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Cao X, Sun Y, Wang Y, Wang Y, Cheng X, Zhang W, Zong J, Wang R. Coastal erosion and flooding risk assessment based on grid scale: A case study of six coastal metropolitan areas. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174393. [PMID: 38960161 DOI: 10.1016/j.scitotenv.2024.174393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/28/2024] [Accepted: 06/28/2024] [Indexed: 07/05/2024]
Abstract
Coastal areas, situated at the critical juncture of sea-land interaction, are confronted with significant challenges from coastal erosion and flooding. It is imperative to evaluate these risks and offer scientific guidance to foster regional sustainable development. This article developed a coastal risk assessment model based on grid scale, integrating both coastal exposure and socio-ecological environment. Fourteen indicators were selected, aiming to offer a systematic approach for estimating and comparing disaster risks in coastal areas. This risk assessment model was applied to Shanghai, New York, Sydney, San Francisco, Randstad, and Tokyo metropolitan areas. The results indicate: (1) Accounting for the protective role of habitat types like mangroves and the distance attenuation effect offered a more precise representation of hazard situation; (2) The integration of the Game Theory weighting method with both subjective Analytic Hierarchy Process and objective CRITIC weighting enhanced the scientific validity and rationality of the results by minimizing deviations between subjective and objective weights; (3) Shanghai exhibited the highest average hazard and vulnerability, San Francisco had the lowest average hazard and Sydney had the lowest average vulnerability; In terms of comprehensive risk, Shanghai possessed the highest average risk, while Sydney presented the lowest. The proposed model framework is designed to swiftly identify high-risk zones, providing detailed information references for local governments to devise efficacious risk management and prevention strategies.
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Affiliation(s)
- Xuyue Cao
- Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China; College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China; State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China; Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China
| | - Yonghua Sun
- Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China; College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China; State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China; Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China.
| | - Yanzhao Wang
- Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China; College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China; State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China; Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China
| | - Yihan Wang
- Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China; College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China; State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China; Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China
| | - Xinglu Cheng
- Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China; College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China; State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China; Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China
| | - Wangkuan Zhang
- Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China; College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China; State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China; Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China
| | - JinKun Zong
- Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China; College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China; State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China; Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China
| | - Ruozeng Wang
- Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China; College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China; State Key Laboratory of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China; Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China
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