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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

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

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

A process-based approach to restoring depositional river valleys to Stage 0, an anastomosing channel network - Powers, Paul D.; Helstab, Matt; Niezgoda, Sue L. (River Research and Applications, 2019)
Stream restoration approaches most often quantify habitat degradation, and therefore recovery objectives, on aquatic habitat metrics based on a narrow range of species needs (e.g., salmon and trout), as well as channel evolution models and channel design tools biased toward single-threaded, and “sediment-balanced” channel patterns. Although this strategy enhances perceived habitat needs, it often fails to properly identify the underlying geomorphological and ecological processes limiting species recovery and ecosystem restoration. In this paper, a unique process-based approach to restoration that strives to restore degraded stream, river, or meadow systems to the premanipulated condition is presented. The proposed relatively simple Geomorphic Grade Line (GGL) design method is based on Geographic Information System (GIS) and field-based analyses and the development of design maps using relative elevation models that expose the relic predisturbance valley surface. Several case studies are presented to both describe the development of the GGL method and to illustrate how the GGL method of evaluating valley surfaces has been applied to Stage 0 restoration design. The paper also summarizes the wide applicability of the GGL method, the advantages and limitations of the method, and key considerations for future designers of Stage 0 systems anywhere in the world. By presenting this ongoing Stage 0 restoration work, the authors hope to inspire other practitioners to embrace the restoration of dynamism and diversity through restoring the processes that create multifaceted river systems that provide long-term resiliency, meta-stability, larger and more complex and diverse habitats, and optimal ecosystem benefits.
Keywords: Ouvrage_Collectif_Numéro1

A systematic review of school‐based interventions and their outcomes for youth exposed to traumatic events - Yohannan, Justina; Carlson, John S. (Psychology in the Schools, 2019)
Abstract Youth exposed to traumatic events are at higher risk for negative developmental outcomes, including low academic performance, poor social skills, and mental health concerns. To best address these risks, school‐based intervention services, and trauma‐informed practices can be provided. The goal of this study was to systematically review the intervention research conducted on school‐based trauma interventions, with specific attention to examine intervention effectiveness, feasibility, and acceptability across studies. It was found that feasibility and acceptability are not frequently examined, though the data available showed that Enhancing Resiliency Amongst Students Experiencing‐Stress (ERASE‐Stress) and school‐based cognitive behavioral therapy (CBT) had high rates of fidelity; and school‐based CBT had high levels of acceptability. The review also examined demographic variables and found that U. S.‐based research reported racially/ethnically diverse samples, and most samples were from low‐income populations. Most studies examined youth exposed to war‐ and terror‐related traumas or natural disaster‐related traumas. Additionally, this review provides future directions for research and reveals the need for further research on intervention feasibility and acceptability. A brief description of practice recommendations based on prior research has also been included. It also exposes the need for studies that examine various student demographic variables that are currently not examined and consistency in rating scale use in school‐based trauma intervention research.
Keywords: Ouvrage_Collectif_Numéro1

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

When disaster strikes: Under-insurance in Australian households - Booth, Kate; Tranter, Bruce (Urban Studies, 2018)
In undertaking what we believe is the first national-scale study of its kind, we provide methodologically transparent, statistically robust insights into associations and potential unfolding effects of house and contents under-insurance. We identify new dimensions in the complex relationship between householders and insurance, including the salience of interpersonal – and likely institutional – trust. Under-insurance is (re)produced along socio-economic and geographical lines, with those of lower socio-economic status or living in cities more likely to be under-insured. Should a disaster strike, such communities are likely to suffer further disadvantage, especially if governments continue to shift the responsibility for risk onto households. Our findings support the observation that insurance can contribute to increasing socio-economic urban polarisation in light of natural disasters. We conclude by considering how under-insurance may contribute to growing urban social stratification, as well as how it may produce situated ethical and political responses that exceed neoliberal aspirations.
Keywords: Ouvrage_Collectif_Numéro1

Accounting for three sources of uncertainty in ensemble hydrological forecasting - Thiboult, Antoine; Anctil, François; Boucher, Marie-Amélie (Hydrology and Earth System Sciences, 2016)
Abstract. Seeking more accuracy and reliability, the hydrometeorological community has developed several tools to decipher the different sources of uncertainty in relevant modeling processes. Among them, the ensemble Kalman filter (EnKF), multimodel approaches and meteorological ensemble forecasting proved to have the capability to improve upon deterministic hydrological forecast. This study aims to untangle the sources of uncertainty by studying the combination of these tools and assessing their respective contribution to the overall forecast quality. Each of these components is able to capture a certain aspect of the total uncertainty and improve the forecast at different stages in the forecasting process by using different means. Their combination outperforms any of the tools used solely. The EnKF is shown to contribute largely to the ensemble accuracy and dispersion, indicating that the initial conditions uncertainty is dominant. However, it fails to maintain the required dispersion throughout the entire forecast horizon and needs to be supported by a multimodel approach to take into account structural uncertainty. Moreover, the multimodel approach contributes to improving the general forecasting performance and prevents this performance from falling into the model selection pitfall since models differ strongly in their ability. Finally, the use of probabilistic meteorological forcing was found to contribute mostly to long lead time reliability. Particular attention needs to be paid to the combination of the tools, especially in the EnKF tuning to avoid overlapping in error deciphering.
Keywords: Ouvrage_Collectif_Numéro1

River predisposition to ice jams: a simplified geospatial model - De Munck, Stéphane; Gauthier, Yves; Bernier, Monique; Chokmani, Karem; Légaré, Serge (Natural Hazards and Earth System Sciences, 2017)
Abstract. Floods resulting from river ice jams pose a great risk to many riverside municipalities in Canada. The location of an ice jam is mainly influenced by channel morphology. The goal of this work was therefore to develop a simplified geospatial model to estimate the predisposition of a river channel to ice jams. Rather than predicting the timing of river ice breakup, the main question here was to predict where the broken ice is susceptible to jam based on the river's geomorphological characteristics. Thus, six parameters referred to potential causes for ice jams in the literature were initially selected: presence of an island, narrowing of the channel, high sinuosity, presence of a bridge, confluence of rivers, and slope break. A GIS-based tool was used to generate the aforementioned factors over regular-spaced segments along the entire channel using available geospatial data. An ice jam predisposition index (IJPI) was calculated by combining the weighted optimal factors. Three Canadian rivers (province of Québec) were chosen as test sites. The resulting maps were assessed from historical observations and local knowledge. Results show that 77 % of the observed ice jam sites on record occurred in river sections that the model considered as having high or medium predisposition. This leaves 23 % of false negative errors (missed occurrence). Between 7 and 11 % of the highly predisposed river sections did not have an ice jam on record (false-positive cases). Results, limitations, and potential improvements are discussed.
Keywords: Ouvrage_Collectif_Numéro1

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

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

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

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

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

A comparative assessment of hydrologic models of varying complexity applied to a semi-arid region (Sardinia, Italy). for climate change studies - Perra, Enrica (Università degli Studi di Cagliari - Université du Québec, Institut national de la recherche scientifique, 2018)
L'évaluation de l'impact hydrologique du changement climatique présente une importance particulière pour les bassins de la Méditerranée, qui sont très sensibles aux événements hydrologiques extrêmes. La modélisation des systèmes aussi complexes pour la gestion des ressources hydriques est un défi difficile. L'objectif global de ce travail est de contribuer au développement d'une approche de modélisation qui permette l'évaluation de l'impact hydrologique du changement climatique sur deux bassins de la Méditerranée, localisés en Sardaigne. Cette contribution se concentre sur deux sujets principaux: comprendre comment la représentation physique des modèles hydrologiques grave sur l'évaluation de l'impact hydrologique dû au changement climatique sur un bassin avec un climat semi-aride, le Rio Mannu di San Sperate, et montrer comme le modélisation avancé puisse aider à définir de mesures de modération et adaptation dans un système complexe enclin aux événements hydrique extrêmes, le Flumendosa, en conditions de changement climatique. Pour atteindre cet objectif le travail s'articule en trois phases. Les effets du changement climatique sur le bassin du Rio Mannu sont évalués à travers la comparaison des résultats de cinq modèles hydrologiques, CATchment HYdrology (CATHY), Soil and Water Assessment Tool (SWAT), TIN-based Real time Integrated Basin Simulator (tRIBS), TOPographic Kinematic APproximation and Integration-eXtended (TOPKAPI-X), and Water flow and balance Simulation Model (WASIM), en utilisant comme forçage atmosphérique les données de quatre combinaisons de modèles climatiques globaux (GCM) et régionaux (RCM). Pour évaluer les incertitudes une métrique récemment proposée est utilisée: les résultats des modèles sont comparés pendant une période de référence et future, en utilisant l'index de corrélation de Pearson et le bias de Duveiller. Même si certaines différences existent, en tout les modèles hydrologiques montrent une bonne concordance, et ils répondent de manière semblable à la réduction de la précipitation et à l'accroissement de la température prévu par les modèles climatiques. Il s'attend donc que le bassin dans l'avenir sera sujet à une réduction de la disponibilité de ressource hydrique, avec des conséquences négatives en particulier pour le secteur agricole. Une comparaison détaillée des réponses obtenue sur le même bassin avec trois modèles hydrologique à base physique avec différent degré pour ce qui concerne la représentation des procès physiques et des caractéristiques du terrain, CATHY, TOPKAPI-X, tRIBS, est effectué dans le but de tester la transférabilité des paramètres entre les trois modèles hydrologiques, avec une attention particulière sur les difficultés relevées dans les périodes de calibrage et validation. Tandis que les trois modèles ont répondu de manière semblable pendant la période de calibrage, significatives différences ont été relevées pendant la période de validation, caractérisé par un climat très sec, avec le modèle CATHY, qu'il a produit un très bas décharge. En conséquence, pour obtenir résultats satisfaisants avec le modèle CATHY, l’hypothèse de croûtage de sol a été assumée, sur la base dont la couche premier de sol a été modelée avec une conductibilité hydraulique saturée réduite. Finalement le modèle TOPKAPI-X est implémenté sur un des principaux bassins de la Sardaigne, d'importance stratégique pour le système hydrique de la région, le Flumendosa, afin d’évaluer les effets du changement climatique à plus grande échelle. Le modèle répond avec une diminution des valeurs de décharge, contenu hydrique et évapotranspiration réelle à la réduction de la précipitation et accroissement des températures prévus par les modèles climatiques en donnant aussi support à une scène future de carence de la ressource hydrique dans ce bassin de la zone Méditerranéenne. Assessing the hydrologic impacts of climate change is of great importance in the Mediterranean basins, which are heavily sensitive to climate variability, with significant impacts on water resources and hydrologic extremes. Modeling such complex systems to manage water resources and predict hydrologic extremes is a difficult task. The overall aim of the work described in this thesis is to bring a contribution in developing a modeling approach that allows evaluation of local hydrologic impacts of climate changes in two Mediterranean catchments located in Sardinia. This contribution revolves around two main themes: understanding how physical representation of hydrologic models can affect hydrologic impact assessment under climate change on a semi-arid basin of the Mediterranean region, the Rio Mannu catchment, and demonstrating how advanced hydrologic modeling can help in defining adaptation measures in a complex water system, the Flumendosa basin, under climate change. The work to achieve the general objective is elaborated into three stages. The effects of climate change are evaluated on the Rio Mannu catchment through comparison of the results from five hydrologic models, CATchment HYdrology (CATHY), Soil and Water Assessment Tool (SWAT), TIN-based Real time Integrated Basin Simulator (tRIBS), TOPographic Kinematic APproximation and Integration-eXtended (TOPKAPI-X), and Water flow and balance Simulation Model (WASIM), and using as atmospheric input outputs of four climate global (GCM) and regional (RCM) model combinations. In order to evaluate uncertainties, a recently proposed metric is used: climate and hydrologic models results are compared in terms of agreement with each other in reference and future periods using Pearson correlation values and Duveiller bias. Notwithstanding some differences, overall the five hydrologic models show good agreement, and they respond similarly to the reduced precipitation and increased temperatures predicted by the climate models, lending strong support to a future scenario of increased water shortages for this region of the Mediterranean, with negative consequences especially for the agricultural sector. Detailed comparison of the responses obtained with three physically based hydrologic models, but to varying degrees as regards physical processes and terrain features representation – CATHY, tRIBS, and TOPKAPI-X – on the same catchment is carried out, with the aim to test the transferability of parameters between the three hydrologic models, focusing in particular on the calibration and validation difficulties. While the three hydrologic models responded similarly during the calibration year, significant differences were found for the drier validation period for the CATHY model, which produced very low streamflow. To obtain satisfactory results for the CATHY model, an hypothesis of soil crusting was assumed and the first soil layer was modeled with a lower saturated hydraulic conductivity. Finally, the TOPKAPI-X model is applied on a large Sardinian basin prone to extreme flood events, the Flumendosa basin, to assess the hydrologic impact of climate change at much larger scale. The model responds with decreasing value of discharge, soil water content, and actual evapotranspiration to the reduced precipitation and increased temperature predicted by the climate models, lending strong support to a future scenario of increased water shortages also in this basin of the Mediterranean region. La valutazione dell’impatto idrologico del cambiamento climatico riveste particolare importanza per i bacini del Mediterraneo, sensibili ad eventi idrologici estremi. Modellizzare dei sistemi così complessi per la gestione della risorse idriche è una sfida difficile. L’obiettivo globale di questo lavoro è contribuire allo sviluppo di un approccio modellistico che consenta la valutazione dell’impatto idrologico del cambiamento climatico su due bacini del Mediterraneo localizzati in Sardegna. Questo contributo si focalizza su due temi principali: capire come la rappresentazione fisica dei modelli idrologici incida sulla valutazione dell’impatto idrologico dovuto al cambiamento climatico su un bacino con un clima semi-arido, il Rio Mannu di San Sperate, e dimostrare come la modellizzazione avanzata possa aiutare nel definire misure di adattamento in un sistema idrico complesso incline ad eventi estremi, il Flumendosa, in condizioni di cambiamento climatico. Per raggiungere tale obiettivo il lavoro si articola in tre fasi. Gli effetti del cambiamento climatico sul bacino del Rio Mannu sono stati valutati attraverso il confronto dei risultati di cinque modelli idrologici, CATchment HYdrology (CATHY), Soil and Water Assessment Tool (SWAT), TIN-based Real time Integrated Basin Simulator (tRIBS), TOPographic Kinematic APproximation and Integration-eXtended (TOPKAPI-X), and Water flow and balance Simulation Model (WASIM), utilizzando come forzante atmosferica gli output di quattro combinazioni di modelli climatici globali (GCM) e regionali (RCM). Per valutare le incertezze è stata utilizzata una metrica recentemente proposta: i risultati dei modelli sono stati comparati durante un periodo di riferimento e futuro, utilizzando l’indice di correlazione di Pearson e il bias di Duveiller. Pur con qualche differenza, complessivamente i modelli idrologici mostrano una buona concordanza tra loro, e rispondono in maniera simile alla riduzione della precipitazione e all’incremento della temperatura previsti dai modelli climatici. Ci si aspetta pertanto che il bacino nel futuro sarà soggetto ad una riduzione della disponibilità di risorsa idrica, con conseguenze negative in particolare per il settore agricolo. È stato effettuato un confronto dettagliato delle risposte ottenute sullo stesso bacino con tre modelli idrologici fisicamente basati di diverso grado per quanto riguarda la rappresentazione dei processi fisici e delle caratteristiche del terreno, CATHY, TOPKAPI-X, tRIBS, con lo scopo di testare la trasferibilità dei parametri tra i tre modelli idrologici, concentrandosi sulle difficoltà riscontrate nei periodi di calibrazione e validazione. Mentre i tre modelli hanno risposto in maniera simile durante il periodo di calibrazione, sono state riscontrate significative differenze durante il periodo di validazione, caratterizzato da un clima molto secco, con il modello CATHY, che ha prodotto una portata molto bassa. Pertanto, per ottenere risultati soddisfacenti con il modello CATHY, è stata assunta l’ipotesi di soil crusting, sulla base della quale il primo strato di suolo è stato modellato con una ridotta conducibilità idraulica satura. Infine il modello TOPKAPI-X è stato implementato su uno dei principali bacini sardi di importanza strategica per il sistema idrico della regione, il Flumendosa, per valutare gli effetti del cambiamento climatico a scala maggiore. Il modello risponde con una diminuzione dei valori di portata, contenuto idrico ed evapotraspirazione reale alla riduzione della precipitazione ed incremento della temperature previsto dai modelli climatici, dando supporto ad uno scenario futuro di carenza della risorsa idrica anche in questo bacino dell’area Mediterranea.

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

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

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

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

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

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

Establishing the Transitory Existence of Amorphous Phases in Crystallization Pathways by the CLASSIC NMR Technique - Hughes, Colan E.; Williams, P. Andrew; Kariuki, Benson M.; Harris, Kenneth D. M. (Chemphyschem: A European Journal of Chemical Physics and Physical Chemistry, 2018)
With the growing realization that crystallization processes may evolve through a sequence of different solid forms, including amorphous precursor phases, the development of suitable in-situ experimental probes is essential for comprehensively mapping the time-evolution of such processes. Here we demonstrate that the CLASSIC NMR (Combined Liquid- And Solid-State In-situ Crystallization NMR) strategy is a powerful technique for revealing the transitory existence of amorphous phases during crystallization processes, applying this technique to study crystallization of dl-menthol and l-menthol from their molten liquid phases. The CLASSIC NMR results provide direct insights into the conditions (including the specific time period) under which the molten liquid phase, transitory amorphous phases and final crystalline phases exist during these crystallization processes.

Groundwater Buffers Decreasing Glacier Melt in an Andean Watershed—But Not Forever - Somers, Lauren D.; McKenzie, Jeffrey M.; Mark, Bryan G.; Lagos, Pablo; Ng, Gene‐Hua Crystal; Wickert, Andrew D.; Yarleque, Christian; Baraër, Michel; Silva, Yamina (Geophysical Research Letters, 2019)
Abstract Accelerating mountain glacier recession in a warming climate threatens the sustainability of mountain water resources. The extent to which groundwater will provide resilience to these water resources is unknown, in part due to a lack of data and poorly understood interactions between groundwater and surface water. Here we address this knowledge gap by linking climate, glaciers, surface water, and groundwater into an integrated model of the Shullcas Watershed, Peru, in the tropical Andes, the region experiencing the most rapid mountain‐glacier retreat on Earth. For a range of climate scenarios, our model projects that glaciers will disappear by 2100. The loss of glacial meltwater will be buffered by relatively consistent groundwater discharge, which only receives minor recharge (~2%) from glacier melt. However, increasing temperature and associated evapotranspiration, alongside potential decreases in precipitation, will decrease groundwater recharge and streamflow, particularly for the RCP 8.5 emission scenario. , Plain Language Summary Mountain regions play an important role in water supply, because meltwater from snow and ice feeds rivers during dry periods. Groundwater (water stored in the pore spaces of soils and rock), which flows into rivers, is also an important store of water in mountain areas and may help to protect water resources against the negative impacts of shrinking mountain glaciers. We used extensive field measurements and computer modeling of the Shullcas Watershed in the Peruvian Andes to determine the current and future role of groundwater in the face of climate change. Our model projects that glaciers in our study area will disappear by 2100. The loss of glacier meltwater is buffered in the short term (~30 years) by consistent groundwater flow to rivers. However, in the long term (>60 years), precipitation is expected to decrease and rising temperatures lead to increased evaporation and water use by plants. These factors reduce groundwater recharge and storage, causing dry season streamflow to drop. , Key Points Groundwater accounts for a large fraction of streamflow and only receives minor (~2%) recharge from glaciers in the study catchment in Peru As meltwater decreases, groundwater provides consistent discharge in the near term (~30 years), becoming a larger fraction of streamflow In the long term (>60 years), groundwater storage and discharge decrease in response to higher evapotranspiration and lower precipitation
Keywords: Baraer_Michel

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

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

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

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

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

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

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

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

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

Power and politics in climate change adaptation efforts: Struggles over authority and recognition in the context of political instability - Nightingale, Andrea J. (Geoforum, 2017)

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

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

Interface bureaucrats and the everyday remaking of climate interventions: Evidence from climate change adaptation in Zambia - Funder, Mikkel; Mweemba, Carol Emma (Global Environmental Change, 2019)
Keywords: Ouvrage_Collectif_Numéro1

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

Differing Modes of Biotic Connectivity within Freshwater Ecosystem Mosaics - Mushet, David M.; Alexander, Laurie C.; Bennett, Micah; Schofield, Kate; Christensen, Jay R.; Ali, Genevieve; Pollard, Amina; Fritz, Ken; Lang, Megan W. (JAWRA Journal of the American Water Resources Association, 2019)
Abstract We describe a collection of aquatic and wetland habitats in an inland landscape, and their occurrence within a terrestrial matrix, as a “freshwater ecosystem mosaic” (FEM). Aquatic and wetland habitats in any FEM can vary widely, from permanently ponded lakes, to ephemerally ponded wetlands, to groundwater‐fed springs, to flowing rivers and streams. The terrestrial matrix can also vary, including in its influence on flows of energy, materials, and organisms among ecosystems. Biota occurring in a specific region are adapted to the unique opportunities and challenges presented by spatial and temporal patterns of habitat types inherent to each FEM. To persist in any given landscape, most species move to recolonize habitats and maintain mixtures of genetic materials. Species also connect habitats through time if they possess needed morphological, physiological, or behavioral traits to persist in a habitat through periods of unfavorable environmental conditions. By examining key spatial and temporal patterns underlying FEMs, and species‐specific adaptations to these patterns, a better understanding of the structural and functional connectivity of a landscape can be obtained. Fully including aquatic, wetland, and terrestrial habitats in FEMs facilitates adoption of the next generation of individual‐based models that integrate the principles of population, community, and ecosystem ecology. , Research Impact Statement : Fully including aquatic, wetland, and terrestrial habitats facilitates adoption of next‐generation, individual‐based, models that integrate principles of population, community, and ecosystem ecology.

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

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

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

Evaluating Alternative Techniques Floodplain Mapping - Wolman, M. Gordon (Water Resources Research, 1971)
A variety of techniques is available for providing information on the frequency and extent of flooding in river valleys. These techniques include the use of physiography, pedology, vegetation, occasional floods, regional floods of selected frequency, and flood profiles and backwater curves. Preliminary estimates of costs suggest that these range from a low of $1–4/mile of channel to a high of $400–1000/mile of channel. All estimates of flood hazards and damages contain significant uncertainties deriving from the variability and uncertainty of the estimates of hydrologic, hydraulic, and social phenomena. An accelerating demand for information coupled with recognition of the inherent element of judgment in any determination of flood or damage zones suggests additional emphasis on the adoption of different mapping techniques appropriate to the needs of different locations.
Keywords: Ouvrage_Collectif_Numéro1

Flood Spatial Modeling in Northern Iran Using Remote Sensing and GIS: A Comparison between Evidential Belief Functions and Its Ensemble with a Multivariate Logistic Regression Model - Tien Bui, Duie; Khosravi, Khabat; Shahabi, Himan; Daggupati, Prasad; Adamowski, Jan F.; M.Melesse, Assefa; Thai Pham, Binh; Pourghasemi, Hamid Reza; Mahmoudi, Mehrnoosh; Bahrami, Sepideh; Pradhan, Biswajeet; Shirzadi, Ataollah; et al. (Remote Sensing, 2019)
Floods are some of the most dangerous and most frequent natural disasters occurring in the northern region of Iran. Flooding in this area frequently leads to major urban, financial, anthropogenic, and environmental impacts. Therefore, the development of flood susceptibility maps used to identify flood zones in the catchment is necessary for improved flood management and decision making. The main objective of this study was to evaluate the performance of an Evidential Belief Function (EBF) model, both as an individual model and in combination with Logistic Regression (LR) methods, in preparing flood susceptibility maps for the Haraz Catchment in the Mazandaran Province, Iran. The spatial database created consisted of a flood inventory, altitude, slope angle, plan curvature, Topographic Wetness Index (TWI), Stream Power Index (SPI), distance from river, rainfall, geology, land use, and Normalized Difference Vegetation Index (NDVI) for the region. After obtaining the required information from various sources, 151 of 211 recorded flooding points were used for model training and preparation of the flood susceptibility maps. For validation, the results of the models were compared to the 60 remaining flooding points. The Receiver Operating Characteristic (ROC) curve was drawn, and the Area Under the Curve (AUC) was calculated to obtain the accuracy of the flood susceptibility maps prepared through success rates (using training data) and prediction rates (using validation data). The AUC results indicated that the EBF, EBF from LR, EBF-LR (enter), and EBF-LR (stepwise) success rates were 94.61%, 67.94%, 86.45%, and 56.31%, respectively, and the prediction rates were 94.55%, 66.41%, 83.19%, and 52.98%, respectively. The results showed that the EBF model had the highest accuracy in predicting flood susceptibility within the catchment, in which 15% of the total areas were located in high and very high susceptibility classes, and 62% were located in low and very low susceptibility classes. These results can be used for the planning and management of areas vulnerable to floods in order to prevent flood-induced damage; the results may also be useful for natural disaster assessment.
Keywords: Site_internet_RIISQ

The Monetary Measurement of Flood Damage and the Valuation of the Proactive Policies in Sicily - Trovato, Maria Rosa; Giuffrida, Salvatore (Geosciences, 2018)
Although floods, as well as other natural disasters, can be considered as relevant causes of intra-generational inequalities, frequent catastrophes and the resulting damage to the territory can be seen as a consequence of a generalized indifference about future. Land protection is one of the societal issues typically concerning inter-generational solidarity, involving the administrative system in the implementation of proactive policies. In the last three decades, the widespread demand for subsidiarity has made local communities more and more independent, so that attention to the long-term effects—typically concerning the territorial system as a whole at geographical scale—has been dispersed, and the proactive policies that come from the central government have become more ineffective. Regarding the case of the 2009 flood in the Fiumedinisi-Capo Peloro river basin in North Eastern Sicily, we propose an economic valuation of the land protection policy. This valuation, compared to the cost of recovery of the damaged areas, can provide helpful information on the decision-making process concerning the trade-off between reactive and proactive land policy. The economic value of land protection was calculated by means of the method of the imputed preferences, to obtain a real measure of the social territorial value from the point of view of the harmony between social system and environment. This method consists of an estimate based on the attribution of the expenditures according to the importance of the different areas. Since the value of land protection has been calculated by discounting the expenditures stream, some considerations about the economic significance of the proactive policy are referred to the role played by the social discount rate in the inter-temporal economic calculation.

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

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

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

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

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

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

What determines flood risk perception? A review of factors of flood risk perception and relations between its basic elements - Lechowska, Ewa (Natural Hazards, 2018)
While the methods of risk analysis are generally based on objective measurements, the subjective assessment of risk, such as risk perception, is currently considered a crucial aspect in the context of flood risk management. Risk perception is regarded as an assessment of the perceived probability of hazard and the perceived probability of the results (most often—negative consequences). The work attempts to answer the question: What determines flood risk perception? The knowledge of the factors influencing flood risk perception can solve the issue of the society’s underestimation of flood risk. This issue was considered both in terms of the impact of particular factors on flood risk perception and the interrelationship between three characteristics of flood risk perception: preparedness, worry and awareness. The results were developed based on critical analysis of the empirical research. The review shows that the way particular characteristics determine flood risk perception is not clear and many authors show the diverse conclusions from the similar research. Taking into account various research results, the following factors were distinguished: primary (which clearly influence risk perception), secondary (which influence it unclearly and require further research) and intervening (often describing the context). The organization of the results of the research on the flood risk assessment conducted herein aims to improve the understanding of the human perception of flood risk and, as a result, will lead to the decrease in flood risk by improving the communication of the issue and motivating the residents of the endangered areas to take actions that reduce the negative effects of floods.

Ice‐jam flood risk assessment and mapping - Lindenschmidt, Karl‐Erich; Das, Apurba; Rokaya, Prabin; Chu, Thuan (Hydrological Processes, 2016)
Abstract In northern regions, river ice‐ jam flooding can be more severe than open‐water flooding causing property and infrastructure damages, loss of human life and adverse impacts on aquatic ecosystems. Very little has been performed to assess the risk induced by ice‐related floods because most risk assessments are limited to open‐water floods. The specific objective of this study is to incorporate ice‐jam numerical modelling tools (e.g. RIVICE, Monte‐Carlo simulation) into flood hazard and risk assessment along the Peace River at the Town of Peace River (TPR) in Alberta, Canada. Adequate historical data for different ice‐jam and open‐water flooding events were available for this study site and were useful in developing ice‐affected stage‐frequency curves. These curves were then applied to calibrate a numerical hydraulic model, which simulated different ice jams and flood scenarios along the Peace River at the TPR. A Monte‐Carlo analysis was then carried out to acquire an ensemble of water level profiles to determine the 1 : 100‐year and 1 : 200‐year annual exceedance probability flood stages for the TPR. These flood stages were then used to map flood hazard and vulnerability of the TPR. Finally, the flood risk for a 200‐year return period was calculated to be an average of $32/m 2 /a ($/m 2 /a corresponds to a unit of annual expected damages or risk). Copyright © 2016 John Wiley & Sons, Ltd.
Keywords: Ouvrage_Collectif_Numéro1

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

Gravel-bed river floodplains are the ecological nexus of glaciated mountain landscapes - Hauer, F. Richard; Locke, Harvey; Dreitz, Victoria J.; Hebblewhite, Mark; Lowe, Winsor H.; Muhlfeld, Clint C.; Nelson, Cara R.; Proctor, Michael F.; Rood, Stewart B. (Science Advances, 2016)
Gravel-bed rivers are disproportionately important to regional biodiversity, species interactions, connectivity, and conservation. , Gravel-bed river floodplains in mountain landscapes disproportionately concentrate diverse habitats, nutrient cycling, productivity of biota, and species interactions. Although stream ecologists know that river channel and floodplain habitats used by aquatic organisms are maintained by hydrologic regimes that mobilize gravel-bed sediments, terrestrial ecologists have largely been unaware of the importance of floodplain structures and processes to the life requirements of a wide variety of species. We provide insight into gravel-bed rivers as the ecological nexus of glaciated mountain landscapes. We show why gravel-bed river floodplains are the primary arena where interactions take place among aquatic, avian, and terrestrial species from microbes to grizzly bears and provide essential connectivity as corridors for movement for both aquatic and terrestrial species. Paradoxically, gravel-bed river floodplains are also disproportionately unprotected where human developments are concentrated. Structural modifications to floodplains such as roads, railways, and housing and hydrologic-altering hydroelectric or water storage dams have severe impacts to floodplain habitat diversity and productivity, restrict local and regional connectivity, and reduce the resilience of both aquatic and terrestrial species, including adaptation to climate change. To be effective, conservation efforts in glaciated mountain landscapes intended to benefit the widest variety of organisms need a paradigm shift that has gravel-bed rivers and their floodplains as the central focus and that prioritizes the maintenance or restoration of the intact structure and processes of these critically important systems throughout their length and breadth.
Keywords: Ouvrage_Collectif_Numéro1

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

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

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

Which downscaled rainfall data for climate change impact studies in urban areas? Review of current approaches and trends - Gooré Bi, Eustache; Gachon, Philippe; Vrac, Mathieu; Monette, Frédéric (Theoretical and Applied Climatology, 2017)
Changes in extreme precipitation should be one of the primary impacts of climate change (CC) in urban areas. To assess these impacts, rainfall data from climate models are commonly used. The main goal of this paper is to report on the state of knowledge and recent works on the study of CC impacts with a focus on urban areas, in order to produce an integrated review of various approaches to which future studies can then be compared or constructed. Model output statistics (MOS) methods are increasingly used in the literature to study the impacts of CC in urban settings. A review of previous works highlights the non-stationarity nature of future climate data, underscoring the need to revise urban drainage system design criteria. A comparison of these studies is made difficult, however, by the numerous sources of uncertainty arising from a plethora of assumptions, scenarios, and modeling options. All the methods used do, however, predict increased extreme precipitation in the future, suggesting potential risks of combined sewer overflow frequencies, flooding, and back-up in existing sewer systems in urban areas. Future studies must quantify more accurately the different sources of uncertainty by improving downscaling and correction methods. New research is necessary to improve the data validation process, an aspect that is seldom reported in the literature. Finally, the potential application of non-stationarity conditions into generalized extreme value (GEV) distribution should be assessed more closely, which will require close collaboration between engineers, hydrologists, statisticians, and climatologists, thus contributing to the ongoing reflection on this issue of social concern.
Keywords: Gachon_Philippe

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

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

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

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

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

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

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

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

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

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

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

Raising risk preparedness by flood risk communication - Maidl, E.; Buchecker, M. (Natural Hazards and Earth System Sciences, 2015)
Abstract. During the last decade, most European countries have produced hazard maps of natural hazards, but little is known about how to communicate these maps most efficiently to the public. In October 2011, Zurich's local authorities informed owners of buildings located in the urban flood hazard zone about potential flood damage, the probability of flood events and protection measures. The campaign was based on the assumptions that informing citizens increases their risk awareness and that citizens who are aware of risks are more likely to undertake actions to protect themselves and their property. This study is intended as a contribution to better understand the factors that influence flood risk preparedness, with a special focus on the effects of such a one-way risk communication strategy. We conducted a standardized mail survey of 1500 property owners in the hazard zones in Zurich (response rate main survey: 34 %). The questionnaire included items to measure respondents' risk awareness, risk preparedness, flood experience, information-seeking behaviour, knowledge about flood risk, evaluation of the information material, risk acceptance, attachment to the property and trust in local authorities. Data about the type of property and socio-demographic variables were also collected. Multivariate data analysis revealed that the average level of risk awareness and preparedness was low, but the results confirmed that the campaign had a statistically significant effect on the level of preparedness. The main influencing factors on the intention to prepare for a flood were the extent to which respondents evaluated the information material positively as well as their risk awareness. Respondents who had never taken any previous interest in floods were less likely to read the material. For future campaigns, we therefore recommend repeated communication that is tailored to the information needs of the target population.
Keywords: Ouvrage_Collectif_Numéro1

Communicating disaster risk? An evaluation of the availability and quality of flood maps - Henstra, Daniel; Minano, Andrea; Thistlethwaite, Jason (Natural Hazards and Earth System Sciences, 2019)
Abstract. One of the key priorities for disaster risk reduction is to ensure decision makers, stakeholders, and the public understand their exposure to disaster risk, so that they can take protective action. Flood maps are a potentially valuable tool for facilitating this understanding of flood risk, but previous research has found that they vary considerably in availability and quality. Using an evaluation framework comprising nine criteria grounded in existing scholarship, this study assessed the quality of flood maps available to the public in Canadian communities located in designated flood risk areas. It found that flood maps in most municipalities (62 %) are low quality (meeting less than 50 % of the criteria) and the highest score was 78 % (seven of nine criteria met). The findings suggest that a more concerted effort to produce high-quality, publicly accessible flood maps is required to support Canada's international commitment to disaster risk reduction. Further questions surround possible weighting of quality assessment criteria, whether and how individuals seek out flood maps, and how flood risk information could be better communicated using modern technology.
Keywords: Ouvrage_Collectif_Numéro1

Exploring local risk managers' use of flood hazard maps for risk communication purposes in Baden-Württemberg - Kjellgren, S. (Natural Hazards and Earth System Sciences, 2013)
Abstract. In response to the EU Floods Directive (2007/60/EC), flood hazard maps are currently produced all over Europe, reflecting a wider shift in focus from "flood protection" to "risk management", for which not only public authorities but also populations at risk are seen as responsible. By providing a visual image of the foreseen consequences of flooding, flood hazard maps can enhance people's knowledge about flood risk, making them more capable of an adequate response. Current literature, however, questions the maps' awareness raising capacity, arguing that their content and design are rarely adjusted to laypeople's needs. This paper wants to complement this perspective with a focus on risk communication by studying how these tools are disseminated and marketed to the public in the first place. Judging from communication theory, simply making hazard maps publicly available is unlikely to lead to attitudinal or behavioral effects, since this typically requires two-way communication and material or symbolic incentives. Consequently, it is relevant to investigate whether and how local risk managers, who are well positioned to interact with the local population, make use of flood hazard maps for risk communication purposes. A qualitative case study of this issue in the German state of Baden-Württemberg suggests that many municipalities lack a clear strategy for using this new information tool for hazard and risk communication. Four barriers in this regard are identified: perceived disinterest/sufficient awareness on behalf of the population at risk; unwillingness to cause worry or distress; lack of skills and resources; and insufficient support. These barriers are important to address – in research as well as in practice – since it is only if flood hazard maps are used to enhance local knowledge resources that they can be expected to contribute to social capacity building.
Keywords: Ouvrage_Collectif_Numéro1

Perception and Communication of Flood Risks: A Systematic Review of Empirical Research - Kellens, Wim; Terpstra, Teun; De Maeyer, Philippe (Risk Analysis, 2013)
Flood hazards are the most common and destructive of all natural disasters. For decades, experts have been examining how flood losses can be mitigated. Just as in other risk domains, the study of risk perception and risk communication has gained increasing interest in flood risk management. Because of this research growth, a review of the state of the art in this domain is believed necessary. The review comprises 57 empirically based peer‐reviewed articles on flood risk perception and communication from the Web of Science and Scopus databases. The characteristics of these articles are listed in a comprehensive table, presenting research design, research variables, and key findings. From this review, it follows that the majority of studies are of exploratory nature and have not applied any of the theoretical frameworks that are available in social science research. Consequently, a methodological standardization in measuring and analyzing people's flood risk perceptions and their adaptive behaviors is hardly present. This heterogeneity leads to difficulties in comparing results among studies. It is also shown that theoretical and empirical studies on flood risk communication are nearly nonexistent. The article concludes with a summary on methodological issues in the fields of flood‐risk perception and flood‐risk communication and proposes an agenda for future research.
Keywords: Ouvrage_Collectif_Numéro1

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

Enhancing flash flood risk perception and awareness of mitigation actions through risk communication: A pre-post survey design - Bodoque, J.M.; Díez-Herrero, A.; Amerigo, M.; García, J.A.; Olcina, J. (Journal of Hydrology, 2019)
Keywords: Ouvrage_Collectif_Numéro1

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.

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

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

A place-based model for understanding community resilience to natural disasters - Cutter, Susan L.; Barnes, Lindsey; Berry, Melissa; Burton, Christopher; Evans, Elijah; Tate, Eric; Webb, Jennifer (Global Environmental Change, 2008)

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

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

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

Seniors Who Experienced the Lac-Mégantic Train Derailment Tragedy: What Are the Consequences on Physical and Mental Health? - Maltais, Danielle; Tremblay, Anne-Julie; Labra, Oscar; Fortin, Geneviève; Généreux, Mélissa; Roy, Mathieu; Lansard, Anne-Lise (Gerontology and Geriatric Medicine, 2019)
Introduction: In July 2013, a train derailment caused the death of 47 people and destroyed the downtown area in the city of Lac-Mégantic (Quebec, Canada). This tragedy had several impacts on this small community. Method: Three years after this disaster, we used a representative population-based survey conducted among 800 adults (including 265 seniors aged 65 or above) to assess the physical and mental health of seniors. Results: Several differences were observed in seniors’ physical and mental health based on their level of exposure to the tragedy. Nearly half of seniors highly exposed to the train derailment (41.7%) believe that their health has deteriorated in the past 3 years. The majority of seniors highly exposed to the train derailment (68.7%) also show symptoms of posttraumatic stress disorders. Seniors highly or moderately exposed to the tragedy were also more likely to have found positive changes in their personal and social life as compared with nonexposed seniors. Discussion: A technological disaster such as a train derailment still had negative impacts on seniors’ physical and mental health 3 years later. Conclusion: Public health authorities must tailor prevention and promotion programs to restore health and well-being in this population.
Keywords: Généreux_Mélissa

An interdisciplinary perspective on social and physical determinants of seismic risk - Lin, K.-H. E.; Chang, Y.-C.; Liu, G.-Y.; Chan, C.-H.; Lin, T.-H.; Yeh, C.-H. (Natural Hazards and Earth System Sciences, 2015)
Abstract. While disaster studies researchers usually view risk as a function of hazard, exposure, and vulnerability, few studies have systematically examined the relationships among the various physical and socioeconomic determinants underlying disasters, and fewer have done so through seismic risk analysis. In the context of the 1999 Chi-Chi earthquake in Taiwan, this study constructs three statistical models to test different determinants that affect disaster fatality at the village level, including seismic hazard, exposure of population and fragile buildings, and demographic and socioeconomic vulnerability. The Poisson regression model is used to estimate the impact of these factors on fatalities. Research results indicate that although all of the determinants have an impact on seismic fatality, some indicators of vulnerability, such as gender ratio, percentages of young and aged population, income and its standard deviation, are the important determinants deteriorating seismic risk. These findings have strong social implications for policy interventions to mitigate such disasters.

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

Flood- and Weather-Damaged Homes and Mental Health: An Analysis Using England’s Mental Health Survey - Graham, Hilary; White, Piran; Cotton, Jacqui; McManus, Sally (International Journal of Environmental Research and Public Health, 2019)
There is increasing evidence that exposure to weather-related hazards like storms and floods adversely affects mental health. However, evidence of treated and untreated mental disorders based on diagnostic criteria for the general population is limited. We analysed the Adult Psychiatric Morbidity Survey, a large probability sample survey of adults in England (n = 7525), that provides the only national data on the prevalence of mental disorders assessed to diagnostic criteria. The most recent survey (2014–2015) asked participants if they had experienced damage to their home (due to wind, rain, snow or flood) in the six months prior to interview, a period that included months of unprecedented population exposure to flooding, particularly in Southern England. One in twenty (4.5%) reported living in a storm- or flood-damaged home in the previous six months. Social advantage (home ownership, higher household income) increased the odds of exposure to storm or flood damage. Exposure predicted having a common mental disorder over and above the effects of other known predictors of poor mental health. With climate change increasing the frequency and severity of storms and flooding, improving community resilience and disaster preparedness is a priority. Evidence on the mental health of exposed populations is key to building this capacity.
Keywords: Ouvrage_Collectif_Numéro1

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

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

From Science to Policy and Practice: A Critical Assessment of Knowledge Management before, during, and after Environmental Public Health Disasters - Généreux, Mélissa; Lafontaine, Marc; Eykelbosh, Angela (International Journal of Environmental Research and Public Health, 2019)
Canada regularly faces environmental public health (EPH) disasters. Given the importance of evidence-based, risk-informed decision-making, we aimed to critically assess the integration of EPH expertise and research into each phase of disaster management. In-depth interviews were conducted with 23 leaders in disaster management from Canada, the United States, the United Kingdom, and Australia, and were complemented by other qualitative methods. Three topics were examined: governance, knowledge creation/translation, and related barriers/needs. Data were analyzed through a four-step content analysis. Six critical success factors emerged from the analysis: blending the best of traditional and modern approaches; fostering community engagement; cultivating relationships; investing in preparedness and recovery; putting knowledge into practice; and ensuring sufficient human and financial resources. Several promising knowledge-to-action strategies were also identified, including mentorship programs, communities of practice, advisory groups, systematized learning, and comprehensive repositories of tools and resources. There is no single roadmap to incorporate EPH expertise and research into disaster management. Our findings suggest that preparation for and management of EPH disaster risks requires effective long-term collaboration between science, policy, and EPH practitioners at all levels in order to facilitate coordinated and timely deployment of multi-sectoral/jurisdictional resources when and where they are most needed.
Keywords: Généreux_Mélissa

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

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

Neglecting uncertainties biases house-elevation decisions to manage riverine flood risks - Zarekarizi, Mahkameh; Srikrishnan, Vivek; Keller, Klaus (Nature Communications, 2020)
Abstract Homeowners around the world elevate houses to manage flood risks. Deciding how high to elevate a house poses a nontrivial decision problem. The U.S. Federal Emergency Management Agency (FEMA) recommends elevating existing houses to the Base Flood Elevation (the elevation of the 100-year flood) plus a freeboard. This recommendation neglects many uncertainties. Here we analyze a case-study of riverine flood risk management using a multi-objective robust decision-making framework in the face of deep uncertainties. While the quantitative results are location-specific, the approach and overall insights are generalizable. We find strong interactions between the economic, engineering, and Earth science uncertainties, illustrating the need for expanding on previous integrated analyses to further understand the nature and strength of these connections. Considering deep uncertainties surrounding flood hazards, the discount rate, the house lifetime, and the fragility can increase the economically optimal house elevation to values well above FEMA’s recommendation.
Keywords: Ouvrage_Collectif_Numéro1

Multi-objective decision-making for green infrastructure planning (LID-BMPs) in urban storm water management under uncertainty - Raei, Ehsan; Reza Alizadeh, Mohammad; Reza Nikoo, Mohammad; Adamowski, Jan (Journal of Hydrology, 2019)

A review of the flood risk management governance and resilience literature - Morrison, A.; Westbrook, C.J.; Noble, B.F. (Journal of Flood Risk Management, 2018)
The environmental management literature suggests that resilience is key to managing complex systems and reducing vulnerability resulting from uncertainty and unexpected change. Yet, flood risk management (FRM) has emerged largely from a culture of resistance. This paper takes the pulse of the current state of FRM research, with a focus on how the scholarly community has approached governance for flood resilience. Our analysis of the FRM journal literature identified 258 articles addressing governance and flooding, resilience and adaptation. Five main research themes emerged from these articles, addressing a variety of issues, but mostly lacking the degree of integration needed to address the social‐ecological complexity of FRM. Overall, research supporting the governance of FRM for resilience lacks integration, and methods of mitigating this lack of integration are poorly studied. We conclude with a discussion about the nature and scope of FRM research for resilience, and identify opportunities for more integrative FRM research that is more tightly coupled with policy and practice.
Keywords: Ouvrage_Collectif_Numéro1

Economic inequality and institutional adaptation in response to flood hazards: a historical analysis - Van Bavel, Bas; Curtis, Daniel R.; Soens, Tim (Ecology and Society, 2018)

Limited progress in global reduction of vulnerability to flood impacts over the past two decades - Sauer, Inga J.; Mester, Benedikt; Frieler, Katja; Zimmermann, Sandra; Schewe, Jacob; Otto, Christian (Communications Earth & Environment, 2024)
Abstract Global flood impacts have risen in recent decades. While increasing exposure was the dominant driver of surging impacts, counteracting vulnerability reductions have been detected, but were too weak to reverse this trend. To assess the ongoing progress on vulnerability reduction, we combine a recently available dataset of flooded areas derived from satellite imagery for 913 events with four global disaster databases and socio-economic data. Event-specific flood vulnerabilities for assets, fatalities and displacements reveal a lack of progress in reducing global flood vulnerability from 2000—2018. We examine the relationship between vulnerabilities and human development, inequality, flood exposure and local structural characteristics. We find that vulnerability levels are significantly lower in areas with good structural characteristics and significantly higher in low developed areas. However, socio-economic development was insufficient to reduce vulnerabilities over the study period. Nevertheless, the strong correlation between vulnerability and structural characteristics suggests further potential for adaptation through vulnerability reduction.

Methodological approach for mapping the flood physical vulnerability index with geographical open-source data: an example in a small-middle city (Ponferrada, Spain) - Tascón-González, Laura; Ferrer-Julià, Montserrat; García-Meléndez, Eduardo (Natural Hazards, 2024)
Abstract To increase the resilience of communities against floods, it is necessary to develop methodologies to estimate the vulnerability. The concept of vulnerability is multidimensional, but most flood vulnerability studies have focused only on the social approach. Nevertheless, in recent years, following seismic analysis, the physical point of view has increased its relevance. Therefore, the present study proposes a methodology to map the flood physical vulnerability and applies it using an index at urban parcel scale for a medium-sized town (Ponferrada, Spain). This index is based on multiple indicators fed by geographical open-source data, once they have been normalized and combined with different weights extracted from an Analytic Hierarchic Process. The results show a raster map of the physical vulnerability index that facilitates future emergency and flood risk management to diminish potential damages. A total of 22.7% of the urban parcels in the studied town present an index value higher than 0.4, which is considered highly vulnerable. The location of these urban parcels would have passed unnoticed without the use of open governmental datasets, when an average value would have been calculated for the overall municipality. Moreover, the building percentage covered by water was the most influential indicator in the study area, where the simulated flood was generated by an alleged dam break. The study exceeds the spatial constraints of collecting this type of data by direct interviews with inhabitants and allows for working with larger areas, identifying the physical buildings and infrastructure differences among the urban parcels.

The Hazards of Mainstreaming: Climate change adaptation politics in three dimensions - Scoville-Simonds, Morgan; Jamali, Hameed; Hufty, Marc (World Development, 2020)

Analyser la vulnérabilité sociétale et territoriale aux inondations en milieu urbain dans le contexte des changements climatiques, en prenant comme cas d'étude la Ville de Montréal - Thomas, I.; Bleau, N. (2018)
28 Figure 7 : limites de la zone inondable et la zone inondée historiquement de la rive de Montréal de la rivière des prairies. [...] 68 Figure 27 : Aperçu de la table d’attributs de la base des données de la description de la sensibilité territoriale. [...] 41 Graphique 3 : Distribution des degrés de la sensibilité sociale par nombre d’aires de diffusion (206 AD au total) du secteur de la rivière des Prairies à Montréal à partir des résultats de l’indice ISSAIP des groupes de l’atelier de travail. [...] Cette analyse implique plusieurs étapes et le développement de plusieurs outils dont : la collecte des données disponibles et nécessaires pour réaliser un état des lieux des zones inondées historiquement pour une partie de la Ville de Montréal, la modélisation de l'espace occupé par l'eau selon différents niveaux d'eau possiblement atteints lors de débordement de la rivière, la collecte des donnée. [...] : la formation de réseaux de communication, la prise de décision, la création de consensus), qu’il est possible de mesurer, mais pas au moyen de données d’archives secondaires.
Keywords: Thomas_Isabelle

An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”) - Reimann, Lena; Koks, Elco; De Moel, Hans; Ton, Marijn J.; Aerts, Jeroen C. J. H. (Earth's Future, 2024)
Abstract Fatalities caused by natural hazards are driven not only by population exposure, but also by their vulnerability to these events, determined by intersecting characteristics such as education, age and income. Empirical evidence of the drivers of social vulnerability, however, is limited due to a lack of relevant data, in particular on a global scale. Consequently, existing global‐scale risk assessments rarely account for social vulnerability. To address this gap, we estimate regression models that predict fatalities caused by past flooding events ( n = 913) based on potential social vulnerability drivers. Analyzing 47 variables calculated from publicly available spatial data sets, we establish five statistically significant vulnerability variables: mean years of schooling; share of elderly; gender income gap; rural settlements; and walking time to nearest healthcare facility. We use the regression coefficients as weights to calculate the “ Glob al‐ E mpirical So cial V ulnerability I ndex (GlobE‐SoVI)” at a spatial resolution of ∼1 km. We find distinct spatial patterns of vulnerability within and across countries, with low GlobE‐SoVI scores (i.e., 1–2) in for example, Northern America, northern Europe, and Australia; and high scores (i.e., 9–10) in for example, northern Africa, the Middle East, and southern Asia. Globally, education has the highest relative contribution to vulnerability (roughly 58%), acting as a driver that reduces vulnerability; all other drivers increase vulnerability, with the gender income gap contributing ∼24% and the elderly another 11%. Due to its empirical foundation, the GlobE‐SoVI advances our understanding of social vulnerability drivers at global scale and can be used for global (flood) risk assessments. , Plain Language Summary Social vulnerability is rarely accounted for in global‐scale risk assessments. We develop an empirical social vulnerability map (“GlobE‐SoVI”) based on five key drivers of social vulnerability to flooding, that is, education, elderly, income inequality, rural settlements and travel time to healthcare, which we establish based on flood fatalities caused by past flooding events. Globally, we find education to have a high and reducing effect on social vulnerability, while all other drivers increase vulnerability. Integrating social vulnerability in global‐scale (flood) risk assessments can help inform global policy frameworks that aim to reduce risks posed by natural hazards and climate change as well as to foster more equitable development globally. , Key Points We develop a global map of social vulnerability at ∼1 km spatial resolution based on five key vulnerability drivers (“GlobE‐SoVI”) We establish vulnerability drivers empirically based on their contribution to predicting fatalities caused by past flooding events Accounting for social vulnerability in global‐scale (flood) risk assessments can inform global policy frameworks that aim to reduce risk

Flood hazards, environmental rewards, and the social reproduction of risk - Oulahen, Greg (Geoforum, 2021)

Spatial Analysis of Social Vulnerability to Floods Based on the MOVE Framework and Information Entropy Method: Case Study of Katsushika Ward, Tokyo - Lianxiao; Morimoto, Takehiro (Sustainability, 2019)
Tokyo is located in a lowland area that is vulnerable to flooding. Due to global climate change, the scalability and frequency of flooding is increasing. On the other hand, population aging and family structural changes, as well as the lack of adaptation measures, would accelerate flooding vulnerability. The key factors involved in social vulnerability must be studied to reduce the risk of flooding. In this study, we refer to the MOVE framework (a disaster vulnerability assessment framework) and analyze it from three perspectives: Exposure to social vulnerability, susceptibility, and resilience. We subsequently develop an index system to complete the evaluation using 11 indicators. The collected data will help reveal social vulnerability to floods in the Katsushika Ward, Tokyo, using the information entropy method and GIS. We found that the western region of the Katsushika Ward is at more risk than the eastern region during flooding. Additionally, the possibility of a serious crisis erupting is greater in the southwestern region than in the northwestern region. Consequently, we conclude that the spatial distribution of flooding varies in the region. The results of this study will help in understanding social vulnerability, in selecting and combining adaptation measures suited to the characteristics of the area, and in the effective and efficient implementation of these measures by the local government’s disaster department.

Integrating social vulnerability into high-resolution global flood risk mapping - Fox, Sean; Agyemang, Felix; Hawker, Laurence; Neal, Jeffrey (Nature Communications, 2024)
Abstract High-resolution global flood risk maps are increasingly used to inform disaster risk planning and response, particularly in lower income countries with limited data or capacity. However, current approaches do not adequately account for spatial variation in social vulnerability, which is a key determinant of variation in outcomes for exposed populations. Here we integrate annual average exceedance probability estimates from a high-resolution fluvial flood model with gridded population and poverty data to create a global vulnerability-adjusted risk index for flooding (VARI Flood) at 90-meter resolution. The index provides estimates of relative risk within or between countries and changes how we understand the geography of risk by identifying ‘hotspots’ characterised by high population density and high levels of social vulnerability. This approach, which emphasises risks to human well-being, could be used as a complement to traditional population or asset-centred approaches.

Declining vulnerability but rising impacts: the trends of climatic disasters in Nepal - Chapagain, Dipesh; Bharati, Luna; Borgemeister, Christian (Regional Environmental Change, 2022)
Abstract The impacts of climatic disasters have been rising globally. Several studies argue that this upward trend is due to rapid growth in the population and wealth exposed to disasters. Others argue that rising extreme weather events due to anthropogenic climate change are responsible for the increase. Hence, the causes of the increase in disaster impacts remain elusive. Disaster impacts relative to income are higher in low-income countries, but existing studies are mostly from developed countries or at the cross-country level. Here we assess the spatiotemporal trends of climatic disaster impacts and vulnerability and their attribution to climatic and socioeconomic factors at the subnational scale in a low-income country, using Nepal as a case study. Loss of life is the most extreme consequence of disasters. Therefore, we employed human mortality as a measure of disaster impacts, and mortality normalized by exposed population as a measure of human vulnerability. We found that climatic disaster frequency and mortality increased in Nepal from 1992 to 2021. However, vulnerability decreased, most likely due to economic growth and progress in disaster risk reduction and climate change adaptation. Disaster mortality is positively correlated with disaster frequency and negatively correlated with per capita income but is not correlated with the exposed population. Hence, population growth may not have caused the rise in disaster mortality in Nepal. The strong rise in disaster incidence, potentially due to climate change, has overcome the effect of decreasing vulnerability and caused the rise in disaster mortality.

Environmental vulnerability and resilience: Social differentiation in short‐ and long‐term flood impacts - Houston, Donald; Werritty, Alan; Ball, Tom; Black, Andrew (Transactions of the Institute of British Geographers, 2021)
This paper finds that social differentiation in flood impacts is relatively small soon after a flood, with some surprising results such as professionals and homeowners badly affected in the short‐term – but widens over time, with socially disadvantaged groups displaying less recovery. The paper concludes that vulnerability and resilience to flooding are sensitive to financial resources, institutional support (chiefly from a landlord), and capacity to deal with disruption (chiefly time availability, which is low among professionals and high among retired people). An implication of these findings is that existing indices of flood vulnerability that use multiple measures of social deprivation should be used with caution, as not all conventional aspects of social deprivation are necessarily associated with greater vulnerability to flood impacts. , This paper reports household questionnaire survey results on vulnerability and resilience to flooding from one of the largest and most representative samples ( n = 593) of households up to 12 years after they were flooded, and is one of the first to provide detailed analysis of social differentiation in long‐term flood impacts. A novel finding is that social differentiation in flood impacts is relatively small soon after a flood, but widens over time, with socially disadvantaged groups displaying less recovery. The patterns of social differentiation in vulnerability and resilience to flooding differ markedly according to the type and timescale of the impact, with some normally socially advantaged groups (e.g., professionals and homeowners) being most vulnerable to short‐term impacts. Consistent with some existing studies, we found that older residents (age 70+) have greater resilience to flood impacts, although our sample may not capture the frailest individuals. As in previous research, low income is linked to lower resilience, particularly in the long term. We find that prior experience of flooding, despite enhancing preparedness, overall erodes rather than enhances resilience to flooding. Flood warnings are effective at reducing vulnerability to short‐term impacts. Underlying influences on resilience to natural disasters are complex and may only be revealed by multivariate analysis and not always be evident in simple observed patterns. The paper concludes that vulnerability and resilience to flooding are sensitive to financial resources, institutional support (chiefly from a landlord), and capacity to deal with disruption (chiefly time availability, which is low among professionals and high among retired people). An implication of these findings is that existing indices of flood vulnerability that use multiple measures of social deprivation should be used with caution, as not all conventional aspects of social deprivation are necessarily associated with greater vulnerability to flood impacts.

Application of Social Vulnerability Index (SoVI) and delineation of natural risk zones in Greater Lisbon, Portugal - Guillard-Gonçalves, Clémence; Cutter, Susan L.; Emrich, Christopher T.; Zêzere, José Luís (Journal of Risk Research, 2015)

A place-based socioeconomic status index: Measuring social vulnerability to flood hazards in the context of environmental justice - Chakraborty, Liton; Rus, Horatiu; Henstra, Daniel; Thistlethwaite, Jason; Scott, Daniel (International Journal of Disaster Risk Reduction, 2020)
Keywords: Ouvrage_Collectif_Numéro1

Determinants of Risk: Exposure and Vulnerability - Cardona, Omar-Dario; Van Aalst, Maarten K.; Birkmann, Jörn; Fordham, Maureen; McGregor, Glenn; Perez, Rosa; Pulwarty, Roger S.; Schipper, E. Lisa F.; Sinh, Bach Tan; Décamps, Henri; Keim, Mark; Davis, Ian; et al. (Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, 2012)
Keywords: Ouvrage_Collectif_Numéro1