Estimating Ground Snow Load Based on Ground Snow Depth and Climatological Elements for Snow Hazard Assessment in Northeastern China

Huamei Mo; Guolong Zhang; Qingwen Zhang; H. P. Hong; Feng Fan

doi:10.1007/s13753-022-00443-0

Volume 13 Issue 5

Oct. 2022

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Article Navigation > International Journal of Disaster Risk Science > 2022 > 13(5): 743-757

Huamei Mo, Guolong Zhang, Qingwen Zhang, H. P. Hong, Feng Fan. Estimating Ground Snow Load Based on Ground Snow Depth and Climatological Elements for Snow Hazard Assessment in Northeastern China[J]. International Journal of Disaster Risk Science, 2022, 13(5): 743-757. doi: 10.1007/s13753-022-00443-0

Citation:

Huamei Mo, Guolong Zhang, Qingwen Zhang, H. P. Hong, Feng Fan. Estimating Ground Snow Load Based on Ground Snow Depth and Climatological Elements for Snow Hazard Assessment in Northeastern China[J]. International Journal of Disaster Risk Science, 2022, 13(5): 743-757. doi: 10.1007/s13753-022-00443-0

Citation:

Huamei Mo, Guolong Zhang, Qingwen Zhang, H. P. Hong, Feng Fan. Estimating Ground Snow Load Based on Ground Snow Depth and Climatological Elements for Snow Hazard Assessment in Northeastern China[J]. International Journal of Disaster Risk Science, 2022, 13(5): 743-757. doi: 10.1007/s13753-022-00443-0

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Estimating Ground Snow Load Based on Ground Snow Depth and Climatological Elements for Snow Hazard Assessment in Northeastern China

doi: 10.1007/s13753-022-00443-0

Huamei Mo^{1,2
,
,},
Guolong Zhang^1,2,
Qingwen Zhang^1,2,
H. P. Hong³,
Feng Fan^1,2

1. Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education, Harbin Institute of Technology, Harbin, 150090, China;
2. Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, Harbin, 150090, China;
3. Department of Civil and Environmental Engineering, University of Western Ontario, London, Ontario, N6A 5B9, Canada

Funds:

Financial support from the National Natural Science Foundation of China (Grant Nos. 51808169 and 51927813), and the Fundamental Research Funds for the Central Universities (Grant No. HIT. NSRIF. 2020083) are gratefully acknowledged.

Available Online: 2022-11-01

Abstract

Abstract

Extreme snow loads can collapse roofs. This load is calculated based on the ground snow load (that is, the snow water equivalent on the ground). However, snow water equivalent (SWE) measurements are unavailable for most sites, while the ground snow depth is frequently measured and recorded. A new simple practical algorithm was proposed in this study to evaluate the SWE by utilizing ground snow depth, precipitation data, wind speed, and air temperature. For the evaluation, the precipitation was classified as snowfall or rainfall according to the air temperature, the snowfall or rainfall was then corrected for measurement error that is mainly caused by wind-induced undercatch, and the effect of snow water loss was considered. The developed algorithm was applied and validated using data from 57 meteorological stations located in the northeastern region of China. The annual maximum SWE obtained based on the proposed algorithm was compared with that obtained from the actual SWE measurements. The return period values of the annual maximum ground snow load were estimated and compared to those obtained according to the procedure suggested by the Chinese structural design code. The comparison indicated that the use of the proposed algorithm leads to a good estimated SWE or ground snow load. Its use allowed the estimation of the ground snow load for sites without SWE measurement and facilitated snow hazard mapping.
- Ground snow depth,
- Ground snow load,
- Northeastern China,
- Precipitation data,
- Snow hazard mapping,
- Snow water equivalent

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References(53)

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