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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.

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.

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

Les inondations causent de lourds dommages tant économiques, sociaux qu'environnementaux, en plus d'avoir des effets sur la santé physique et psychologique des sinistrés.

Orages violents, pluies diluviennes, records battus à Québec comme à Montréal: l'été 2025 rappelle combien les prévisions météo sont essentielles. Selon des experts, les récentes coupes budgétaires dans les agences américaines pourraient être de mauvais augure chez nous.

Understanding the combination of meteorological, geomorphological and hydrological factors that led to the Texas flood could help prevent future disasters.

Dans un monde de plus en plus polarisé, où la diplomatie scientifique devient parfois la dernière ligne de dialogue entre nations, les partenariats entre chercheurs jouent un rôle critique.

AbstractThe frequency and severity of floods has increased in different regions of the world due to climate change. Although the impact of floods on human health has been extensively studied, the increase in the segments of the population that are likely to be impacted by floods in the future makes it necessary to examine how adaptation measures impact the mental health of individuals affected by these natural disasters. The goal of this scoping review is to document the existing studies on flood adaptation measures and their impact on the mental health of affected populations, in order to identify the best preventive strategies as well as limitations that deserve further exploration. This study employed the methodology of the PRISMA-ScR extension for scoping reviews to systematically search the databases Medline and Web of Science to identify studies that examined the impact of adaptation measures on the mental health of flood victims. The database queries resulted in a total of 857 records from both databases. Following two rounds of screening, 9 studies were included for full-text analysis. Most of the analyzed studies sought to identify the factors that drive resilience in flood victims, particularly in the context of social capital (6 studies), whereas the remaining studies analyzed the impact of external interventions on the mental health of flood victims, either from preventive or post-disaster measures (3 studies). There is a very limited number of studies that analyze the impact of adaptation measures on the mental health of populations and individuals affected by floods, which complicates the generalizability of their findings. There is a need for public health policies and guidelines for the development of flood adaptation measures that adequately consider a social component that can be used to support the mental health of flood victims.

The communication of information about natural hazard risks to the public is a difficult task for decision makers. Research suggests that newer forms of technology present useful options for building disaster resilience. However, how effectively these newer forms of media can be used to inform populations of the potential hazard risks in their community remains unclear. This research uses primary data from an in-person survey of 164 residents of Newport Beach, California during the spring of 2014 to ascertain the current and preferred mechanisms through which individuals receive information on flood risks in their community. Factor analysis of survey data identified two predominant routes of dissemination for risk information: older traditional media and newer social media sources. A logistic regression model was specified to identify predictors for choosing a particular communication route. This analysis revealed that age is the central factor in predicting the sources people use to receive risk information. We follow the analysis by discussing this finding and its policy implications.

Les récits médiatiques et culturels qui circulent sur les événements météorologiques extrêmes (EME) ne sont pas représentatifs de l’ensemble des expériences de personnes sinistrées. Les groupes qui en subissent les conséquences les plus sévères tendent à être ceux que l’on « entend » le moins dans l’espace public. L’approche de recherche narrative permet de documenter une diversité d’expériences d’EME pour en tracer un panorama plus complet. Adoptant une approche narrative féministe, notre recherche a été menée auprès de femmes touchées par des inondations en Beauce. Des extraits d’entrevues semi-directives menées avec des femmes sinistrées offrent une illustration des conséquences psychosociales entrainées par les inondations. Les forces des participantes et certains défis rencontrés en lien avec leurs rôles dans la famille et la communauté sont aussi abordés. La méthode adoptée a permis de collecter des récits d’expérience riches et singuliers qui rendent plus tangibles les effets différenciés des EME. Tenir compte de cette diversité d’expériences favoriserait une prise en charge plus équitable des personnes sinistrées à court, moyen et long terme.

Le territoire de la vallée du Gave de Gavarnie a connu un épisode d’inondation/crue particulièrement catastrophique en 2013, ayant entrainé de forts dégâts matériels et des pertes humaines. Dans ce contexte, la culture du risque est un enjeu tant pour les acteurs de la gestion de ce territoire que pour les citoyens, d’autant plus que les risques présents y sont multiples (avalanches, glissements de terrain et séismes). Dans cette perspective, l’école peut jouer un rôle déterminant à travers la mise en place de projets d’éducations au(x) risque(s). Ce type d’éducation doit commencer par la perception et la conscience du (des) risque(s), rendues possibles par le vécu et/ou par la culture du groupe dans lequel l’élève vit. Cette étude a pour objectif d’examiner les représentations et la perception du risque des élèves d’une école élémentaire française située sur une commune fortement impactée par cette crue, et l’évolution de ces représentations et cette perception un an après la mise en œuvre du projet éducatif. Les résultats montrent une représentation plurielle du risque par les élèves avec des différences entre classes. La classe de CP-CE (enfants âgés de 6 à 8 ans) associe essentiellement le risque à l’aléa naturel (avalanche, inondation…) alors que les élèves en CM (enfants âgés de 9 à 10 ans) sont centrés sur ce qui pourrait leur arriver (accident, maladie…). Le risque inondation/crue est dans un premier temps très peu évoqué dans les représentations des élèves, mais lorsque les activités pédagogiques permettent de contextualiser cette notion sur leur territoire, il est alors plus fortement perçu.

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

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

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.

Management and control of flood hazards, the most frequent natural disaster worldwide, has become a greater challenge due to the increasingly unpredictable precipitation and runoff due to climate change. As many rural areas in Iran are vulnerable to flash floods occurring mainly in the spring, more accurate plans are needed to help reduce the risk of related damage. To address this concern, a robust methodology using multi-objective optimization is proposed, which incorporates the large uncertainties in the modeling parameters defining the risk of flooding. The proposed framework has been implemented in the upper catchment of the Taleghanrood river in the Taleghan district in Iran, which is vulnerable to flooding. The results provide a detailed performance assessment of alternative infrastructure designs, which will help to increase the efficiency of flood management strategies. The optimization uses multi-criteria optimization evolutionary algorithms (MOEA) and Bayesian estimation concepts. The resulting specific design plans, as levees’ height increases over a 50-year time horizon, for controlling floods under given scenarios reflect the uncertainty in the parameters.

Questions have been raised about the correctness of water quality models with complete mixing assumptions in cross junctions of water distribution systems. Recent developments in the mixing phenomenon within cross junctions of water distribution networks (WDNs) have heightened the need for evaluating the existing incomplete mixing models under real-world conditions. Therefore, in this study, two cross junctions with pipe diameters of 100 Â 100 Â 100 Â 100 mm and 150 Â 150 Â 150 Â 150 mm were employed in laboratory experiments to evaluate six existing incomplete mixing models for 25 flow rate scenarios ranging between 1.5 and 3.0 L/s. It was observed that within the same flow rate scenario, the degree of mixing in a cross junction with a pipe relative roughness of 6.00 Â 10À5 (pipe diameter of 25 mm) was higher than that in a cross junction with a pipe relative roughness of 3.00 Â 10À5 (pipe diameter of 50 mm) and smaller. Considering the real-world size of pipes in evaluating the incomplete mixing models showed that two incomplete mixing models, AZRED and the one by Shao et al., had the best accordance with the results of the laboratory experiments.