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Application of region of influence approach to estimate extreme snow load for a northeastern province in China

International Conference on Applications of Statistics and Probability (12th : 2015 : Vancouver, B.C.)

The consideration of snow load is important for regions experiencing severe winter climate and snowfall, such as Heilongjiang Province located in northeastern China. In this study, annual maximum snow depth from 1981 to 2010 for 83 stations in Heilongjiang was used as the basis to carry out extreme value analysis and to estimate ground snow load. To reduce the sample size effect in the extreme value analysis, the region of influence (ROI) approach is considered and the results are compared with those obtained from at-site analysis as well as from the current Chinese load code. Maps are developed for the region based on the estimated return period value of the ground snow load.

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This collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.

Vancouver : University of British Columbia Library

10.14288/1.0076204

Non UBC

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/