Abstract
The estimation of annual maximum snow load is important for designing light-weight structures experiencing severe winter climate. The specified (basic) snow load in the Chinese design code is based on statistics of the return period values of ground snow load. The code tabulates the values for a few locations in a region. For example, values are only available at 31 sites for Heilongjiang Province with an area of more than 470,000 km2, China. The snow load needs to be spatially interpolated for sites far away from the tabulated locations. However, the statistical justification of the selected probability distribution to model snow depth or load hazard is unclear and the preferred spatial interpolation technique is unknown. This study focuses on the extreme value analysis and spatial interpolation of the annual maximum snow depth and ground snow load using the records at 83 stations in Heilongjiang Province from 1981 to 2010. The statistical analysis results show that the use of the lognormal distribution rather than the Gumbel distribution for the annual maximum snow depth suggested in the code is preferred for most sites, and the application of the ordinary co-kriging is adequate for spatial interpolation of extreme snow depth. The results also show that the uncertainty in snowpack bulk density should not be neglected in estimating the extreme (ground) snow load for updating the snow load in Chinese design code.
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Acknowledgments
Financial support received from National Science and Engineering Research Council of Canada and the University of Western Ontario is much appreciated. The China Scholarship Council (No. 201206120219 for HMM) is gratefully acknowledged. The authors are grateful to Messrs. Y. G. Sun and S. Liu from Heilongjiang Bureau of Meteorology for providing the snow depth data used in this study. We thank Dr. W. Ye for useful comments and suggestions.
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Mo, H.M., Fan, F. & Hong, H.P. Snow hazard estimation and mapping for a province in northeast China. Nat Hazards 77, 543–558 (2015). https://doi.org/10.1007/s11069-014-1566-9
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DOI: https://doi.org/10.1007/s11069-014-1566-9