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

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  • H. Hong
  • W. Ye

Abstract

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. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • H. Hong & W. Ye, 2014. "Analysis of extreme ground snow loads for Canada using snow depth records," 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. 73(2), pages 355-371, September.
  • Handle: RePEc:spr:nathaz:v:73:y:2014:i:2:p:355-371
    DOI: 10.1007/s11069-014-1073-z
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    Citations

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    Cited by:

    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. Veli Yavuz & Ali Deniz & Emrah Tuncay Özdemir, 2021. "Analysis of a vortex causing sea-effect snowfall in the western part of the Black Sea: a case study of events that occurred on 30–31 January 2012," 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. 108(1), pages 819-846, August.
    3. 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.
    4. 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.
    5. H. Mo & F. Fan & H. Hong, 2015. "Snow hazard estimation and mapping for a province in northeast 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. 77(2), pages 543-558, June.

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