Quantitative assessment of building risks and loss ratios caused by storm surge disasters: A case study of Xiamen, China

被引:6
|
作者
Shi, Xianwu [1 ,2 ,3 ,4 ]
Lv, Yafei [5 ]
Dong, Dibo [6 ]
Jia, Ning [7 ]
Ge, Jianzhong [8 ]
Yin, Jie [9 ]
机构
[1] Beijing Normal Univ, Key Lab Environm Change & Nat Disasters, Chinese Minist Educ, Beijing 100875, Peoples R China
[2] Minist Emergency Management, Acad Disaster Reduct & Emergency Management, Beijing 100875, Peoples R China
[3] Minist Educ, Beijing 100875, Peoples R China
[4] Beijing Normal Univ, Fac Geog Sci, Beijing 100875, Peoples R China
[5] Hohai Univ, Coll Oceanog, Nanjing 210098, Peoples R China
[6] Fujian Univ Technol, Inst Smart Marine & Engn, Fuzhou 350118, Peoples R China
[7] Natl Marine Hazard Mitigat Serv, Beijing 100194, Peoples R China
[8] East China Normal Univ, State Key Lab Estuarine & Coastal Res, Shanghai 200241, Peoples R China
[9] East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
关键词
Storm surge; Numerical simulation; Vulnerability curve; Risk assessment; Xiamen; COASTAL; VULNERABILITY; IMPACTS; MODEL;
D O I
10.1016/j.apor.2024.103934
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
China is severely affected by storm surge disasters, which result in substantial economic losses and casualties in coastal regions. Assessing the risk of storm surge disasters can provide valuable insights into the expected losses and severity of future impacts, offering critical foresight for disaster prevention and mitigation strategies. This study assesses the quantitative risk of storm surge disasters, focusing on coastal buildings since they are particularly susceptible to storm surges and frequently bear the brunt such disasters. Xiamen city, China, was used as case study. A high-precision numerical model, using Finite Volume Community Ocean Model (FVCOM), was developed to simulate inundation during storm surges. By referencing historical storm surge records, we defined key parameters for probable maximum typhoon-induced storm surge (PMTSS) in Xiamen. These parameters were used to calculate the corresponding inundation range and water depth distribution within the region. Subsequently, the results were integrated with vulnerability curves that represent the susceptibility of buildings in Xiamen to storm surge-induced damage, enabling the quantitative risk assessment for associated loss risks. The study findings offer valuable guidance for urban planning and functional layout design in coastal areas. Furthermore, the findings contribute to understanding storm surge disaster risks and facilitating informed decision-making processes, ultimately enhancing disaster preparedness and resilience in vulnerable coastal regions.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] A quantitative method for storm surge vulnerability assessment - a case study of Weihai city
    Liu, Jin
    Gong, Jian-Hua
    Liang, Jian-Ming
    Li, Yi
    Kang, Lin-Chong
    Song, Li-Li
    Shi, Sui-Xiang
    INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2017, 10 (05) : 539 - 559
  • [2] Comprehensive economic losses assessment of storm surge disasters using open data: a case study of Zhoushan, China
    Chen, Bairu
    He, Zhiguo
    Li, Li
    Chen, Qian
    He, Junyu
    Li, Feixiang
    Chu, Dongdong
    Cao, Zeng
    Yang, Xuchao
    JOURNAL OF WATER AND CLIMATE CHANGE, 2024, 15 (08) : 3647 - 3665
  • [3] Storm surge risk assessment method for a coastal county in China: case study of Jinshan District, Shanghai
    Shi, Xianwu
    Qiu, Jufei
    Chen, Bingrui
    Zhang, Xiaojie
    Guo, Haoshuang
    Wang, Jun
    Bei, Zhuyuan
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2020, 34 (05) : 627 - 640
  • [4] Ecological Risk Assessment of Typhoon and Storm-surge Disasters in the Coastal Land of China
    Xu, Lifen
    Xu, Xuegong
    Yan, Lei
    Lu, Yaling
    PROCEEDINGS OF THE FIRST SYMPOSIUM ON DISASTER RISK ANALYSIS AND MANAGEMENT IN CHINESE LITTORAL REGIONS, 2011, 18 : 74 - 82
  • [5] Storm surge risk assessment method for a coastal county in China: case study of Jinshan District, Shanghai
    Shi Xianwu
    Qiu Jufei
    Chen Bingrui
    Zhang Xiaojie
    Guo Haoshuang
    Wang Jun
    Bei Zhuyuan
    Stochastic Environmental Research and Risk Assessment, 2020, 34 : 627 - 640
  • [6] Storm surge risk assessment for the insurance system: A case study in Tokyo Bay, Japan
    Hisamatsu, Rikito
    Tabeta, Shigeru
    Kim, Sooyoul
    Mizuno, Katsunori
    OCEAN & COASTAL MANAGEMENT, 2020, 189
  • [7] Fine-Scale Coastal Storm Surge Disaster Vulnerability and Risk Assessment Model: A Case Study of Laizhou Bay, China
    Liu, Yueming
    Lu, Chen
    Yang, Xiaomei
    Wang, Zhihua
    Liu, Bin
    REMOTE SENSING, 2020, 12 (08)
  • [8] Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups
    Jin, Xue
    Shi, Xiaoxia
    Gao, Jintian
    Xu, Tongbin
    Yin, Kedong
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2018, 15 (04):
  • [9] Integrated Visualization Approach for Real-Time and Dynamic Assessment of Storm Surge Disasters for China's Seas
    Zhou, Lin
    Hu, Wei
    Jia, Zhen
    Li, Xinfang
    Li, Yaru
    Su, Tianyun
    Guo, Qingsheng
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2020, 9 (01)
  • [10] Economic loss assessment of typhoon-induced storm surge disasters in the South China Sea based on GSA-BP model
    Zhang, Yuxuan
    Zhang, Tianyu
    Shen, Wenqi
    Ou, Zijing
    Zhang, Junping
    FRONTIERS IN EARTH SCIENCE, 2023, 11