Journal of Flood Risk Management最新文献

Prediction of Future Land Use and Land Cover Change Impact on Peak Flood: In Case of Babur Watershed, Tekeze Basin, Ethiopia 未来土地利用和土地覆盖变化对洪峰影响的预测——以埃塞俄比亚Tekeze盆地Babur流域为例

IF 3 3区环境科学与生态学

Journal of Flood Risk Management Pub Date : 2025-05-29 DOI: 10.1111/jfr3.70077

Kahsu Hubot, Haddush Goitom, Gebremeskel Aregay, Teame Yisfa

{"title":"Prediction of Future Land Use and Land Cover Change Impact on Peak Flood: In Case of Babur Watershed, Tekeze Basin, Ethiopia","authors":"Kahsu Hubot, Haddush Goitom, Gebremeskel Aregay, Teame Yisfa","doi":"10.1111/jfr3.70077","DOIUrl":"https://doi.org/10.1111/jfr3.70077","url":null,"abstract":"Land use land cover (LULC) classification has been widely studied in remote sensing and GIS for agricultural, ecological, and hydrological processes. This study mainly focused on the prediction of the future impact of LULC change on peak stream flow through quantum GIS (QGIS) with the MOLUSCE plugin for LULC prediction, Geographical Information System (GIS) integrated with the HEC-GeoHMS to prepare input data, and HEC-HMS for hydrologic modeling. ERDAS IMAGINE was used to classify the watershed into six major LULC classes. Based on the Landsat image analyses for 1996–2016, the cropland area, built-up area and vegetation had increased within two decades, and the annual rate of change was 0.11%, 0.83%, and 0.36%, respectively. However, forestland, shrubland, and bareland decreased at an annual rate of change of 0.26%, 0.21%, and 1.56%, respectively. The statistical downscaling model (SDSM) was used for the prediction of future rainfall of the Babur watershed, which helps to predict its future peak stream flow. The performance of the HEC-HMS model was evaluated through sensitivity analysis, calibration, and validation. Both the calibration (1992–1998) and validation (1999–2001) results showed a good match between measured and simulated flow data with the coefficient of determination (R2) of 0.72, percent of bias (PBIAS) of 1.60%, root mean square error (RMSE) of 0.5, and Nash–Sutcliffe efficiency (NSE) of 0.774 for the calibration, and R2 of 0.86, PBIAS of −9.54%, RMSE of 0.4, and NSE of 0.842 for the validation period. Because of the change in LULC, the peak flow has increased by 19.33% and 45.91% during 1996–2016 and 2016–2036, respectively.","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70077","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144171502","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}

引用次数: 0

What Has Rainfall Got to Do With It? Landscape Antecedent Conditions Have a First Order Effect on Flood Inundation Extent in the Hawkesbury-Nepean Valley 降雨与它有什么关系？景观前置条件对霍克斯伯里-尼皮恩河谷洪水淹没程度的一级影响

IF 3 3区环境科学与生态学

Journal of Flood Risk Management Pub Date : 2025-05-28 DOI: 10.1111/jfr3.70064

Wendy Sharples, Jiawei Hou, Katayoon Bahramian, Christopher Pickett-Heaps, Fitsum Woldesmekel, Ulrike Bende-Michl, Elisabetta Carrara

{"title":"What Has Rainfall Got to Do With It? Landscape Antecedent Conditions Have a First Order Effect on Flood Inundation Extent in the Hawkesbury-Nepean Valley","authors":"Wendy Sharples, Jiawei Hou, Katayoon Bahramian, Christopher Pickett-Heaps, Fitsum Woldesmekel, Ulrike Bende-Michl, Elisabetta Carrara","doi":"10.1111/jfr3.70064","DOIUrl":"https://doi.org/10.1111/jfr3.70064","url":null,"abstract":"The Hawkesbury-Nepean valley has a long history of hazardous flooding dating back to when records began, in the 18th century. It is one of the largest coastal basins in the eastern Australian region and supports a large population, agriculture, and industry, as well as being an important environmental asset. Multiple flooding events with differing socioeconomic impacts occurred in the valley between 2020 and 2022, brought about by a rare triple La Niña event—only the third since 1900. In this study, upon examination of the four significant floods in the area, the reasons for the variation in impacts are explored by investigating the climate drivers and antecedent conditions preceding these events, the streamflow during the events, and the hazard footprints themselves. It was found that antecedent landscape conditions exerted a first-order effect on the hazard footprint's size and thus impact. These results imply that with the current landscape drying trends and projected increase in landscape dryness for this region, the projected increase in extreme rainfall events will not affect the flood hazard footprint of medium-sized floods. Thus, impacts from flooding will not necessarily increase in severity in this region in the future.","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144171201","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}

引用次数: 0

Correction to “Flood Risk Mitigation by Spatial Planning—Lessons Learned From Municipal Consultation” 更正“通过空间规划减轻洪水风险-市政咨询的经验教训”

IF 3 3区环境科学与生态学

Journal of Flood Risk Management Pub Date : 2025-05-28 DOI: 10.1111/jfr3.70081

引用次数: 0

Optimized Allocation of Flood Control Emergency Materials Based on Loss Quantification 基于损失量化的防洪应急物资优化配置

IF 3 3区环境科学与生态学

Journal of Flood Risk Management Pub Date : 2025-05-27 DOI: 10.1111/jfr3.70071

Wei Wang, Yunqing Wang, Li Huang, Yue Song

{"title":"Optimized Allocation of Flood Control Emergency Materials Based on Loss Quantification","authors":"Wei Wang, Yunqing Wang, Li Huang, Yue Song","doi":"10.1111/jfr3.70071","DOIUrl":"https://doi.org/10.1111/jfr3.70071","url":null,"abstract":"Reserve management of emergency materials for flood control is the basis for the smooth development of flood control emergency work. To optimize the allocation of flood control emergency materials in each emergency node warehouse, a multiobjective optimization model is constructed from the perspective of multiwarehouse collaborative reservation with the shortest transportation time, the lowest storage and transportation costs, and the minimum out-of-stock loss. The center of gravity method is used to address demand when constructing the quantitative function of out-of-stock loss. The NSGA-II algorithm was selected to generate the results after the method comparison to ultimately determine the Pareto solution of the model. The TOPSIS method was subsequently used to screen and determine the optimal allocation scheme to rationally determine the reserve sizes of different categories of flood control emergency materials in each warehouse. The Jiangsu provincial warehouse materials were used for empirical analysis. Some of the optimized warehouses (e.g., Zhenjiang and Xuzhou) received increased stock of critical materials such as bags, steel pipes, and shovels, whereas others (e.g., Suzhou and Yangzhou) had reduced excess inventory to avoid overstocking. Compared with the initial allocation, the optimized scheme reduces out-of-stock losses by approximately $392,000, lowers transportation costs by over $110,000, and improves the efficiency of flood control emergency scheduling, which can help management make better decisions on the allocation of flood control emergency materials in the future.","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70071","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140610","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}

引用次数: 0

Correction to “Evaluating the French Flash Flood Warning System Using Hydrological and Impact Data in Southeastern France” 更正“利用法国东南部水文和影响数据评估法国山洪预警系统”

IF 3 3区环境科学与生态学

Journal of Flood Risk Management Pub Date : 2025-05-25 DOI: 10.1111/jfr3.70073

引用次数: 0

Postdisaster Reconstruction After the 2021 Floods From the Neighborhood Perspective 从邻里视角看2021年洪水后的灾后重建

IF 3 3区环境科学与生态学

Journal of Flood Risk Management Pub Date : 2025-05-15 DOI: 10.1111/jfr3.70068

Marisa Fuchs

{"title":"Postdisaster Reconstruction After the 2021 Floods From the Neighborhood Perspective","authors":"Marisa Fuchs","doi":"10.1111/jfr3.70068","DOIUrl":"https://doi.org/10.1111/jfr3.70068","url":null,"abstract":"The floods in Western Europe in July 2021 demonstrated the diverse ways and varying paces at which neighborhoods recover from disasters. Based on two exemplary neighborhoods affected by the floods in the city of Hagen, Germany, this study examines the reconstruction process, highlighting the influence of social vulnerabilities and community resilience on private reconstruction processes. Despite differing contexts, both case studies demonstrated a significant reliance on external support during reconstruction. Individual needs varied based on social vulnerabilities within and between population groups, primarily manifesting as challenges in information dissemination and access to support services like funding and expertise. The findings reveal differences in the ability and capacity of neighborhoods to collectively address these vulnerabilities. While small neighborhood networks effectively facilitated information sharing in both cases, one case study relied more heavily on external assistance from nonprofit organizations for larger and longer-term community-driven initiatives. The study underscores the need for improvements in postdisaster reconstruction governance. Public authorities predominantly view neighborhoods as recipients rather than partners in the reconstruction process, without adequately addressing their social vulnerabilities within their governance approaches. Supporting local social infrastructures is crucial, as they connect formal reconstruction with the neighborhood, aiding resource access and resilience building.","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70068","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074375","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}

引用次数: 0

Evacuating Flash Flood Victims: Key Drivers and Psychological Burden 疏散山洪灾民：主要驱动因素和心理负担

IF 3 3区环境科学与生态学

Journal of Flood Risk Management Pub Date : 2025-05-15 DOI: 10.1111/jfr3.70065

Nivedita Sairam, Doménica Michelle Jaramillo Sánchez, Lisa Dillenardt, Annegret H. Thieken

{"title":"Evacuating Flash Flood Victims: Key Drivers and Psychological Burden","authors":"Nivedita Sairam, Doménica Michelle Jaramillo Sánchez, Lisa Dillenardt, Annegret H. Thieken","doi":"10.1111/jfr3.70065","DOIUrl":"https://doi.org/10.1111/jfr3.70065","url":null,"abstract":"Effective, timely, and fair evacuation is crucial to mitigate flood impacts. We aim to identify socio-economic attributes and flood event characteristics influencing evacuation and to quantify the psychological burden of people who experienced evacuation. We implement regression models and matching methods on an empirical dataset (n = 557) collected from the people affected by the 2021 flood in Germany. Homeowners, people with low socioeconomic status, and younger age groups were more likely to be evacuated before/during the flood event. In addition to the severity of the flood experience, high income and insured households were more likely to be evacuated after the event. In instances of evacuation before or during a flood, the psychological burden on those evacuated was found to be 10.3% higher compared to those who were not evacuated. Evacuation did not directly impact the psychological burden of people evacuated after the event. However, the duration of evacuation influenced the psychological burden on the evacuated people. The identification of the drivers of evacuation and quantification of the resulting psychological burden call for improved risk communication, preparedness, and support systems to recognize and address psychological distress in evacuated people.","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074374","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}

引用次数: 0

A Discrete Boltzmann Model for Transcritical Flows Governed by the Saint-Venant Equations 由Saint-Venant方程控制的跨临界流动的离散Boltzmann模型

IF 3 3区环境科学与生态学

Journal of Flood Risk Management Pub Date : 2025-05-15 DOI: 10.1111/jfr3.70058

Yong Peng, Bo Wang, Jianping Meng, Xianfei Yin

{"title":"A Discrete Boltzmann Model for Transcritical Flows Governed by the Saint-Venant Equations","authors":"Yong Peng, Bo Wang, Jianping Meng, Xianfei Yin","doi":"10.1111/jfr3.70058","DOIUrl":"https://doi.org/10.1111/jfr3.70058","url":null,"abstract":"Based on the Hermite expansion approach, a type of discrete Boltzmann model is devised to simulate the open channel flows governed by the Saint-Venant equations. In this model, a four-discrete-velocity set is adopted, and a local equilibrium distribution with the fourth-order polynomials is kept to simulate the supercritical flows. To numerically solve the kinetic equation, the finite difference method is employed. The model is numerically validated by using four benchmark problems, i.e., dam-break flows, hydraulic jump, steady flow over a bump, and the flume dam-break flows with rectangular and triangular cross-sections. Then, the thin film method is incorporated into the proposed model to deal with the wet-dry boundaries, and this ability has been validated by two cases, i.e., the dam-break flows in a converging–diverging channel and over a triangular obstacle. It is found that the present discrete Boltzmann model can accurately predict the subcritical, transcritical, and supercritical flows with source terms and wet-dry boundaries.","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074373","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}

引用次数: 0

Climate Change, Floods, and Community Resilience: A Study of the Kamala River Basin, Nepal 气候变化、洪水和社区恢复力：尼泊尔卡玛拉河流域的研究

IF 3 3区环境科学与生态学

Journal of Flood Risk Management Pub Date : 2025-05-14 DOI: 10.1111/jfr3.70069

Chandra Lal Pandey

{"title":"Climate Change, Floods, and Community Resilience: A Study of the Kamala River Basin, Nepal","authors":"Chandra Lal Pandey","doi":"10.1111/jfr3.70069","DOIUrl":"https://doi.org/10.1111/jfr3.70069","url":null,"abstract":"Climate change is one of the biggest threats humanity is facing in the 21st century. Nepal, being a low-income country located on the lap of the Himalayas, is experiencing a wide range of impacts from changing climate and climate-induced disasters. Communities of the Kamala river basin are increasingly affected by climate-induced hazards such as floods. Land use change, deforestation, and climate change-induced disasters such as landslides, droughts, and floods are affecting the riverine communities. Floods have been one of the most serious threats for centuries; however, their frequency and scope are being amplified by climate-induced extreme weather events. Employing a convergent mixed-method approach, this study explored the impacts of climate-induced disasters, especially focusing on floods in Ward 12 of Siraha and Ward 11 of Dudhauli municipalities in Nepal's Kamala river basin. It investigated the current status of impacts of climate change-induced disasters; the availability, usage and effectiveness of flood early warning systems; and analyzed local community practices for making communities flood and disaster resilient. The findings suggested that the climate-induced disasters are becoming key concerns for the communities as they are affecting multiple areas from water security to livelihood options. In addition, the existing early warning systems for floods are still weak. While communities are attempting adaptation strategies including increasing social cohesion, their resilience level is insufficient. This study has made original contribution to the relevant literature and developed applicable knowledge for strengthening local communities' capacities to build climate, flood, and disaster resilience.","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949951","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}

引用次数: 0

Flood Inundation Mapping of a River Stretch Using Machine Learning Algorithms in the Google Earth Engine Environment 在b谷歌地球引擎环境下使用机器学习算法绘制河段洪水淹没图

IF 3 3区环境科学与生态学

Journal of Flood Risk Management Pub Date : 2025-05-13 DOI: 10.1111/jfr3.70062

Maaz Ashhar, Venkata Reddy Keesara, Venkataramana Sridhar

{"title":"Flood Inundation Mapping of a River Stretch Using Machine Learning Algorithms in the Google Earth Engine Environment","authors":"Maaz Ashhar, Venkata Reddy Keesara, Venkataramana Sridhar","doi":"10.1111/jfr3.70062","DOIUrl":"https://doi.org/10.1111/jfr3.70062","url":null,"abstract":"Floods are among the most common natural disasters in India, causing significant socio-economic and environmental impacts. This study focuses on a frequently flooded stretch of the Godavari River in Telangana, India, to analyze the flood event that occurred between 14th July 2022 and 20th July 2022. Sentinel-1 SAR data from 6th July 2022 to 20th July 2022 were used to perform flood inundation mapping. Various machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Tree (GBT), and Classification and Regression Tree (CART), were employed. The analysis revealed that out of the total study area of 1,556,544 ha, SVM classified 59,823 ha, RF classified 60,088 ha, GBT classified 57,497 ha, and CART classified 58,374 ha as flooded areas. In contrast, Otsu's Thresholding technique identified a significantly larger flooded area of 359,253 ha. For validation, 70 flooded and 30 non-flooded points were randomly selected from the flood map provided by the National Remote Sensing Center (NRSC). The RF algorithm achieved the best performance, correctly classifying 58 flooded points and 26 non-flooded points, resulting in an overall accuracy of 84%. The findings highlight the effectiveness of machine learning algorithms, particularly Random Forest, in flood inundation mapping.","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70062","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143939302","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}

引用次数: 0