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Estimating and mapping snow hazard based on at-site analysis and regional approaches

Author

Listed:
  • H. M. Mo

    (Harbin Institute of Technology
    Harbin Institute of Technology)

  • W. Ye

    (University of Western Ontario)

  • H. P. Hong

    (University of Western Ontario)

Abstract

The estimation of snow hazard and load faces the small sample size effect because of the short snow depth record at a station. To reduce such an effect, we propose to estimate the return period value of the annual maximum ground snow depth S, sT, for Canada sites by applying the regional frequency analysis (RFA) and the region of influence approach (ROIA). The use of RFA and ROIA to map Canadian snow hazard is new. The comparison of their performance for snow hazard mapping has not been explored in the literature. We also consider the at-site analysis approach (ASA) for estimating sT by using three often used probability distributions for S. A comparison of the estimated sT by using the three approaches (ASA, RFA, ROIA) indicates that there is considerable scatter between the estimated sT value although the identified overall spatial trends of sT are similar. It is shown that the two-parameter lognormal distribution for S at most Canadian sites, based on the at-site analysis, is preferred; this differs from the Gumbel distribution used to develop the design snow load in Canadian structural design code. The new findings indicate that it is valuable to consider the lognormal distribution for developing design snow load for Canadian sites.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:nathaz:v:111:y:2022:i:3:d:10.1007_s11069-021-05144-3
    DOI: 10.1007/s11069-021-05144-3
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
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    1. 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.
    2. 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.

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