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Generation of artificial rainfall events for flood risk assessment in Taiwan

Author

Listed:
  • Wen-Ko Hsu

    (National Central University)

  • Pei-Chiung Huang

    (National Central University)

  • Ching-Cheng Chang

    (National Taiwan University)

  • Wei-Ling Chiang

    (National Central University)

  • Dung-Jiang Chiou

    (National Central University)

  • Cheng-Wu Chen

    (National Kaohsiung Marine University
    King Abdulaziz University)

Abstract

Typhoons frequently cause casualties, property damage and economic losses in Taiwan. Several flood risk models have been developed to assess loss for Taiwan’s property insurance industry. However, these models have ignored the potential for extreme rainfalls, which could lead to underestimation of assessments of potential property loss. This could be a problem if, e.g., only data from the 239 typhoon alert events recorded by Taiwan’s Central Weather Bureau from 1960–2010 are considered in the flood risk models. This work generates a sufficient number of artificial rainfall events, including potentially extreme rainfall events using truncated lognormal distributions and correlation matrices of historic rainfall amounts for the watershed basins in Taiwan. The artificial events basically demonstrate similar probability distributions and spatial distributions of rainfall as historic events. A practical case study is carried out that includes different artificial events. Comparisons of different event cases and their application for flood risk assessment for a property portfolio are made. Higher losses could occur in the artificial cases of extreme rainfall than the losses from historic cases. This outcome should be seen as a practical supplement for flood risk assessments, considering the influence of potentially extreme future rainfall events.

Suggested Citation

  • Wen-Ko Hsu & Pei-Chiung Huang & Ching-Cheng Chang & Wei-Ling Chiang & Dung-Jiang Chiou & Cheng-Wu Chen, 2023. "Generation of artificial rainfall events for flood risk assessment in Taiwan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 119(3), pages 2235-2250, December.
  • Handle: RePEc:spr:nathaz:v:119:y:2023:i:3:d:10.1007_s11069-014-1233-1
    DOI: 10.1007/s11069-014-1233-1
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    References listed on IDEAS

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    1. Jean-Luc Kok & Malte Grossmann, 2010. "Large-scale assessment of flood risk and the effects of mitigation measures along the Elbe River," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 52(1), pages 143-166, January.
    2. Mohammadreza Rajabalinejad & Tew-Fik Mahdi, 2010. "The inclusive and simplified forms of Bayesian interpolation for general and monotonic models using Gaussian and Generalized Beta distributions with application to Monte Carlo simulations," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 55(1), pages 29-49, October.
    3. Heiko Apel & Annegret Thieken & Bruno Merz & Günter Blöschl, 2006. "A Probabilistic Modelling System for Assessing Flood Risks," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 38(1), pages 79-100, May.
    4. Wen-Ko Hsu & Pei-Chiung Huang & Ching-Cheng Chang & Cheng-Wu Chen & Dung-Moung Hung & Wei-Ling Chiang, 2011. "An integrated flood risk assessment model for property insurance industry in Taiwan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 58(3), pages 1295-1309, September.
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