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Urban Flood Loss Assessment and Index Insurance Compensation Estimation by Integrating Remote Sensing and Rainfall Multi-Source Data: A Case Study of the 2021 Henan Rainstorm

Author

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  • Zhixia Wu

    (College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China
    College of Management, Sichuan University of Science & Engineering, Zigong 643000, China)

  • Xiazhong Zheng

    (College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China)

  • Yijun Chen

    (College of Management, Sichuan University of Science & Engineering, Zigong 643000, China)

  • Shan Huang

    (Municipal Construction Engineering Center of Cuiping District, Yibin 644000, China)

  • Wenli Hu

    (College of Management, Sichuan University of Science & Engineering, Zigong 643000, China)

  • Chenfei Duan

    (College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China)

Abstract

To address the problems of traditional insurance compensation methods for flood losses, such as difficulty in determining losses, poor timeliness, a complicated compensation process and moral hazard, an urban flood index insurance tiered compensation model integrating remote sensing and rainfall multi-source data was proposed. This paper first extracted the area of water bodies using the Normalized Difference Water Index and estimates the urban flood area loss based on the flood loss model of remote sensing pixels. Second, the tiered compensation mechanism triggered by rainfall was determined, and the urban flood index insurance tiered compensation model was constructed using remote sensing and rainfall multi-source data. Finally, the economic losses and flood insurance compensation in urban flood were estimated. The results show that: (1) the geo-spatial distribution of flood-affected areas by remote sensing inversion is consistent with the actual rainfall characteristics of Henan Province, China; (2) based on the flood losses model of remote sensing pixels, the estimated flood losses for Henan Province are CNY 110.20 billion, which is consistent with the official data (accuracy ≥ 90%); and (3) the proposed model has good accuracy (R 2 = 0.98, F = 1379.42, p < 0.05). The flood index insurance compensation in Henan Province is classified as a three-tier payout, with a total compensation of CNY 24,137 million. This paper can provide a new approach to estimate large-scale urban flood losses and the scientific design of flood index insurance products. It can also provide theoretical and technical support to many countries around the world, particularly those with underdeveloped flood insurance systems.

Suggested Citation

  • Zhixia Wu & Xiazhong Zheng & Yijun Chen & Shan Huang & Wenli Hu & Chenfei Duan, 2023. "Urban Flood Loss Assessment and Index Insurance Compensation Estimation by Integrating Remote Sensing and Rainfall Multi-Source Data: A Case Study of the 2021 Henan Rainstorm," Sustainability, MDPI, vol. 15(15), pages 1-18, July.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11639-:d:1204528
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    References listed on IDEAS

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    1. Boudreault, Mathieu & Ojeda, Angelica, 2022. "Ratemaking territories and adverse selection for flood insurance," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 349-360.
    2. Donatella Porrini & Reimund Schwarze, 2014. "Insurance models and European climate change policies: an assessment," European Journal of Law and Economics, Springer, vol. 38(1), pages 7-28, August.
    3. David Crichton, 2008. "Role of Insurance in Reducing Flood Risk," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 33(1), pages 117-132, January.
    4. Yasuhide Okuyama & Joost R. Santos, 2014. "Disaster Impact And Input--Output Analysis," Economic Systems Research, Taylor & Francis Journals, vol. 26(1), pages 1-12, March.
    5. Carolyn Kousky & Erwann Michel-Kerjan, 2017. "Examining Flood Insurance Claims in the United States: Six Key Findings," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(3), pages 819-850, September.
    6. Quirin Schiermeier, 2011. "Increased flood risk linked to global warming," Nature, Nature, vol. 470(7334), pages 316-316, February.
    7. Barry J. Barnett & Olivier Mahul, 2007. "Weather Index Insurance for Agriculture and Rural Areas in Lower-Income Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(5), pages 1241-1247.
    8. Craig E. Landry & Mohammad R. Jahan‐Parvar, 2011. "Flood Insurance Coverage in the Coastal Zone," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 78(2), pages 361-388, June.
    9. Kousky, Carolyn & Michel-Kerjan, Erwann O. & Raschky, Paul A., 2018. "Does federal disaster assistance crowd out flood insurance?," Journal of Environmental Economics and Management, Elsevier, vol. 87(C), pages 150-164.
    10. Shawn Cole & Daniel Stein & Jeremy Tobacman, 2014. "Dynamics of Demand for Index Insurance: Evidence from a Long-Run Field Experiment," American Economic Review, American Economic Association, vol. 104(5), pages 284-290, May.
    11. Breckner, Miriam & Englmaier, Florian & Stowasser, Till & Sunde, Uwe, 2016. "Resilience to natural disasters — Insurance penetration, institutions, and disaster types," Economics Letters, Elsevier, vol. 148(C), pages 106-110.
    12. Xue Jin & U. Rashid Sumaila & Kedong Yin, 2020. "Direct and Indirect Loss Evaluation of Storm Surge Disaster Based on Static and Dynamic Input-Output Models," Sustainability, MDPI, vol. 12(18), pages 1-25, September.
    13. Craig E. Landry & Dylan Turner & Daniel Petrolia, 2021. "Flood Insurance Market Penetration and Expectations of Disaster Assistance," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(2), pages 357-386, June.
    14. Xavier Giné & Robert Townsend & James Vickery, 2008. "Patterns of Rainfall Insurance Participation in Rural India," The World Bank Economic Review, World Bank, vol. 22(3), pages 539-566, October.
    15. Tse‐Ling Teh & Christopher Woolnough, 2019. "A Better Trigger: Indices for Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 86(4), pages 861-885, December.
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