Yuxin Cai, Chao Chen, Yi Shi, Rong Liu, Xiaoyang Wang, Xilei Tao, Dan Yang
{"title":"基于 GIS 和混合多标准决策分析的中国湖北省汉川市城市洪水风险评估","authors":"Yuxin Cai, Chao Chen, Yi Shi, Rong Liu, Xiaoyang Wang, Xilei Tao, Dan Yang","doi":"10.1007/s12665-024-11934-2","DOIUrl":null,"url":null,"abstract":"<div><p>The risk mapping of flood-prone areas enables the visualization of disaster risks, which can serve as a basis for the development of disaster mitigation strategies. This study presents a new hybrid multi-criteria decision analysis method that combines geographic information systems in Hanchuan City, integrating multidisciplinary fields to develop a more systematic and accurate assessment method. We selected 19 factors to create models for hazard, sensitivity, vulnerability, and disaster prevention. For the first time, a vulnerability model considered the impacts of population, economy, housing, and crops to optimize the indicator system. This model calculated weights using the improved analytic hierarchy process based on the cloud model, combined the entropy weighting method and game theory, and applied ArcGIS 10.8 to generate a risk map. The model results were validated using historical disaster sites, with an accuracy of up to 92%. The results indicate that the annual waterlogging index in the hazard model, land use in the sensitivity model, population and GDP in the vulnerability model, and shelter capacity in the disaster prevention model had larger weights and were closely related to meteorological, hydrological, and emergency responses. Approximately 17.55% of the study area falls within the high-risk zone, while 35.10% classified as medium–high risk is concentrated in the east-central region of the Han River. This risk assessment will serve as a basis for urban emergency policies, helping similar urban areas realize sustainable development strategies.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"83 22","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GIS and hybrid multi-criteria decision analysis based urban flood risk assessment in Hanchuan City, Hubei Province, China\",\"authors\":\"Yuxin Cai, Chao Chen, Yi Shi, Rong Liu, Xiaoyang Wang, Xilei Tao, Dan Yang\",\"doi\":\"10.1007/s12665-024-11934-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The risk mapping of flood-prone areas enables the visualization of disaster risks, which can serve as a basis for the development of disaster mitigation strategies. This study presents a new hybrid multi-criteria decision analysis method that combines geographic information systems in Hanchuan City, integrating multidisciplinary fields to develop a more systematic and accurate assessment method. We selected 19 factors to create models for hazard, sensitivity, vulnerability, and disaster prevention. For the first time, a vulnerability model considered the impacts of population, economy, housing, and crops to optimize the indicator system. This model calculated weights using the improved analytic hierarchy process based on the cloud model, combined the entropy weighting method and game theory, and applied ArcGIS 10.8 to generate a risk map. The model results were validated using historical disaster sites, with an accuracy of up to 92%. The results indicate that the annual waterlogging index in the hazard model, land use in the sensitivity model, population and GDP in the vulnerability model, and shelter capacity in the disaster prevention model had larger weights and were closely related to meteorological, hydrological, and emergency responses. Approximately 17.55% of the study area falls within the high-risk zone, while 35.10% classified as medium–high risk is concentrated in the east-central region of the Han River. This risk assessment will serve as a basis for urban emergency policies, helping similar urban areas realize sustainable development strategies.</p></div>\",\"PeriodicalId\":542,\"journal\":{\"name\":\"Environmental Earth Sciences\",\"volume\":\"83 22\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Earth Sciences\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12665-024-11934-2\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Earth Sciences","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s12665-024-11934-2","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
GIS and hybrid multi-criteria decision analysis based urban flood risk assessment in Hanchuan City, Hubei Province, China
The risk mapping of flood-prone areas enables the visualization of disaster risks, which can serve as a basis for the development of disaster mitigation strategies. This study presents a new hybrid multi-criteria decision analysis method that combines geographic information systems in Hanchuan City, integrating multidisciplinary fields to develop a more systematic and accurate assessment method. We selected 19 factors to create models for hazard, sensitivity, vulnerability, and disaster prevention. For the first time, a vulnerability model considered the impacts of population, economy, housing, and crops to optimize the indicator system. This model calculated weights using the improved analytic hierarchy process based on the cloud model, combined the entropy weighting method and game theory, and applied ArcGIS 10.8 to generate a risk map. The model results were validated using historical disaster sites, with an accuracy of up to 92%. The results indicate that the annual waterlogging index in the hazard model, land use in the sensitivity model, population and GDP in the vulnerability model, and shelter capacity in the disaster prevention model had larger weights and were closely related to meteorological, hydrological, and emergency responses. Approximately 17.55% of the study area falls within the high-risk zone, while 35.10% classified as medium–high risk is concentrated in the east-central region of the Han River. This risk assessment will serve as a basis for urban emergency policies, helping similar urban areas realize sustainable development strategies.
期刊介绍:
Environmental Earth Sciences is an international multidisciplinary journal concerned with all aspects of interaction between humans, natural resources, ecosystems, special climates or unique geographic zones, and the earth:
Water and soil contamination caused by waste management and disposal practices
Environmental problems associated with transportation by land, air, or water
Geological processes that may impact biosystems or humans
Man-made or naturally occurring geological or hydrological hazards
Environmental problems associated with the recovery of materials from the earth
Environmental problems caused by extraction of minerals, coal, and ores, as well as oil and gas, water and alternative energy sources
Environmental impacts of exploration and recultivation – Environmental impacts of hazardous materials
Management of environmental data and information in data banks and information systems
Dissemination of knowledge on techniques, methods, approaches and experiences to improve and remediate the environment
In pursuit of these topics, the geoscientific disciplines are invited to contribute their knowledge and experience. Major disciplines include: hydrogeology, hydrochemistry, geochemistry, geophysics, engineering geology, remediation science, natural resources management, environmental climatology and biota, environmental geography, soil science and geomicrobiology.