Analysis of extreme ground snow loads for Canada using snow depth records

• Published in: Natural hazards (Dordrecht) Vol. 73; no. 2; pp. 355 - 371
• Main Authors: Hong, H. P., Ye, W.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-09-2014; Springer; Springer Nature B.V
• Subjects: Building codes; Civil Engineering; Climate science; Data analysis; Earth and Environmental Science; Earth Sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Environmental Management; Exact sciences and technology; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Hydrogeology; Natural Hazards; Natural hazards: prediction, damages, etc; Original Paper; Snow; Snow depth; Statistical analysis; Canada; Canada; Gumbel distribution; Ground snow load; Generalized extreme value distribution; Design code; Snow depth; thickness; kriging; North America; interpolation; depth; extreme value; snow; buildings; statistical analysis
• ISSN: 0921-030X; 1573-0840
• DOI: 10.1007/s11069-014-1073-z

Snow depth records from daily measurements at climatological stations were obtained from Environment Canada and were processed and analyzed. It was identified that there are 549 stations, each with at least 20 years of useable annual maximum snow depth data. Both the Gumbel distribution and generalized extreme value distribution were used to fit the annual maximum snow depth, considering several distribution fitting methods. Statistical analysis results indicated that, according to the Akaike information criterion, the Gumbel distribution is preferred for 72 % stations. The estimated return period value of annual maximum snow depth at stations was used to calculate their corresponding ground snow load. The at-site analysis results were used as the basis to spatially interpolate the ground snow loads for locations tabulated in the National Building Code of Canada (NBCC) since a code location and a climatological site are usually not co-located. For the interpolation, the ordinary co-kriging method with elevation as co-variate was used because a cross-validation analysis by using several deterministic and probabilistic spatial interpolation techniques indicated that the ordinary co-kriging method is preferred. A comparison of the newly estimated ground snow loads to those locations tabulated in the 1995 edition and 2010 edition of the NBCC was also presented.