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Developing Flood Risk Zones during an Extreme Rain Event from the Perspective of Social Insurance Management

Author

Listed:
  • Shakti P. C.

    (National Research Institute for Earth Science and Disaster Resilience (NIED), Tsukuba 305-0006, Japan)

  • Kohin Hirano

    (National Research Institute for Earth Science and Disaster Resilience (NIED), Tsukuba 305-0006, Japan)

  • Koyuru Iwanami

    (National Research Institute for Earth Science and Disaster Resilience (NIED), Tsukuba 305-0006, Japan)

Abstract

Recently, Japan has been hit by more frequent and severe rainstorms and floods. Typhoon Hagibis caused heavy flooding in many river basins in central and eastern Japan from 12–13 October 2019, resulting in loss of life, substantial damage, and many flood insurance claims. Considering that obtaining accurate assessments of flood situations remains a significant challenge, this study used a geographic information system (GIS)-based analytical hierarchy process (AHP) approach to develop flood susceptibility maps for the Abukuma, Naka, and Natsui River Basins during the Typhoon Hagibis event. The maps were based on population density, building density, land-use profile, distance from the river, slope, and flood inundation. A novel approach was also employed to simulate the flood inundation profiles of the river basins. In addition, a crosscheck evaluated the relationship between flood insurance claims and the developed flood risk zones within the river basins. Over 70% of insurance claims were concentrated in high to very high risk zones identified by the flood susceptibility maps. These findings demonstrate the effectiveness of this type of assessment in identifying areas that are particularly vulnerable to flood damage, which can be a useful reference for flood disaster management and related stakeholder concerns for future extreme flood events.

Suggested Citation

  • Shakti P. C. & Kohin Hirano & Koyuru Iwanami, 2023. "Developing Flood Risk Zones during an Extreme Rain Event from the Perspective of Social Insurance Management," Sustainability, MDPI, vol. 15(6), pages 1-21, March.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:4909-:d:1092798
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    References listed on IDEAS

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    1. Yukiko Hirabayashi & Roobavannan Mahendran & Sujan Koirala & Lisako Konoshima & Dai Yamazaki & Satoshi Watanabe & Hyungjun Kim & Shinjiro Kanae, 2013. "Global flood risk under climate change," Nature Climate Change, Nature, vol. 3(9), pages 816-821, September.
    2. Juan Fan & Guangwei Huang, 2020. "Evaluation of Flood Risk Management in Japan through a Recent Case," Sustainability, MDPI, vol. 12(13), pages 1-17, July.
    3. Eseosa Halima Ighile & Hiroaki Shirakawa & Hiroki Tanikawa, 2022. "Application of GIS and Machine Learning to Predict Flood Areas in Nigeria," Sustainability, MDPI, vol. 14(9), pages 1-33, April.
    4. 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.
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