Comprehensive Assessment of Large-Scale Regional Fluvial Flood Exposure Using Public Datasets: A Case Study from China DOI Creative Commons
Xuanchi Chen,

Bingjie Liang,

Junhua Li

et al.

ISPRS International Journal of Geo-Information, Journal Year: 2024, Volume and Issue: 13(10), P. 357 - 357

Published: Oct. 8, 2024

China’s vulnerability to fluvial floods necessitates extensive exposure studies. Previous large-scale regional analyses often relied on a limited set of assessment indicators due challenges in data acquisition, compounded by the scarcity corresponding flood distribution data. The integration public datasets offers potential solution these challenges. In this study, we obtained four key indicators—population, built-up area (BA), road length (RL), and average gross domestic product (GDP)—and conducted an innovative analysis their correlations both overall locally. Utilising indicators, developed comprehensive index employing entropy-weighting k-means clustering methods assessed across multiple return periods using maps. used for as well maps, are primarily derived from remote sensing products. Our findings indicate weak correlation between various at global local scales, underscoring limitations singular thorough assessment. Notably, observed significant concentration river flooding east Hu Line, particularly within eastern coastal region. As extended 10 500 years, extent areas with depths exceeding 1 m expanded markedly, encompassing 2.24% territory. This expansion heightened risks 15 administrative regions varying levels, Jiangsu (JS) Shanghai (SH). research provides robust framework understanding risk dynamics, advocating resource allocation towards prevention control high-exposure, high-flood areas. establish solid scientific foundation effectively mitigating China promoting sustainable development.

Language: Английский

A novel framework for urban flood risk assessment: Multiple perspectives and causal analysis DOI
Yongheng Wang, Qingtao Zhang, Kairong Lin

et al.

Water Research, Journal Year: 2024, Volume and Issue: 256, P. 121591 - 121591

Published: April 8, 2024

Language: Английский

Citations

16
Efficiency evaluation of low impact development practices on urban flood risk DOI

Sara Ayoubi Ayoublu,

Mehdi Vafakhah, Hamid Reza Pourghasemi

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 356, P. 120467 - 120467

Published: March 13, 2024

Language: Английский

Citations

12
Dynamic risk assessment of urban flood disasters based on functional area division—A case study in Shenzhen, China DOI
Ting Wang, Huimin Wang, Zhiqiang Wang

et al.

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 345, P. 118787 - 118787

Published: Aug. 26, 2023

Language: Английский

Citations

21
Mobility behaviors shift disparity in flood exposure in U.S. population groups DOI
Bo Li, Chao Fan,

Yu-Heng Chien

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: 108, P. 104545 - 104545

Published: May 10, 2024

Language: Английский

Citations

5
Assessing the social risks of flooding for coastal societies: a case study for Prince Edward Island, Canada DOI Creative Commons
Tianze Pang, Mohammad Aminur Rahman Shah, Quan Van Dau

et al.

Environmental Research Communications, Journal Year: 2024, Volume and Issue: 6(7), P. 075027 - 075027

Published: July 1, 2024

Abstract With the worldwide growing threat of flooding, assessing flood risks for human societies and associated social vulnerability has become a necessary but challenging task. Earlier research indicates that islands usually face heightened due to higher population density, isolation, oceanic activities, while there is an existing lack experience in island-focused risk under complex interactions between geography socioeconomics. In this context, our study employs high-resolution hazard data principal component analysis (PCA) method comprehensively assess exposure Prince Edward Island (PEI), Canada, where limited been delivered on assessments. The findings reveal exposed populations are closely related distribution areas, with increasingly severe impact from current future climate conditions, especially island’s north shore. Exposed buildings exhibit concentrated at different levels community centers, change projected significantly worsen building compared population, possibly urban agglomeration effect. most populated cities towns show highest vulnerabilities PEI, results reflect relatively less economic structure islands. Recommendations management coming stage include necessity particular actions, recognizing centers as critical sites responses, incorporating hazards into planning mitigate impacts continuous urbanization ecosystem services prevention.

Language: Английский

Citations

5
Flood risk assessment using machine learning, hydrodynamic modelling, and the analytic hierarchy process DOI Creative Commons

Nguyen Huu Duy,

Le T. Pham,

Nguyen Xuan Linh

et al.

Journal of Hydroinformatics, Journal Year: 2024, Volume and Issue: 26(8), P. 1852 - 1882

Published: July 30, 2024

ABSTRACT The objective of this study was to develop a theoretical framework based on machine learning, the hydrodynamic model, and analytic hierarchy process (AHP) assess risk flooding downstream Ba River in Phu Yen. made up three main factors: flood risk, exposure, vulnerability. Hazard calculated from depth, velocity, susceptibility, which depth velocity were using susceptibility built namely, support vector machines, decision trees, AdaBoost, CatBoost. Flood exposure constructed by combining population density, distance river, land use/land cover. vulnerability poverty level road density. indices each factor integrated AHP. results showed that hydraulic model successful simulating events 1993 2020, with Nash–Sutcliffe efficiency values 0.95 0.79, respectively. All learning models performed well, area under curve (AUC) more than 0.90; among them, AdaBoost most accurate, an AUC value 0.99.

Language: Английский

Citations

5
Social vulnerability correlates of flood risk to crops and buildings DOI Creative Commons
Sina Razzaghi Asl, Atiya Rahman, Eric Tate

et al.

Natural Hazards, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 24, 2025

Language: Английский

Citations

0
Deciphering the Social Vulnerability of Landslides Using the Coefficient of Variation-Kullback-Leibler-TOPSIS at an Administrative Village Scale DOI Creative Commons

Yueyue Wang,

Xueling Wu, Guo Lin

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(4), P. 714 - 714

Published: Feb. 19, 2025

Yu’nan County is located in the Pacific Rim geological disaster-prone area. Frequent landslides are an important cause of population, property, and infrastructure losses, which directly threaten sustainable development regional social economy. Based on field survey data, this paper employs coefficient variation method (CV) improved TOPSIS model (Kullback-Leibler-Technique for Order Preference by Similarity to Ideal Solution) assess vulnerability landslide disasters 182 administrative villages County. Also, it conducts a ranking comprehensive analysis their levels. Finally, accuracy evaluation results validated applying losses incurred from per unit area within same year. The indicate significant spatial variability across County, with 68 out exhibiting moderate levels or higher. This suggests high risk widespread damage potential disasters. Among these, Xincheng village has highest score, while Chongtai lowest, 0.979 difference vulnerabilities. By comparing actual landslides, found that predicted CV-KL-TOPSIS more consistent results. Furthermore, among ten sub-factors, population density, building value, road value contribute most significantly overall weight 0.269, 0.152, 0.105, respectively, suggesting mountainous areas where relatively concentrated, hazards reflection characteristics local economic level. framework indicators proposed can systematically accurately evaluate landslide-prone areas, provide reference urban planning management areas.

Language: Английский

Citations

0
Current and Future Trends for Resilient Inland Waterway Transportation Systems during Flood Disruptions DOI
Shokoufeh Ahmadi, Jennifer I. Lather, Christine E. Wittich

et al.

Journal of Construction Engineering and Management, Journal Year: 2025, Volume and Issue: 151(6)

Published: March 25, 2025

Language: Английский

Citations

0
Development of a Social Vulnerability Index: Enhancing approaches to support climate justice DOI Creative Commons

Denise McCullagh,

Walther Cámaro-García,

Declan Dunne

et al.

MethodsX, Journal Year: 2025, Volume and Issue: unknown, P. 103290 - 103290

Published: March 1, 2025

Climate change is causing increasing frequency and severity of various hazards such as flooding extreme temperatures. Vulnerability analysis that broadens the focus beyond exposure to invaluable in supporting just climate action. This study outlines modifications made social vulnerability environmental index developed by Fitton et al., [1] building upon previous work make hazard specific applicable across a range locations, with case studies Ireland, Italy, Northern Ireland Spain variety users. New indicators have been included current version Social Index (SVI) weighting methods proposed. method was using programming tools R GIS (Geographic Information Systems), both which are accessible easily adapted updated, support wider dissemination overall usability.•Step-by-step guidance on use SVI so can be replicated•A methodology options suit users different levels data availability•Tailored needs local authorities adaptation measures equitable.

Language: Английский

Citations

0