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Flood Risk Assessment Based on a Cloud Model in Sichuan Province, China

Author

Listed:
  • Jian Liu

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China)

  • Kangjie Wang

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China)

  • Shan Lv

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China)

  • Xiangtao Fan

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China)

  • Haixia He

    (National Disaster Reduction Center, Ministry of Emergency Management, Beijing 100124, China)

Abstract

Floods are serious threats to the safety of people’s lives and property. This paper systematically introduces the basic theories and methods of flood risk assessment, takes Sichuan Province as the study area, and establishes a flood risk assessment index system with 14 indicators in four aspects—disaster-causing factors, disaster-forming environment, disaster-bearing body, and regional disaster resilience capacity—from the causes of disaster losses and flood formation mechanisms. Furthermore, this paper constructs a flood disaster risk assessment model for Sichuan Province based on a cloud model, entropy value, and GIS technology. The model is validated by taking the July–August 2023 flood disaster as an example, and the results show that the distribution of the disaster was consistent with the flood risk assessment results of this paper, which verifies that the selected indicators are appropriate and the model is accurate and valid.

Suggested Citation

  • Jian Liu & Kangjie Wang & Shan Lv & Xiangtao Fan & Haixia He, 2023. "Flood Risk Assessment Based on a Cloud Model in Sichuan Province, China," Sustainability, MDPI, vol. 15(20), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:20:p:14714-:d:1257123
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    References listed on IDEAS

    as
    1. Xuming Wang & Xianrui Yu & Xiaobing Yu, 2022. "Flood Disaster Risk Assessment Based on DEA Model in Southeast Asia along “The Belt and Road”," Sustainability, MDPI, vol. 14(20), pages 1-10, October.
    2. Efthimios Karymbalis & Maria Andreou & Dimitrios-Vasileios Batzakis & Konstantinos Tsanakas & Sotirios Karalis, 2021. "Integration of GIS-Based Multicriteria Decision Analysis and Analytic Hierarchy Process for Flood-Hazard Assessment in the Megalo Rema River Catchment (East Attica, Greece)," Sustainability, MDPI, vol. 13(18), pages 1-25, September.
    3. Guangpeng Wang & Yong Liu & Ziying Hu & Yanli Lyu & Guoming Zhang & Jifu Liu & Yun Liu & Yu Gu & Xichen Huang & Hao Zheng & Qingyan Zhang & Zongze Tong & Chang Hong & Lianyou Liu, 2020. "Flood Risk Assessment Based on Fuzzy Synthetic Evaluation Method in the Beijing-Tianjin-Hebei Metropolitan Area, China," Sustainability, MDPI, vol. 12(4), pages 1-30, February.
    4. Minh Pham Quang & Krti Tallam, 2022. "Predicting Flood Hazards in the Vietnam Central Region: An Artificial Neural Network Approach," Sustainability, MDPI, vol. 14(19), pages 1-18, September.
    5. Xia Bai & Yimin Wang & Juliang Jin & Xiaoming Qi & Chengguo Wu, 2018. "Precondition Cloud and Maximum Entropy Principle Coupling Model-Based Approach for the Comprehensive Assessment of Drought Risk," Sustainability, MDPI, vol. 10(9), pages 1-14, September.
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