Journal of Flood Risk Management最新文献

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148075692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Evaluation of Automated Flood Inundation Mapping Techniques Using Multi-Temporal Sentinel-1 SAR Data","authors":"Gautam Dadhich,&nbsp;Mukand Babel,&nbsp;Hiroyuki Miyazaki,&nbsp;Indrajit Pal,&nbsp;Nitin Kumar Tripathi,&nbsp;Salvatore G. P. Virdis","doi":"10.1111/jfr3.70201","DOIUrl":"10.1111/jfr3.70201","url":null,"abstract":"<p>In recent times, the development of algorithms to delineate water surface maps has significantly boosted flood monitoring and mitigation efforts by utilizing dual polarization, multi-temporal Sentinel-1 synthetic aperture radar (SAR) data. The Sentinel-1 mission, with its global land monitoring capability, has been widely employed for SAR-based flood mapping. Compared to single-image flood algorithms, change-detection methods offer superior results by deriving flood extent from classified changes, requiring data-based parameterization. This study critically evaluates the effectiveness of three cutting-edge thresholding algorithms—Edge Otsu, Bmax Otsu, and Kittler–Illingworth (KI)—for automated flood water detection using dual polarization, multi-temporal Sentinel-1 SAR data, focusing on the September 2019 flood event in North-eastern Thailand. Utilizing Google Earth Engine for preprocessing and image correction, the study examines three Sentinel-1 change detection models—Difference Image, Normalized Difference Flood Index (NDFI), and Normalized Difference Sigma-naught Index (NDSI). Among 27 combinations of inputs, change detection methods, and thresholding algorithms, the “Harmonic data-S1GBM (2016–2017)” input paired with the KI thresholding algorithm and the NDSI change detection method achieved the highest overall accuracy of 86.29% (calculated using user accuracy, producer accuracy, and overall accuracy metrics against 2000 validation samples from GISTDA flood maps and Sentinel-2 NDWI data). This combination proved most effective in distinguishing flooded from non-flooded areas, underscoring the importance of selecting optimal data inputs and algorithms for accurate flood inundation mapping. The results highlight the superiority of the KI thresholding algorithm, particularly when used with harmonic data inputs, and establish a robust framework for future flood monitoring applications using Sentinel-1 SAR data. Furthermore, the study emphasizes that for global and automatic flood services, algorithms should not depend on locally optimized parameters, as these cannot be automatically estimated and vary spatially, significantly affecting mapping accuracy.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70201","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668517","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":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148108302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148108303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148075693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to “Empowering Communities Through Urban Flood Resilience: A New Vision for Sustainable Drainage Delivery”","authors":"","doi":"10.1111/jfr3.70213","DOIUrl":"10.1111/jfr3.70213","url":null,"abstract":"<p>Starkey, E., M. Davinson, S. Liu, M. Elges, E. Rollason, and L. J. Bracken. 2026. “Empowering Communities Through Urban Flood Resilience: A New Vision for Sustainable Drainage Delivery.” <i>Journal of Flood Risk Management</i> 19, no. 1: e70202. https://doi.org/10.1111/jfr3.70202.</p><p>The initial longlist of SuDS+ concepts mapped (Footnote <b>5</b>) with examples highlighted and surface water flood maps for comparison (A). This process resulted in 46 themes and their coding scores (B). The <b>Supporting Information</b> contains a supporting coding framework.</p><p>We apologize for this error.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70213","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668485","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":"Rainstorm Flood Risk Assessment in the China–Pakistan Economic Corridor Under Different Shared Socioeconomic Pathways of the 21st Century","authors":"Mengting Liu,&nbsp;Min Xu,&nbsp;Xingdong Li","doi":"10.1111/jfr3.70215","DOIUrl":"10.1111/jfr3.70215","url":null,"abstract":"<p>Global warming has intensified the atmospheric water cycle, leading to more frequent and severe extreme precipitation events, which are a major driver of rainstorm-induced flooding. Developing regions such as the China–Pakistan economic corridor (CPEC), spanning highly heterogeneous terrain and climate zones, face elevated risk due to limited infrastructure and preparedness. This study establishes a comprehensive flood risk assessment framework based on the Hazard–Sensitivity–Vulnerability–Adaptive Capacity (HSVA) model, integrating bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) multimodel precipitation, quantitative socio-environmental indicators, and Geographic Information System (GIS)-based spatial analysis. Applied to Shared Socioeconomic Pathway (SSP) scenarios SSP1–2.6, SSP2–4.5, and SSP5–8.5 for the period 2025–2100, the framework captures the spatiotemporal evolution of rainstorm flood risk. Results show a consistent intensification of extreme precipitation, with high-risk zones expanding northwestward along the Indus River corridor. Quantitatively, high-risk areas range from approximately 5% under SSP1–2.6 to over 6% under SSP5–8.5, indicating an upward trend under high-emission pathways. Model validation demonstrates strong agreement with historical flood records, achieving hit rates above 72% across all scenarios. These findings provide actionable insights for targeted flood mitigation, climate-resilient infrastructure planning, and sustainable water resource management in the CPEC region.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"19 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70215","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668409","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":"Reviewing the Levee Effect: From Theory to Practice","authors":"Angela J. Catalano,&nbsp;Damon M. Hall","doi":"10.1111/jfr3.70211","DOIUrl":"10.1111/jfr3.70211","url":null,"abstract":"<p>Ongoing development in flood-prone areas has intensified focus on flood-risk management strategies. Constructed flood protections, like levees, lead to a false sense of security. Resulting development behind levees paradoxically increases flood risk, referred to as the levee effect. In the 2010s, the nascent field of socio-hydrology revived levee effect research, extending its use as a descriptive and analytic framework for empirically understanding flood-risk–development dynamics. We systematically reviewed the evolution, applications, and leading edge of the levee effect between 2015–2024. From 62 peer-reviewed articles, we found that studies primarily assessed flood risk and risk perceptions (<i>n</i> = 31; 50%), with economic, policy, and vulnerability assessments as emerging areas. We identified three gaps. First, simply identifying the existence of a levee effect fails to advance practical solutions. Second, analysis of the political economy and long-term economic impacts (i.e., weighing costs of maintaining levees versus relocation) is underdeveloped. Third, most studies examined adaptation (e.g., raising home elevation) and mitigation (e.g., improved drainage) separately, but comprehensive flood risk management planning considering both together is lacking. Under the urgency of climate change, the levee effect offers a framework for examining complex social, economic, and political factors that make communities vulnerable to floods.</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/jfr3.70211","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668924","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":"From Forecast to Action: Using Flood Impact Storylines to Optimize Mobile Levee Deployment and Emergency Response Strategies","authors":"Lukas Munz,&nbsp;Markus Mosimann,&nbsp;Martina Kauzlaric,&nbsp;Govert Verhoeven,&nbsp;Andreas Paul Zischg","doi":"10.1111/jfr3.70210","DOIUrl":"10.1111/jfr3.70210","url":null,"abstract":"<p>Preparing for unprecedented natural hazard events is challenging because the lack of records and experience makes it impossible to know how such events will unfold. Repeated record-breaking floods in central Europe have increased awareness of the need for proactive planning beyond observed extremes. In a participatory approach involving firefighters and civil protection officers, we developed a method to identify locations where mobile levees can be deployed to protect critical infrastructure during extreme flood events. The approach is based on event storylines derived from synthetic design hydrographs, reforecast-based precipitation scenarios, and physical modeling of river discharge, inundation, and flood impacts. Optimized locations for mobile levee installation were identified by evaluating their effectiveness in reducing flood impacts and delaying inundation to gain time for evacuations. The approach shows that rapid and anticipatory deployment of mobile levees at selected weak points can delay flooding by several hours, providing valuable time for evacuation and the protection of critical infrastructure. The participatory approach proved to be valuable for decision-makers to exclude or prioritize strategies, raise awareness among actors, and train for event interventions with emergency services.</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/jfr3.70210","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668923","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":"Data Resolution and Model Complexity in Pluvial Flood Risk Assessment: Insights and Trade-Offs","authors":"Fabrizia Fappiano,&nbsp;Max Maurer,&nbsp;João P. Leitão","doi":"10.1111/jfr3.70187","DOIUrl":"10.1111/jfr3.70187","url":null,"abstract":"<p>The increasing severity and frequency of urban pluvial floods has prompted numerous research studies on pluvial flood risk assessment. However, the literature reveals significant variability in the data resolutions and model types employed. In this study, we aim to provide quantitative insights on the data and modelling requirements for pluvial flood risk practitioners and scientists. We analyse combinations of various data resolutions, ranging from 2 to 50 m, and model complexities, including cellular automata (CA), 2D hydrological models, and coupled 2D–1D models. We evaluate each combination's performance against a benchmark, assessing accuracy in flood mapping, hazard, damage, and risk quantification. Our findings indicate that data resolution affects accuracy more than model complexity. Lower data resolutions lead to underpredictions in flood depth, which subsequently affect hazard, damage, and risk assessment. Thus, we recommend using a digital elevation model (DEM) resolution between 2 and 5 m for accurate flood modelling. With respect to model complexity, we show that combining CA models with high-resolution data (e.g., 2 m DEM) offers substantial computational time savings while maintaining high <i>F</i>-statistic values (between 0.76 and 0.78). Additionally, we found that all models were able to estimate relative residential damage with errors between +10% to −20% when combined with DEMs with 2 and 5 m resolution, while lower DEM resolutions were associated to higher errors (above −30%). The results presented in this study, and their discussion, serve as a guide in selecting appropriate models and data resolutions for pluvial flood risk modelling, and in understanding the loss in accuracy related to multiple model–data combinations.</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/jfr3.70187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668987","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}