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

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

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

Climate teleconnection-driven stochastic simulation for future water-related risk management - Lee, Taesam; Ouarda, Taha B. M. J. (Journal of Hydrology, 2025)
Water risk management has been adversely affected by climate variations, including recent climate change. Climate variations have highly impacted the hydrological cycles in the atmosphere and biosphere, and their impact can be defined with the teleconnection between climate signals and hydrological variables. Water managers should practice future risk management to mitigate risks, including the impact of teleconnection, and stochastically simulated scenarios can be employed as an effective tool to take advantage of water management preparation. A stochastic simulation model for hydrological variables teleconnected with climate signals is very useful for water managers. Therefore, the objective of the current study was to develop a novel stochastic simulation model for the simulation of synthetic series teleconnected with climate signals. By jointly decomposing the hydrological variables and a climate signal with bivariate empirical mode decomposition (BEMD), the bivariate nonstationary oscillation resampling (B-NSOR) model was applied to the significant components. The remaining components were simulated with the newly developed method of climate signal-led K-nearest neighbor-based local linear regression (CKLR). This entire approach is referred to as the climate signal-led hydrologic stochastic simulation (CSHS) model. The key statistics were estimated from the 200 simulated series and compared with the observed data, and the results showed that the CSHS model could reproduce the key statistics including extremes while the SML model showed slight underestimation in the skewness and maximum values. Additionally, the observed long-term variability of hydrological variables was reproduced well with the CSHS model by analyzing drought statistics. Moreover, the Hurst coefficient with slightly higher than 0.8 was fairly preserved by the CSHS model while the SML model is underestimated as 0.75. The overall results demonstrate that the proposed CSHS model outperformed the existing shifting mean level (SML) model, which has been used to simulate hydroclimatological variables. Future projections until 2100 were obtained with the CSHS model. The overall results indicated that the proposed CSHS model could represent a reasonable alternative to teleconnect climate signals with hydrological variables.
Keywords: Infolettre_Septembre_2025

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.

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)

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.

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.
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.
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

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.
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.
Keywords: Scopus_Alert_15_Aout_2025

Entendre et comprendre les expériences de désastre par la recherche narrative - Leclerc, Typhaine; Lessard, Lily; Saint-Charles, Johanne (Intervention, 2024)
Les événements météorologiques extrêmes (EME) et les désastres qu’ils entrainent provoquent des conséquences psychosociales qui sont modulées en fonction de différents facteurs sociaux. On constate aussi que les récits médiatiques et culturels qui circulent au sujet des EME ne sont pas représentatifs de l’ensemble des expériences de personnes sinistrées : celles qui en subissent les conséquences les plus sévères tendent aussi à être celles qu’on « entend » le moins dans l’espace public. Ces personnes sont ainsi susceptibles de vivre de l’injustice épistémique, ce qui a des effets délétères sur le soutien qu’elles reçoivent. Face à ces constats s’impose la nécessité de mieux comprendre la diversité des expériences d’EME et d’explorer des stratégies pour soutenir l’ensemble des personnes sinistrées dans leur rétablissement psychosocial. Cet article soutient que la recherche narrative peut contribuer à répondre à ces objectifs. En dépeignant des réalités multiples, la recherche narrative centrée sur les récits de personnes sinistrées présente aussi un intérêt significatif pour l’amélioration des pratiques d’intervention en contexte de désastre. , Extreme weather events (EWE) and their resulting disasters cause psychosocial consequences that are moderated by different social factors. Media and cultural accounts of EWEs do not represent the full range of disaster survivor experiences, that is, those who experienced the most severe consequences also tend to be those least “heard” in the public arena. These people are therefore most likely to experience forms of epistemic injustice that negatively impact the support offered to cope with disaster. Considering these findings, there is a need to better understand the diversity of EWE experiences and explore strategies for supporting all disaster survivors in their psychosocial recovery. This article argues that narrative research can help meet these needs. By portraying the multiple realities of people affected by EWEs, narrative research focusing on the stories of disaster survivors is also of significant interest for improving intervention practices in this context.

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

Impacts of Adjusting Solid Precipitation Amounts in the Canadian Precipitation Analysis System - Aubry, Catherine; Bélair, Stéphane; Thériault, Julie M.; Mekis, Eva; Feng, Pei-Ning; Lespinas, Franck; Khedhaouiria, Dikra; Beaudry, Florence (Journal of Applied Meteorology and Climatology, 2025)
Abstract Real-time precipitation data are essential for weather forecasting, flood prediction, drought monitoring, irrigation, fire prevention, and hydroelectric management. To optimize these activities, reliable precipitation estimates are crucial. Environment and Climate Change Canada (ECCC) leads the Canadian Precipitation Analysis (CaPA) project, providing near-real-time precipitation estimates across North America. However, during winter, CaPA’s 6-hourly accuracy is limited because many automatic surface observations are not assimilated due to wind-induced gauge undercatch. The objective of this study is to evaluate the added value of adjusted hourly precipitation amounts for gauge undercatch due to wind speed in CaPA. A recent ECCC dataset of hourly precipitation measurements from automatic precipitation gauges across Canada is included in CaPA as part of this study. Precipitation amounts are adjusted based on several types of transfer functions, which convert measured precipitation into what high-quality equipment would have measured with reduced undercatch. First, there are no notable differences in CaPA when comparing the performance of the universal transfer function with that of several climate-specific transfer functions based on wind speed and air temperature. However, increasing solid precipitation amounts using a specific type of transfer function that depends on snowfall intensity rather than near-surface air temperature is more likely to improve CaPA’s precipitation estimates during the winter season. This improvement is more evident when the objective evaluation is performed with direct comparison with the Adjusted Daily Rainfall and Snowfall (AdjDlyRS) dataset.
Keywords: Infolettre_Ete_2025

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.

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

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

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

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

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

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

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

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

Deep learning applications to climate change mitigation - Schmidt, Victor (2024)
Les changements climatiques sont un défi mondial imminent, dont les conséquences sont déjà observées. On sait que ces effets s’intensifieront, entraînant une augmentation de la fréquence et de la gravité des événements météorologiques extrêmes, une perturbation substantielle de la production alimentaire et le déplacement de dizaines de millions de personnes en raison de vagues de chaleur mortelles et de sécheresses. La question est donc : que peut-on y faire ? Dans cette thèse, nous faisons des changements climatiques notre objet central et explorons les voies par lesquelles la recherche en apprentissage profond peut contribuer à son atténuation. Un obstacle connu à des politiques climatiques ambitieuses est le manque de soutien et de demande populaires. Cela peut être attribué, en partie, aux causes et conséquences extrêmement complexes et imbriquées des changements climatiques. Une mauvaise conception courante est qu'ils affecteront principalement d’autres personnes que soi-même, des personnes éloignées dans le temps ou l’espace. Pour y remédier, la recherche a montré que présenter aux gens des images authentiques, locales et pertinentes d'un concept les aide à mieux comprendre et appréhender ce qui est en jeu. Dans notre première contribution, nous explorons donc comment les récentes avancées en apprentissage profond pour la vision par ordinateur et les réseaux antagonistes génératifs peuvent être utilisées pour générer des images personnalisées représentant les impacts du changement climatique. Notre objectif avec ClimateGAN est de visualiser à quoi pourrait ressembler une inondation d’un mètre à n’importe quelle adresse, indépendamment de son risque réel d’inondation sous l’effet des changements climatiques. Cette approche vise à susciter l’empathie en rendant les impacts abstraits du changement climatique plus tangibles et personnalisés. En utilisant une image de Google Street View et en la traitant avec ClimateGAN, nous générons des images d’inondation physiquement plausibles et visuellement réalistes basées sur l’adaptation de domaine à partir d’un environnement simulé, la prédiction de profondeur et la segmentation sémantique. Ce modèle a été déployé sur un site web dans le but de sensibiliser et d’engager l’action en faveur des changements climatiques. En plus d’aider les gens à mieux visualiser à quoi pourrait ressembler un avenir climatique hors de contrôle, nous étudions également dans cette thèse comment l’apprentissage profond peut améliorer les technologies existantes. Un domaine majeur de recherche dans cette direction est la recherche de nouveaux matériaux. Dans cette thèse, nous explorons plus particulièrement la prédiction des propriétés des matériaux comme moyen d’accélérer la découverte d'électro-catalyseurs, une famille de matériaux impliqués dans le stockage d’énergie à base d’hydrogène. Nous présentons deux contributions, PhAST et FAENet, qui se concentrent sur l’amélioration du compromis performance/scalabilité dans les réseaux de neurones géométriques de graphe (GNN). Avec PhAST, nous introduisons un ensemble de méthodes pour adapter la procédure GNN classique--de la création du graphe d’entrée aux prédictions d’énergie et de forces de sortie--à la tâche spécifique de prédire l’énergie d’un système atomique adsorbant-catalyseur relaxé. Nous démontrons comment, en plus d’améliorer les performances, ces modifications améliorent l’efficacité et permettent un entraînement compétitif des GNN dans des environnements CPU. Dans FAENet, nous présentons un nouveau GNN efficace pour les prédictions équivariantes E(3). En particulier, nous transposons la charge de l’équivarience sur la représentation des données afin de réduire les contraintes sur le modèle lui-même. Cette approche nous permet d’introduire une nouvelle architecture légère et expressive visant à faire des prédictions meilleures et plus rapides de diverses propriétés des matériaux. Enfin, nous examinons de manière critique notre propre domaine et discutons des impacts environnementaux associés aux technologies de l’IA. Nous nous penchons sur la façon dont les praticiens peuvent estimer leurs émissions de carbone, quelles mesures ils peuvent prendre aujourd’hui pour les réduire, et quelles autres étapes sont nécessaires pour des déclarations et responsabilités environnementales plus précises.

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

Essays on Water Infrastructure Investments and Infectious Diseases Management - Kouassi, Régis (2024)
En étant nécessaire à la vie humaine, l’eau est également nécessaire au fonctionnement des économies. Pour qu’elle soit utile à la société, l’eau doit être disponible en quantité et en qualité adéquates, caractéristiques qui ne sont pas toujours disponibles dans la nature. Ainsi, trop ou pas assez d’eau entraînerait des inondations ou des sécheresses, tandis qu’une eau contaminée pourrait être le vecteur de maladies contagieuses mortelles, chacun de ces fléaux entraînant des dommages économiques. Cette thèse est organisée en trois chapitres traitant de thématiques liées aux investissements dans les infrastructures d'eau et à la gestion des maladies infectieuses. Le premier chapitre étudie comment les améliorations apportées aux réseaux d’égouts atténuent les impacts économiques des inondations provoquées par la pluie. Pour estimer l’effet causal de ces investissements, ce chapitre utilise un resserrement inattendu du financement fédéral américain en faveur des réseaux d’égouts, à la suite de l’amendement de 1977 à la politique du Clean Water Act. L'analyse empirique combine un nouveau modèle statistique du risque d'inondation induit par la pluie avec des données horaires sur la quantité de pluie dans les comtés et les codes postaux américains de 1996 à 2019. Les résultats indiquent que des investissements plus importants dans les réseaux d'égouts ont conduit à des réductions substantielles des inondations locales. Les bénéfices de ces investissements sont supérieurs à leurs coûts, économisant près de 23 millions de dollars pour le comté moyen. Dans l’ensemble, ces résultats mettent en évidence à quel point la détérioration des infrastructures publiques peut exacerber les conséquences du changement climatique. Le deuxième chapitre étudie le rôle des épidémies locales de maladies infectieuses dans l'adoption de systèmes centralisés d'approvisionnement en eau dans les premières villes américaines au XIXe siècle. À l’aide d’un vaste corpus de données provenant d’archives de journaux de 1800 à 1896, je construis un nouvel indicateur capturant les épidémies de fièvre jaune, de choléra et de fièvre typhoïde au niveau des villes. Les résultats indiquent que (1) les épidémies locales de maladies infectieuses ont entraîné une augmentation du nombre systèmes d'approvisionnement en eau construits par les villes et ont joué un rôle crucial dans la décision de construire environ 12% des ouvrages d’adduction d’eau en activité en 1897 ; (2) La réponse des villes aux épidémies de typhoïde a été deux fois plus importante que celle qui a suivi les épidémies de fièvre jaune ou de choléra. (3) Les entreprises privées ont construit davantage de nouveaux réseaux d’adduction d’eau après les épidémies locales, tandis que les gouvernements locaux ont procédé à davantage d’améliorations et d’extensions des réseaux d’adduction d’eau publics existants ainsi qu’à des rachats de sociétés d’eau privées. Enfin, je discute du rôle potentiel de divers facteurs sociodémographiques. Le troisième chapitre étudie les coûts économiques associés à une stratégie utilisée pour gérer les épidémies locales lors de la récente pandémie de COVID-19. Dans ce travail en collaboration avec Jian Tang, nous quantifions les effets de la politique ‘zéro-COVID’ à l’aide d’un riche ensemble de données sur les confinements au niveau des comtés en Chine et d’images satellitaires nocturnes. Nous constatons que des confinements plus stricts induisent une forte baisse de la luminosité nocturne au cours de la même période, suivie d’une lente reprise, qui se produit au moins deux trimestres après l’instauration du confinement. En l’absence de contagions généralisées, un comté soumis à un confinement total subit en moyenne une perte de PIB de 6% par rapport aux comtés non confinés. L’effet négatif est particulièrement persistant dans les zones où la production est dominée par les services, par opposition aux zones où la production est dominée par l’activité manufacturière. L’on note par ailleurs la présence d’effets d’entraînement à proximité des comtés confinés, mais ces effets sont de courte durée.

Gestion intégrée des catastrophes en Afrique Subsaharienne : rôle de l’assurance, pour un système de gestion performant et la résilience des populations au Bénin - Goundjo, Antoine (2018)
Les variabilités et changements climatiques et les incapacités pour faire face à leurs risques, à leurs effets et, plus précisément, à gérer les catastrophes hydrométéorologiques (inondation et sécheresse) qui les accompagnent, viennent en ajouter aux vulnérabilités et aux problèmes, qui sont déjà une préoccupation en Afrique Subsaharienne et au Bénin. Face à leurs manifestations de plus en plus récurrentes – la faiblesse des systèmes de financement local de la gestion des catastrophes et le déficit des systèmes de protection sociale, qui témoignent des limites des capacités de transfert des risques de catastrophe – cette étude a identifié la structure (gouvernance-ressources), comme le problème essentiel de la gestion des catastrophes au Bénin. Une étude synthétique, étude de cas multiples avec trois niveaux d’analyse imbriqués, dans une approche qualitative, a permis de mieux comprendre comment, dans un contexte de pauvreté, l’intégration de la micro assurance climatique, modifie la structure, le processus et le résultat de la gestion des catastrophes et assure la performance du système et la résilience des populations. Elle a documenté les différents aspects de la structure et des vulnérabilités des systèmes et des populations et a identifié l’absence d’intégration de la micro assurance climatique aux systèmes de gestion des catastrophes, comme un problème au coeur de la complexité des déterminants de la résilience, aussi confrontée à une autre complexité, celle de la diversité des interconnexions entre les différentes catégories de risques, qui place la santé au coeur de tous les risques. La nécessité d’une gestion holistique du risque global, ou d’une gestion tout risque, telle que retenue par le Cadre d’Action de Hyōgo et le Cadre d’Action de Sendai; et l’importance d’apporter une réponse en accord au contexte et à son profil de risques, qui prend l’option pour la "démocratisation" d’une micro assurance climatique, gouvernée sur la base de fondements idéologiques d’équité et d’efficience, cette recherche a préconisé – pour une gestion plus rationnelle, pertinente, efficace et efficiente des catastrophes – une intégration de trois systèmes : le système de la gestion des catastrophes; le système de protection sociale, y compris celui de la micro assurance climatique, et le système de la santé; tous reconnus outillés pour la gestion des risques. Elle a retenu, qu’une telle approche saurait aussi assurer une gestion efficace du changement qu’induirait l’intégration de la micro assurance climatique à la gestion des catastrophes; de ii même qu’une meilleure utilisation des outils et méthodes de sensibilisation, de prévention, de prévision et d’évaluation des risques et des dommages dont recèlent les pratiques en micro assurance climatique. Elle constate que la réussite de l’intégration de la MAC et son développement sont essentiellement plus déterminés par les acteurs et leurs intérêts, que par les ressources financières, même si elles sont aussi indispensables. Cette recherche préconise qu’à partir de choix de modèles et de modes d’intégration bien étudiés, son intégration ou sa prise en compte dans les différents programmes d’aide et de protection sociale mis en oeuvre au Bénin pourrait être, à travers les subventions de l’État, un moyen de mobilisation de fonds en faveur de son financement et de sa viabilité/durabilité. Ce financement pourra aussi s’appuyer sur les mécanismes traditionnels de financement de l’assurance, de la micro assurance, des changements climatiques et de la réduction des risques de catastrophe au Bénin, en Afrique et dans le monde. C’est pourquoi, en termes de gouvernance, ce travail soutien une restructuration avec une gestion entièrement centrée sur les communes, dans une approche des services de première ligne avec les réseaux de services ; en termes de ressources, il a aussi analysé les conditions et les possibilités de développement d’une micro assurance climatique, qui dépend avant tout de la qualité de la gestion des catastrophes (capacités à réduire les risques et limiter les pertes ou capacités à induire la résilience des systèmes et des populations). Cette approche puise dans les réalités et pratiques endogènes de gestion des catastrophes et surtout de protection sociale ou de transfert de risques ; elle s’inspire des bonnes pratiques d’ailleurs ; elle contribue à instaurer l’équité, comme principe de la gestion intégrée des catastrophes et, au-delà de la résilience, à susciter une convergence des efforts pour l’autonomisation de la structure et des populations, face aux manifestations catastrophiques des inondations et de la sécheresse. Cette recherche pense qu’il faut oser la micro assurance universelle pour la gestion des catastrophes hydrométéorologiques; qu’elle est réalisable ou faisable, même en contexte de pauvreté; et qu’il est aussi possible de combiner micro assurance climatique universelle et assurance médicale universelle, dans une dynamique qui mobilise des approches efficientes et les intérêts.

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

Trends and historical patterns of meteorological droughts in New Brunswick, Canada, using PDSI and SEDI indices - Faghfouri, Ali; Fortin, Guillaume; Ullmann, Albin; Raymond, Florian; Poirier, Charlotte; Dubreuil, Vincent; Germain, Daniel (Theoretical and Applied Climatology, 2025)
Droughts are increasingly recognized as a significant global challenge, with severe impacts observed in Canada's Prairie provinces. While less frequent in Eastern Canada, prolonged precipitation deficits, particularly during summer, can lead to severe drought conditions. This study investigates the causes and consequences of droughts in New Brunswick (NB) by employing two drought indices: the Palmer Drought Severity Index (PDSI) and Standardized Evapotranspiration Deficit Index (SEDI)– at ten weather stations across NB from 1971 to 2020. Additionally, the Canadian Gridded Temperature and Precipitation Anomalies (CANGRD) dataset (1979–2014) was utilized to examine spatial and temporal drought variability and its alignment with station-based observations. Statistical analyses, including the Mann–Kendall test and Sen's slope estimator, were applied to assess trends in drought indices on annual and seasonal timescales using both station and gridded data. The results identified the most drought-vulnerable regions in NB and revealed significant spatial and temporal variability in drought severity over the 1971–2020 period. Trend analyses further highlighted the intensification of extreme drought events during specific years. Coastal areas in southern NB were found to be particularly susceptible to severe drought conditions compared to inland regions, consistent with observed declines in both the frequency of rainy days and daily precipitation amounts in these areas. These findings underscore the need for targeted drought mitigation strategies particularly in NB’s coastal zones, to address the region’s increasing vulnerability to extreme drought events.

Quel regard porter sur le travail social à l’ère des changements climatiques? : le cas des inondations (2017-2019) au Québec - Hamelin, Marilou (2021)
Les changements climatiques anthropogéniques posent des défis énormes pour toutes les sociétés humaines. Ces défis majeurs mettront à l’épreuve les capacités d’adaptation des États et de ses institutions et des communautés partout dans le monde et devront se résoudre par un élan de solidarité humaine afin d’en atténuer les conséquences. Le Canada connaît déjà un réchauffement climatique important. Le pays a d’ailleurs récemment été touché par des événements climatiques extrêmes : des canicules, des feux de forêt, une sécheresse anormale et des inondations dont l’intensité est prévue d’augmenter avec les changements climatiques anthropogéniques. La province du Québec a quant à elle été touchée par de fortes inondations entre 2017 et 2019. L’objectif principal de la présente étude vise à discuter la manière dont le paradigme écosocial peut faire évoluer le travail social en tant que champ de savoir et d’intervention dans un contexte de changements climatiques. Cette étude s’est appuyée sur des données issues de groupes focus réalisés avec des intervenants suite aux inondations survenues au Québec (2017-2019). Notre analyse vise les interventions réalisées en contexte d’inondations, dans le sud de la province, mise en œuvre par le système de santé. Les données ont été collectées lors d’entrevues de groupe réalisées avec des intervenants psychosociaux et des gestionnaires de CI(U)SSS au courant des mois d’octobre et de novembre 2019. Les thèmes suivants ont émergé des analyses: les caractéristiques des inondations de 2019, les divergences d’opinions vis-à-vis des changements climatiques, l’aide et le soutien apportés durant les inondations et la participation citoyenne. J’insisterai également sur l’exacerbation possible des inégalités sociales dans ce contexte. D’autres thèmes se sont également révélés importants : l’engagement des intervenants psychosociaux, la participation et la décentralisation des décisions politiques. Enfin, mes réflexions porteront sur les conséquences sociales qu’entrainent les inondations et sur les types de pratiques sociales qui s’avèrent pertinentes à l’ère des changements climatiques et dans un contexte d’urgence.

Impacts of summer and winter conditions on summer river low flows in low elevation, snow-affected catchments - Kinnard, Christophe; Bzeouich, Ghada; Assani, Ali (Journal of Hydrology, 2022)
Reduced snow storage has been associated with lower river low flows in mountainous catchments, exacerbating summer hydrological droughts. However, the impacts of changing snow storage on summer low flows in low-elevation, snow-affected catchments has not yet been investigated. To address this knowledge gap, the dominant hydroclimate predictors of summer low flows were first identified through correlation analysis in 12 tributary catchments of the St. Lawrence River in the Canadian province of Quebec. The correlation results show that summer low flow is most sensitive to summer rainfall, while maximum snow water equivalent (SWE) is the dominant winter preconditioning factor of low flows, particularly at the end of summer. The multivariate sensitivity of summer low flow to hydroclimate predictors was then quantified by multilevel regression analysis, considering also the effect of catchment biophysical attributes. Accumulated rainfall since snow cover disappearance was found to be the prime control on summer low flow, as expected for the humid climate of Quebec. Maximum SWE had a secondary but significant positive influence on low flow, sometimes on the same order as the negative effect of evapotranspiration losses. As a whole, our results show that in these low elevation catchments, thicker winter snowpacks that last longer and melt slower in the spring are conducive to higher low flows in the following summer. More rugged and forested catchments with coarser soils were found to have higher summer low flows than flatter agricultural catchments with compacted clayed soils. This emphasizes the role of soils and geology on infiltration, aquifer recharge and related river baseflow in summer. Further climate warming and snowpack depletion could reduce future summer low flow, exacerbating hydrological droughts and impacting ecosystems integrity and ecological services.
Keywords: Infolettre; Infolettre_Juillet_2022; Kinnard_Christophe; Site_internet_RIISQ

Development of a methodology to assess future trends in low flows at the watershed scale using solely climate data - Foulon, Étienne; Rousseau, Alain N.; Gagnon, Patrick (Journal of Hydrology, 2018)
Abstract Low flow conditions are governed by short-to-medium term weather conditions or long term climate conditions. This prompts the question: given climate scenarios, is it possible to assess future extreme low flow conditions from climate data indices (CDIs)? Or should we rely on the conventional approach of using outputs of climate models as inputs to a hydrological model? Several CDIs were computed using 42 climate scenarios over the years 1961–2100 for two watersheds located in Quebec, Canada. The relationship between the CDIs and hydrological data indices (HDIs; 7- and 30-day low flows for two hydrological seasons) were examined through correlation analysis to identify the indices governing low flows. Results of the Mann-Kendall test, with a modification for autocorrelated data, clearly identified trends. A partial correlation analysis allowed attributing the observed trends in HDIs to trends in specific CDIs. Furthermore, results showed that, even during the spatial validation process, the methodological framework was able to assess trends in low flow series from: (i) trends in the effective drought index (EDI) computed from rainfall plus snowmelt minus PET amounts over ten to twelve months of the hydrological snow cover season or (ii) the cumulative difference between rainfall and potential evapotranspiration over five months of the snow free season. For 80% of the climate scenarios, trends in HDIs were successfully attributed to trends in CDIs. Overall, this paper introduces an efficient methodological framework to assess future trends in low flows given climate scenarios. The outcome may prove useful to municipalities concerned with source water management under changing climate conditions.
Keywords: Rousseau_Alain

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

Development and validation of an index to measure progress in adaptation to climate change at the municipal level - Jacob, Johann; Valois, Pierre; Tessier, Maxime (Ecological Indicators, 2022)
Background Given the important role that municipalities must play in adapting to climate change, it is more than ever essential to measure their progress in this area. However, measuring municipalities’ adaptation progress presents its share of difficulties especially when it comes to comparing (on similar dimensions and over time) the situation of different municipal entities and to linking adaptation impacts to local actions. Longitudinal studies with recurring indicators could capture changes occurring over time, but the development of such indicators requires great emphasis on methodological and psychometric aspects, such as measurement validity. Therefore, this study aimed to develop and validate an index of adaptation to heatwaves and flooding at the level of municipal urbanists and urban planners. Methods A sample of 139 officers working in urbanism and urban planning for municipal entities in the province of Quebec (Canada) completed an online questionnaire. Developed based on a literature review and consultation of representatives from the municipal sector, the questionnaire measured whether the respondent’s municipal entity did or did not adopt the behaviors that are recommended in the scientific and gray literature to adapt to heatwaves and flooding. Results Results of the various metrological analyses (indicator reliability analysis, first order confirmatory factor analysis, concurrent validity analysis, and nomological validity assessment analysis) confirmed the validity of the index developed to measure progress in climate change adaptation at the municipal level. The first dimension of the index corresponds to preliminary measures that inform and prepare stakeholders for action (i.e., groundwork adaptation initiatives), whereas the second refers to measures that aim to concretely reduce vulnerability to climate change, to improve the adaptive capacity or the resilience of human and natural systems (i.e., adaptation actions). Conclusion The results of a series of psychometric analyses showed that the index has good validity and could properly measure the adoption of actions to prepare for adaptation as well as adaptation actions per se. Municipal and government officials can therefore consider using it to monitor and evaluate adaptation efforts at the municipal level.
Keywords: Infolettre; Infolettre_Avril_2022; Site_internet_RIISQ

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

Simulation of aquifer-peatland-river interactions under climate change - Bourgault, M. A.; Larocque, M.; Roy, M. (Hydrology Research, 2014)
Wetlands play an important role in preventing extreme low flows in rivers and groundwater level drawdowns during drought periods. This hydrological function could become increasingly important under a warmer climate. Links between peatlands, aquifers, and rivers remain inadequately understood. The objective of this study was to evaluate the hydrologic functions of the Lanoraie peatland complex in southern Quebec, Canada, under different climate conditions. This peatland complex has developed in the beds of former fluvial channels during the final stages of the last deglaciation. The peatland covers a surface area of ~76 km2 and feeds five rivers. Numerical simulations were performed using a steady-state groundwater flow model. Results show that the peatland contributes on average to 77% of the mean annual river base flow. The peatland receives 52% of its water from the aquifer. Reduced recharge scenarios (−20 and −50% of current conditions) were used as a surrogate of climate change. With these scenarios, the simulated mean head decreases by 0.6 and 1.6 m in the sand. The mean river base flow decreases by 16 and 41% with the two scenarios. These results strongly underline the importance of aquifer-peatland-river interactions at the regional scale. They also point to the necessity of considering the entire hydrosystem in conservation initiatives.
Keywords: Ouvrage_Collectif_Numéro1

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

Impact of Soil Moisture Data Characteristics on the Sensitivity to Crop Yields Under Drought and Excess Moisture Conditions - Champagne, Catherine; White, Jenelle; Berg, Aaron A.; Bélair, Stéphane; Carrera, Marco L. (Remote Sensing, 2019)
Soil moisture is often considered a direct way of quantifying agricultural drought since it is a measure of the availability of water to support crop growth. Measurements of soil moisture at regional scales have traditionally been sparse, but advances in land surface modelling and the development of satellite technology to indirectly measure surface soil moisture has led to the emergence of a number of national and global soil moisture data sets that can provide insight into the dynamics of agricultural drought. Droughts are often defined by normal conditions for a given time and place; as a result, data sets used to quantify drought need a representative baseline of conditions in order to accurately establish a normal. This presents a challenge when working with earth observation data sets which often have very short baselines for a single instrument. This study assessed three soil moisture data sets: a surface satellite soil moisture data set from the Soil Moisture and Ocean Salinity (SMOS) mission operating since 2010; a blended surface satellite soil moisture data set from the European Space Agency Climate Change Initiative (ESA-CCI) that has a long history and a surface and root zone soil moisture data set from the Canadian Meteorology Centre (CMC)’s Regional Deterministic Prediction System (RDPS). An iterative chi-squared statistical routine was used to evaluate each data set’s sensitivity to canola yields in Saskatchewan, Canada. The surface soil moisture from all three data sets showed a similar temporal trend related to crop yields, showing a negative impact on canola yields when soil moisture exceeded a threshold in May and June. The strength and timing of this relationship varied with the accuracy and statistical properties of the data set, with the SMOS data set showing the strongest relationship (peak X2 = 170 for Day of Year 145), followed by the ESA-CCI (peak X2 = 89 on Day of Year 129) and then the RDPS (peak X2 = 65 on Day of Year 129). Using short baseline soil moisture data sets can produce consistent results compared to using a longer data set, but the characteristics of the years used for the baseline are important. Soil moisture baselines of 18–20 years or more are needed to reliably estimate the relationship between high soil moisture and high yielding years. For the relationship between low soil moisture and low yielding years, a shorter baseline can be used, with reliable results obtained when 10–15 years of data are available, but with reasonably consistent results obtained with as few as 7 years of data. This suggests that the negative impacts of drought on agriculture may be reliably estimated with a relatively short baseline of data.

Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region - Mouatadid, Soukayna; Raj, Nawin; Deo, Ravinesh C.; Adamowski, Jan F. (Atmospheric Research, 2018)

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

Disaster risk, climate change, and poverty: assessing the global exposure of poor people to floods and droughts - Winsemius, Hessel C.; Jongman, Brenden; Veldkamp, Ted I.E.; Hallegatte, Stephane; Bangalore, Mook; Ward, Philip J. (Environment and Development Economics, 2018)
Abstract People living in poverty are particularly vulnerable to shocks, including those caused by natural disasters such as floods and droughts. This paper analyses household survey data and hydrological riverine flood and drought data for 52 countries to find out whether poor people are disproportionally exposed to floods and droughts, and how this exposure may change in a future climate. We find that poor people are often disproportionally exposed to droughts and floods, particularly in urban areas. This pattern does not change significantly under future climate scenarios, although the absolute number of people potentially exposed to floods or droughts can increase or decrease significantly, depending on the scenario and region. In particular, many countries in Africa show a disproportionally high exposure of poor people to floods and droughts. For these hotspots, implementing risk-sensitive land-use and development policies that protect poor people should be a priority.

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

Dendrohydrology in Canada’s western interior and applications to water resource management - Sauchyn, David J.; Vanstone, Jessica; St. Jacques, Jeannine-Marie; Sauchyn, Robert (Journal of Hydrology, 2015)
Summary Across the southern Canadian Prairies, annual precipitation is relatively low (200–400mm) and periodic water deficits limit economic and environmental productivity. Rapid population growth, economic development and climate change have exposed this region to increasing vulnerability to hydrologic drought. There is high demand for surface water, streamflow from the Rocky Mountains in particular. This paper describes the application of dendrohydrology to water resource management in this region. Four projects were initiated by the sponsoring organizations: a private utility, an urban municipality and two federal government agencies. The fact that government and industry would initiate and fund tree-ring research indicates that practitioners recognize paleohydrology as a legitimate source of technical support for water resource planning and management. The major advantage of tree-rings as a proxy of annual and seasonal streamflow is that the reconstructions exceed the length of gauge records by at least several centuries. The extent of our network of 180 tree-ring chronologies, spanning AD 549–2013 and ∼20° of latitude, with a high density of sites in the headwaters of the major river basins, enables us to construct large ensembles of tree-ring reconstructions as a means of expressing uncertainty in the inference of streamflow from tree rings. We characterize paleo-droughts in terms of modern analogues, translating the tree-ring reconstructions from a paleo-time scale to the time frame in which engineers and planners operate. Water resource managers and policy analysts have used our paleo-drought scenarios in their various forms to inform and assist drought preparedness planning, a re-evaluation of surface water apportionment policy and an assessment of the reliability of urban water supply systems.

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

Climate and water availability indicators in Canada: Challenges and a way forward. Part II – Historic trends - Mortsch, Linda; Cohen, Stewart J.; Koshida, Grace (2015)
Climate variability is recognized as an important influence on the availability of water throughout Canada, and projected climate change is anticipated to alter the amount, timing and distribution of water. This is Part II of a three-part (Parts I and III, this issue) analysis of water availability in Canada. Part II surveys current research, primarily Canadian in origin, on historical trends in climate and hydrologic indicators relevant to assessing water availability. Information on hydro-climate trends is not evenly distributed across Canada. Hydrologic trend research focuses on the North, British Columbia and the Prairies (Saskatchewan) with some research in Quebec, very little in Ontario and minimal analysis for Atlantic Canada. Overall, there is less research on trends in climatological indicators (drought, evapotranspiration, soil moisture); generally, the focus is on the Prairies. Hydrologic trends from basin-scale case studies are reported but inter-comparison is constrained by different periods ...

Climate and water availability indicators in Canada: Challenges and a way forward. Part I – Indicators - Koshida, Grace; Cohen, Stewart J.; Mortsch, Linda (2015)
Climate variability influences the availability of water resources throughout Canada, and projected climate change is anticipated to affect future water availability. This is the first paper of a three-part analysis of water availability indicators in Canada (Parts II and III, this issue). The concept of water availability has been described in different ways in the literature. In Part I, the various approaches for estimating water availability are reviewed and compared, with a focus on Canadian studies. Global examples are used when necessary. The approaches to estimate water availability are organized into three categories: (1) climate-based indicators, (2) hydrology-based indicators and (3) water demand/supply-based indicators. Climate-based indicators use variables such as precipitation, and potential or actual evapotranspiration to calculate water budgets. Widely used meteorological drought indices that calculate moisture surpluses and deficits are also examined. Hydrology-based indicators focus on v...

Extreme Hydrological Drought in Southern Quebec (Canada): Natural and Anthropogenic Factors Interactions on its Spatio-Temporal Variability - Assani, Ali Arkamose (International Journal of Environmental Sciences & Natural Resources, 2023)

Mitigation of Concurrent Flood and Drought Risks Through Land Modifications: Potential and Perspectives of Land Users - Slavíková, Lenka; Milman, Anita (2023)
Modifications to land can serve to jointly reduce risks of floods and droughts to people and to ecosystems. Whether land modifications are implemented will depend on the willingness and ability of a diversity of actors. This article reviews the state of knowledge on land modification use in areas exposed to dual hydrologic risks and the land owners, managers, and users who directly make decisions about action on lands they control. The review presents a typology of land modifications and explains how land modifications interact with the hydrological cycle to reduce risks. It then addresses the roles and perspectives of the land owners, managers, and users undertaking land modifications, summarizing theories explaining motivations for, as well as barriers to and enablers of, land modification implementation. The analysis reveals geographical differences in narratives on land modifications as well as knowledge gaps regarding variation across actors and types of land modifications.

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

Quantifying Changes in Extreme Weather Events in Response to Warmer Global Temperature - Moore, Travis R.; Matthews, H. Damon; Simmons, Christopher; Leduc, Martin (Atmosphere-Ocean, 2015)
Global warming is expected to affect both the frequency and severity of extreme weather events, though projections of the response of these events to climate warming remain highly uncertain. The range of changes reported in the climate modelling literature is very large, sometimes leading to contradictory results for a given extreme weather event. Much of this uncertainty stems from the incomplete understanding of the physics of extreme weather processes, the lack of representation of mesoscale processes in coarse-resolution climate models, and the effect of natural climate variability at multi-decadal time scales. However, some of the spread in results originates simply from the variety of scenarios for future climate change used to drive climate model simulations, which hampers the ability to make generalizations about predicted changes in extreme weather events. In this study, we present a meta-analysis of the literature on projected future extreme weather events in order to quantify expected changes in weather extremes as a function of a common metric of global mean temperature increases. We find that many extreme weather events are likely to be significantly affected by global warming. In particular, our analysis indicates that the overall frequency of global tropical cyclones could decrease with global warming but that the intensity of these storms, as well as the frequency of the most intense cyclones could increase, particularly in the northwestern Pacific basin. We also found increases in the intensity of South Asian monsoonal rainfall, the frequency of global heavy precipitation events, the number of North American severe thunderstorm days, North American drought conditions, and European heatwaves, with rising global mean temperatures. In addition, the periodicity of the El Niño–Southern Oscillation may decrease, which could, in itself, influence extreme weather frequency in many areas of the climate system.

The tale of three floods: From extreme events and cascades of highs to anthropogenic floods - Alborzi, Aneseh; Zhao, Yunxia; Nazemi, Ali; Mirchi, Ali; Mallakpour, Iman; Moftakhari, Hamed; Ashraf, Samaneh; Izadi, Reza; AghaKouchak, Amir (Weather and Climate Extremes, 2022)
Right after a devastating multi-year drought, a number of flood events with unprecedented spatial extent hit different parts of Iran over the 2-week period of March 17th to April 1st, 2019, causing a human disaster and substantial loss of assets and infrastructure across urban and rural areas. Here, we investigate natural (e.g., rainfall, snow accumulation/melt, soil moisture) and anthropogenic drivers (e.g., deforestation, urbanization, and management practices) of these events using a range of ground-based data and satellite observations. These drivers can range from exceptionally extreme rainfall intensities, to cascades of several extreme and moderate events, and various anthropogenic interventions that exacerbated flooding. Our results reveal strong compounding impacts of natural drivers and anthropogenic triggers in escalating flood risks to unprecedented levels. We argue that a new form of floods, i.e. anthropogenic floods, is becoming more common and should be recognized during the “Anthropocene”. This specific form of floods refers to high to extreme streamflow/runoff events that are primarily caused, or largely exacerbated, by anthropogenic drivers. We demonstrate how the growing risk of anthropogenic floods can be assessed using a wide range of climatic and non-climatic satellite and in-situ data.
Keywords: Infolettre; Infolettre_Octobre_2022; Site_internet_RIISQ

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

Assessment of the Dynamics towards Effective and Efficient Post-Flood Disaster Adaptive Capacity and Resilience in South Africa - Nyide, Sindisiwe; Simatele, Mulala Danny; Grab, Stefan; Adom, Richard Kwame (2023)
Government employees, municipal officials, and communities in South Africa have grappled with post-apartheid environmental challenges, such as floods, droughts, severe storms, and wildfires. These disasters are a result of both natural and human activities. The government implemented different policies and strategies after 1994 to address these issues. While acknowledging some success in managing these disasters with the current adaptive measures, the frequency and intensity of disasters have increased, causing significant damage to life and property, particularly among the vulnerable population. This paper uses qualitative and quantitative data collection approaches to explore possible systematic and structural weaknesses in addressing post-disaster situations in South Africa. Floods appear to be the most frequent natural disaster in South Africa. The paper uncovered the fact that disaster management is a multi-sectoral and multidisciplinary field. Although various institutional arrangements exist, they do not seem appropriate for assisting vulnerable groups. While officials have made some progress in implementing post-disaster projects, challenges still hinder sustainability. Furthermore, regrettably, despite the level of success in addressing disasters, most measures have failed to achieve the intended results for a variety of reasons. The consolidated long-term measures suggested by the participants yielded a proposed ‘South African Floods Post-Disaster Checklist or Model’, which was non-existent in South Africa. By implementing more effective and efficient post-disaster measures, the proposed tool can help policymakers and strategic partners standardise post-disaster resilience and adaptive capacity in various sectors’ sustainability contexts.

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

Risk and Resilience: A Case of Perception versus Reality in Flood Management - Agrawal, Nirupama; Elliott, Mark; Simonovic, Slobodan P. (Water, 2020)
Canada’s vast regions are reacting to climate change in uncertain ways. Understanding of local disaster risks and knowledge of underlying causes for negative impacts of disasters are critical factors to working toward a resilient environment across the social, economic, and the built sectors. Historically, floods have caused more economical and social damage around the world than other types of natural hazards. Since the 1900s, the most frequent hazards in Canada have been floods, wildfire, drought, and extreme cold, in terms of economic damage. The recent flood events in the Canadian provinces of Ontario, New Brunswick, Quebec, Alberta, and Manitoba have raised compelling concerns. These include should communities be educated with useful knowledge on hazard risk and resilience so they would be interested in the discussion on the vital role they can play in building resilience in their communities. Increasing awareness that perceived risk can be very different from the real threat is the motivation behind this study. The main objectives of this study include identifying and quantifying the gap between people’s perception of exposure and susceptibility to the risk and a lack of coping capacity and objective assessment of risk and resilience, as well as estimating an integrated measure of disaster resilience in a community. The proposed method has been applied to floods as an example, using actual data on the geomorphology of the study area, including terrain and low lying regions. It is hoped that the study will encourage a broader debate if a unified strategy for disaster resilience would be feasible and beneficial in Canada.

The Social Life of Heatwave in London: Recasting the Role of Community and Resilience - Nobert, Sebastien; Pelling, Mark (Framing Community Disaster Resilience, 2018)
Keywords: Nobert_Sebastien

On the relation between weather-related disaster impacts, vulnerability and climate change - Visser, Hans; Petersen, Arthur C.; Ligtvoet, Willem (Climatic Change, 2014)
Disasters such as floods, storms, heatwaves and droughts can have enormous implications for health, the environment and economic development. In this article, we address the question of how climate change might have influenced the impact of weather-related disasters. This relation is not straightforward, since disaster burden is not influenced by weather and climate events alone—other drivers are growth in population and wealth, and changes in vulnerability. We normalized disaster impacts, analyzed trends in the data and compared them with trends in extreme weather and climate events and vulnerability, following a 3 by 4 by 3 set-up, with three disaster burden categories, four regions and three extreme weather event categories. The trends in normalized disaster impacts show large differences between regions and weather event categories. Despite these variations, our overall conclusion is that the increasing exposure of people and economic assets is the major cause of increasing trends in disaster impacts. This holds for long-term trends in economic losses as well as the number of people affected. We also found similar, though more qualitative, results for the number of people killed; in all three cases, the role played by climate change cannot be excluded. Furthermore, we found that trends in historic vulnerability tend to be stable over time, despite adaptation measures taken by countries. Based on these findings, we derived disaster impact projections for the coming decades. We argue that projections beyond 2030 are too uncertain, not only due to unknown changes in vulnerability, but also due to increasing non-stationarities in normalization relations.

At Risk: Natural Hazards, People's Vulnerability and Disasters - Wisner, Benjamin Goodwin; Blaikie, Piers; Cannon, Terry; Davis, Ian J. (1994)
Many disasters are a complex mix of natural hazards and human action. At Risk argues that the social, political and economic environment is as much a cause of disasters as the natural environment. Published within the International Decade of Natural Hazard Reduction, this book suggests ways in which both the social and natural sciences can be analytically combined through a 'disaster pressure and release' model. Arguing that the concept of vulnerability is central to an understanding of disasters and their prevention or mitigation, the authors explore the extent and ways in which people gain access to resources. Individual chapters apply analytical concepts to famines and drought, biological hazards, floods, coastal storms, and earthquakes, volcanos and landslides - the hazards that become disasters'. Finally, the book draws practical and policy conclusions to promote a safer environment and reduce vulnerability.

Spatiotemporal Variations in Meteorological Disasters and Vulnerability in China During 2001–2020 - Li, Ying; Zhao, Shanshan; Zhao, Shiqiang; Wang, Guojie (Frontiers in Earth Science, 2021)
Based on the Yearbook of Meteorological Disasters in China, we analyzed the spatiotemporal variations in major meteorological disaster (MD) losses at the provincial scale during 2001–2020 to determine the spatiotemporal variations in MDs and vulnerability in China. Our results suggest that the impacts of MDs, including floods, droughts, hail and strong winds (HSs), low temperature and frosts (LTFs), and typhoons, have been substantial in China. MDs in China affect an average of 316.3 million people and 34.3 million hectares of crops each year, causing 1,739 deaths and costing 372.3 billion yuan in direct economic losses (DELs). Floods and droughts affected more of the population in China than the other MDs. Fatalities and DELs were mainly caused by floods, and the affected crop area was mainly impacted by drought. The national average MD losses decreased significantly, except for DELs. The trends in the affected population and crop area were mainly caused by droughts, and the trends in fatalities and DELs were dominated by floods. Floods and typhoons showed increasing influence in the last two decades relative to other disasters. The annual mean and long-term trends in MD losses exhibited regional heterogeneity and were subject to different dominant hazards in different regions. The disaster losses and their trends in southeastern China were mainly attributed to typhoons. The affected population, crop area, and DELs were all significantly and positively correlated with exposure. The vulnerability of the population, crops, and economy tended to decrease. Economic development reduced the vulnerability of the population and economy but showed no significant influence on the vulnerability of crops. Our findings suggest that more focus should be placed on the impacts of floods and typhoons and that socioeconomic development has an important influence on the vulnerability of the population and economy. These results provide a foundation for designing effective disaster prevention and mitigation measures.