On extreme ground snow depth and ground snow load at Canadian sites

Q. Tang; H. P. Hong; P. Jarrett

doi:10.1139/cjce-2020-0557

On extreme ground snow depth and ground snow load at Canadian sites

Q. Tang
, H. P. Hong^*
, P. Jarrett

^*Corresponding author for this work

Western University
Environment and Climate Change Canada

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

The roof snow load in the National Building Code of Canada (NBCC) is expressed as the sum of the snow and rain components. A probabilistic analysis of the components was carried out by using the recorded historical meteorological data. Probabilistic characterizations of the annual maximum ground snow depth S_A, ground snow load S_L, and snowpack bulk density were given. By considering the commonly adopted probabilistic models for S_A, it was found that the use of the lognormal distribution, Gumbel distribution, and generalized extreme value distribution (GEVD) for S_A is preferred for 46%, 35%, and 19% of the considered meteorological stations. A similar observation was made for S_L. Snow hazard maps in terms of return period values of S_A and S_L were developed. Also, the hazard maps of (winter) rain load, S_R, were developed. It was found that the correlation coefficient between S_A and S_R is negligible; the implication of this is discussed.

Original language	English
Pages (from-to)	1483-1498
Number of pages	16
Journal	Canadian Journal of Civil Engineering
Volume	49
Issue number	9
DOIs	https://doi.org/10.1139/cjce-2020-0557
State	Published - Sep 2022
Externally published	Yes

Keywords

ground snow depth
rain load
rain load hazard mapping
snow load hazard mapping
snowpack bulk density

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10.1139/cjce-2020-0557

Cite this

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title = "On extreme ground snow depth and ground snow load at Canadian sites",

abstract = "The roof snow load in the National Building Code of Canada (NBCC) is expressed as the sum of the snow and rain components. A probabilistic analysis of the components was carried out by using the recorded historical meteorological data. Probabilistic characterizations of the annual maximum ground snow depth SA, ground snow load SL, and snowpack bulk density were given. By considering the commonly adopted probabilistic models for SA, it was found that the use of the lognormal distribution, Gumbel distribution, and generalized extreme value distribution (GEVD) for SA is preferred for 46\%, 35\%, and 19\% of the considered meteorological stations. A similar observation was made for SL. Snow hazard maps in terms of return period values of SA and SL were developed. Also, the hazard maps of (winter) rain load, SR, were developed. It was found that the correlation coefficient between SA and SR is negligible; the implication of this is discussed.",

keywords = "ground snow depth, rain load, rain load hazard mapping, snow load hazard mapping, snowpack bulk density",

author = "Q. Tang and Hong, \{H. P.\} and P. Jarrett",

note = "Publisher Copyright: {\textcopyright} 2022 The Author(s).",

year = "2022",

month = sep,

doi = "10.1139/cjce-2020-0557",

language = "英语",

volume = "49",

pages = "1483--1498",

journal = "Canadian Journal of Civil Engineering",

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}

TY - JOUR

T1 - On extreme ground snow depth and ground snow load at Canadian sites

AU - Tang, Q.

AU - Hong, H. P.

AU - Jarrett, P.

PY - 2022/9

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N2 - The roof snow load in the National Building Code of Canada (NBCC) is expressed as the sum of the snow and rain components. A probabilistic analysis of the components was carried out by using the recorded historical meteorological data. Probabilistic characterizations of the annual maximum ground snow depth SA, ground snow load SL, and snowpack bulk density were given. By considering the commonly adopted probabilistic models for SA, it was found that the use of the lognormal distribution, Gumbel distribution, and generalized extreme value distribution (GEVD) for SA is preferred for 46%, 35%, and 19% of the considered meteorological stations. A similar observation was made for SL. Snow hazard maps in terms of return period values of SA and SL were developed. Also, the hazard maps of (winter) rain load, SR, were developed. It was found that the correlation coefficient between SA and SR is negligible; the implication of this is discussed.

AB - The roof snow load in the National Building Code of Canada (NBCC) is expressed as the sum of the snow and rain components. A probabilistic analysis of the components was carried out by using the recorded historical meteorological data. Probabilistic characterizations of the annual maximum ground snow depth SA, ground snow load SL, and snowpack bulk density were given. By considering the commonly adopted probabilistic models for SA, it was found that the use of the lognormal distribution, Gumbel distribution, and generalized extreme value distribution (GEVD) for SA is preferred for 46%, 35%, and 19% of the considered meteorological stations. A similar observation was made for SL. Snow hazard maps in terms of return period values of SA and SL were developed. Also, the hazard maps of (winter) rain load, SR, were developed. It was found that the correlation coefficient between SA and SR is negligible; the implication of this is discussed.

KW - ground snow depth

KW - rain load

KW - rain load hazard mapping

KW - snow load hazard mapping

KW - snowpack bulk density

UR - https://www.scopus.com/pages/publications/85138317428

U2 - 10.1139/cjce-2020-0557

DO - 10.1139/cjce-2020-0557

M3 - 文章

AN - SCOPUS:85138317428

SN - 0315-1468

VL - 49

SP - 1483

EP - 1498

JO - Canadian Journal of Civil Engineering

JF - Canadian Journal of Civil Engineering

IS - 9

ER -

On extreme ground snow depth and ground snow load at Canadian sites

Abstract

Keywords

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