globally observed in the three hydroclimatic regions despite the decrease in the snowfall due to the increase in the rainfall. In fall, flows increased significantly south of 47°N on both shores due to the increase in the rainfall. This study demonstrates that, unlike extreme flows, the temporal variability of seasonal daily average flows is exclusively influenced by climatic variables in southern Quebec. Due to this influence, seasonal daily mean flows thus appear to be the best indicator for monitoring the impacts of changes in precipitation regimes and seasonal temperatures on river flows in southern Quebec.
Keywords: Infolettre; Infolettre_Mai_2024

Comparison of Spatio-Temporal Variability of Daily Maximum Flows in Cold-Season (Winter and Spring) in Southern Quebec (Canada) - Assani, Ali Arkamose (Hydrology, 2023)
Quebec has experienced a significant decrease in the amount of snow and an increase in temperature during the cold season. The objective of this study is to analyze the impacts of these climate changes on the spatio-temporal variability of the daily maximum flows generated by snowmelt in winter and spring using several statistical tests of correlation (spatial variability) and long-term trend (temporal variability). The study is based on the analysis of flows measured in 17 watersheds (1930–2019) grouped into three hydroclimatic regions. Regarding the spatial variability, the correlation analysis revealed that in winter, the flows are positively correlated with the agricultural area and the daily maximum winter temperature. In the spring, the flows are positively correlated with the drainage density and the snowfall but negatively correlated with the area of wetlands and the daily maximum spring temperature. As for temporal variability (long-term trend), the application of eight statistical tests revealed a generalized increase in flows in winter due to early snowmelt. In the spring, despite the decreased snow cover, no negative trend was observed due to the increase in the spring rainfall, which compensates for the decrease in the snowfall. This temporal evolution of flows in the spring does not correspond to the predictions of climate models. These predict a decrease in the magnitude of spring floods due to the decrease in the snowfall in southern Quebec.
Number: 2 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Infolettre; Infolettre_Avril_2023; Site_internet_RIISQ

Impact of Wetland Surface Area on Seasonal Daily Extreme Flow Characteristics during the Summer-Fall Season in Southern Quebec (Canada) - Assani, Ali Arkamose (International Journal of Environmental Sciences & Natural Resources, 2022)
Publisher: Juniper Publishers
Keywords: Site_internet_RIISQ

Comparison of annual flood characteristics in four watersheds in relation to the wetland surface areas (Southern Quebec, Canada) - Assani, Ali A. (Wetlands Ecology and Management, 2022)

Setting Targets for Wetland Restoration to Mitigate Climate Change Effects on Watershed Hydrology - Goyette, Jean-Olivier; Savary, Stéphane; Blanchette, Marianne; Rousseau, Alain N.; Pellerin, Stéphanie; Poulin, Monique (Environmental Management, 2023)
Keywords: Infolettre; Infolettre_Fevrier_2023; Rousseau_Alain

Wetland mitigation functions on hydrological droughts: From drought characteristics to propagation of meteorological droughts to hydrological droughts - Wu, Yanfeng; Sun, Jingxuan; Blanchette, Marianne; Rousseau, Alain N.; Xu, Y. Jun; Hu, Boting; Zhang, Guangxin (Journal of Hydrology, 2023)
Keywords: Rousseau_Alain

Are spatial distribution and aggregation of wetlands reliable indicators of stream flow mitigation? - Blanchette, Marianne; Rousseau, Alain N.; Savary, Stéphane; Foulon, Étienne (Journal of Hydrology, 2022)
Keywords: Rousseau_Alain

Toward a framework for systemic multi-hazard and multi-risk assessment and management - Hochrainer-Stigler, Stefan; Šakić Trogrlić, Robert; Reiter, Karina; Ward, Philip J.; De Ruiter, Marleen C.; Duncan, Melanie J.; Torresan, Silvia; Ciurean, Roxana; Mysiak, Jaroslav; Stuparu, Dana; Gottardo, Stefania (iScience, 2023)

Extreme events and gender-based violence: a mixed-methods systematic review - Van Daalen, Kim Robin; Kallesøe, Sarah Savić; Davey, Fiona; Dada, Sara; Jung, Laura; Singh, Lucy; Issa, Rita; Emilian, Christina Alma; Kuhn, Isla; Keygnaert, Ines; Nilsson, Maria (The Lancet Planetary Health, 2022)

Insuring homes against extreme weather events: a systematic review of the research - Lucas, Chloe H.; Booth, Kate I.; Garcia, Carolina (Climatic Change, 2021)
Keywords: Ouvrage_Collectif_Numéro1

Evaluating the Dependence between Temperature and Precipitation to Better Estimate the Risks of Concurrent Extreme Weather Events - Wazneh, Hussein; Arain, M. Altaf; Coulibaly, Paulin; Gachon, Philippe (Advances in Meteorology, 2020)
Precipitation and temperature are among major climatic variables that are used to characterize extreme weather events, which can have profound impacts on ecosystems and society. Accurate simulation of these variables at the local scale is essential to adapt urban systems and policies to future climatic changes. However, accurate simulation of these climatic variables is difficult due to possible interdependence and feedbacks among them. In this paper, the concept of copulas was used to model seasonal interdependence between precipitation and temperature. Five copula functions were fitted to grid (approximately 10 km × 10 km) climate data from 1960 to 2013 in southern Ontario, Canada. Theoretical and empirical copulas were then compared with each other to select the most appropriate copula family for this region. Results showed that, of the tested copulas, none of them consistently performed the best over the entire region during all seasons. However, Gumbel copula was the best performer during the winter season, and Clayton performed best in the summer. More variability in terms of best copula was found in spring and fall seasons. By examining the likelihoods of concurrent extreme temperature and precipitation periods including wet/cool in the winter and dry/hot in the summer, we found that ignoring the joint distribution and confounding impacts of precipitation and temperature lead to the underestimation of occurrence of probabilities for these two concurrent extreme modes. This underestimation can also lead to incorrect conclusions and flawed decisions in terms of the severity of these extreme events.
Keywords: Gachon_Philippe

Winter hydrometeorological extreme events modulated by large-scale atmospheric circulation in southern Ontario - Champagne, Olivier; Leduc, Martin; Coulibaly, Paulin; Arain, M. Altaf (Earth System Dynamics, 2020)
Extreme events are widely studied across the world because of their major implications for many aspects of society and especially floods. These events are generally studied in terms of precipitation or temperature extreme indices that are often not adapted for regions affected by floods caused by snowmelt. The rain on snow index has been widely used, but it neglects rain-only events which are expected to be more frequent in the future. In this study, we identified a new winter compound index and assessed how large-scale atmospheric circulation controls the past and future evolution of these events in the Great Lakes region. The future evolution of this index was projected using temperature and precipitation from the Canadian Regional Climate Model large ensemble (CRCM5-LE). These climate data were used as input in Precipitation Runoff Modelling System (PRMS) hydrological model to simulate the future evolution of high flows in three watersheds in southern Ontario. We also used five recurrent large-scale atmospheric circulation patterns in north-eastern North America and identified how they control the past and future variability of the newly created index and high flows. The results show that daily precipitation higher than 10 mm and temperature higher than 5 ∘C were necessary historical conditions to produce high flows in these three watersheds. In the historical period, the occurrences of these heavy rain and warm events as well as high flows were associated with two main patterns characterized by high Z500 anomalies centred on eastern Great Lakes (HP regime) and the Atlantic Ocean (South regime). These hydrometeorological extreme events will still be associated with the same atmospheric patterns in the near future. The future evolution of the index will be modulated by the internal variability of the climate system, as higher Z500 on the east coast will amplify the increase in the number of events, especially the warm events. The relationship between the extreme weather index and high flows will be modified in the future as the snowpack reduces and rain becomes the main component of high-flow generation. This study shows the value of the CRCM5-LE dataset in simulating hydrometeorological extreme events in eastern Canada and better understanding the uncertainties associated with internal variability of climate.
Publisher: Copernicus GmbH

Multivariate extremes and compound events - Zscheischler, Jakob; Van Den Hurk, Bart; Ward, Philip J.; Westra, Seth (Climate Extremes and Their Implications for Impact and Risk Assessment, 2020)
Keywords: Ouvrage_Collectif_Numéro1

Wetland-based solutions against extreme flood and severe drought: Efficiency evaluation of risk mitigation - Wu, Yanfeng; Sun, Jingxuan; Hu, Boting; Zhang, Guangxin; Rousseau, Alain N. (Climate Risk Management, 2023)
Keywords: Infolettre; Infolettre_Juin_2023; Rousseau_Alain

An Integrated Extreme Rainfall Modeling Tool (SDExtreme) for Climate Change Impacts and Adaptation - Yeo, Myeong-Ho; Nguyen, Van-Thanh-Van; Kim, Yong Sang; Kpodonu, Theodore A. (Water Resources Management, 2022)
Abstract The estimation of the Intensity–Duration–Frequency (IDF) relation is often necessary for the planning and design of various hydraulic structures and design storms. It has been an increasingly greater challenge due to climate change conditions. This paper therefore proposes an integrated extreme rainfall modeling software package (SDExtreme) for constructing the IDF relations at a local site in the context of climate change. The proposed tool is based on a temporal downscaling method to describe the relationships between daily and sub-daily extreme precipitation using the scale-invariance General Extreme Value (GEV) distribution. In addition, SDExtreme provides a modified bootstrap technique to determine confidence intervals (CIs) of the estimated IDF curves for current and the future climate conditions. The feasibility and accuracy of SDExtreme were assessed using rainfall data available from the selected rain gauge stations in Quebec and Ontario provinces (Canada) and climate simulations under three different climate change scenarios provided by the Canadian Earth System Model (CanESM2) and the Canadian Regional Climate Model (CanRCM4).
Keywords: Infolettre; Infolettre_Juillet_2022; Site_internet_RIISQ

A rapid high-resolution multi-sensory urban flood mapping framework via DEM upscaling - Tan, Weikai; Qin, Nannan; Zhang, Ying; McGrath, Heather; Fortin, Maxim; Li, Jonathan (Remote Sensing of Environment, 2024)

Adoption of flood-related preventive behaviours by people having different risks and histories of flooding - Valois, Pierre; Bouchard, David; Talbot, Denis; Caron, Maxime; Renaud, Jean-Sébastien; Gosselin, Pierre; Jacob, Johann (Natural Hazards, 2020)
The increase in the frequency of floods, which is a projected consequence of climate change, can have wide-ranging health and economic impacts. To cope with these floods and to reduce their impacts, households can adopt some preventive behaviours. The main goal of this research was to compare the adoption of flood mitigation behaviours in three populations presenting distinctive characteristics with a valid and an invariant measure of behavioural adaptation, as well as a baseline measure (comparison group). The article also aims to test the moderated effect of having experienced a flood on the relation between the perception of risk of being flooded and the adoption of preventive behaviours. A survey was conducted in flood-prone areas and in some areas that were not at risk in Quebec, Canada, through phone interviews. Results confirmed that people who lived in an at-risk area and had experienced past flooding events are more inclined to adopt preventive behaviours than people who lived in an at-risk area but had never experienced such an event, and those who lived outside at-risk areas. In addition, our results indicate that the at-risk population who have never experienced a flood engage in few flood preventive behaviours. This is worrisome, as their rate of adopting adaptive behaviour is very similar to the one seen in populations living outside at-risk areas, despite the increased risk inherent to their situation. This could be partly explained by our data showing that around a quarter of the at-risk population did not know they were living in a flood-prone area. Our results show that communication efforts are necessary in order to better inform the population of the risk related to living in a flood-prone area and that incentives should be developed to help enhance the rate of preventive behaviours in at-risk populations having never experienced a flood.

Barriers to Insurance as a Flood Risk Management Tool: Evidence from a Survey of Property Owners - Thistlethwaite, Jason; Henstra, Daniel; Brown, Craig; Scott, Daniel (International Journal of Disaster Risk Science, 2020)
Abstract By using risk-adjusted price signals to transfer responsibility for property-level flood protection and recovery from governments to property owners, flood insurance represents a key tenet of the flood risk management (FRM) paradigm. The Government of Canada has worked with insurers to introduce flood insurance for the first time as a part of a broader shift towards FRM to limit the growing costs of flooding. The viability of flood insurance in Canada, however, has been questioned by research that disputes the utility of purchasing coverage by property owners. This study tested this assumption by drawing on public opinion survey data to assess factors that influence decisions about the utility of insurance. The findings reveal that Canadians have limited knowledge of flood insurance coverage, exhibit a low willingness-to-pay for both insurance and property-level flood protection measures, and expect governments to shoulder much of the financial burden of flood recovery through disaster assistance.
Keywords: Ouvrage_Collectif_Numéro1

How Ice Mapping Can Help Manage and Prevent Ice Jams: Remote Sensing Monitoring of the Saint-François River, Québec - Plante Lévesque, Valérie; Persent, Marc-Antoine; Lhissou, Rachid; Chokmani, Karem; Gauthier, Yves; Bernier, Monique (Canadian Journal of Remote Sensing, 2024)
Keywords: Infolettre; Infolettre_Octobre_2024

High-temporal-resolution hydrometeorological data collected in the tropical Cordillera Blanca, Peru (2004–2020) - Mateo, Emilio I.; Mark, Bryan G.; Hellström, Robert Å.; Baraer, Michel; McKenzie, Jeffrey M.; Condom, Thomas; Rapre, Alejo Cochachín; Gonzales, Gilber; Gómez, Joe Quijano; Encarnación, Rolando Cesai Crúz (Earth System Science Data, 2022)
Abstract. This article presents a comprehensive hydrometeorological dataset collected over the past two decades throughout the Cordillera Blanca, Peru. The data-recording sites, located in the upper portion of the Rio Santa valley, also known as the Callejon de Huaylas, span an elevation range of 3738–4750 m a.s.l. As many historical hydrological stations measuring daily discharge across the region became defunct after their installation in the 1950s, there was a need for new stations to be installed and an opportunity to increase the temporal resolution of the streamflow observations. Through inter-institutional collaboration, the hydrometeorological network described in this paper was deployed with the goal of evaluating how progressive glacier mass loss was impacting stream hydrology, and understanding better the local manifestation of climate change over diurnal to seasonal and interannual time scales. The four automatic weather stations supply detailed meteorological observations and are situated in a variety of mountain landscapes, with one on a high-mountain pass, another next to a glacial lake, and two in glacially carved valleys. Four additional temperature and relative humidity loggers complement the weather stations within the Llanganuco valley by providing these data across an elevation gradient. The six streamflow gauges are located in tributaries to the Rio Santa and collect high-temporal-resolution runoff data. The datasets presented here are available freely from https://doi.org/10.4211/hs.35a670e6c5824ff89b3b74fe45ca90e0 (Mateo et al., 2021). Combined, the hydrological and meteorological data collected throughout the Cordillera Blanca enable detailed research of atmospheric and hydrological processes in tropical high-mountain terrain.
Keywords: Baraer_Michel

High-resolution spatiotemporal analysis of hydrologic connectivity in the historical floodplain of straightened lowland agricultural streams - Marchand, Jean-Philippe; Biron, Pascale; Buffin-Bélanger, Thomas; Larocque, Marie (River Research and Applications, 2022)
In agricultural watersheds, human interventions such as channel straightening have disrupted the hydrologic connectivity between headwater streams and their riparian environment and have thus undermined the ecological services provided by these small streams. Knowledge of the hydrologic connectivity between these streams and their immediate environment (shallow riparian groundwater in the historical floodplain and on adjacent hillslopes) in human-impacted settings is critical for understanding and restoring these hydrological systems but remains largely incomplete. The objective of this research is to investigate the hydrogeomorphological conditions controlling hydrologic connectivity in the historical floodplain of straightened lowland streams. Detailed measurements on the spatiotemporal variability of groundwater-surface water interactions between straightened reaches, historical floodplain including abandoned meanders, and the adjacent hillslopes were obtained using a dense network of piezometers at two sites in the St. Lawrence Lowlands (Quebec, Canada). Results show that the complex mechanisms controlling hydrologic connectivity in naturally meandering lowland rivers also operate in highly disturbed straightened reaches, despite backfilling and agricultural practices. The pre-straightening hydrogeomorphological configuration of the floodplain partly explains the complex patterns of piezometric fluctuations observed at the sites. The apex of the abandoned meanders stands out as a focal area of hydrologic connectivity as water levels indicate pressure transfer that may reflect flows from the stream, the hillslopes, and the surrounding historical floodplain. These unique field observations suggest that abandoned meanders should be promoted as key elements of restoration strategies in lowland agricultural straightened headwater streams.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/rra.3990
Keywords: Infolettre; Infolettre_Juillet_2022; Site_internet_RIISQ

Application of a High‐Resolution Distributed Hydrological Model on a U.S.‐Canada Transboundary Basin: Simulation of the Multiyear Mean AnnualHydrograph and 2011 Flood of theRichelieu River Basin - Lucas‐Picher, Philippe; Arsenault, Richard; Poulin, Annie; Ricard, Simon; Lachance‐Cloutier, Simon; Turcotte, Richard (Journal of Advances in Modeling Earth Systems, 2020)
Abstract During spring 2011, an extreme flood occurred along the Richelieu River located in southern Quebec, Canada. The Richelieu River is the last section of the complex Richelieu basin, which is composed of the large Lake Champlain located in a valley between two large mountains. Previous attempts in reproducing the Richelieu River flow relied on the use of simplified lumped models and showed mixed results. In order to prepare a tool to assess accurately the change of flood recurrences in the future, a state‐of‐the‐art distributed hydrological model was applied over the Richelieu basin. The model setup comprises several novel methods and data sets such as a very high resolution river network, a modern calibration technique considering the net basin supply of Lake Champlain, a new optimization algorithm, and the use of an up‐to‐date meteorological data set to force the model. The results show that the hydrological model is able to satisfactorily reproduce the multiyear mean annual hydrograph and the 2011 flow time series when compared with the observed river flow and an estimation of the Lake Champlain net basin supply. Many factors, such as the quality of the meteorological forcing data, that are affected by the low density of the station network, the steep terrain, and the lake storage effect challenged the simulation of the river flow. Overall, the satisfactory validation of the hydrological model allows to move to the next step, which consists in assessing the impacts of climate change on the recurrence of Richelieu River floods. , Plain Language Summary In order to study the 2011 Richelieu flood and prepare a tool capable of estimating the effects of climate change on the recurrence of floods, a hydrological model is applied over the Richelieu basin. The application of a distributed hydrological model is useful to simulate the flow of all the tributaries of the Richelieu basin. This new model setup stands out from past models due to its distribution in several hydrological units, its high‐resolution river network, the calibration technique, and the high‐resolution weather forcing data set used to drive the model. The model successfully reproduced the 2011 Richelieu River flood and the annual hydrograph. The simulation of the Richelieu flow was challenging due to the contrasted elevation of the Richelieu basin and the presence of the large Lake Champlain that acts as a reservoir and attenuates short‐term fluctuations. Overall, the application was deemed satisfactory, and the tool is ready to assess the impacts of climate change on the recurrence of Richelieu River floods. , Key Points An advanced high‐resolution distributed hydrological model is applied over a U.S.‐Canada transboundary basin The simulated net basin supply of Lake Champlain and the Richelieu River discharge are in good agreement with observations of the 2011 flood The flow simulation is challenging due to the topographic and meteorological complexities of the basin and uncertainties in the observations

A consistent multi-resolution particle method for fluid-driven granular dynamics - Jandaghian, Mojtaba; Shakibaeinia, Ahmad (Advances in Water Resources, 2023)
Keywords: Ahmad_Shakibaeinia

Locating illicit discharges in storm sewers in urban areas using multi-parameter source tracking: Field validation of a toolbox composite index to prioritize high risk areas - Hachad, Mounia; Lanoue, Martine; Vo Duy, Sung; Villemur, Richard; Sauvé, Sébastien; Prévost, Michèle; Dorner, Sarah (Science of The Total Environment, 2022)
Keywords: Dorner_Sarah

Improvement of Soil Water Assessment Tool (SWAT) wetland module for modelling of ephemeral pond hydrology - Bizhanimanzar, Mohammad; Larocque, Marie; Roux, Marjolaine (Hydrological Processes, 2024)
Abstract Ephemeral ponds (EPs) are seasonally flooded isolated wetlands that provide a variety of hydroecological benefits, including the provision of breeding habitat for several amphibian and invertebrate species. However, the lack of their explicit representation in hydrological models limits a comprehensive understanding of their interaction with surrounding landscapes and their vulnerability in the context of human interventions and climate change. The purpose of this research was to improve the isolated wetland module of the Soil Water Assessment Tool (SWAT) to better represent EP hydrology. The changes include (1) representation of groundwater and hypodermic flow as the only inflows from the pond drainage surface, due to the intermittent and negligible presence of inflow from surface runoff in forested ponds, (2) revision of how evapotranspiration within EPs is represented and (3) implementation of distinct volume‐area‐depth relationships for ponds based on their geometrical shape. The accuracy of these improvements was assessed against that of a previous isolated wetland formulation in replicating water depth observations of 10 EPs of a portion of the Kenauk forest (68 km 2 ) in the Canadian Shield of the Outaouais region (Québec, Canada). The comparison results show that the revised SWAT model presented here significantly improves the distinct filling and drying water cycle of EPs (average root mean square error of 0.1 m of the revised model vs. 0.23 m for the original model). Besides, the new module allowed to identify that hypodermic flow, evapotranspiration and seepage to the underlying soil are the main EP source and sinks. The new module also allowed to explicitly quantify the differences in filling/drying pattern of the EPs of the Kenauk forest and unlike the original model structure, the new module was able to closely replicate the interannual variation of spring and annual hydroperiod duration.
Keywords: Infolettre; Infolettre_Avril_2024

Selection and Evaluation of Integrated Solutions in a Combined Sewer Network - Demard, Emmanuel; Binesh, Negin; Duchesne, Sophie; Pelletier, Geneviève (Journal of Infrastructure Systems, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

A spatially adaptive multi-resolution generative algorithm: Application to simulating flood wave propagation - Carreau, Julie; Naveau, Philippe (Weather and Climate Extremes, 2023)
Keywords: Infolettre; Infolettre_Septembre_2023

Urban flood resilience, a multi-level institutional analysis of planning practices in the Metropolitan City of Naples - Vitale, Corinne; Meijerink, Sander; Moccia, Francesco Domenico (Journal of Environmental Planning and Management, 2023)
Keywords: Ouvrage_Collectif_Numéro1

Disrupting the riskscapes of inequities: a case study of planning for resilience in Canada’s Metro Vancouver region - Yumagulova, Lilia (Cambridge Journal of Regions, Economy and Society, 2020)
Abstract The analysis across spatial, temporal and governance scales shows an inequitable distribution of risk across Canada’s Metro Vancouver region. For First Nation communities in this region, this risk is rooted in the colonial history of land dispossession. This article makes a contribution by expanding our understanding of historic creation of riskscapes and a discussion of its implications as a multiscale governance issue that persists across space and time. This article also situates the impacts of projected sea level rise on Indigenous communities in the context of regional, provincial and federal settler-colonial flood risk management regime.

Resilience patterns of human mobility in response to extreme urban floods - Tang, Junqing; Zhao, Pengjun; Gong, Zhaoya; Zhao, Hongbo; Huang, Fengjue; Li, Jiaying; Chen, Zhihe; Yu, Ling; Chen, Jun (National Science Review, 2023)
ABSTRACT Large-scale disasters can disproportionately impact different population groups, causing prominent disparity and inequality, especially for the vulnerable and marginalized. Here, we investigate the resilience of human mobility under the disturbance of the unprecedented ‘720’ Zhengzhou flood in China in 2021 using records of 1.32 billion mobile phone signaling generated by 4.35 million people. We find that although pluvial floods can trigger mobility reductions, the overall structural dynamics of mobility networks remain relatively stable. We also find that the low levels of mobility resilience in female, adolescent and older adult groups are mainly due to their insufficient capabilities to maintain business-as-usual travel frequency during the flood. Most importantly, we reveal three types of counter-intuitive, yet widely existing, resilience patterns of human mobility (namely, ‘reverse bathtub’, ‘ever-increasing’ and ‘ever-decreasing’ patterns), and demonstrate a universal mechanism of disaster-avoidance response by further corroborating that those abnormal resilience patterns are not associated with people’s gender or age. In view of the common association between travel behaviors and travelers’ socio-demographic characteristics, our findings provide a caveat for scholars when disclosing disparities in human travel behaviors during flood-induced emergencies.

Vulnerable Waters are Essential to Watershed Resilience - Lane, Charles R.; Creed, Irena F.; Golden, Heather E.; Leibowitz, Scott G.; Mushet, David M.; Rains, Mark C.; Wu, Qiusheng; D’Amico, Ellen; Alexander, Laurie C.; Ali, Genevieve A.; Basu, Nandita B.; Bennett, Micah G.; et al. (Ecosystems, 2023)
Abstract Watershed resilience is the ability of a watershed to maintain its characteristic system state while concurrently resisting, adapting to, and reorganizing after hydrological (for example, drought, flooding) or biogeochemical (for example, excessive nutrient) disturbances. Vulnerable waters include non-floodplain wetlands and headwater streams, abundant watershed components representing the most distal extent of the freshwater aquatic network. Vulnerable waters are hydrologically dynamic and biogeochemically reactive aquatic systems, storing, processing, and releasing water and entrained (that is, dissolved and particulate) materials along expanding and contracting aquatic networks. The hydrological and biogeochemical functions emerging from these processes affect the magnitude, frequency, timing, duration, storage, and rate of change of material and energy fluxes among watershed components and to downstream waters, thereby maintaining watershed states and imparting watershed resilience. We present here a conceptual framework for understanding how vulnerable waters confer watershed resilience. We demonstrate how individual and cumulative vulnerable-water modifications (for example, reduced extent, altered connectivity) affect watershed-scale hydrological and biogeochemical disturbance response and recovery, which decreases watershed resilience and can trigger transitions across thresholds to alternative watershed states (for example, states conducive to increased flood frequency or nutrient concentrations). We subsequently describe how resilient watersheds require spatial heterogeneity and temporal variability in hydrological and biogeochemical interactions between terrestrial systems and down-gradient waters, which necessitates attention to the conservation and restoration of vulnerable waters and their downstream connectivity gradients. To conclude, we provide actionable principles for resilient watersheds and articulate research needs to further watershed resilience science and vulnerable-water management.

Four core principles to reconcile sociocultural conditions and disaster risk reduction in pursuit of community resilience - Graveline, Marie-Hélène; Germain, Daniel; Boyer-Villemaire, Ursule; Guimond, Laurie (Environmental Hazards, 2025)
Keywords: Infolettre; Infolettre_Fevrier_2025

How Plans Prepare for Future Uncertainty: Integrating Land Change Modeling and the Plan Integration for Resilience Scorecard™ - Kim, Youjung; Newman, Galen; Berke, Philip; Lee, Jaekyung; Malecha, Matthew; Yu, Siyu (Journal of Planning Education and Research, 2024)
This study integrates Land Change Modeling with the Plan Integration for Resilience Scorecard™ methodology to assess coastal communities’ preparedness for uncertain future urban growth and flood hazards. Findings indicate that, under static climate conditions, the network of plans in Tampa is well prepared across all urban growth scenarios, but less so in the face of a changing climate. Specifically, scenario outputs that consider climate change suggest the need for more resilient growth to reduce flood vulnerability compared with the current land use plan. Notably, some existing policies are likely to lead to counterproductive outcomes in a future with more extensive flooding.
Keywords: Infolettre; Infolettre_Septembre_2024

Operating urban resilience strategies to face climate change and associated risks: some advances from theory to application in Canada and France - Heinzlef, Charlotte; Robert, Benoît; Hémond, Yannick; Serre, Damien (Cities, 2020)
Keywords: Hémond_Yannick; Ouvrage_Collectif_Numéro1

Retrofitting for Flood Resilience: A Guide to Building & Community Design - Barsley, Edward (RIBA Publishing, 2020)
Keywords: Ouvrage_Collectif_Numéro1

Do floods widen the economic disparity gap? - Vin, Leon; Kawasaki, Akiyuki (Progress in Disaster Science, 2024)

Transformative learning for a sustainable and healthy future through ecosystem approaches to health: insights from 15 years of co-designed ecohealth teaching and learning experiences - Webb, Jena; Raez-Villanueva, Sergio; Carrière, Paul D; Beauchamp, Audrey-Anne; Bell, Isaac; Day, Angela; Elton, Sarah; Feagan, Mathieu; Giacinti, Jolene; Kabemba Lukusa, Jean Paul; Kingsbury, Celia; Torres-Slimming, Paola A; et al. (The Lancet Planetary Health, 2023)

Energy poverty: an overlooked determinant of health and climate resilience in Canada - Riva, Mylène; Kingunza Makasi, Sophie; O’Sullivan, Kimberley C.; Das, Runa R.; Dufresne, Philippe; Kaiser, David; Breau, Sébastien (Canadian Journal of Public Health, 2023)
Abstract Objective Despite Canada being an important energy producer, not all Canadians can access or afford adequate levels of energy services at home to meet their needs, maintain healthy indoor temperatures, and live a decent life—a situation known as energy poverty. Depending on the measure, 6–19% of Canadian households face energy poverty. Health risks associated with energy poverty are documented in countries with milder climates. This study explores, for the first time in the Canadian context, the association between energy poverty and health. Methods Cross-sectional data are from the 2018 Canadian Housing Survey. Analyses are conducted on a sample weighted to represent 14 million Canadian households. The associations between expenditure-based and self-reported measures of energy poverty and self-rated general and mental health were assessed using logistic regression models, adjusted for potential confounding variables. Results The odds of rating one’s general (OR: 1.48; 95%CI: 1.29, 1.70) and mental (OR: 1.21; 1.04, 1.41) health as poor are significantly higher for Canadian adults in households with a high share of energy expenditure to income. The likelihood of poor general and mental health was significantly higher for those dissatisfied with the energy efficiency of their dwelling, and with their ability to maintain a comfortable temperature both in the winter and in the summer. Conclusion Exposure to energy poverty is associated with significantly increased likelihood of poor general and mental health. Given the high proportion of Canadian households facing energy poverty, with demonstrated implications for population health, tackling energy poverty is essential for an equitable energy transition and for climate resilience. , Résumé Objectif Bien que le Canada soit un important producteur d’énergie, entre 6 % et 19 % des ménages canadiens, selon la mesure retenue, sont en précarité énergétique, une situation qui survient lorsqu’un ménage n’a pas les moyens ou l’accès à des services énergétiques résidentiels adéquats pour maintenir une température ambiante confortable, répondre à ses besoins et vivre dans la dignité. Les risques socio-sanitaires associés à la précarité énergétique sont documentés dans des pays au climat tempéré. Cette étude explore, pour la première fois dans le contexte canadien, l’association entre la précarité énergétique et la santé. Méthodes Les données transversales proviennent de l’Enquête canadienne sur le logement de 2018. Les associations entre différentes mesures de précarité énergétique (mesures basées sur les dépenses des ménages et auto-rapportées) et la santé générale et mentale perçue sont estimées à l’aide de modèles de régression logistique ajustés pour des variables de confusion potentielles. Les analyses sont réalisées sur un échantillon pondéré pour représenter 14 millions de ménages. Résultats Les probabilités de déclarer une mauvaise santé générale (OR : 1,48; IC95% : 1,29-1,70) et mentale (OR : 1,21; 1,04-1,41) sont significativement plus élevées pour les adultes canadiens dont le ménage consacre une part importante de son revenu aux coûts énergétiques. Elles sont aussi significativement plus élevées pour ceux qui déclarent être insatisfaits avec l’efficacité énergétique de leur logement et de leur capacité à maintenir une température confortable en hiver et en été. Conclusion Vivre en situation de précarité énergétique est associée à des probabilités accrues de déclarer une mauvaise santé générale et mentale chez les adultes canadiens. En raison de la proportion élevée de ménages canadiens confrontés à la précarité énergétique et des effets socio-sanitaires que cette situation engendre, lutter contre la précarité énergétique est essentiel pour une transition énergétique équitable et pour la résilience climatique.

Social housing construction and improvements in housing outcomes for Inuit in Northern Canada - Riva, Mylene; Perreault, Karine; Dufresne, Philippe; Fletcher, Christopher; Muckle, Gina; Potvin, Louise; Bailie, Ross; Baron, Marie (Housing Studies, 2021)

Scenarios of Human Responses to Unprecedented Social‐Environmental Extreme Events - Rusca, Maria; Messori, Gabriele; Di Baldassarre, Giuliano (Earth's Future, 2021)
Abstract In a rapidly changing world, what is today an unprecedented extreme may soon become the norm. As a result, extreme‐related disasters are expected to become more frequent and intense. This will have widespread socio‐economic consequences and affect the ability of different societal groups to recover from and adapt to rapidly changing environmental conditions. Therefore, there is the need to decipher the relation between genesis of unprecedented events, accumulation and distribution of risk, and recovery trajectories across different societal groups. Here, we develop an analytical approach to unravel the complexity of future extremes and multiscalar societal responses—from households to national governments and from immediate impacts to longer term recovery. This requires creating new forms of knowledge that integrate analyses of the past—that is, structural causes and political processes of risk accumulation and differentiated recovery trajectories—with plausible scenarios of future environmental extremes grounded in the event‐specific literature. We specifically seek to combine the physical characteristics of the extremes with examinations of how culture, politics, power, and policy visions shape societal responses to unprecedented events, and interpret the events as social‐environmental extremes. This new approach, at the nexus between social and natural sciences, has the concrete advantage of providing an impact‐focused vision of future social‐environmental risks, beyond what is achievable within conventional disciplinary boundaries. In this paper, we focus on extreme flooding events and the societal responses they elicit. However, our approach is flexible and applicable to a wide range of extreme events. We see it as the first building block of a new field of research, allowing for novel and integrated theoretical explanations and forecasting of social‐environmental extremes. , Key Points We conceptualize unprecedented extremes as social‐environmental processes shaped by institutional, political, and economic change As social‐environmental extremes become more frequent, there is an urgency to unravel their genesis and the possible societal responses This approach is the first building block of a new field of research in social‐environmental extreme event forecasts , Plain Language Summary The world is seeing increases in a range of extreme events, and this increase may continue or even accelerate in the future, due to anthropogenic climate change. Furthermore, it is often those who are already vulnerable that experience the biggest impacts from these extremes. Yet, there is little understanding of the possible societal responses to unprecedented events. This underscores the urgency of creating innovative approaches to develop plausible scenarios of societal responses and, in turn, mitigate hazards and reduce vulnerability and exposure to extreme events. In this commentary, we develop a truly interdisciplinary conceptual approach to better understand how different societal groups might interact with and respond to future unprecedented extreme events. We combine social science theories describing how different societal groups are affected by, and recover from, extreme events with projections from the literature identifying plausible areas at risk of unprecedented occurrences and local analyses of past extreme events. We see this as the first building block of a new field of research in forecasting social‐environmental extremes that could support governments, civil protection agencies, and civil society organizations to ensure a fairer, improved response to future events.

Indice du potentiel de participation sociale des Québécois âgés : cartographie des inégalités des zones métropolitaines, urbaines et rurales: IPPS : cartographie des inégalités - Naud, Daniel; Généreux, Mélissa; Bruneau, Jean-François; Levasseur, Mélanie (Canadian Journal on Aging / La Revue canadienne du vieillissement, 2024)
Afin de mieux comprendre la distribution géographique des facilitateurs et des obstacles à la participation sociale des Québécois âgés, cette étude visait à documenter l’Indice du potentiel de participation sociale (IPPS) selon les zones métropolitaines, urbaines et rurales. Des analyses de données secondaires, dont l’Enquête transversale sur la santé des collectivités canadiennes, ont permis de développer et de cartographier un indice composé de facteurs environnementaux associés à la participation sociale, pondérés par une analyse factorielle. En zones métropolitaines, l’IPPS était supérieur au centre qu’en périphérie, compte tenu d’une concentration accrue d’aînés et des transports. Bien qu’atténuée, la configuration était similaire en zones urbaines. En zone rurale, un IPPS élevé était associé à une concentration d’aînés et un accès aux ressources accru, sans configuration spatiale. Pour favoriser la participation sociale, l’IPPS soutient que les transports et l’accès aux ressources doivent respectivement être améliorés en périphérie des métropoles et en zone rurale., AbstractTo better understand the geographic distribution of facilitators of, and barriers to, social participation among older Quebecers, this study aimed to document the Social Participation Potential Index (SPPI; Indice du potentiel de participation sociale) in metropolitan, urban and rural areas. Secondary data analyses, including the Canadian Community Health Survey, were used to develop and map a composite index of environmental factors associated with social participation, weighted by factor analysis. In metropolitan areas, the SPPI was higher in the center than in the periphery, due to an increased concentration of seniors and transportation. Although reduced, the pattern was similar in urban areas. In rural areas, a higher SPPI was associated with an increased concentration of older adults and access to resources, showing no spatial pattern. To promote social participation, the SPPI suggests that transportation and access to resources must be improved in the periphery of metropolitan areas and in rural areas, respectively.
Keywords: Généreux_Mélissa

Organic UV absorbents in the deepwater redfish (Sebastes mentella) from the St. Lawrence Estuary and Gulf: Distribution and human health risk assessment - Moualek, Fella; Babin, Mathieu; Parent, Geneviève J.; Ponton, Dominic E.; Senay, Caroline; Amyot, Marc; Robert, Dominique; Lu, Zhe (Science of The Total Environment, 2024)

Snow particles physiochemistry: feedback on air quality, climate change, and human health - Rangel-Alvarado, Rodrigo; Li, Houjie; Ariya, Parisa A. (Environmental Science: Atmospheres, 2022)
During the last several decades, numerous researchers have provided evidence that physical and biogeochemical processes at air-snow/ice-water interfaces are very complex, and, in many cases, interlinked. , During the last several decades, numerous researchers have provided evidence that physical and biogeochemical processes at air-snow/ice-water interfaces are very complex, and, in many cases, interlinked. This review focuses on the current state of knowledge regarding snow-borne particles. It integrates snow science from different angles: from the formation of snow and precipitation to transformations through natural and anthropogenic processes and impacts and snow management in urban areas sites. We discuss the physical, chemical, and biological characteristics of particles in snow, such as their composition, abundance, size distribution, ice nucleation properties, genomic features, and microphysical processes, in urban settings, remote areas of the Arctic, and remote industrial regions (oil sands). We explore physicochemical processes of snow particles: from microbial to emerging contaminants, like nano/microplastics, light-absorbing carbonaceous organics, halogenated and nanometals particles. We review the possible contributions of snow particles to atmospheric radiation and climate, biogeochemistry, human health, and urban snow management. We propose further research directions to improve understanding of air-snow feedback, and sustainable snow management in urban areas, in the age of emerging contaminants in a changing climate.

Economic ‘normalisation’ of disaster losses 1998–2020: a literature review and assessment - Pielke, Roger (Environmental Hazards, 2021)

Modeling the Impacts of Urban Flood Risk Management on Social Inequality - Moulds, Simon; Buytaert, Wouter; Templeton, Michael R.; Kanu, Ishmael (Water Resources Research, 2021)
Abstract The exposure of urban populations to flooding is highly heterogeneous, with the negative impacts of flooding experienced disproportionately by the poor. In developing countries experiencing rapid urbanization and population growth a key distinction in the urban landscape is between planned development and unplanned, informal development, which often occurs on marginal, flood‐prone land. Flood risk management in the context of informality is challenging, and may exacerbate existing social inequalities and entrench poverty. Here, we adapt an existing socio‐hydrological model of human‐flood interactions to account for a stratified urban society consisting of planned and informal settlements. In the first instance, we use the model to construct four system archetypes based on idealized scenarios of risk reduction and disaster recovery. We then perform a sensitivity analysis to examine the relative importance of the differential values of vulnerability, risk‐aversion, and flood awareness in determining the relationship between flood risk management and social inequality. The model results suggest that reducing the vulnerability of informal communities to flooding plays an important role in reducing social inequality and enabling sustainable economic growth, even when the exposure to the flood hazard remains high. Conversely, our model shows that increasing risk aversion may accelerate the decline of informal communities by suppressing economic growth. On this basis, we argue for urban flood risk management which is rooted in pro‐poor urban governance and planning agendas which recognize the legitimacy and permanence of informal communities in cities. , Key Points The distribution of flood risk in urban areas is uneven, with the negative impacts experienced disproportionately by the urban poor Our model shows that reducing the vulnerability of informal residents to flooding can reduce inequality, even when their exposure is high Based on the model results, we argue that urban flood risk management should be rooted in pro‐poor urban governance and planning agendas

Flooded Social Connections - Ratnadiwakara, Dimuthu (The Quarterly Journal of Finance, 2021)
Does salient information on social media influence individuals’ economic decisions and beliefs? Using aggregated data from Facebook and a difference-in-differences strategy, I show that individuals who are socially connected to someone affected by Hurricane Harvey are more likely to purchase flood insurance policies after the event. This effect is stronger in areas at higher risk of flooding. Being socially connected to someone affected by Hurricane Harvey also influences individuals’ perceptions of global warming.

Energy poverty in Canada: Prevalence, social and spatial distribution, and implications for research and policy - Riva, Mylene; Kingunza Makasi, Sophie; Dufresne, Philippe; O'Sullivan, Kimberley; Toth, Megan (Energy Research & Social Science, 2021)

Human displacements, fatalities, and economic damages linked to remotely observed floods - Mester, Benedikt; Frieler, Katja; Schewe, Jacob (Scientific Data, 2023)
Abstract We present a new open source dataset FLODIS that links estimates of flood-induced human displacements, fatalities, and economic damages to flooded areas observed through remote sensing. The dataset connects displacement data from the Internal Displacement Monitoring Centre (IDMC), as well as data on fatalities and damages from the Emergency Events Database (EM-DAT), with the Global Flood Database (GFD), a satellite-based inventory of historic flood footprints. It thereby provides a spatially explicit estimate of the flood hazard underlying each individual disaster event. FLODIS contains two datasets with event-specific information for 335 human displacement events and 695 mortality/damage events that occurred around the world between 2000 and 2018. Additionally, we provide estimates of affected population, GDP, and critical infrastructure, as well as socio-economic indicators; and we provide geocoding for displacement events ascribed to other types of disasters, such as tropical cyclones, so that they may be linked to corresponding hazard estimates in future work. FLODIS facilitates integrated flood risk analysis, allowing, for example, for detailed assessments of local flood-damage and displacement vulnerability.

Eco-anxiety in children: A scoping review of the mental health impacts of the awareness of climate change - Léger-Goodes, Terra; Malboeuf-Hurtubise, Catherine; Mastine, Trinity; Généreux, Mélissa; Paradis, Pier-Olivier; Camden, Chantal (Frontiers in Psychology, 2022)
Background Youth are increasingly aware of the negative effects of climate change on the planet and human health, but this knowledge can often come with significant affective responses, such as psychological distress, anger, or despair. Experiencing major “negative” emotions, like worry, guilt, and hopelessness in anticipation of climate change has been identified with the term eco-anxiety. Emerging literature focuses on adults' experience; however, little is known about the ways in which children and youth experience eco-anxiety. Objectives The aim of this review was to: (1) identify the available evidence on the topic of eco-anxiety in children, (2) clarify the mental health consequences brought by the awareness of climate change in this population, and (3) identify knowledge gaps in the literature and considerations for future research. Methods Given that the research on the topic of eco-anxiety in children is limited, that there are very few randomized controlled trials, and that the goal is not to analyze individual studies in-depth, a scoping review was used. Keywords pertaining to the themes of eco-anxiety, climate change and children (aged < 18 years) were used as search terms in five databases. Journal articles using qualitative and quantitative methods, as well as gray literature were examined by two independent reviewers. A descriptive-analytical method was used to chart the data that emerged from the literature. Eighteen articles were considered in the final analysis. Results Evidence confirms that children experience affective responses and eco-anxiety in reaction to then awareness of climate change. Mental health outcomes include depression, anxiety, and extreme emotions like sadness, anger, and fear. Youth from vulnerable communities, like indigenous communities, or those who have strong ties to the land are often identified as being emotionally impacted by climate change. The literature analyzed also describes how children and youth are coping with eco-anxiety, including maladaptive (e.g., denial) and adaptive responses (such as constructive hope, used as a positive coping mechanism). Preliminary considerations for parents, teachers and educators, mental health care providers, school systems, adults and people of power include adding age-appropriate climate education to the school curriculum, considering youth's emotions, and promoting healthy coping through empowerment. Important gaps exist in the definition of eco-anxiety in youth, as various characterizations of this emerging concept are found across articles.
Keywords: Généreux_Mélissa

Flood occurrence and impact models for socioeconomic applications over Canada and the United States - Grenier, Manuel; Boudreault, Mathieu; Carozza, David A.; Boudreault, Jérémie; Raymond, Sébastien (Natural Hazards and Earth System Sciences, 2024)
Abstract. Large-scale socioeconomic studies of the impacts of floods are difficult and costly for countries such as Canada and the United States due to the large number of rivers and size of watersheds. Such studies are however very important for analyzing spatial patterns and temporal trends to inform large-scale flood risk management decisions and policies. In this paper, we present different flood occurrence and impact models based upon statistical and machine learning methods of over 31 000 watersheds spread across Canada and the US. The models can be quickly calibrated and thereby easily run predictions over thousands of scenarios in a matter of minutes. As applications of the models, we present the geographical distribution of the modelled average annual number of people displaced due to flooding in Canada and the US, as well as various scenario analyses. We find for example that an increase of 10 % in average precipitation yields an increase in the displaced population of 18 % in Canada and 14 % in the US. The model can therefore be used by a broad range of end users ranging from climate scientists to economists who seek to translate climate and socioeconomic scenarios into flood probabilities and impacts measured in terms of the displaced population.
Keywords: Infolettre; Infolettre_Decembre_2024

Interregional imbalance in the Yellow River Basin: Insights from flood-sediment transport, socioeconomic, and environmental subsystems - Hu, Hao; Tian, Guiliang; Adamowski, Jan F.; Albano, Raffaele; Liu, Yixue; Jing, Xiaodong; Zhao, Qiuya (Journal of Environmental Management, 2024)
Keywords: Infolettre; Infolettre_Decembre_2024

Climate change, poverty and child health inequality: evidence from Vietnam’s provincial analysis - Huynh, Cong Minh; Tran, Bao Khuyen (Economic Change and Restructuring, 2024)

HIV/AIDS knowledge and attitudes among social work students: A comparative study - Labra, Oscar; Ependa, Augustin; Chamblas, Isis; Gingras-Lacroix, Gabriel; Antoniadis, André; Biston, Cristine; Mukeshimana, Marthe; Giroux, Marie-Ève (International Social Work, 2023)
The article describes a quantitative cross-sectional study of a sample of 674 university students enrolled in social work programmes in four countries: Belgium, Canada, Chile and Switzerland. The study aimed to assess HIV/AIDS knowledge and attitudes among participants. The median HIV-KQ-18 score for the sample was 14.0, which Carey and Schroder classify as indicating borderline low levels of knowledge. Based on the results, the authors argue that social work education and training programmes should more comprehensively address HIV/AIDS within their curricula to better equip future social workers to challenge stigmatising and exclusionary practices rooted in long-standing lack of knowledge and erroneous beliefs about the disease.

Caregiver Support in Mental Health Recovery: A Critical Realist Qualitative Research - Lauzier-Jobin, François; Houle, Janie (Qualitative Health Research, 2021)
Support from caregivers is an important element of mental health recovery. However, the mechanisms by which social support influences the recovery of persons with depressive, anxiety, or bipolar disorders are less understood. In this study, we describe the social support mechanisms that influence mental health recovery. A cross-sectional qualitative study was undertaken in Québec (Canada) with 15 persons in recovery and 15 caregivers—those having played the most significant role in their recovery. A deductive thematic analysis allowed for the identification and description of different mechanisms through a triangulation of perspectives from different actors. Regarding classic social support functions, several of the support mechanisms for mental health recovery were identified (emotional support, companionship, instrumental support, and validation). However, informational support was not mentioned. New mechanisms were also identified: presence, communication, and influence. Social support mechanisms evoke a model containing a hierarchy as well as links among them.

The Economic Impacts of Direct Natural Disaster Exposure - Johar, Meliyanni; Johnston, David W.; Shields, Michael; Siminski, Peter; Stavrunova, Olena (SSRN Electronic Journal, 2020)
Keywords: Ouvrage_Collectif_Numéro1

Assessment of socio-economic strategies for managing regional flood risk in an urban coastal catchment - Ghosh, Mousumi; Ghosh, Subimal; Karmakar, Subhankar (Urban Climate, 2024)

Intersectoral approaches: the key to mitigating psychosocial and health consequences of disasters and systemic risks - Gousse-Lessard, Anne-Sophie; Gachon, Philippe; Lessard, Lily; Vermeulen, Valérie; Boivin, Maxime; Maltais, Danielle; Landaverde, Elsa; Généreux, Mélissa; Motulsky, Bernard; Le Beller, Julien (Disaster Prevention and Management: An International Journal, 2023)
Purpose The current pandemic and ongoing climate risks highlight the limited capacity of various systems, including health and social ones, to respond to population-scale and long-term threats. Practices to reduce the impacts on the health and well-being of populations must evolve from a reactive mode to preventive, proactive and concerted actions beginning at individual and community levels. Experiences and lessons learned from the pandemic will help to better prevent and reduce the psychosocial impacts of floods, or other hydroclimatic risks, in a climate change context. Design/methodology/approach The present paper first describes the complexity and the challenges associated with climate change and systemic risks. It also presents some systemic frameworks of mental health determinants, and provides an overview of the different types of psychosocial impacts of disasters. Through various Quebec case studies and using lessons learned from past and recent flood-related events, recommendations are made on how to better integrate individual and community factors in disaster response. Findings Results highlight the fact that people who have been affected by the events are significantly more likely to have mental health problems than those not exposed to flooding. They further demonstrate the adverse and long-term effects of floods on psychological health, notably stemming from indirect stressors at the community and institutional levels. Different strategies are proposed from individual-centered to systemic approaches, in putting forward the advantages from intersectoral and multirisk researches and interventions. Originality/value The establishment of an intersectoral flood network, namely the InterSectoral Flood Network of Québec (RIISQ), is presented as an interesting avenue to foster interdisciplinary collaboration and a systemic view of flood risks. Intersectoral work is proving to be a major issue in the management of systemic risks, and should concern communities, health and mental health professionals, and the various levels of governance. As climate change is called upon to lead to more and more systemic risks, close collaboration between all the areas concerned with the management of the factors of vulnerability and exposure of populations will be necessary to respond effectively to damages and impacts (direct and indirect) linked to new meteorological and compound hazards. This means as well to better integrate the communication managers into the risk management team.
Keywords: Boivin_Maxime; Gachon_Philippe; Gousse-Lessard_Anne-Sophie; Généreux_Mélissa; Infolettre; Infolettre_Fevrier_2023; Lessard_Lily; Site_internet_RIISQ

Intersectoral research and multi-risk approaches in Québec: systemic risk management and its psychosocial consequences - Gousse-Lessard, Anne-Sophie; Gachon, Philippe; Lessard, Lily; Vermeulen, Valérie; Boivin, Maxime; Maltais, Danielle; Landaverde, Elsa; Généreux, Mélissa; Motulsky, Bernard; Le Beller, Julien (Contribution paper to the Global Assessment Report on Disaster Risk Reduction, 2022)
Purpose The current pandemic and ongoing climate risks highlight the limited capacity of various systems, including health and social ones, to respond to population-scale and long-term threats. Practices to reduce the impacts on the health and well-being of populations must evolve from a reactive mode to preventive, proactive and concerted actions beginning at individual and community levels. Experiences and lessons learned from the pandemic will help to better prevent and reduce the psychosocial impacts of floods, or other hydroclimatic risks, in a climate change context. Design/methodology/approach The present paper first describes the complexity and the challenges associated with climate change and systemic risks. It also presents some systemic frameworks of mental health determinants, and provides an overview of the different types of psychosocial impacts of disasters. Through various Quebec case studies and using lessons learned from past and recent flood-related events, recommendations are made on how to better integrate individual and community factors in disaster response. Findings Results highlight the fact that people who have been affected by the events are significantly more likely to have mental health problems than those not exposed to flooding. They further demonstrate the adverse and long-term effects of floods on psychological health, notably stemming from indirect stressors at the community and institutional levels. Different strategies are proposed from individual-centered to systemic approaches, in putting forward the advantages from intersectoral and multirisk researches and interventions. Originality/value The establishment of an intersectoral flood network, namely the InterSectoral Flood Network of Québec (RIISQ), is presented as an interesting avenue to foster interdisciplinary collaboration and a systemic view of flood risks. Intersectoral work is proving to be a major issue in the management of systemic risks, and should concern communities, health and mental health professionals, and the various levels of governance. As climate change is called upon to lead to more and more systemic risks, close collaboration between all the areas concerned with the management of the factors of vulnerability and exposure of populations will be necessary to respond effectively to damages and impacts (direct and indirect) linked to new meteorological and compound hazards. This means as well to better integrate the communication managers into the risk management team.
Keywords: Boivin_Maxime; Gachon_Philippe; Gousse-Lessard_Anne-Sophie; Généreux_Mélissa; Lessard_Lily; Site_internet_RIISQ

Health impacts of climate change in the UK: A qualitative synthesis detailing the conjuncture of social structure, extreme weather, and mental health - Dodd, Steven; Kragh-Furbo, Mette; Davies, Jessica; Butterfield, Scott; Morris, Abigail; Brown, Heather (SSM - Qualitative Research in Health, 2024)

The effect of an Internet‐based cognitive behavioral therapy intervention on social support in disaster evacuees - Frenette, Émilie; Ouellet, Marie‐Christine; Guay, Stéphane; Lebel, Jessica; Békés, Vera; Belleville, Geneviève (Journal of Clinical Psychology, 2023)
Abstract Introduction Both exposure to a natural disaster and psychological symptoms may lead to decreases in social support. Few studies have examined ways to improve social support among victims of natural disasters. Aims The objective of the study was to assess emotional and tangible support following a 12‐session Internet‐based cognitive behavioral therapy (ICBT) targeting posttraumatic stress (PTS), insomnia, and depression symptoms and to examine the association between posttreatment symptoms and emotional and tangible support. Materials and Methods One hundred and seventy‐eight wildfire evacuees with significant PTS, depression and/or insomnia symptoms were given access to the ICBT. They completed questionnaires at pre‐ and posttreatment to measure social support and symptom severity. Results Results show that completion of the treatment led to an improvement in emotional support. Lower posttreatment PTS and insomnia symptoms were associated with higher posttreatment emotional support. Conclusion ICBT may contribute to enhance emotional support through symptom improvement and probably more so when social support is address directly in treatment.
Keywords: Infolettre; Infolettre_Mars_2023

Measuring social equity in flood recovery funding - Emrich, Christopher T.; Tate, Eric; Larson, Sarah E.; Zhou, Yao (Environmental Hazards, 2020)

Socioeconomic implications of national flood insurance policy reform and flood insurance rate map revisions - Frazier, Tim; Boyden, Elizabeth E.; Wood, Erik (Natural Hazards, 2020)

Discussing linkages between climate change, human mobility and health in the Caribbean: The case of Dominica. A qualitative study - Cloos, Patrick; Belloiseau, Maeva; Mc Pherson, Nickez; Harris-Glenville, Fiona; Joseph, Debra D.; Zinszer, Kate (The Journal of Climate Change and Health, 2023)
Keywords: Cloos_Patrick

B’ the Change you Want to See: How Commensurating Water Health Impedes Collective Action - Couture, Fannie; Le, Jane Kirsten (Academy of Management Proceedings, 2023)

Waterway health in a sunburnt country: A dive into the process of responding to a grand challenge - Couture, Fannie (2022)

Avoiding the vicious cycle, engendering the virtuous circle: Understanding the interaction of human, social and organizational capitals in non-profit and voluntary organizations - Currie, Denise; McCracken, Martin; Venter, Katharine (Journal of Business Research, 2022)

Let the rich be flooded: The distribution of financial aid and distress after hurricane harvey - Billings, Stephen B.; Gallagher, Emily A.; Ricketts, Lowell (Journal of Financial Economics, 2022)

Leveraging public adaptation finance through urban land reclamation: cases from Germany, the Netherlands and the Maldives - Bisaro, Alexander; De Bel, Mark; Hinkel, Jochen; Kok, Sien; Bouwer, Laurens M. (Climatic Change, 2020)

A novel hybrid GIS ‐based multi‐criteria decision‐making approach for flood susceptibility analysis in large ungauged watersheds - Sahraei, Roya; Kanani‐Sadat, Yousef; Homayouni, Saeid; Safari, Abdolreza; Oubennaceur, Khalid; Chokmani, Karem (Journal of Flood Risk Management, 2023)
Abstract Characterizing and identification of flood‐susceptible areas can be a solution to mitigate the damages and fatality rate. This study proposes a novel hybrid MCDM framework to assess flood susceptibility in large ungauged watersheds dealing with data scarcity issues. The proposed method examines the interdependencies and causal relationships between various criteria affecting the flooding procedure using the DEcision‐MAking Trial and Evaluation Laboratory (DEMATEL). Moreover, since experts' opinions contain uncertainty, the fuzzy logic is integrated with DEMATEL to overcome this shortcoming. Then, the local weights of criteria were estimated using the Best–Worst Method (BWM) to enhance the pairwise comparisons process. Final criteria weights were obtained using Fuzzy DEMATEL and BWM results in Analytical Network Process (ANP) super‐matrix. Finally, the criteria were distributed spatially using the Complex Proportional Assessment of Alternatives (COPRAS) method based on obtained weights. The proposed method was compared with different approaches such as Fuzzy‐DEMATEL ANP, BWM, and AHP using several statistical measures. We concluded that the novel hybrid proposed method outperformed other approaches based on our results. Moreover, by overlaying classified maps with the historical flood events locations, it was concluded that 85.96% of flooded areas were classified as “high” and “very high.”
Keywords: Infolettre; Infolettre_Fevrier_2023

WebFRIS: An efficient web-based decision support tool to disseminate end-to-end risk information for flood management - Mohanty, Mohit Prakash; Karmakar, Subhankar (Journal of Environmental Management, 2021)

Neglecting uncertainties biases house-elevation decisions to manage riverine flood risks - Zarekarizi, Mahkameh; Srikrishnan, Vivek; Keller, Klaus (Nature Communications, 2020)
Abstract Homeowners around the world elevate houses to manage flood risks. Deciding how high to elevate a house poses a nontrivial decision problem. The U.S. Federal Emergency Management Agency (FEMA) recommends elevating existing houses to the Base Flood Elevation (the elevation of the 100-year flood) plus a freeboard. This recommendation neglects many uncertainties. Here we analyze a case-study of riverine flood risk management using a multi-objective robust decision-making framework in the face of deep uncertainties. While the quantitative results are location-specific, the approach and overall insights are generalizable. We find strong interactions between the economic, engineering, and Earth science uncertainties, illustrating the need for expanding on previous integrated analyses to further understand the nature and strength of these connections. Considering deep uncertainties surrounding flood hazards, the discount rate, the house lifetime, and the fragility can increase the economically optimal house elevation to values well above FEMA’s recommendation.
Keywords: Ouvrage_Collectif_Numéro1

From Policy Challenge to Implementation Strategy: Enabling Strategies for Network Governance of Urban Resilience - Therrien, Marie‐Christine; Normandin, Julie‐Maude (Risk, Hazards & Crisis in Public Policy, 2020)
What transformations do municipal administrations implement to enact a resilience policy? This article responds to this question from a comparative perspective by analyzing enabling and impeding mechanisms developed in the cities of Montreal (Canada) and London (UK) as they establish their strategies. Collaborative network governance and institutional work mechanisms used in Montreal and London are analyzed in connection with the influence of macro‐ and micro‐contextual elements under which a network can resiliently manage risk and crises. In both cases, the development of resilience emerges from their emergency management structures, as units in charge try to animate their new area of responsibility through collaborative governance. As a siloed approach this is embedded in daily routines, organizations with limited resources focused on shared motivation and values, collaboration across organizational boundaries and creation of joint capacity to implement resilience. This transformative process concerns the organization in charge of resilience in the municipal administration and the wider network that they build and animate. , 从政策挑战到落实战略: 为都市韧性网络管理创造战略 自治政府为颁布一项韧性政策会经历哪些转型?本文透过比较视角, 通过分析蒙特利尔(加拿大)和伦敦(英国)在建立各自战略时开发的推动机制和阻碍机制, 对该疑问进行了回应。分析了蒙特利尔和伦敦所使用的协作网络治理及机构工作机制与“宏观和微观情境元素的影响”之间的关系, 在这些情境元素中网络能发挥韧性管理风险和危机。在这两个案例中, 当应急管理结构中各主管单位试图通过协作治理开启新的责任区时, 韧性便得以发展。作为一项孤立的措施, 其被应用于日常活动中、应用于在共享动机和价值观方面资源有限的机构中、还被用于跨组织界限的协作以及为发挥韧性而创造的共同行动。该转型过程与负责自治政府韧性建设的机构有关, 还与后者建立和推动的更广网络有关。 , Del desafío político a la estrategia de implementación: estrategias habilitantes para la gobernanza de la red de resiliencia urbana ¿Qué transformaciones implementan las administraciones municipales para promulgar una política de resiliencia? Este artículo responde a esta pregunta desde una perspectiva comparativa analizando los mecanismos habilitadores e impedidores desarrollados en las ciudades de Montreal (Canadá) y Londres (Reino Unido) a medida que establecen sus estrategias. La gobernanza de la red colaborativa y los mecanismos de trabajo institucional utilizados en Montreal y Londres se analizan en relación con la influencia de elementos macro y micro contextuales bajo los cuales una red puede gestionar de manera resiliente los riesgos y las crisis. En ambos casos, el desarrollo de la resiliencia surge de sus estructuras de gestión de emergencias, ya que las unidades a cargo intentan animar su nueva área de responsabilidad a través de la gobernanza colaborativa. Como un enfoque aislado, esto se integra en las rutinas diarias, las organizaciones con recursos limitados se centraron en la motivación y los valores compartidos, la colaboración a través de los límites de la organización y la creación de capacidad conjunta para implementar la resiliencia. Este proceso transformador concierne a la organización a cargo de la resiliencia en la administración municipal y la red más amplia que construyen y animan.

Optimal pricing strategy in the closed-loop supply chain using game theory under government subsidy scenario: A case study - Dehghani Sadrabadi, Mohammad Hossein; Makui, Ahmad; Ghousi, Rouzbeh; Jabbarzadeh, Armin (Journal of Energy Storage, 2024)

Fully integrating probabilistic flood forecasts into the decision-making process across southern Quebec, Canada: some factors to consider - Jean, Valérie; Boucher, Marie-Amélie; Frini, Anissa; Roussel, Dominic (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2023)
Keywords: Infolettre; Infolettre_Septembre_2023

Triggers, Traps, and Disconnect: How Governance Obstacles Hinder Progress on Grand Challenges - Couture, Fannie; Jarzabkowski, Paula; Lê, Jane K. (Academy of Management Journal, 2023)

Imported Project Management Practices in Developing Countries: The Problem of Insufficient Adaptation to Local Project Governance Systems in the Construction Sector - Lizarralde, Gonzalo; Páez, Holmes; Herazo, Benjamin (Domain-Specific Bodies of Knowledge in Project Management, 2023)
Keywords: Lizarralde_Gonzalo

Improving flood resilience through governance strategies: Gauging the state of the art - Matczak, Piotr; Hegger, Dries (WIREs Water, 2021)
Abstract There has been an upsurge in studies of flood risk governance (FRG): steering and decision‐making by public and private actors as a complement to risk assessments and technical management options. The scholarly debate is, however, highly fragmented, complicating the production of cumulative insights. To address this knowledge gap, we used six governance strategies for achieving flood resilience that previously have been put forward as a conceptual framework to review 121 articles published between 2016 and 2019, complemented with insights contained in recent overview articles, to gauge the state‐of‐the‐art in FRG literature: to (a) diversify flood risk management strategies; (b) align the strategies; (c) adequately involve private actors, including citizens; (d) put an adequate rule system in place; (e) cater for sufficient monetary and non‐monetary resources; (f) inspire an open and inclusive normative debate. We found, first, that literature is producing insights on increasingly technically advanced risk assessments and agent‐based models but societal debate on justice in flood risk governance is getting attention. A clearly emerging topic is that of citizen engagement in flood risk governance. Second, the geographical focus of the studies is still skewed toward the Global North. To make progress in understanding flood risk governance for better resilience more systematic and comparative empirical assessments of flood risk governance in order to derive generalizable lessons while better taking into account the context‐specificity of FRG. Testing flood risk governance solutions against comparative cases, by balancing the geographical scope of research efforts, and enhancing interdisciplinary and transdisciplinary working is a way to deliver knowledge for more resilience. This article is categorized under: Human Water > Water Governance Engineering Water > Planning Water
Keywords: Ouvrage_Collectif_Numéro1

Governance of flood risk data: A comparative analysis of government and insurance geospatial data for identifying properties at risk of flood - Minano, A.; Thistlethwaite, J.; Henstra, D.; Scott, D. (Computers, Environment and Urban Systems, 2021)
Keywords: Ouvrage_Collectif_Numéro1

Scoping review: understanding the barriers and drivers of risk management in local governments - Bourgeois, Eve; Baril, Pierre-Luc; Normandin, Julie-Maude; Therrien, Marie-Christine (International Journal of Disaster Resilience in the Built Environment, 2023)
Purpose This paper aims to provide scholars with a deep understanding of the field through the identification of strengths and weaknesses in the literature and support decision-makers in the development of new practices in local risk management based on scientific data. The specific question in this review asks: what are the drivers and barriers to local risk management? Design/methodology/approach This paper provides an overview of the scientific literature produce over the past 20 years of the divers and barriers to local risk management. This paper presents a scoping review of peer-reviewed articles published between 2000 and 2019 inclusively in the fields of public policy and public administration. Findings This paper makes three main observations regarding the state of the literature. First, this paper finds that scholars mainly focus on single risk and certain regions of the world. Second, there is multiple approached used by the literature to study risk management at the local level. Third, little attention is given to the political context in which local risk management takes place. Originality/value This paper is a complete literature review of more than 500 peer-reviewed articles published in academic journals regarding risk prevention policies over the past two decades. This paper analyzed the main findings of the current literature to provide a general view of the scholarship and improve the collective understanding of risk management at the local level by providing future research avenues.
Keywords: Infolettre; Infolettre_Mars_2023

Inside the black box of collaboration: a process-tracing study of collaborative flood risk governance in the Netherlands - Avoyan, Emma (Journal of Environmental Policy & Planning, 2022)
Keywords: Ouvrage_Collectif_Numéro1

Incorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment - Azareh, Ali; Rafiei Sardooi, Elham; Choubin, Bahram; Barkhori, Saeed; Shahdadi, Ali; Adamowski, Jan; Shamshirband, Shahaboddin (Geocarto International, 2021)
Keywords: Site_internet_RIISQ

Démarche de gouvernance collaborative d'appréciation des risques des systèmes essentiels - Baril, G.; Hémond, Y.; Lépine, C.; Préval, J.; Robert, B.; Therrien, M.-C. (2020)
schéma de couverture de risques et schéma d’aménagement et de développement), visant à développer de manière concertée avec les municipalités locales une vision commune et une planification conjointe, la MRC est la structure administrative qui, dans le cadre de l’appréciation des risques des SE, pourrait intégrer les principes de gouvernance multiniveau et de gouvernance horizontale. [...] 3.1.5 Le suivi et la révision Un système de suivi avec des indicateurs de performance doit être mis en place dans le but de valider toutes les étapes du processus de gestion des risques, la justesse des évaluations et des priorités établies ainsi que l’efficacité des mesures implantées et l’atteinte des objectifs fixés. [...] La composante "planification" correspond à l’élaboration de plans de mesures d’urgence, de plans de continuité des opérations et de plans de sécurité des actifs établis à l’issue des processus de gestion des risques. [...] Ce cadre théorique fait écho à l’approche globale et intégrée de la sécurité civile du Ministère de la sécurité publique qui repose sur trois principes « la prise en compte de tous les aléas, l’adoption de mesures couvrant les quatre dimensions de la sécurité ́civile et des actions concertées de tous les acteurs à tous les niveaux. [...] 32 Figure 1 - Extrait de la base de données de la MRC d’Argenteuil Figure 2 - Extrait de la base de données de la MRC de Brome-Missisquoi Fait saillant Malgré une bonne connaissance de son territoire par la MRC, la contribution des municipalités locales est fondamentale pour assurer un inventaire détaillé des SE.
Keywords: Hémond_Yannick

Governance for Flood Risk Reduction: Assessing Quebec’s Special Planning Zone Approach to Landowner Compensations and Restricted Redevelopment - Bornstein, L.; Merkoukhina, K. (2020)

Limited progress in global reduction of vulnerability to flood impacts over the past two decades - Sauer, Inga J.; Mester, Benedikt; Frieler, Katja; Zimmermann, Sandra; Schewe, Jacob; Otto, Christian (Communications Earth & Environment, 2024)
Abstract Global flood impacts have risen in recent decades. While increasing exposure was the dominant driver of surging impacts, counteracting vulnerability reductions have been detected, but were too weak to reverse this trend. To assess the ongoing progress on vulnerability reduction, we combine a recently available dataset of flooded areas derived from satellite imagery for 913 events with four global disaster databases and socio-economic data. Event-specific flood vulnerabilities for assets, fatalities and displacements reveal a lack of progress in reducing global flood vulnerability from 2000—2018. We examine the relationship between vulnerabilities and human development, inequality, flood exposure and local structural characteristics. We find that vulnerability levels are significantly lower in areas with good structural characteristics and significantly higher in low developed areas. However, socio-economic development was insufficient to reduce vulnerabilities over the study period. Nevertheless, the strong correlation between vulnerability and structural characteristics suggests further potential for adaptation through vulnerability reduction.

Methodological approach for mapping the flood physical vulnerability index with geographical open-source data: an example in a small-middle city (Ponferrada, Spain) - Tascón-González, Laura; Ferrer-Julià, Montserrat; García-Meléndez, Eduardo (Natural Hazards, 2024)
Abstract To increase the resilience of communities against floods, it is necessary to develop methodologies to estimate the vulnerability. The concept of vulnerability is multidimensional, but most flood vulnerability studies have focused only on the social approach. Nevertheless, in recent years, following seismic analysis, the physical point of view has increased its relevance. Therefore, the present study proposes a methodology to map the flood physical vulnerability and applies it using an index at urban parcel scale for a medium-sized town (Ponferrada, Spain). This index is based on multiple indicators fed by geographical open-source data, once they have been normalized and combined with different weights extracted from an Analytic Hierarchic Process. The results show a raster map of the physical vulnerability index that facilitates future emergency and flood risk management to diminish potential damages. A total of 22.7% of the urban parcels in the studied town present an index value higher than 0.4, which is considered highly vulnerable. The location of these urban parcels would have passed unnoticed without the use of open governmental datasets, when an average value would have been calculated for the overall municipality. Moreover, the building percentage covered by water was the most influential indicator in the study area, where the simulated flood was generated by an alleged dam break. The study exceeds the spatial constraints of collecting this type of data by direct interviews with inhabitants and allows for working with larger areas, identifying the physical buildings and infrastructure differences among the urban parcels.

The Hazards of Mainstreaming: Climate change adaptation politics in three dimensions - Scoville-Simonds, Morgan; Jamali, Hameed; Hufty, Marc (World Development, 2020)

An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”) - Reimann, Lena; Koks, Elco; De Moel, Hans; Ton, Marijn J.; Aerts, Jeroen C. J. H. (Earth's Future, 2024)
Abstract Fatalities caused by natural hazards are driven not only by population exposure, but also by their vulnerability to these events, determined by intersecting characteristics such as education, age and income. Empirical evidence of the drivers of social vulnerability, however, is limited due to a lack of relevant data, in particular on a global scale. Consequently, existing global‐scale risk assessments rarely account for social vulnerability. To address this gap, we estimate regression models that predict fatalities caused by past flooding events ( n = 913) based on potential social vulnerability drivers. Analyzing 47 variables calculated from publicly available spatial data sets, we establish five statistically significant vulnerability variables: mean years of schooling; share of elderly; gender income gap; rural settlements; and walking time to nearest healthcare facility. We use the regression coefficients as weights to calculate the “ Glob al‐ E mpirical So cial V ulnerability I ndex (GlobE‐SoVI)” at a spatial resolution of ∼1 km. We find distinct spatial patterns of vulnerability within and across countries, with low GlobE‐SoVI scores (i.e., 1–2) in for example, Northern America, northern Europe, and Australia; and high scores (i.e., 9–10) in for example, northern Africa, the Middle East, and southern Asia. Globally, education has the highest relative contribution to vulnerability (roughly 58%), acting as a driver that reduces vulnerability; all other drivers increase vulnerability, with the gender income gap contributing ∼24% and the elderly another 11%. Due to its empirical foundation, the GlobE‐SoVI advances our understanding of social vulnerability drivers at global scale and can be used for global (flood) risk assessments. , Plain Language Summary Social vulnerability is rarely accounted for in global‐scale risk assessments. We develop an empirical social vulnerability map (“GlobE‐SoVI”) based on five key drivers of social vulnerability to flooding, that is, education, elderly, income inequality, rural settlements and travel time to healthcare, which we establish based on flood fatalities caused by past flooding events. Globally, we find education to have a high and reducing effect on social vulnerability, while all other drivers increase vulnerability. Integrating social vulnerability in global‐scale (flood) risk assessments can help inform global policy frameworks that aim to reduce risks posed by natural hazards and climate change as well as to foster more equitable development globally. , Key Points We develop a global map of social vulnerability at ∼1 km spatial resolution based on five key vulnerability drivers (“GlobE‐SoVI”) We establish vulnerability drivers empirically based on their contribution to predicting fatalities caused by past flooding events Accounting for social vulnerability in global‐scale (flood) risk assessments can inform global policy frameworks that aim to reduce risk

Reclassifying historical disasters: From single to multi-hazards - Lee, Ryan; White, Christopher J.; Adnan, Mohammed Sarfaraz Gani; Douglas, John; Mahecha, Miguel D.; O'Loughlin, Fiachra E.; Patelli, Edoardo; Ramos, Alexandre M.; Roberts, Matthew J.; Martius, Olivia; Tubaldi, Enrico; Van Den Hurk, Bart; et al. (Science of The Total Environment, 2024)

Assessing the vulnerability of urban drinking water intakes to water scarcity under global change: A bottom-up approach - Leveque, Baptiste; Irakiza Shyaka, Albert; Ndong, Mouhamed; Jalbert, Jonathan; Burnet, Jean-Baptiste; Kammoun, Raja; Dorner, Sarah; Bichai, Françoise (Environmental Challenges, 2024)
Keywords: Dorner_Sarah

Comparing spatially explicit approaches to assess social vulnerability dynamics to flooding - Meijer, L.G.; Reimann, L.; Aerts, J.C.J.H. (International Journal of Disaster Risk Reduction, 2023)

Impact of climate change on the vulnerability of drinking water intakes in a northern region - Leveque, B.; Burnet, J.-B.; Dorner, S.; Bichai, F. (Sustainable Cities and Society, 2021)
Keywords: Dorner_Sarah

Flood hazards, environmental rewards, and the social reproduction of risk - Oulahen, Greg (Geoforum, 2021)

Development of a damage simulator for probabilistic seismic vulnerability assessment of electrical installations - Hosseinpour, Vahid; Saeidi, Ali; Nastev, Miroslav; Nollet, Marie-José (International Journal of Disaster Risk Reduction, 2025)

A random forest machine learning model to detect fluvial hazards - Gava, Marco; Biron, Pascale M.; Buffin‐Bélanger, Thomas (River Research and Applications, 2024)
Abstract Fluvial hazards of river mobility and flooding are often problematic for road infrastructure and need to be considered in the planning process. The extent of river and road infrastructure networks and their tendency to be close to each other creates a need to be able to identify the most dangerous areas quickly and cost‐effectively. In this study, we propose a novel methodology using random forest (RF) machine learning methods to provide easily interpretable fine‐scale fluvial hazard predictions for large river systems. The tools developed provide predictions for three models: presence of flooding (PFM), presence of mobility (PMM) and type of erosion model (TEM, lateral migration, or incision) at reference points every 100 m along the fluvial network of three watersheds within the province of Quebec, Canada. The RF models use variables focused on river conditions and hydrogeomorphological processes such as confinement, sinuosity, and upstream slope. Training/validation data included field observations, results from hydraulic and erosion models, government infrastructure databases, and hydro‐ geomorphological assessments using 1‐m DEM and satellite/historical imagery. A total of 1807 reference points were classified for flooding, 1542 for mobility, and 847 for the type of erosion out of the 11,452 reference points for the 1145 km of rivers included in the study. These were divided into training (75%) and validation (25%) datasets, with the training dataset used to train supervised RF models. The validation dataset indicated the models were capable of accurately predicting the potential for fluvial hazards to occur, with precision results for the three models ranging from 83% to 94% of points accurately predicted. The results of this study suggest that RF models are a cost‐effective tool to quickly evaluate the potential for fluvial hazards to occur at the watershed scale.
Keywords: Infolettre; Infolettre_Septembre_2024

Integrating social vulnerability into high-resolution global flood risk mapping - Fox, Sean; Agyemang, Felix; Hawker, Laurence; Neal, Jeffrey (Nature Communications, 2024)
Abstract High-resolution global flood risk maps are increasingly used to inform disaster risk planning and response, particularly in lower income countries with limited data or capacity. However, current approaches do not adequately account for spatial variation in social vulnerability, which is a key determinant of variation in outcomes for exposed populations. Here we integrate annual average exceedance probability estimates from a high-resolution fluvial flood model with gridded population and poverty data to create a global vulnerability-adjusted risk index for flooding (VARI Flood) at 90-meter resolution. The index provides estimates of relative risk within or between countries and changes how we understand the geography of risk by identifying ‘hotspots’ characterised by high population density and high levels of social vulnerability. This approach, which emphasises risks to human well-being, could be used as a complement to traditional population or asset-centred approaches.

On mapping urban community resilience: Land use vulnerability, coping and adaptive strategies in Ghana - Ibrahim, Abdul-Salam; Kuuire, Vincent; Kepe, Thembela (Journal of Environmental Management, 2024)

Declining vulnerability but rising impacts: the trends of climatic disasters in Nepal - Chapagain, Dipesh; Bharati, Luna; Borgemeister, Christian (Regional Environmental Change, 2022)
Abstract The impacts of climatic disasters have been rising globally. Several studies argue that this upward trend is due to rapid growth in the population and wealth exposed to disasters. Others argue that rising extreme weather events due to anthropogenic climate change are responsible for the increase. Hence, the causes of the increase in disaster impacts remain elusive. Disaster impacts relative to income are higher in low-income countries, but existing studies are mostly from developed countries or at the cross-country level. Here we assess the spatiotemporal trends of climatic disaster impacts and vulnerability and their attribution to climatic and socioeconomic factors at the subnational scale in a low-income country, using Nepal as a case study. Loss of life is the most extreme consequence of disasters. Therefore, we employed human mortality as a measure of disaster impacts, and mortality normalized by exposed population as a measure of human vulnerability. We found that climatic disaster frequency and mortality increased in Nepal from 1992 to 2021. However, vulnerability decreased, most likely due to economic growth and progress in disaster risk reduction and climate change adaptation. Disaster mortality is positively correlated with disaster frequency and negatively correlated with per capita income but is not correlated with the exposed population. Hence, population growth may not have caused the rise in disaster mortality in Nepal. The strong rise in disaster incidence, potentially due to climate change, has overcome the effect of decreasing vulnerability and caused the rise in disaster mortality.

Leveraging Hazard, Exposure, and Social Vulnerability Data to Assess Flood Risk to Indigenous Communities in Canada - Chakraborty, Liton; Thistlethwaite, Jason; Minano, Andrea; Henstra, Daniel; Scott, Daniel (International Journal of Disaster Risk Science, 2021)
Abstract This study integrates novel data on 100-year flood hazard extents, exposure of residential properties, and place-based social vulnerability to comprehensively assess and compare flood risk between Indigenous communities living on 985 reserve lands and other Canadian communities across 3701 census subdivisions. National-scale exposure of residential properties to fluvial, pluvial, and coastal flooding was estimated at the 100-year return period. A social vulnerability index (SVI) was developed and included 49 variables from the national census that represent demographic, social, economic, cultural, and infrastructure/community indicators of vulnerability. Geographic information system-based bivariate choropleth mapping of the composite SVI scores and of flood exposure of residential properties and population was completed to assess the spatial variation of flood risk. We found that about 81% of the 985 Indigenous land reserves had some flood exposure that impacted either population or residential properties. Our analysis indicates that residential property-level flood exposure is similar between non-Indigenous and Indigenous communities, but socioeconomic vulnerability is higher on reserve lands, which confirms that the overall risk of Indigenous communities is higher. Findings suggest the need for more local verification of flood risk in Indigenous communities to address uncertainty in national scale analysis.

Environmental vulnerability and resilience: Social differentiation in short‐ and long‐term flood impacts - Houston, Donald; Werritty, Alan; Ball, Tom; Black, Andrew (Transactions of the Institute of British Geographers, 2021)
This paper finds that social differentiation in flood impacts is relatively small soon after a flood, with some surprising results such as professionals and homeowners badly affected in the short‐term – but widens over time, with socially disadvantaged groups displaying less recovery. The paper concludes that vulnerability and resilience to flooding are sensitive to financial resources, institutional support (chiefly from a landlord), and capacity to deal with disruption (chiefly time availability, which is low among professionals and high among retired people). An implication of these findings is that existing indices of flood vulnerability that use multiple measures of social deprivation should be used with caution, as not all conventional aspects of social deprivation are necessarily associated with greater vulnerability to flood impacts. , This paper reports household questionnaire survey results on vulnerability and resilience to flooding from one of the largest and most representative samples ( n = 593) of households up to 12 years after they were flooded, and is one of the first to provide detailed analysis of social differentiation in long‐term flood impacts. A novel finding is that social differentiation in flood impacts is relatively small soon after a flood, but widens over time, with socially disadvantaged groups displaying less recovery. The patterns of social differentiation in vulnerability and resilience to flooding differ markedly according to the type and timescale of the impact, with some normally socially advantaged groups (e.g., professionals and homeowners) being most vulnerable to short‐term impacts. Consistent with some existing studies, we found that older residents (age 70+) have greater resilience to flood impacts, although our sample may not capture the frailest individuals. As in previous research, low income is linked to lower resilience, particularly in the long term. We find that prior experience of flooding, despite enhancing preparedness, overall erodes rather than enhances resilience to flooding. Flood warnings are effective at reducing vulnerability to short‐term impacts. Underlying influences on resilience to natural disasters are complex and may only be revealed by multivariate analysis and not always be evident in simple observed patterns. The paper concludes that vulnerability and resilience to flooding are sensitive to financial resources, institutional support (chiefly from a landlord), and capacity to deal with disruption (chiefly time availability, which is low among professionals and high among retired people). An implication of these findings is that existing indices of flood vulnerability that use multiple measures of social deprivation should be used with caution, as not all conventional aspects of social deprivation are necessarily associated with greater vulnerability to flood impacts.

Exploring spatial heterogeneity and environmental injustices in exposure to flood hazards using geographically weighted regression - Chakraborty, Liton; Rus, Horatiu; Henstra, Daniel; Thistlethwaite, Jason; Minano, Andrea; Scott, Daniel (Environmental Research, 2022)

Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models - Barzegar, Rahim; Razzagh, Siamak; Quilty, John; Adamowski, Jan; Kheyrollah Pour, Homa; Booij, Martijn J. (Journal of Hydrology, 2021)

Understanding compound hazards from a weather system perspective - Catto, Jennifer L.; Dowdy, Andrew (Weather and Climate Extremes, 2021)
Keywords: Ouvrage_Collectif_Numéro1

Modification of the DRASTIC Framework for Mapping Groundwater Vulnerability Zones - Barzegar, Rahim; Asghari Moghaddam, Asghar; Norallahi, Shahrokh; Inam, Azhar; Adamowski, Jan; Alizadeh, Mohammad Reza; Bou Nassar, Jessica (Groundwater, 2020)
Abstract The DRASTIC technique is commonly used to assess groundwater vulnerability. The main disadvantage of the DRASTIC method is the difficulty associated with identifying appropriate ratings and weight assignments for each parameter. To mitigate this issue, ratings and weights can be approximated using different methods appropriate to the conditions of the study area. In this study, different linear (i.e., Wilcoxon test and statistical approaches) and nonlinear (Genetic algorithm [GA]) modifications for calibration of the DRASTIC framework using nitrate (NO 3 ) concentrations were compared through the preparation of groundwater vulnerability maps of the Meshqin‐Shahr plain, Iran. Twenty‐two groundwater samples were collected from wells in the study area, and their respective NO 3 concentrations were used to modify the ratings and weights of the DRASTIC parameters. The areas found to have the highest vulnerability were in the eastern, central, and western regions of the plain. Results showed that the modified DRASTIC frameworks performed well, compared to the unmodified DRASTIC. When measured NO 3 concentrations were correlated with the vulnerability indices produced by each method, the unmodified DRASTIC method performed most poorly, and the Wilcoxon–GA–DRASTIC method proved optimal. Compared to the unmodified DRASTIC method with an R 2 of 0.22, the Wilcoxon–GA–DRASTIC obtained a maximum R 2 value of 0.78. Modification of DRASTIC parameter ratings was found to be more efficient than the modification of the weights in establishing an accurately calibrated DRASTIC framework. However, modification of parameter ratings and weights together increased the R 2 value to the highest degree. , Article impact statement : The results showed that both linear and nonlinear methods are useful in modifying the ratings and weights of the DRASTIC method for assessing the groundwater vulnerability.

A place-based socioeconomic status index: Measuring social vulnerability to flood hazards in the context of environmental justice - Chakraborty, Liton; Rus, Horatiu; Henstra, Daniel; Thistlethwaite, Jason; Scott, Daniel (International Journal of Disaster Risk Reduction, 2020)
Keywords: Ouvrage_Collectif_Numéro1