Journal of Flood Risk Management最新文献

{"title":"Hybrid Hydrodynamic-Machine Learning Modelling for Rapid Flood Scenario Assessment: A Case Study in Aotearoa New Zealand","authors":"Andrea Pozo,&nbsp;Matthew Wilson,&nbsp;Marwan Katurji,&nbsp;Fernando J. Méndez,&nbsp;Cyprien Bosserelle,&nbsp;Emily Lane","doi":"10.1111/jfr3.70206","DOIUrl":"10.1111/jfr3.70206","url":null,"abstract":"<p>Flooding is one of the most devastating natural disasters worldwide. It is also expected to become more severe as climate change impacts are realised. Two-dimensional (2D) hydrodynamic models are used to obtain reliable inundation estimations. However, these models are computationally expensive and time-consuming, making rapid and ensemble flood scenario assessment challenging. This study investigates the application of hybrid hydrodynamic-machine learning techniques to develop two rapid flood inundation scenario assessment models in a study catchment in Aotearoa New Zealand. This approach aims to reduce the numerical modelling load to rapidly make robust predictions of potential flooding events from an ensemble of previously assessed events. The proposed framework is based on an innovative combination of a flexible climate-informed synthetic storm approach and a hybrid hydrodynamic (BG-Flood 2D hydrodynamic model)—machine learning (Random Forest algorithm) approach. A catalogue of synthetic storms was created based on the characteristics of the main inundation driver (heavy rainfall) and the synoptic conditions in the New Zealand region using statistical techniques. Two hybrid models based on the Random Forest algorithm were developed to emulate the BG-Flood outputs and efficiently predict flood/non-flood and maximum inundation depth in the floodplain catchment. The storms' features and the geographic characteristics of the catchment were used as predictor features, and the inundation maps produced by BG-Flood were used as the target data to develop the hybrid models. Validation results show that the hybrid models can rapidly (under 1 s) and accurately predict flood/non-flood (mean Recall = 0.878, Precision = 0.895 and F1 score = 0.886) and maximum inundation depth (mean RMSE = 0.0610 m and NSE = 0.866) in the catchment, producing reliable and valuable flood hazard information for flood risk management.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70206","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flood Risk Assessment of Urban Critical Infrastructures Using Crowd-Sourced and Open Data on Hazard, Exposure and Vulnerability","authors":"Andreas Burzel,&nbsp;Martine van den Boomen,&nbsp;Matthijs Kok","doi":"10.1111/jfr3.70188","DOIUrl":"https://doi.org/10.1111/jfr3.70188","url":null,"abstract":"<p>Worldwide, cities rely on the proper functioning of critical infrastructures (CIs) such as electricity, telecommunication, water supply and transportation. Failure of those infrastructures can lead to significant and long-lasting impacts, even far beyond the flooded areas due to cascading effects. Local authorities are eager to take action to reduce flood risk and strive to increase the resilience of their communities. However, CI are often not considered in flood risk assessments. One of the reasons is that CI operators do not share their CI data and internal risk assessments. Therefore, an integral view on flood risk is lacking and risks may be unidentified or underestimated. To overcome this limitation, in this paper we propose an integrated framework for flood risk assessment of urban critical infrastructures (UCIs) for local authorities, which is based on publicly available and field-surveyed CI data. The proposed framework supports cities to carry out cross-sectoral risk screenings on urban district level to evaluate the need for in-depth risk assessments and risk dialogues with CI operators.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70188","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147567772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive Framework for the Assessment of Multi-Level Pluvial Flood Risk","authors":"Murel Truu,&nbsp;Ivar Annus,&nbsp;Nils Kändler","doi":"10.1111/jfr3.70193","DOIUrl":"https://doi.org/10.1111/jfr3.70193","url":null,"abstract":"<p>Urban areas are increasingly vulnerable to pluvial floods, a threat that is exacerbated by climate change and urbanisation. Current risk assessment methods often lack scalability and practical applicability across diverse urban contexts and varying capacities. This study introduces a novel comprehensive framework for multi-level pluvial flood risk assessment, which provides a systematic approach to evaluating hazard, exposure, and vulnerability across citywide, catchment, and sub-catchment levels. By integrating geographic information systems with adaptive modelling techniques, the framework enables resource-efficient prioritisation and dynamic risk management tailored to urban development and climate change scenarios. Case studies based on Estonian cities illustrate how this approach can guide effective flood risk mitigation at various spatial scales.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70193","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147315591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nonstationary Flood Frequency Analysis Using Reconstructing Past Millennium Floods Based on Large-Scale Climate Indices","authors":"Yue Guo,&nbsp;Jianzhu Li,&nbsp;Hang Zeng,&nbsp;Ting Zhang,&nbsp;Ping Feng,&nbsp;Jiankai Geng","doi":"10.1111/jfr3.70189","DOIUrl":"https://doi.org/10.1111/jfr3.70189","url":null,"abstract":"<p>With global climate change and human activities, environmental uncertainties are increasing, and extreme flood events are occurring more frequently. The reliability of traditional hydrological frequency analysis theories, based on the assumption of stationarity, is being increasingly questioned. This study aims to develop a non-stationary flood frequency analysis model using the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) framework, with time and climate indices as covariates. The model calculation and frequency analysis are conducted using 2000 years of climate indices reconstructed by the Paleo Hydrodynamics Data Assimilation product (PHYDA). Design floods for different return periods are then quantified based on the reconstructed data. The results show that the nonstationary model established with climate indices as covariates can accurately identify the trend of first decreasing and then increasing flood series at the FP and ZJG stations in the Daqing River Basin, achieving the best model performance. Moreover, using the PHYDA-reconstructed climate indices from the past 2000 years to extrapolate floods and calculate design floods provides higher safety for certain return periods than observed series. However, under longer return periods, the design values are smaller than those of the existing observed series. Overall, the nonstationary model proposed in this study can serve as a tool for flood frequency analysis under climate change. Additionally, incorporating the climate indices from the past 2000 years into nonstationary flood frequency analysis provides design results that can offer valuable references for regional water infrastructure design.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70189","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146217268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Flood Event in July 2021 in Europe—Observations, Conclusions, Challenges","authors":"Holger Schüttrumpf,&nbsp;Jörn Birkmann,&nbsp;Stefanie Stenger-Wolf,&nbsp;Elena-Maria Klopries,&nbsp;Annegret H. Thieken","doi":"10.1111/jfr3.70175","DOIUrl":"https://doi.org/10.1111/jfr3.70175","url":null,"abstract":"&lt;p&gt;Globally, 2021 was a year of extremes with, for instance, heatwaves in the US and Canada and outstanding floods in Europe and China (Manandhar et al. &lt;span&gt;2023&lt;/span&gt;). Belgium, Germany, Luxemburg, and the Netherlands experienced a severe flood between July 13 and 15, 2021 (Lehmkuhl, Schüttrumpf, et al. &lt;span&gt;2022&lt;/span&gt;). This event caused disastrous impacts, particularly a significant number of fatalities: 39 in Belgium (Dewals et al. &lt;span&gt;2021&lt;/span&gt;) and 190 (and one missing person) in Germany (Thieken, Zenker, and Bubeck &lt;span&gt;2023&lt;/span&gt;), along with substantial economic damages: 2.8 billion € in Belgium (Journée et al. &lt;span&gt;2023&lt;/span&gt;); 33 billion € in Germany (Thieken, Zenker, and Bubeck &lt;span&gt;2023&lt;/span&gt;); and 383 Mio. € in the Netherlands (Pot et al. &lt;span&gt;2024&lt;/span&gt;). Due to the high death toll, this event is regarded the worst flood event in Belgium, the Netherlands, and in Germany since the two storm surges of February 1953 with 1836 fatalities in the Netherlands and 18 in Belgium and February 1962 with 347 fatalities in Germany. The German federal government identified adaptation to the consequences of climate change as a key challenge alongside ambitious climate protection measures and created a new, binding framework—the Federal Climate Adaptation Act (KAnG) (BMUKN &lt;span&gt;2024&lt;/span&gt;). The strategy aims, amongst other, to reduce the flood-induced damages (BMUKN &lt;span&gt;2024&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;The flood event was triggered by the low-pressure system Bernd, which caused heavy precipitation in large parts of North Rhine-Westphalia (DE), Rhineland-Palatinate (DE), and the Walloon Region (BE) (Mohr et al. &lt;span&gt;2023&lt;/span&gt;). In Germany, this low-pressure system formed two hotspots of precipitation. The main hotspot was located on the left side of the Rhine River in the districts of Rhein-Sieg, Rhein-Erft, Düren, Euskirchen, Städteregion Aachen in North Rhine-Westphalia, as well as Ahrweiler, Vulkaneifel, and Bitburg-Prüm in Rhineland-Palatinate (Figure 1). A second area of intense rainfall developed on the right side of the Rhine River in the catchment areas of the Ennepe, Sieg, Volme, and Wupper rivers in North Rhine-Westphalia. Here, the cities of Hagen and Wuppertal were particularly affected alongside the Bergisch, Märkisch, and Rhein-Sieg districts.&lt;/p&gt;&lt;p&gt;The storm track particularly affected the low mountain ranges of Eifel and High Fens between Germany and Belgium, with the highest runoff recorded in the catchment areas of the Ahr, Amblève, Erft, Geelenbeek, Geul, Inde, Meuse, Ourthe, Roer, Vicht, and Vesdre rivers (Table 1). In some regions, over 150 mm of precipitation fell within 24 h (Junghänel et al. &lt;span&gt;2021&lt;/span&gt;; Mohr et al. &lt;span&gt;2023&lt;/span&gt;) on already saturated soil. The Netherlands documented observed rainfall up to 182 mm in 48 h (Jonkman et al. &lt;span&gt;2023&lt;/span&gt;). In Belgium, certain areas recorded up to 270 mm of precipitation in 72 h (Junghänel et al. &lt;span&gt;2021&lt;/span&gt;). The region's topographical characteris","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70175","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146224279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Approaching Urban Flood Modelling According to Available Data: A State-of-the-Art Review and Future Challenges","authors":"Dina Pirone,&nbsp;Roberta Padulano,&nbsp;Giuseppe Del Giudice","doi":"10.1111/jfr3.70184","DOIUrl":"https://doi.org/10.1111/jfr3.70184","url":null,"abstract":"<p>Urban flood modelling allows for developing effective strategies for mitigating flood risks and improving urban resilience. Different urban models can be selected according to the desired objective, ranging from simplified frameworks to more sophisticated numerical models. While several studies explored the advantages and limitations of existing model types, very few publications address the urban flood modelling issue based on data availability and data collection. Urban data regarding digital elevation models, sewer networks, and small-scale features can vary significantly. Thus, the availability and resolution of available data strongly influence urban flood modelling. This study reviews existing approaches to achieve satisfactory urban flood modelling according to the available data and desired objectives. We explored the advantages and limitations of data-rich environments and the benefits of the simplifications. We identified two primary objectives most concerned with ongoing urban flood simulation research: flood modelling for preliminary flood susceptibility assessment and flood hazard mapping. For each category, we investigated how previous authors approached data collection tasks and which resolution they considered sufficiently high to retain their objectives achieved. This study provides valuable guidance for scientists, engineers, and decision-makers, promoting a more informed and mindful approach to urban flood modelling.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70184","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146224108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Future Climate Change Assessment in Flood Risk Management: A Synthesis of Practices in Germany and the BeNeLux Countries","authors":"Elena Macdonald,&nbsp;Bruno Merz,&nbsp;Jeroen C. J. H. Aerts,&nbsp;Benjamin Dewals,&nbsp;Jaap C. J. Kwadijk,&nbsp;Kymo Slager,&nbsp;Patrick Willems,&nbsp;Davide Zoccatelli,&nbsp;Sergiy Vorogushyn","doi":"10.1111/jfr3.70173","DOIUrl":"https://doi.org/10.1111/jfr3.70173","url":null,"abstract":"<p>Climate change, with its links to an intensified water cycle, heavier rainfall, and potentially higher flood peaks, raises concerns about the adequacy of current flood risk management. The devastating July 2021 floods in western Europe underscored these concerns, highlighting the need for transboundary cooperation and shared expertise in adapting flood risk management to climate change. However, uncertainty in future flood projections presents challenges for agencies and governments in upgrading existing measures or designing new ones. Here, we review how climate change information is integrated into flood risk management, focusing on flood design values and flood hazard and risk maps. Focusing on Germany, The Netherlands, Belgium, and Luxembourg—the countries significantly impacted by the 2021 floods—we examine regional practices, as flood risk management is often organized at the sub-national level. Specifically, we assess whether regions have published flood policy papers, developed future flooding scenarios under climate change, and translated these scenarios to flood hazard and risk maps and the design of protection measures. Our findings reveal that all 20 regions have adaptation plans addressing climate change and almost all regions have developed future flood projections but only three incorporate them into climate-adjusted design values and only one provides flood hazard and risk maps under future climate scenarios. Assessments of the future climate vary widely. For example, Flanders in Belgium uses a full range of CMIP5 emission scenarios (RCP2.6 to RCP8.5), while Baden-Württemberg and Bavaria in Germany rely on the worst-case scenario (RCP8.5). Similarly, The Netherlands adopts an approach using 33 global climate models and a dynamic adaptation pathway framework to address uncertainties, whereas Saxony in Germany argues that the spread of projections is too large to derive design values and emphasizes the need for standardized scenarios and methods. In summary, our synthesis highlights substantial gaps in climate-proofing flood risk management and significant regional variation in approaches. Enhanced and faster cross-border learning could improve the effectiveness of climate-informed flood risk management.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70173","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146216769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of Vehicle Stability Processes Under Unsteady Flow Conditions","authors":"Fatima Azhar,&nbsp;Ha Hong Bui,&nbsp;Valentijn R. N. Pauwels","doi":"10.1111/jfr3.70181","DOIUrl":"https://doi.org/10.1111/jfr3.70181","url":null,"abstract":"<p>The vehicle stability criteria are based on experimental and theoretical studies that do not account for the unsteady nature of floods. The rapid variation of depths and velocities in floods causes an additional hydrodynamic force in the direction of the flow, destabilising a vehicle that would otherwise be safe in steady flow conditions. This study shows the changes in drag and lift forces when the vehicle encounters a floodfront or experiences accelerating flow past it. The numerical model built with smoothed particle hydrodynamics (SPH) is first validated for its use in studying unsteady flows by comparing it with 1:14 scale physical model results. The SPH model is then further extended to study the variation in drag and lift forces when the flow is accelerated past the vehicle from a steady state. The results show that the hydrodynamic drag can increase by 40%–50% in unsteady flows. This increase varies linearly with the acceleration of flow. Moreover, the build-up of water in front of a watertight vehicle can further amplify the destabilising forces on the vehicle. It is the first such study wherein the hydrodynamic forces on a partially submerged object in high Reynolds number flow have been studied.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146199371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Influencing Flood Risk Management Integration in U.S. Municipal Planning: An Expert Mental Model Approach","authors":"Kyle McElroy,&nbsp;Austin Becker","doi":"10.1111/jfr3.70169","DOIUrl":"https://doi.org/10.1111/jfr3.70169","url":null,"abstract":"<p>An expert mental model (EMM) explores how U.S. municipalities integrate flood risk management (FRM) into urban planning, offering insights beyond existing literature. Motivated by the challenges urban planners face in balancing flood risk with competing priorities like development, housing, and economic growth, this study combines a literature review, expert interviews, and model analysis to map the influences shaping FRM integration. The EMM highlights an interplay between external (physical risks, societal support, funding), institutional (political will, resources), and process influences (data, collaboration). The model brings forward perception and value influences, individual biases, and shared municipal values, showing how these shape FRM integration alongside technical and institutional factors commonly emphasized in FRM planning literature. External pressures, existing practices, political realities, and internal capabilities all influence urban planners. The model reveals power asymmetry between plan developers and decision-makers, the limits of technical tools once planning moves beyond analysis, and the strong influence of federal and state guidance, funding, regulations, capacity, partnerships, and physical drivers. By considering institutional, cognitive, and political influences, municipalities can develop more resilient FRM strategies. This approach offers a framework for understanding barriers to FRM integration and can be adapted for use in different municipal contexts.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70169","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146199370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimisation of Temporary and Demountable Flood Protection for Infrastructure Resilience","authors":"Fulvio D. Lopane,&nbsp;Richard J. Dawson","doi":"10.1111/jfr3.70182","DOIUrl":"https://doi.org/10.1111/jfr3.70182","url":null,"abstract":"<p>Infrastructure systems provide crucial services to human settlements. Extreme weather events, especially flooding, can disrupt these vital services. Temporary and demountable flood protections (TDFPs) are increasingly used to protect infrastructure assets and provide resilience. Budget constraints mean that TDFP are typically deployed to multiple sites from a single warehouse. Identifying optimal locations to maximise coverage and minimise costs is a complex spatial problem not yet tackled in the literature. To address this, a Spatial Resource Allocation Optimisation (SRAO) framework, using a genetic algorithm (GA), has been developed. The SRAO framework is applied to a case study in the Humber Estuary (UK) where 133 strategic infrastructure assets serve over 400,000 people in the floodplain. Eight scenarios assess how cost, TDFP availability, transport and asset prioritisation for protection influence warehouse size and sites. The SRAO identifies optimal strategies that, relative to other strategies, reduce annual costs by 40%–50% and deployment times by 60%–70%. Furthermore, 8 ‘hotspot’ sites appear in over 60% of optimal solutions; these can be considered robust to model uncertainties and scenario assumptions, providing decision-makers with locations performing well under varied conditions. The methodology benefits local authorities, infrastructure operators and emergency management agencies, reducing costs and improving resilience for communities.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70182","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146199451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}