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Extreme snow hazard and ground snow load for China

Author

Listed:
  • H. M. Mo

    (Harbin Institute of Technology
    Harbin Institute of Technology)

  • L. Y. Dai

    (Chinese Academy of Sciences)

  • F. Fan

    (Harbin Institute of Technology)

  • T. Che

    (Chinese Academy of Sciences
    Chinese Academy of Sciences)

  • H. P. Hong

    (University of Western Ontario)

Abstract

The ground snow load is used as the reference snow load to estimate the design snow load on roofs. The ground snow load is recommended in Chinese load code for the design of building structures in the applicable jurisdiction; this load needs to be updated regularly by integrating new available snow measurements and new analysis techniques. This study is concentrated on the estimation of extreme snow depth and ground snow load and on snow hazard mapping in China by using historical snow measurement data. A probabilistic model of the snowpack bulk density was developed. For the extreme value analysis of annual maximum snow depth, both the at-site analysis and region of influence approach were applied. Also, several commonly used probabilistic models and distribution fitting methods were considered for the extreme value analysis. For the annual maximum snow depth, it was identified from the at-site analysis results that the number of sites where the lognormal distribution is preferred is greater than that where the Gumbel distribution is preferred. The 50-year return period value obtained from the ROI approach is insensitive to whether the three-parameter lognormal distribution or the generalized extreme value distribution is adopted. Maps of annual maximum snow depth and ground snow load were developed. Comparison of the estimated ground snow load to that recommended in the design code was presented, and potential updating to the ground snow load in the design code was suggested.

Suggested Citation

  • H. M. Mo & L. Y. Dai & F. Fan & T. Che & H. P. Hong, 2016. "Extreme snow hazard and ground snow load for 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. 84(3), pages 2095-2120, December.
  • Handle: RePEc:spr:nathaz:v:84:y:2016:i:3:d:10.1007_s11069-016-2536-1
    DOI: 10.1007/s11069-016-2536-1
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    References listed on IDEAS

    as
    1. H. Hong & W. Ye, 2014. "Analysis of extreme ground snow loads for Canada using snow depth records," 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. 73(2), pages 355-371, September.
    2. Xuanyi Zhou & Jialiang Li & Ming Gu & Lulu Sun, 2015. "A new simulation method on sliding snow load on sloped roofs," 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. 77(1), pages 39-65, May.
    3. Xuanyi Zhou & Yunqing Zhang & Ming Gu & Jialiang Li, 2013. "Simulation method of sliding snow load on roofs and its application in some representative regions of 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. 67(2), pages 295-320, June.
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    Citations

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    Cited by:

    1. Harald Schellander & Tobias Hell, 2018. "Modeling snow depth extremes in Austria," 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. 94(3), pages 1367-1389, December.
    2. H. M. Mo & W. Ye & H. P. Hong, 2022. "Estimating and mapping snow hazard based on at-site analysis and regional approaches," 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. 111(3), pages 2459-2485, April.
    3. H. M. Mo & H. P. Hong & F. Fan, 2017. "Using remote sensing information to estimate snow hazard and extreme snow load 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. 89(1), pages 1-17, October.

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