Back to Search Start Over

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

Authors :
Mo, Huamei
Zhang, Guolong
Zhang, Qingwen
Hong, H. P.
Fan, Feng
Source :
International Journal of Disaster Risk Science; Oct2022, Vol. 13 Issue 5, p743-757, 15p
Publication Year :
2022

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20950055
Volume :
13
Issue :
5
Database :
Complementary Index
Journal :
International Journal of Disaster Risk Science
Publication Type :
Academic Journal
Accession number :
159817110
Full Text :
https://doi.org/10.1007/s13753-022-00443-0