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Scenario-Based Extreme Flood Risk of Residential Buildings and Household Properties in Shanghai

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  • Xinmeng Shan

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

  • Jiahong Wen

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

  • Min Zhang

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China
    State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China)

  • Luyang Wang

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

  • Qian Ke

    (Department of Hydraulic Engineering, Delft University of Technology, 1 Stevinweg, 2628 CN Delft, The Netherlands)

  • Weijiang Li

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

  • Shiqiang Du

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China
    Institute of Urban Studies, Shanghai Normal University, Shanghai 200234, China)

  • Yong Shi

    (Department of Tourism and Management, University of Zhengzhou, Zhengzhou 450001, China)

  • Kun Chen

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

  • Banggu Liao

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

  • Xiande Li

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

  • Hui Xu

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

Abstract

Extreme flooding usually causes huge losses of residential buildings and household properties, which is critical to flood risk analysis and flood resilience building in Shanghai. We developed a scenario-based multidisciplinary approach to analyze the exposure, losses and risks of residential buildings and household properties, and their spatial patterns at the neighborhood committee level in Shanghai, based on extreme storm flood scenarios of 1/200, 1/500, 1/1000 and 1/5000-year. Our findings show that the inundation area of the residential buildings caused by a 1/200-year storm flood reaches 24.9 km 2 , and the total loss of residential buildings and household properties is 29.7 billion CNY (Chinese Yuan) (or 4.4 billion USD), while the inundation area of residential buildings and the total loss increases up to 162.4 km 2 and 366.0 billion CNY (or 54.2 billion USD), respectively for a 1/5000-year storm flood. The estimated average annual loss (AAL) of residential buildings and household properties for Shanghai is 590 million CNY/year (or 87.4 million USD/year), with several hot spots distributed around the main urban area and on the bank of the Hangzhou Bay. Among sixteen districts, Pudong has the highest exposure and annual expected loss, while the inner city is also subject to extreme flooding with an AAL up to near half of the total. An analysis of flood risk in each of 209 subdistricts/towns finds that those most vulnerable to storm flooding are concentrated in Pudong, Jiading, Baoshan Districts and the inner city. Our work can provide meaningful information for risk-sensitive urban planning and resilience building in Shanghai. The methodology can also be used for risk analysis in other coastal cities facing the threat of storm flooding.

Suggested Citation

  • Xinmeng Shan & Jiahong Wen & Min Zhang & Luyang Wang & Qian Ke & Weijiang Li & Shiqiang Du & Yong Shi & Kun Chen & Banggu Liao & Xiande Li & Hui Xu, 2019. "Scenario-Based Extreme Flood Risk of Residential Buildings and Household Properties in Shanghai," Sustainability, MDPI, vol. 11(11), pages 1-18, June.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:11:p:3202-:d:238244
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    References listed on IDEAS

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    Cited by:

    1. Avinash Kaur & Harshit Sosan Lakra & Rajib Shaw & Sameer Ali, 2025. "Pathways to enhanced microscale coastal flood risk assessment amid changing climate," 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. 121(15), pages 17201-17251, August.
    2. Tomáš Hanák & Martin Tuscher & Oto Přibyl, 2020. "Hybrid Genetic Algorithm-Based Approach for Estimating Flood Losses on Structures of Buildings," Sustainability, MDPI, vol. 12(7), pages 1-16, April.
    3. Shuang Liu & Rui Liu & Nengzhi Tan, 2021. "A Spatial Improved-kNN-Based Flood Inundation Risk Framework for Urban Tourism under Two Rainfall Scenarios," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    4. Kai Yin & Sudong Xu & Quan Zhao & Nini Zhang & Mengqi Li, 2021. "Effects of sea surface warming and sea-level rise on tropical cyclone and inundation modeling at Shanghai coast," 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. 109(1), pages 755-784, October.
    5. Yiche Wang & Hai Li & Yong Shi & Qian Yao, 2022. "A Study on Spatial Accessibility of the Urban Stadium Emergency Response under the Flood Disaster Scenario," Sustainability, MDPI, vol. 14(24), pages 1-15, December.
    6. Xinmeng Shan & Jie Yin & Jun Wang, 2022. "Risk assessment of shanghai extreme flooding under the land use change scenario," 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. 110(2), pages 1039-1060, January.

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