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

Inondations: pourra-t-on faire mieux la prochaine fois? - Maltais, Danielle; Gachon, Philippe; King, Suzanne; Raphoz, Marie; Ouarda, Taha (The Conversation, 2019)
Les inondations causent de lourds dommages tant économiques, sociaux qu'environnementaux, en plus d'avoir des effets sur la santé physique et psychologique des sinistrés.

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

Influence of PDO and ENSO on Annual Flood Frequency of the Canadian Prairie Rivers - Gurrapu, Sunil; Jeannine-Marie St. Jacques; Sauchyn, David J.; Hodder, Kyle R. (2014)
Publisher: Unpublished

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.

New Sensitivity Indices of a 2D Flood Inundation Model Using Gauss Quadrature Sampling - Oubennaceur, Khalid; Chokmani, Karem; Nastev, Miroslav; Gauthier, Yves; Poulin, Jimmy; Tanguy, Marion; Raymond, Sebastien; Lhissou, Rachid (Geosciences, 2019)
A new method for sensitivity analysis of water depths is presented based on a two-dimensional hydraulic model as a convenient and cost-effective alternative to Monte Carlo simulations. The method involves perturbation of the probability distribution of input variables. A relative sensitivity index is calculated for each variable, using the Gauss quadrature sampling, thus limiting the number of runs of the hydraulic model. The variable-related highest variation of the expected water depths is considered to be the most influential. The proposed method proved particularly efficient, requiring less information to describe model inputs and fewer model executions to calculate the sensitivity index. It was tested over a 45 km long reach of the Richelieu River, Canada. A 2D hydraulic model was used to solve the shallow water equations (SWE). Three input variables were considered: Flow rate, Manning’s coefficient, and topography of a shoal within the considered reach. Four flow scenarios were simulated with discharge rates of 759, 824, 936, and 1113 m 3 / s . The results show that the predicted water depths were most sensitive to the topography of the shoal, whereas the sensitivity indices of Manning’s coefficient and the flow rate were comparatively lower. These results are important for making better hydraulic models, taking into account the sensitivity analysis.
Number: 5 Publisher: Multidisciplinary Digital Publishing Institute

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.

Using the CAUSE Model to Understand Public Communication about Water Risks: Perspectives from Texas Groundwater District Officials on Drought and Availability - VanDyke, Matthew S.; King, Andy J. (Risk Analysis, 2018)
Abstract Public communication about drought and water availability risks poses challenges to a potentially disinterested public. Water management professionals, though, have a responsibility to work with the public to engage in communication about water and environmental risks. Because limited research in water management examines organizational communication practices and perceptions, insights into research and practice can be gained through investigation of current applications of these risk communication efforts. Guided by the CAUSE model, which explains common goals in communicating risk information to the public (e.g., creating Confidence, generating Awareness, enhancing Understanding, gaining Satisfaction, and motivating Enactment), semistructured interviews of professionals ( N = 25) employed by Texas groundwater conservation districts were conducted. The interviews examined how CAUSE model considerations factor in to communication about drought and water availability risks. These data suggest that many work to build constituents’ confidence in their districts. Although audiences and constituents living in drought‐prone areas were reported as being engaged with water availability risks and solutions, many district officials noted constituents’ lack of perceived risk and engagement. Some managers also indicated that public understanding was a secondary concern of their primary responsibilities and that the public often seemed apathetic about technical details related to water conservation risks. Overall, results suggest complicated dynamics between officials and the public regarding information access and motivation. The article also outlines extensions of the CAUSE model and implications for improving public communication about drought and water availability risks.

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)

The influence of impact-based severe weather warnings on risk perceptions and intended protective actions - Potter, Sally H.; Kreft, Peter V.; Milojev, Petar; Noble, Chris; Montz, Burrell; Dhellemmes, Amandine; Woods, Richard J.; Gauden-Ing, Sarah (International Journal of Disaster Risk Reduction, 2018)

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)

Trends of ice breakup date in south‐central Ontario - Fu, Congsheng; Yao, Huaxia (Journal of Geophysical Research: Atmospheres, 2015)
Abstract Large‐scale ice phenology studies have revealed overall patterns of later freeze, earlier breakup, and shorter duration of ice in the Northern Hemisphere. However, there have been few studies regarding the trends, including their spatial patterns, in ice phenology for individual waterbodies on a local or small regional scale, although the coherence of ice phenology has been shown to decline rapidly in the first few hundred kilometers. In this study, we extracted trends, analyzed affecting factors, and investigated relevant spatial patterns for ice breakup date time series at 10 locations with record length ≥90 years in south‐central Ontario, Canada. Wavelet methods, including the multiresolution analysis (MRA) method for nonlinear trend extraction and the wavelet coherence (WTC) method for identifying the teleconnections between large‐scale climate modes and ice breakup date, are proved to be effective in ice phenology analysis. Using MRA method, the overall trend of ice breakup date time series (1905–1991) varied from earlier ice breakup to later ice breakup, then to earlier breakup again from south to north in south‐central Ontario. Ice breakup date is closely correlated with air temperature during certain winter/spring months, as well as the last day with snow on the ground and number of snow‐on‐ground days. The influences of solar activity and Pacific North American on ice breakup were comparatively uniform across south‐central Ontario, while those of El Niño–Southern Oscillation, North Atlantic Oscillation, and Arctic Oscillation on ice phenology changed with distance of 50–100 km in the north‐south direction. , Key Points Wavelet methods are effective in ice phenology analysis in south‐central Ontario Coherence of ice breakup changes with distance of 50–100 km from south to north Ice breakup in Ontario is affected by solar activity, ENSO, PNA, NAO, and AO

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)

Modeling sustainability visions: A case study of multi-scale food systems in Southwestern Ontario - Halbe, Johannes; Adamowski, Jan (Journal of Environmental Management, 2019)

Quantile-based downscaling of rainfall extremes: Notes on methodological functionality, associated uncertainty and application in practice - Hassanzadeh, Elmira; Nazemi, Ali; Adamowski, Jan; Nguyen, Truong-Huy; Van-Nguyen, Van-Thanh (Advances in Water Resources, 2019)

Hydrological dynamics of prairie pothole wetlands: Dominant processes and landscape controls under contrasted conditions - Haque, Aminul; Ali, Genevieve; Badiou, Pascal (Hydrological Processes, 2018)
Abstract Numerous studies have examined the impact of prairie pothole wetlands on overall watershed dynamics. However, very few have looked at individual wetland dynamics across a continuum of alteration status using subdaily hydrometric data. Here, the importance of surface and subsurface water storage dynamics in the prairie pothole region was documented by (1) characterizing surface fill–spill dynamics in intact and consolidated wetlands; (2) quantifying water‐table fluctuations and the occurrence of overland flow downslope of fully drained wetlands; (3) assessing the relation (or lack thereof) between intact, consolidated or drained wetland hydrological behaviour, and stream dynamics; and (4) relating wetland hydrological behaviour to landscape characteristics. Focus was on southwestern Manitoba, Canada, where ten intact, three consolidated, seven fully drained wetlands, and a nearby creek were monitored over two years with differing antecedent storage conditions. Hourly hydrological time series were used to compute behavioural metrics reflective of year‐specific and season‐specific wetland dynamics. Behavioural metrics were then correlated to wetland physical characteristics to identify landscape controls on wetland hydrology. Predictably, more frequent spillage or overland flow was observed when antecedent storage was high. Consolidated wetlands had a high degree of water permanence and a greater frequency of fill–spill events than intact wetlands. Shallow and highly responsive water tables were present downslope of fully drained wetlands. Potential wetland–stream connectivity was also inferred via time‐series analysis, while some landscape characteristics (e.g., wetland surface, catchment area, and storage volume) strongly correlated with wetland behavioural metrics. The nonstationarity of dominant processes was, however, evident through the lack of consistent correlations across seasons. This, therefore, highlights the importance of combining multiyear high‐frequency hydrometric data and detailed landscape analyses in wetland hydrology studies.

The Suburban Origins of Redlining: A Canadian Case Study, 1935-54 - Harris, Richard; Forrester, Doris (Urban Studies, 2003)
Redlining occurs when institutions decline to make mortgage loans in specific areas. The practice originated in the 1930s, when federal agencies encouraged lenders to rate neighbourhoods for mortgage risk. Since the 1960s, especially in the US, it has been associated with disinvestment, racial discrimination and neighbourhood decline. It has always been viewed as a feature of the inner city. Historical evidence indicates that across Canada the first areas to be redlined were the less-desirable suburbs. Land registry and property assessment data establish the emergent patterns in Hamilton, Ontario. Between 1931 and 1951, institutional lending became a social norm first on new dwellings in suburbs. Individual lenders, previously dominant, were relegated to older inner-city properties or cheaper dwellings in less-desirable suburbs. In 1931, there were only minor geographical variations in the incidence of mortgage finance, and specifically of institutional financing, across the urban area. By 1951, lending institutions, led by insurance companies, were discriminating sharply in favour of the West End, the Mountain and Bartonville, and against those parts of the East End that were unserviced or close to lakefront industry. The evidence for Hamilton confirms that in Canada redlining originated in the suburbs. The same may also be true for US metropolitan areas, although the institutional context was different and relevant data are lacking.

Serious Games as Planning Support Systems: Learning from Playing Maritime Spatial Planning Challenge 2050 - Jean, Steven; Gilbert, Laura; Medema, Wietske; Keijser, Xander; Mayer, Igor; Inam, Azhar; Adamowski, Jan (Water, 2018)
The inherent complexity of planning at sea, called maritime spatial planning (MSP), requires a planning approach where science (data and evidence) and stakeholders (their engagement and involvement) are integrated throughout the planning process. An increasing number of innovative planning support systems (PSS) in terrestrial planning incorporate scientific models and data into multi-player digital game platforms with an element of role-play. However, maritime PSS are still early in their innovation curve, and the use and usefulness of existing tools still needs to be demonstrated. Therefore, the authors investigate the serious game, MSP Challenge 2050, for its potential use as an innovative maritime PSS and present the results of three case studies on participant learning in sessions of game events held in Newfoundland, Venice, and Copenhagen. This paper focusses on the added values of MSP Challenge 2050, specifically at the individual, group, and outcome levels, through the promotion of the knowledge co-creation cycle. During the three game events, data was collected through participant surveys. Additionally, participants of the Newfoundland event were audiovisually recorded to perform an interaction analysis. Results from survey answers and the interaction analysis provide evidence that MSP Challenge 2050 succeeds at the promotion of group and individual learning by translating complex information to players and creating a forum wherein participants can share their thoughts and perspectives all the while (co-) creating new types of knowledge. Overall, MSP Challenge and serious games in general represent promising tools that can be used to facilitate the MSP process.

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)

A statistical approach for the estimation of water quality characteristics of ungauged streams/watersheds under stationary conditions - Khalil, Bahaa; Adamowski, Jan; Abdin, Alaa; Elsaadi, Aiman (Journal of Hydrology, 2019)

Does rising income increase or decrease damage risk from natural disasters? - Kellenberg, Derek K.; Mobarak, Ahmed Mushfiq (Journal of Urban Economics, 2008)

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.

Population Displacement and Housing Dilemmas Due to Catastrophic Disasters - Levine, Joyce N.; Esnard, Ann-Margaret; Sapat, Alka (Journal of Planning Literature, 2007)
As Hurricane Katrina revealed, coastal communities have become far more vulnerable to tropical storms and the long-term displacement of residents. Yet, because the emergency management model presumes that recovery quickly follows response, governments focus only on short-term, localized displacement. However, long-term and long-distance displacement exposes a gray area between immediate shelter and permanent housing, along with concerns about vulnerability, housing availability, and land development. We begin this article by discussing the transition between response and recovery. We then review literature regarding social vulnerability, displacement, provision of temporary housing, households' return decisions, and disaster-driven land development and housing construction processes. We close with thoughts on future research to increase planners' understanding of the issues involved and to help them craft effective policies.

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.

Evaluating Hydrologic Response in Tile‐Drained Landscapes: Implications for Phosphorus Transport - Macrae, M. L.; Ali, G. A.; King, K. W.; Plach, J. M.; Pluer, W. T.; Williams, M.; Morison, M. Q.; Tang, W. (Journal of Environmental Quality, 2019)
Phosphorus (P) loss in agricultural discharge has typically been associated with surface runoff; however, tile drains have been identified as a key P pathway due to preferential transport. Identifying when and where these pathways are active may establish high‐risk periods and regions that are vulnerable for P loss. A synthesis of high‐frequency, runoff data from eight cropped fields across the Great Lakes region of North America over a 3‐yr period showed that both surface and tile flow occurred year‐round, although tile flow occurred more frequently. The relative timing of surface and tile flow activation was classified into four response types to infer runoff‐generation processes. Response types were found to vary with season and soil texture. In most events across all sites, tile responses preceded surface flow, whereas the occurrence of surface flow prior to tile flow was uncommon. The simultaneous activation of pathways, indicating rapid connectivity through the vadose zone, was seldom observed at the loam sites but occurred at clay sites during spring and summer. Surface flow at the loam sites was often generated as saturation‐excess, a phenomenon rarely observed on the clay sites. Contrary to expectations, significant differences in P loads in tiles were not apparent under the different response types. This may be due to the frequency of the water quality sampling or may indicate that factors other than surface‐tile hydrologic connectivity drive tile P concentrations. This work provides new insight into spatial and temporal differences in runoff mechanisms in tile‐drained landscapes. Core Ideas Activation of surface runoff and tile flow differ with soil texture and season. Timing of flow path activation was used to infer hydrological processes. Connectivity between the surface and tiles exists on clay soil during growing season. Rapid connectivity between the surface and tiles occurs less frequently on loam.

Assessing the potential impacts of dam operation on daily flow at ungauged river reaches - Mailhot, A.; Talbot, G.; Ricard, S.; Turcotte, R.; Guinard, K. (Journal of Hydrology: Regional Studies, 2018)

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)

Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting - Mouatadid, Soukayna; Adamowski, Jan F.; Tiwari, Mukesh K.; Quilty, John M. (Agricultural Water Management, 2019)

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.

A multiscale and multivariate analysis of precipitation and streamflow variability in relation to ENSO, NAO and PDO - Nalley, D.; Adamowski, J.; Biswas, A.; Gharabaghi, B.; Hu, W. (Journal of Hydrology, 2019)

A critical review on the application of the National Sanitation Foundation Water Quality Index - Noori, Roohollah; Berndtsson, Ronny; Hosseinzadeh, Majid; Adamowski, Jan Franklin; Abyaneh, Maryam Rabiee (Environmental Pollution, 2019)

Temporal and depth variation of water quality due to thermal stratification in Karkheh Reservoir, Iran - Noori, Roohollah; Berndtsson, Ronny; Franklin Adamowski, Jan; Rabiee Abyaneh, Maryam (Journal of Hydrology: Regional Studies, 2018)

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

Applying the Theory of Reliability to the Assessment of Hazard, Risk and Safety in a Hydrologic System: A Case Study in the Upper Sola River Catchment, Poland - Ozga-Zielinski, Bogdan; Adamowski, Jan; Ciupak, Maurycy (Water, 2018)

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

An Entropy-Based Approach to Fuzzy Multi-objective Optimization of Reservoir Water Quality Monitoring Networks Considering Uncertainties - Pourshahabi, Shokoufeh; Nikoo, Mohammad Reza; Raei, Ehsan; Adamowski, Jan Franklin (Water Resources Management, 2018)

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)

Forcing the Penman-Montheith Formulation with Humidity, Radiation, and Wind Speed Taken from Reanalyses, for Hydrologic Modeling - Ricard, Simon; Anctil, François (Water, 2019)
The Penman-Monteith reference evapotranspiration (ET0) formulation was forced with humidity, radiation, and wind speed (HRW) fields simulated by four reanalyses in order to simulate hydrologic processes over six mid-sized nivo-pluvial watersheds in southern Quebec, Canada. The resulting simulated hydrologic response is comparable to an empirical ET0 formulation based exclusively on air temperature. However, Penman-Montheith provides a sounder representation of the existing relations between evapotranspiration fluctuations and climate drivers. Correcting HRW fields significantly improves the hydrologic bias over the pluvial period (June to November). The latter did not translate into an increase of the hydrologic performance according to the Kling-Gupta Efficiency (KGE) metric. The suggested approach allows for the implementation of physically-based ET0 formulations where HRW observations are insufficient for the calibration and validation of hydrologic models and a potential reinforcement of the confidence affecting the projection of low flow regimes and water availability.

A Stochastic Data‐Driven Ensemble Forecasting Framework for Water Resources: A Case Study Using Ensemble Members Derived From a Database of Deterministic Wavelet‐Based Models - Quilty, John; Adamowski, Jan; Boucher, Marie‐Amélie (Water Resources Research, 2019)
Abstract In water resources applications (e.g., streamflow, rainfall‐runoff, urban water demand [UWD], etc.), ensemble member selection and ensemble member weighting are two difficult yet important tasks in the development of ensemble forecasting systems. We propose and test a stochastic data‐driven ensemble forecasting framework that uses archived deterministic forecasts as input and results in probabilistic water resources forecasts. In addition to input data and (ensemble) model output uncertainty, the proposed approach integrates both ensemble member selection and weighting uncertainties, using input variable selection and data‐driven methods, respectively. Therefore, it does not require one to perform ensemble member selection and weighting separately. We applied the proposed forecasting framework to a previous real‐world case study in Montreal, Canada, to forecast daily UWD at multiple lead times. Using wavelet‐based forecasts as input data, we develop the Ensemble Wavelet‐Stochastic Data‐Driven Forecasting Framework, the first multiwavelet ensemble stochastic forecasting framework that produces probabilistic forecasts. For the considered case study, several variants of Ensemble Wavelet‐Stochastic Data‐Driven Forecasting Framework, produced using different input variable selection methods (partial correlation input selection and Edgeworth Approximations‐based conditional mutual information) and data‐driven models (multiple linear regression, extreme learning machines, and second‐order Volterra series models), are shown to outperform wavelet‐ and nonwavelet‐based benchmarks, especially during a heat wave (first time studied in the UWD forecasting literature). , Key Points A stochastic data‐driven ensemble framework is introduced for probabilistic water resources forecasting Ensemble member selection and weighting uncertainties are explicitly considered alongside input data and model output uncertainties Wavelet‐based model outputs are used as input to the framework for an urban water demand forecasting study outperforming benchmark methods

Estimates of gridded relative changes in 24-h extreme rainfall intensities based on pooled frequency analysis - Requena, Ana I.; Burn, Donald H.; Coulibaly, Paulin (Journal of Hydrology, 2019)

Addressing the incorrect usage of wavelet-based hydrological and water resources forecasting models for real-world applications with best practices and a new forecasting framework - Quilty, John; Adamowski, Jan (Journal of Hydrology, 2018)

A New Approach to Predict Daily pH in Rivers Based on the “à trous” Redundant Wavelet Transform Algorithm - Rajaee, Taher; Ravansalar, Masoud; Adamowski, Jan F.; Deo, Ravinesh C. (Water, Air, & Soil Pollution, 2018)

Assessing structural, functional and effective hydrologic connectivity with brain neuroscience methods: State-of-the-art and research directions - Rinderer, Michael; Ali, Genevieve; Larsen, Laurel G. (Earth-Science Reviews, 2018)

Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach - Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan (Environmental Research, 2018)

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

Laboratory study of the properties of frazil ice particles and flocs in water of different salinities - Schneck, Christopher C.; Ghobrial, Tadros R.; Loewen, Mark R. (The Cryosphere, 2019)
Abstract. Measurements of the size and shape of frazil ice particles and flocs in saline water and of frazil ice flocs in freshwater are limited. This study consisted of a series of laboratory experiments producing frazil ice at salinities of 0 ‰, 15 ‰, 25 ‰ and 35 ‰ to address this lack of data. The experiments were conducted in a large tank in a cold room with bottom-mounted propellers to create turbulence. A high-resolution camera system was used to capture images of frazil ice particles and flocs passing through cross-polarizing lenses. The high-resolution images of the frazil ice were processed using a computer algorithm to differentiate particles from flocs and determine key properties including size, concentration and volume. The size and volume distributions of particles and flocs at all four salinities were found to fit log-normal distributions closely. The concentration, mean size, and standard deviation of flocs and particles were assessed at different times during the supercooling process to determine how these properties evolve with time. Comparisons were made to determine the effect of salinity on the properties of frazil ice particles and flocs. The overall mean size of frazil ice particles in saline water and freshwater was found to range between 0.52 and 0.45 mm, with particles sizes in freshwater ∼13 % larger than in saline water. However, qualitative observations showed that frazil ice particles in saline water tend to be more irregularly shaped. The overall mean size of flocs in freshwater was 2.57 mm compared to a mean size of 1.47 mm for flocs in saline water. The average growth rate of frazil particles was found to be 0.174, 0.070, 0.033, and 0.024 mm min−1 and the average floc growth rate was 0.408, 0.118, 0.089, and 0.072 mm min−1 for the 0 ‰, 15 ‰, 25 ‰, and 35 ‰, respectively. Estimates for the porosity of frazil ice flocs were made by equating the estimated volume of ice produced based on thermodynamic conditions to the estimated volume of ice determined from the digital images. The estimated porosities of frazil ice flocs were determined to be 0.86, 0.82, 0.8 and 0.75 for 0 ‰, 15 ‰, 25 ‰ and 35 ‰ saline water, respectively.

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)

Roadmap towards justice in urban climate adaptation research - Shi, Linda; Chu, Eric; Anguelovski, Isabelle; Aylett, Alexander; Debats, Jessica; Goh, Kian; Schenk, Todd; Seto, Karen C.; Dodman, David; Roberts, Debra; Roberts, J. Timmons; VanDeveer, Stacy D. (Nature Climate Change, 2016)

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

Groundwater Pollution Sources Apportionment in the Ghaen Plain, Iran - Vesali Naseh, Mohammad; Noori, Roohollah; Berndtsson, Ronny; Adamowski, Jan; Sadatipour, Elaheh (International Journal of Environmental Research and Public Health, 2018)

The Canadian land surface scheme (CLASS): Its history and future - Verseghy, Diana L. (Atmosphere-Ocean, 2000)

Class—A Canadian land surface scheme for GCMS. I. Soil model - Verseghy, Diana L. (International Journal of Climatology, 1991)
Abstract A new GCM land surface scheme is introduced, incorporating three soil layers with physically based calculations of heat and moisture transfers at the surface and across the layer boundaries. Snow‐covered and snow‐free areas are treated separately. The energy balance equation is solved iteratively for the surface temperature; the surface infiltration rate is calculated using a simplified theoretical analysis allowing for surface ponding. Snow cover is modelled as a discrete ‘soil’ layer. The results generated by CLASS are compared with those of an older model incorporating the force‐restore method for the calculation of surface temperature and a bucket‐type formulation for the ground moisture. Several month‐long test runs are carried out in stand‐alone mode. It is shown that the surface temperature in the old scheme responds more slowly to diurnal forcing and more quickly to longer term forcing than that modelled by CLASS, while its one‐layer representation of soil moisture proves incapable of reproducing changes in the surface fluxes owing to surface variations of moisture content. Finally, the lumped treatment of snow and soil in the old scheme results in an extremely fast disappearance of the snow pack under certain conditions.

The Human Cost of Weather Related Disasters - 1995 - 2015 - Wallemacq, Pascaline; Debarati Guha-Sapir; McClean, Denis; CRED; UNISDR (2015)

Delineation of homogeneous regions for regional frequency analysis using statistical depth function - Wazneh, H.; Chebana, F.; Ouarda, T.B.M.J. (Journal of Hydrology, 2015)

Effect of Land Use Change on Soil Carbon Storage over the Last 40 Years in the Shi Yang River Basin, China - Yang, Shurong; Sheng, Danrui; Adamowski, Jan; Gong, Yifan; Zhang, Jian; Cao, Jianjun (Land, 2018)

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)

Analysis of trends in annual streamflow to the Arctic Ocean - Durocher, Martin; Requena, Ana I.; Burn, Donald H.; Pellerin, Jennifer (Hydrological Processes, 2019)
Abstract There is increasing interest in the magnitude of the flow of freshwater to the Arctic Ocean due to its impacts on the biogeophysical and socio‐economic systems in the north and its influence on global climate. This study examines freshwater flow based on a dataset of 72 rivers that either directly or indirectly contribute flow to the Arctic Ocean or reflect the hydrologic regime of areas contributing flow to the Arctic Ocean. Annual streamflow for the 72 rivers is categorized as to the nature and location of the contribution to the Arctic Ocean, and composite series of annual flows are determined for each category for the period 1975 to 2015. A trend analysis is then conducted for the annual discharge series assembled for each category. The results reveal a general increase in freshwater flow to the Arctic Ocean with this increase being more prominent from the Eurasian rivers than from the North American rivers. A comparison with trends obtained from an earlier study ending in 2000 indicates similar trend response from the Eurasian rivers, but dramatic differences from some of the North American rivers. A total annual discharge increase of 8.7 km 3 /y/y is found, with an annual discharge increase of 5.8 km 3 /y/y observed for the rivers directly flowing to the Arctic Ocean. The influence of annual or seasonal climate oscillation indices on annual discharge series is also assessed. Several river categories are found to have significant correlations with the Arctic Oscillation, the North Atlantic Oscillation, or the Pacific Decadal Oscillation. However, no significant association with climate indices is found for the river categories leading to the largest freshwater contribution to the Arctic Ocean.

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

Efficient Implementation of Sampling Stochastic Dynamic Programming Algorithm for Multireservoir Management in the Hydropower Sector - Côté, Pascal; Arsenault, Richard (Journal of Water Resources Planning and Management, 2019)

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)

Correcting Satellite Precipitation Data and Assimilating Satellite-Derived Soil Moisture Data to Generate Ensemble Hydrological Forecasts within the HBV Rainfall-Runoff Model - Ciupak, Maurycy; Ozga-Zielinski, Bogdan; Adamowski, Jan; Deo, Ravinesh C; Kochanek, Krzysztof (Water, 2019)
An implementation of bias correction and data assimilation using the ensemble Kalman filter (EnKF) as a procedure, dynamically coupled with the conceptual rainfall-runoff Hydrologiska Byråns Vattenbalansavdelning (HBV) model, was assessed for the hydrological modeling of seasonal hydrographs. The enhanced HBV model generated ensemble hydrographs and an average stream-flow simulation. The proposed approach was developed to examine the possibility of using data (e.g., precipitation and soil moisture) from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility for Support to Operational Hydrology and Water Management (H-SAF), and to explore its usefulness in improving model updating and forecasting. Data from the Sola mountain catchment in southern Poland between 1 January 2008 and 31 July 2014 were used to calibrate the HBV model, while data from 1 August 2014 to 30 April 2015 were used for validation. A bias correction algorithm for a distribution-derived transformation method was developed by exploring generalized exponential (GE) theoretical distributions, along with gamma (GA) and Weibull (WE) distributions for the different data used in this study. When using the ensemble Kalman filter, the stochastically-generated ensemble of the model states generally induced bias in the estimation of non-linear hydrologic processes, thus influencing the accuracy of the Kalman analysis. In order to reduce the bias produced by the assimilation procedure, a post-processing bias correction (BC) procedure was coupled with the ensemble Kalman filter (EnKF), resulting in an ensemble Kalman filter with bias correction (EnKF-BC). The EnKF-BC, dynamically coupled with the HBV model for the assimilation of the satellite soil moisture observations, improved the accuracy of the simulated hydrographs significantly in the summer season, whereas, a positive effect from bias corrected (BC) satellite precipitation, as forcing data, was observed in the winter. Ensemble forecasts generated from the assimilation procedure are shown to be less uncertain. In future studies, the EnKF-BC algorithm proposed in the current study could be applied to a diverse array of practical forecasting problems (e.g., an operational assimilation of snowpack and snow water equivalent in forecasting models).

Inconsistent linear Trends in Senegalese rainfall data indices from 1950 to 2007. - Comby, Jacques; Sarr, Mamadou (Hydrological Sciences Journal, 2014)

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

Influences of afforestation policies on soil moisture content in China’s arid and semi-arid regions - Cao, Jianjun; Tian, Hong; Adamowski, Jan F.; Zhang, Xiaofang; Cao, Zijian (Land Use Policy, 2018)

Multi-household grazing management pattern maintains better soil fertility - Cao, Jianjun; Xu, Xueyun; Deo, Ravinesh C.; Holden, Nicholas M.; Adamowski, Jan F.; Gong, Yifan; Feng, Qi; Yang, Shurong; Li, Mengtian; Zhou, Junju; Zhang, Jian; Liu, Minxia (Agronomy for Sustainable Development, 2018)

How do hydrogeological setting and meteorological conditions influence water table depth and fluctuations in ombrotrophic peatlands? - Bourgault, Marc-André; Larocque, Marie; Garneau, Michelle (Journal of Hydrology X, 2019)

Relationship between water quality and macro-scale parameters (land use, erosion, geology, and population density) in the Siminehrood River Basin - Bostanmaneshrad, Farshid; Partani, Sadegh; Noori, Roohollah; Nachtnebel, Hans-Peter; Berndtsson, Ronny; Adamowski, Jan Franklin (Science of The Total Environment, 2018)

Three‐dimensional turbulent structures at a medium‐sized confluence with and without an ice cover - Biron, Pascale M.; Buffin‐Bélanger, Thomas; Martel, Nancy (Earth Surface Processes and Landforms, 2019)
Abstract River confluences are characterized by a complex mixing zone with three‐dimensional (3D) turbulent structures which have been described as both streamwise‐oriented structures and Kelvin–Helmholtz (KH) vertical‐oriented structures. The latter are visible where there is a turbidity difference between the two tributaries, whereas the former are usually derived from mean velocity measurements or numerical simulations. Few field studies recorded turbulent velocity fluctuations at high frequency to investigate these structures, particularly at medium‐sized confluences where logistical constraints make it difficult to use devices such as acoustic doppler velocimeter (ADV). This study uses the ice cover present at the confluence of the Mitis and Neigette Rivers in Quebec (Canada) to obtain long‐duration, fixed measurements along the mixing zone. The confluence is also characterized by a marked turbidity difference which allows to investigate the mixing zone dynamics from drone imagery during ice‐free conditions. The aim of the study is to characterize and compare the flow structure in the mixing zone at a medium‐sized (~40 m) river confluence with and without an ice cover. Detailed 3D turbulent velocity measurements were taken under the ice along the mixing plane with an ADV through eight holes at around 20 positions on the vertical. For ice‐free conditions, drone imagery results indicate that large (KH) coherent structures are present, occupying up to 50% of the width of the parent channel. During winter, the ice cover affects velocity profiles by moving the highest velocities towards the centre of the profiles. Large turbulent structures are visible in both the streamwise and lateral velocity components. The strong correlation between these velocity components indicates that KH vortices are the dominating coherent structures in the mixing zone. A spatio‐temporal conceptual model is presented to illustrate the main differences on the 3D flow structure at the river confluence with and without the ice cover. © 2019 John Wiley & Sons, Ltd.

Control mechanisms of photosynthetic epibionts on zooplankton: an experimental approach - Bertolo, Andrea; Rodríguez, Marco A.; Lacroix, Gérard (Ecosphere, 2015)
Several top‐down and bottom‐up forces have been put forward to explain variable infestation rates of zooplankton by epibionts. Among top‐down forces, fish predation affects epibiont prevalence on zooplanktonic organisms, either by eliminating more conspicuous, heavily burdened individuals, or by reducing population size of zooplankton hosts, with consequences for substrate availability for epibionts. However, detailed experimental‐based information on the effects of top‐down forces is still lacking. Among bottom‐up forces, light can potentially control populations of photosynthetic epibionts. Therefore, both changes in light penetration in the water column and the vertical position of hosts in the water column could affect the photic conditions in which epibionts live and could thus control their population growth. We tested experimentally the hypothesis that both light limitation and fish predation affect epibiont burden on zooplankton. Moreover, we also tested the hypothesis that zooplanktivorous fish affect the prevalence and burden of the epibiotic alga Colacium sp. (Euglenida) on zooplankton not only by direct predation, but also by affecting the vertical distribution of zooplankton. We analyzed Colacium burden on two zooplankton genera that responded differently to the presence of zooplanktivorous fish by altering their daytime vertical distributions, thus exposing photosynthetic epibionts to different light conditions. Colacium burden on the two zooplankton genera was also compared between enclosures with different degrees of light limitation. Our results suggest that (1) ambient light limitation has the potential to reduce the burden of photosynthetic epibionts on zooplankton in natural conditions, and (2) zooplankton behavior (e.g., daytime refuge use to escape fish predation) can reduce the burden by exposing photosynthetic epibionts to suboptimal light conditions.

Effects of physical refuges on fish–plankton interactions - Bertolo, A.; Lacroix, G.; Lescher‐Moutouš, F.; Sala, S. (Freshwater Biology, 1999)
1.Refuges that reduce fish‐induced mortality of zooplankton are considered to be key factors in controlling phytoplankton growth in lake ecosystems. In order to better understand the role of physical refuges for zooplankton on zooplanktivorous fish‐plankton relationships, an enclosure experiment was run in a mesotrophic lake. Even‐link systems (zooplankton and phytoplankton) and odd‐link systems (zooplanktivorous fish, zooplankton and phytoplankton) were established. We also established an odd‐link system with a physical refuge for zooplankton where fish predation was limited in the upper half of the enclosure. 2.Fish negatively affected density and mean body length of herbivorous zooplankton and total zooplankton, filtering rates with some intermediate effects in the presence of the refuge. A clear refuge effect was observed for the dominant herbivore, Ceriodaphnia . On the other hand, the refuge seemed to increase the vulnerability of those taxa that aggregated in upper layers of the water column. Grazing was thus reduced in both odd‐link systems. 3.The lack of significant correlation between nutrient availability and phytoplankton biomass in enclosures suggested a top‐down control of algal growth in our experimental systems. In both odd‐link systems (‘fish’ and ‘refuge’) phytoplankton biomass was significantly enhanced, and transparency was reduced in comparison with the even‐link system.

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)

Streamwater ages in nested, seasonally cold Canadian watersheds - Bansah, Samuel; Ali, Genevieve (Hydrological Processes, 2019)
Abstract The mean transit time (MTT) is an important descriptor of water storage and release dynamics in watersheds. Although MTT studies are numerous for many regions around the world, they are rare for prairie watersheds where seasonally cold or dry conditions require adequate methodological choices towards MTT estimation, especially regarding the handling of sparse data records and tracer selection. To examine the impact of such choices, we used timeseries of δ 18 O and δ 2 H from two contrasted years (2014 and 2015) and relied on two metrics and two modelling methods to infer MTTs in prairie watersheds. Our focus was on nested outlets with different drainage areas, geologies, and known run‐off generation mechanisms. The damping ratio and young water fraction (i.e., the fraction of streamflow with transit times lesser than 3 months) metrics, as well as the sine‐wave modelling and time‐based convolution modelling methods, were applied to year‐specific data. Results show that young water fractions and modelled MTT values were, respectively, larger and smaller in 2014, which was a wet year, compared with that in 2015. In 2014, most outlets had young water fractions larger than 0.5 and MTT values lesser than 6 months. The damping ratio, young water fraction, and sine‐wave modelling methods led to convergent conclusions about watershed water storage and release dynamics for some of the monitored sites. Contrasting results were, however, obtained when the same method was applied using δ 2 H instead of δ 18 O, due to differing evaporation fractionation, or when the time‐based convolution modelling method was used. Some methods also failed to provide any robust results during the dry year (i.e., 2015), highlighting the difficulty in inferring MTTs when data are sparse due to intermittent streamflow. This study therefore allowed the formulation of empirical recommendations for MTT estimation in prairie environments as a function of data availability and antecedent wetness conditions.

Delimitation of groundwater zones under contamination risk using a bagged ensemble of optimized DRASTIC frameworks - Barzegar, Rahim; Asghari Moghaddam, Asghar; Adamowski, Jan; Nazemi, Amir Hossein (Environmental Science and Pollution Research, 2019)