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Snow Disaster Hazard Assessment on the Tibetan Plateau Based on Copula Function

Author

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  • Qiuxuan Xu

    (The Faculty Geography Resource Sciences, Sichuan Normal University, Chengdu 610101, China
    Key Laboratory of the Evaluation and Monitoring of Southwest Land Resources (Ministry of Education), Sichuan Normal University, Chengdu 610068, China
    These authors contributed equally to this work.)

  • Feiyan Huang

    (The Faculty Geography Resource Sciences, Sichuan Normal University, Chengdu 610101, China
    Key Laboratory of the Evaluation and Monitoring of Southwest Land Resources (Ministry of Education), Sichuan Normal University, Chengdu 610068, China
    These authors contributed equally to this work.)

  • Shuhang Mou

    (The Faculty Geography Resource Sciences, Sichuan Normal University, Chengdu 610101, China
    Key Laboratory of the Evaluation and Monitoring of Southwest Land Resources (Ministry of Education), Sichuan Normal University, Chengdu 610068, China
    These authors contributed equally to this work.)

  • Heng Lu

    (The Faculty Geography Resource Sciences, Sichuan Normal University, Chengdu 610101, China
    Key Laboratory of the Evaluation and Monitoring of Southwest Land Resources (Ministry of Education), Sichuan Normal University, Chengdu 610068, China)

Abstract

In the context of global climate change, the Tibetan Plateau is particularly susceptible to meteorological disasters, including snow disasters. This study utilized daily temperature and precipitation data from 44 meteorological stations on the Tibetan Plateau spanning from 1960 to 2018 to construct a snow event dataset. Optimal marginal distribution and the copula function were chosen to calculate the joint return period and joint probability, which effectively assess the hazard of snow disasters in the region. Additionally, the study analyzed the comprehensive risk of snow disasters under various return periods by integrating social and economic data. The results indicate the following: (1) Based on the five different Archimedean copula functions, the joint return period of an error rate of each station was calculated to be less than 36%, which is significantly lower than the recurrence interval of univariate analysis; (2) High-hazard areas are predominantly concentrated in the northwest region of the Tanggula Mountains and the eastern foothills of the Bayankara Mountains. As the return period increases, the spatial distribution of snow disaster hazard probability shifts gradually from “double-core” to continuous distribution; and (3) the northwestern Karakorum Mountains and Bayankara Mountains are two distinct high-risk areas for snow disasters. The range of high-risk areas in the region expands with an increase in the return period.

Suggested Citation

  • Qiuxuan Xu & Feiyan Huang & Shuhang Mou & Heng Lu, 2023. "Snow Disaster Hazard Assessment on the Tibetan Plateau Based on Copula Function," Sustainability, MDPI, vol. 15(13), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10639-:d:1187781
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    References listed on IDEAS

    as
    1. Daniel Germain, 2016. "Snow avalanche hazard assessment and risk management in northern Quebec, eastern Canada," 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. 80(2), pages 1303-1321, January.
    2. Daniel Germain, 2016. "Snow avalanche hazard assessment and risk management in northern Quebec, eastern Canada," 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. 80(2), pages 1303-1321, January.
    3. Qian Li & Liutong Chen & Zhengtao Yan & Yingjun Xu, 2022. "Exploration of Copula Models Use in Risk Assessment for Freezing and Snow Events: A Case Study in Southern China," Sustainability, MDPI, vol. 14(5), pages 1-12, February.
    4. Walker S. Ashley & Alex M. Haberlie & Vittorio A. Gensini, 2020. "Reduced frequency and size of late-twenty-first-century snowstorms over North America," Nature Climate Change, Nature, vol. 10(6), pages 539-544, June.
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