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

H. M. Mo (), W. Ye and H. P. Hong
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H. M. Mo: Harbin Institute of Technology
W. Ye: University of Western Ontario
H. P. Hong: University of Western Ontario

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 111, issue 3, No 13, 2459-2485

Abstract: 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.

Keywords: Ground snow depth; Snow load; Regional approaches; Lognormal distribution; Gumbel distribution; Generalized extreme value distribution (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11069-021-05144-3

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