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Assessment of the Casualty Risk of Multiple Meteorological Hazards in China

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  • Wei Xu

    (Key Laboratory of Environmental Change and Natural Disasters of Ministry of Education, Beijing Normal University, Beijing 100875, China
    Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs & Ministry of Education, Beijing Normal University, Beijing 100875, China)

  • Li Zhuo

    (Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China)

  • Jing Zheng

    (Guangdong Climate Center, Guangzhou 510080, China)

  • Yi Ge

    (State Key Laboratory of Pollution Control & Resource Re-use, School of the Environment, Nanjing University, Nanjing 210093, China
    These authors contributed equally to this work.)

  • Zhihui Gu

    (College of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China
    These authors contributed equally to this work.)

  • Yugang Tian

    (School of Information Engineering, China University of Geosciences, Wuhan 430074, China
    These authors contributed equally to this work.)

Abstract

A study of the frequency, intensity, and risk of extreme climatic events or natural hazards is important for assessing the impacts of climate change. Many models have been developed to assess the risk of multiple hazards, however, most of the existing approaches can only model the relative levels of risk. This paper reports the development of a method for the quantitative assessment of the risk of multiple hazards based on information diffusion. This method was used to assess the risks of loss of human lives from 11 types of meteorological hazards in China at the prefectural and provincial levels. Risk curves of multiple hazards were obtained for each province and the risks of 10-year, 20-year, 50-year, and 100-year return periods were mapped. The results show that the provinces (municipalities, autonomous regions) in southeastern China are at higher risk of multiple meteorological hazards as a result of their geographical location and topography. The results of this study can be used as references for the management of meteorological disasters in China. The model can be used to quantitatively calculate the risks of casualty, direct economic losses, building collapse, and agricultural losses for any hazards at different spatial scales.

Suggested Citation

  • Wei Xu & Li Zhuo & Jing Zheng & Yi Ge & Zhihui Gu & Yugang Tian, 2016. "Assessment of the Casualty Risk of Multiple Meteorological Hazards in China," IJERPH, MDPI, vol. 13(2), pages 1-12, February.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:2:p:222-:d:63986
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    References listed on IDEAS

    as
    1. Silvia Mosquera-Machado & Maxx Dilley, 2009. "A comparison of selected global disaster risk assessment results," 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. 48(3), pages 439-456, March.
    2. Ke Wang & Lu Wang & Yi-Ming Wei & Maosheng Ye, 2013. "Beijing storm of July 21, 2012: observations and reflections," 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. 67(2), pages 969-974, June.
    3. Elizabeth Christenson & Mark Elliott & Ovik Banerjee & Laura Hamrick & Jamie Bartram, 2014. "Climate-Related Hazards: A Method for Global Assessment of Urban and Rural Population Exposure to Cyclones, Droughts, and Floods," IJERPH, MDPI, vol. 11(2), pages 1-24, February.
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    Cited by:

    1. Weixiao Han & Chen Liang & Baofa Jiang & Wei Ma & Ying Zhang, 2016. "Major Natural Disasters in China, 1985–2014: Occurrence and Damages," IJERPH, MDPI, vol. 13(11), pages 1-14, November.
    2. Yu Yueyue & Yang Wenwen & Zhang Lingli & Guan Zhaoyong & Yang Qinlan & Hu Muxin & Qiu Wentian & Wang Jingyi, 2023. "Region-dependent meteorological conditions for the winter cold hazards with and without precipitation in China," 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. 115(3), pages 2673-2698, February.
    3. Lihong Wang & Zaiwu Gong, 2017. "Priority of a Hesitant Fuzzy Linguistic Preference Relation with a Normal Distribution in Meteorological Disaster Risk Assessment," IJERPH, MDPI, vol. 14(10), pages 1-16, October.
    4. Mohammad Abdul Quader & Amanat Ullah Khan & Matthieu Kervyn, 2017. "Assessing Risks from Cyclones for Human Lives and Livelihoods in the Coastal Region of Bangladesh," IJERPH, MDPI, vol. 14(8), pages 1-26, July.

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