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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.

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.

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.

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

<p>Spring floods have generated colossal damages to residential areas in the Province of Quebec, Canada, in 2017 and 2019. Government authorities need accurate modelling of the impact of theoretical floods in order to prioritize pre-disaster mitigation projects to reduce vulnerability. They also need accurate modelling of forecasted floods in order to direct emergency responses. </p><p>We present a governmental-academic collaboration that aims at modelling flood impact for both theoretical and forecasted flooding events over all populated river reaches of meridional Quebec. The project, funded by the ministère de la Sécurité publique du Québec (Quebec ministry in charge of public security), consists in developing a diagnostic tool and methods to assess the risk and impacts of flooding. Tools under development are intended to be used primarily by policy makers. </p><p>The project relies on water level data based on the hydrological regimes of nearly 25,000 km of rivers, on high-precision digital terrain models, and on a detailed database of building footprints and characterizations. It also relies on 24h and 48h forecasts of maximum flow for the subject rivers. The developed tools integrate large data sets and heterogeneous data sources and produce insightful metrics on the physical extent and costs of floods and on their impact on the population. The software also provides precise information about each building affected by rising water, including an estimated cost of the damages and impact on inhabitants.  </p>

Abstract Action toward strengthened disaster risk reduction (DRR) ideally builds from evidence-based policymaking to inform decisions and priorities. This is a guiding principle for the Sendai Framework for Disaster Risk Reduction (SFDRR), which outlines priorities for action to reduce disaster risk. However, some of these practical guidelines conceal oversimplified or unsubstantiated claims and assumptions, what we refer to as “truisms”, which, if not properly addressed, may jeopardize the long-term goal to reduce disaster risks. Thus far, much DRR research has focused on ways to bridge the gap between science and practice while devoting less attention to the premises that shape the understanding of DRR issues. In this article, written in the spirit of a perspective piece on the state of the DRR field, we utilize the SFDRR as an illustrative case to identify and interrogate ten selected truisms, from across the social and natural sciences, that have been prevalent in shaping DRR research and practice. The ten truisms concern forecasting, loss, conflict, migration, the local level, collaboration, social capital, prevention, policy change, and risk awareness. We discuss central claims associated with each truism, relate those claims to insights in recent DRR scholarship, and end with suggestions for developing the field through advances in conceptualization, measurement, and causal inference.

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

Floods are among the most dangerous and destructive hazards in the world. Stormwater Beneficial Management Practices (BMPs) are a set of strategies that can assist in reducing urban floods and their damages by capturing surface runoff and promoting infiltration. Engagement of citizens in the selection of stormwater BMPs may facilitate the decision-making processes and increase the chance of adopting and maintaining them. Due to existence of catastrophic floods in Brazil, implementing BMPs is essential in the urban areas. The objective of this study is to understand the viewpoints of citizens about a set of stormwater BMPs in Brazil. Moreover, we aim to comprehend whether diverging viewpoints about the BMPs can be associated with existence of different layers in the society. For this purpose, online surveys were used to access wide and diverse groups of citizens from different ages, levels of education and income, as well as geographical location. The questions and descriptions of BMPs were prepared in an accessible language, and then disseminated through various platforms. The responses of more than 1000 participants were analyzed using descriptive and statistical methods. Our results show that the participants found the retention and detention basins, as well as permeable pavement as the most efficient BMPs. Moreover, considering the small-scale practices, although lot related BMPs are considered less efficient, citizens are willing to use green roof, bioretention, and rain barrels in their properties. In addition, most of the respondents support public investments on stormwater BMPs. Our analyses show that participants' age and level of education statistically influenced their choice of BMPs and willingness to pay for their maintenance and construction. These results can help Brazilian policy makers to prepare flood management plans by including stormwater BMPs that would be more accepted by the population. In addition, proposing practices that are aligned with citizens’ perceptions creates a sense of responsibility, and is in accordance with the Brazilian New Framework of Sanitation that includes public participation in policy making.

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

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

<p>Les études portant sur les évènements hydrologiques extrêmes sont d’une grande importance vu leurs nombreux impacts socio-économiques. Ces études reposent dans une large mesure sur la capacité à estimer adéquatement les risques associés à ces évènements. Dans ce cadre, l’analyse fréquentielle (AF) est une des approches les plus utilisées pour la modélisation et l’estimation des risques associés aux évènements extrêmes. Généralement, ces évènements sont caractérisés par plusieurs variables dépendantes, comme le volume, la pointe et la durée pour les crues. Par conséquent, l'analyse de chacune de ces variables séparément ne peut pas fournir une évaluation complète des risques et peut engendrer des pertes de vies humaines ou de biens associés à une sous estimation, ou une augmentation des coûts des ouvrages hydrauliques associés à une surestimation. L’AF multivariée (AFM) permet de pallier ce problème en considérant simultanément ces variables. L’AF classique est basée sur trois hypothèses à savoir l’homogénéité, la stationnarité et l’indépendance. Par ailleurs, différentes conditions non standards telles que la complexité topographique, les perturbations par les aménagements urbains et les changements climatiques peuvent influencer la réponse hydrologique. De telles conditions rendent la prédétermination des crues, par les méthodes classiques d’AFM, un exercice non efficace et mal adapté à de tels contextes. L’objectif de cette thèse consiste à proposer de nouvelles méthodes plus prometteuses pour l'analyse et la modélisation des variables hydrologiques à la fois dans un cadre multivarié et en l’absence de l’hypothèse d’homogénéité. Ces méthodes visent à contourner les limites de celles utilisées dans la littérature. Ces nouvelles méthodes, basées sur les copules, permettent une meilleure estimation des risques des extrêmes hydrologiques en tenant compte des interactions et es dépendances entre les différentes variables. Par conséquent, les gestionnaires des ressources hydriques peuvent prendre des décisions éclairées et mieux adaptées au contexte actuel. Précisément, nous nous intéressons dans une première partie à tester l’homogénéité des séries hydrologiques multivariées. Pour ce faire, nous avons proposé un nouveau test, basé sur les L moments multivariés, capable de détecter la rupture dans la structure de dépendance des variables hydrologiques. Les résultats obtenus montrent la bonne performance du test proposé sous différents scénarios. Par la suite, dans le but de modéliser l’hétérogénéité des séries hydrologiques multivariées, un modèle de mélange de copules a été mis au point. Dans ce cadre, nous avons proposé une nouvelle méthode pour l’estimation des différents paramètres du modèle. La méthode proposée est basée sur l’utilisation des algorithmes génétiques. Sa performance est illustrée sur des séries simulées. Les résultats obtenus montrent que la méthode proposée est un outil efficace capable de fournir de bonnes estimations, en particulier dans un contexte hydrologique. Finalement, deux nouveaux tests d’adéquation pour les copules multiparamètres ont été développés. Le but de ces tests est de vérifier la qualité de l’ajustement de la copule aux données et améliorer ainsi l’estimation des risques associés aux évènements extrêmes. Les résultats révèlent que les tests proposés performent bien dans le contexte hydrologique.<br /><br /> Studies of hydrological extreme events are of great importance given their many socio-economic impacts. These studies rely on the ability to adequately estimate the associated risk. In this context, frequency analysis (FA) is one of the most widely used approaches for modeling and estimating the risks associated with extreme events. Generally, these events are characterized by several correlated random variables. Therefore, analyzing each of these variables separately cannot provide a complete risk assessment and may result in loss of life or property associated with an underestimation, or an increase in the costs of hydraulic structure associated with an overestimation. Multivariate FA (MFA) overcomes this problem by simultaneously considering these variables. Classical FA is based on three assumptions namely homogeneity, stationarity and independence. However, different non-standard conditions such as topographic complexity, disturbances by urban development and climate change can influence the hydrological response. Such conditions make flood predetermination, by conventional MFA methods, an ineffective exercise and unsuitable to such contexts. The main objective of this thesis is to propose new and more promising methods for the analysis and modeling of hydrological variables both in a multivariate framework and in the lack of the homogeneity assumption. These methods aim to overcome the limitations of classical methods used in the literature. These new proposed methods, based on copulas, allow a better estimation of the risks associated to hydrological extremes by taking into account the dependence between the different variables. As a result, water resource managers can make informed decisions that are better suited to the current context. In the first part, we propose a novel statistical test for multivariate heterogeneity detection, based on copula and multivariate L-moments. A simulation study is conducted to evaluate the performance of the proposed test and to compare it with those of existing tests. Results show the ability of the proposed test to discriminate homogeneous and inhomogeneous series. In the second part, we propose a new model based on mixtures of copulas that take into account the heterogeneity of multivariate hydrological series. To estimate the components of this model, we propose a new parameter estimation approach, based on the maximum pseudo-likelihood using genetic algorithms. Results indicate that the proposed method estimates more accurately the parameters even with small sample sizes compared to the existing classical EM method. In the last part, we introduce new goodness of fit (GOF) tests specifically for multiparameter copulas and adapted to hydrometeorological context. More precisely, the proposed GOF tests are based on multivariate L moments. A simulation study is conducted to evaluate and compare the performances of the proposed tests. The results confirm the usefulness of the new GOF tests in comparison with some well-established ones.</p>

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

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

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.

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.

Abstract Flood risk may differ across income levels. In this paper, I employ unique survey data from more than 8000 households in Germany to derive an integrated flood risk indicator that accounts for local flood exposure, assets-at-risk, housing characteristics, and household coping behavior. The results suggest that low-income households, due to their smaller homes and less valuable assets, face lower monetary flood risks than wealthier households despite the former’s limited capacity to implement protection measures and purchase insurance. Relative to the available financial budget, however, expected flood damage weighs higher for low-income households.

Disastrous floods have caused millions of fatalities in the twentieth century, tens of billions of dollars of direct economic loss each year and serious disruption to global trade. In this Review, we provide a synthesis of the atmospheric, land surface and socio-economic processes that produce river floods with disastrous consequences. Disastrous floods have often been caused by processes fundamentally different from those of non-disastrous floods, such as unusual but recurring atmospheric circulation patterns or failures of flood defences, which lead to high levels of damage because they are unexpected both by citizens and by flood managers. Past trends in economic flood impacts show widespread increases, mostly driven by economic and population growth. However, the number of fatalities and people affected has decreased since the mid-1990s because of risk reduction measures, such as improved risk awareness and structural flood defences. Disastrous flooding is projected to increase in many regions, particularly in Asia and Africa, owing to climate and socio-economic changes, although substantial uncertainties remain. Assessing the risk of disastrous river floods requires a deeper understanding of their distinct causes. Transdisciplinary research is needed to understand the potential for surprise in flood risk systems better and to operationalize risk management concepts that account for limited knowledge and unexpected developments. River floods have direct and indirect consequences for society, and can cause fatalities, displacement and economic loss. This Review examines the physical and socioeconomic causes and impacts of disastrous river flooding, and past and projected trends in their occurrence.

Abstract This study presents a global explanatory analysis of the interplay between the severity of flood losses and human presence in floodplain areas. In particular, we relate economic losses and fatalities caused by floods during 1990–2000, with changes in human population and built‐up areas in floodplains during 2000–2015 by exploiting global archives. We found that population and built‐up areas in floodplains increased in the period 2000–2015 for the majority of the analyzed countries, albeit frequent flood losses in the previous period 1990–2000. In some countries, however, population in floodplains decreased in the period 2000–2015, following more severe floods losses that occurred in the period 1975–2000. Our analysis shows that (i) in low‐income countries, population in floodplains increased after a period of high flood fatalities; while (ii) in upper‐middle and high‐income countries, built‐up areas increased after a period of frequent economic losses. In this study, we also provide a general framework to advance knowledge of human‐flood interactions and support the development of sustainable policies and measures for flood risk management and disaster risk reduction. , Key Points We analyzed the interplay between the severity of flood losses and human presence in floodplains using freely available global data sets Despite the frequent flood losses in the period 1990–2000, human presence and built‐up areas in the floodplains increased between 2000 and 2015 In low‐income countries, population in floodplains increased after a period of high flood fatalities