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

International Journal of Disaster Risk Science ›› 2022, Vol. 13 ›› Issue (5) : 743 -757.

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International Journal of Disaster Risk Science ›› 2022, Vol. 13 ›› Issue (5) : 743 -757. DOI: 10.1007/s13753-022-00443-0
Article

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

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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.

Keywords

Ground snow depth / Ground snow load / Northeastern China / Precipitation data / Snow hazard mapping / Snow water equivalent

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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. International Journal of Disaster Risk Science, 2022, 13(5): 743-757 DOI:10.1007/s13753-022-00443-0

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References

[1]

Anderson EA. Development and testing of snow pack energy balance equations. Water Resources Research, 1968, 4(1): 19-37

[2]

ASCE (American Society of Civil Engineering) Minimum design loads for buildings and other structures (ASCE/SEI 7–16), 2016, Reston, VA: American Society of Civil Engineering

[3]

Bartlett FM, Hong HP, Zhou W. Load factor calibration for the proposed 2005 edition of the National Building Code of Canada: Companion-action load combinations. Canadian Journal of Civil Engineering, 2003, 30(2): 440-448

[4]

Bean B, Maguire M, Sun Y, Wagstaff J, Al-Rubaye S, Wheeler J, Jarman S, Rogers M. The 2020 national snow load study. Mathematics and Statistics Faculty Publications, Paper 276, 2021, Logan, UT: Utah State University

[5]

Boudhar A, Boulet G, Hanich L, Sicart JE, Chehbouni A. Energy fluxes and melt rate of a seasonal snow cover in the Moroccan High Atlas. Hydrological Sciences Journal / Journal des Sciences Hydrologiques, 2016, 61(5): 931-943.

[6]

Braithwaite RJ, Zhang Y. Sensitivity of mass balance of five Swiss glaciers to temperature changes assessed by tuning a degree-day model. Journal of Glaciology, 2000, 46(152): 7-14

[7]

Breiman L. Random forests. Machine Learning, 2001, 45(1): 5-32

[8]

Bruland O, Færevåg Å, Steinsland I, Liston GE, Sand K. Weather SDM: Estimating snow density with high precision using snow depth and local climate. Hydrology Research, 2015, 46(4): 494-506

[9]

BSI (British Standards Institution) Eurocode 1: Actions on structures—Part 1–3: General actions—Snow loads (BS EN 1991-1-3: 2003), 2003, London: BSI

[10]

Burnham KP, Anderson DR. Model selection and multimodel inference: A practical information-theoretic approach, 2003, Berlin and Heidelberg, Germany: Springer

[11]

Chen X, Wei W, Liu M. Change in fresh snow density in Tianshan Mountains. China. Chinese Geographical Science, 2011, 21(1): 36-47

[12]

CMA (China Meteorological Administration) Specifications for surface meteorological observation—Snow depth and snow pressure, GB/T 35229–2017, 2017, Beijing: China Standards Press (in Chinese)

[13]

CMA (China Meteorological Administration) Specifications for surface meteorological observation—Precipitation, GB/T 35228–2017, 2017, Beijing: China Standards Press (in Chinese)

[14]

CMA (China Meteorological Administration) Specifications for surface meteorolotical observation—Wind direction and wind speed, GB/T 35227–2017, 2017, Beijing: China Standards Press (in Chinese)

[15]

Coles S. An introduction to statistical modeling of extreme values, 2001, London, UK: Springer

[16]

Ellingwood B, Redfield RK. Ground snow loads for structural design. Journal of Structural Engineering, 1983, 109(4): 950-964

[17]

Fridley KJ, Roberts KA, Mitchell JB. Estimating ground snow loads using local climatological data. Journal of Structural Engineering, 1994, 120(12): 3567-3576

[18]

Goodison, B.E., P.Y.T. Louie, and D. Yang. 1998. WMO solid precipitation measurement intercomparison: Final report. WO: Geneva, Switzerland.

[19]

Hill DF, Burakowski EA, Crumley RL, Keon J, Hu JM, Arendt AA, Jones KW, Wolken GJ. Converting snow depth to snow water equivalent using climatological variables. The Cryosphere, 2019, 13(7): 1767-1784

[20]

Hong, H.P., Q. Tang, S.C. Yang, X.Z. Cui, A.J. Cannon, Z. Lounis, and P. Irwin. 2021. Calibration of the design wind load and snow load considering the historical climate statistics and climate change effects. Structural Safety 93: Article 102135.

[21]

Hong H, Ye W. Analysis of extreme ground snow loads for Canada using snow depth records. Natural Hazards, 2014, 73(2): 355-371

[22]

Hosking JRM, Wallis JR. Regional frequency analysis: An approach based on L-moments, 1997, Cambridge, UK: Cambridge University Press

[23]

Johannesson T, Sigurdsson O, Laumann T, Kennett M. Degree-day glacier mass-balance modelling with applications to glaciers in Iceland, Norway and Greenland. Journal of Glaciology, 1995, 41(138): 345-358

[24]

Jonas T, Marty C, Magnusson J. Estimating the snow water equivalent from snow depth measurements in the Swiss Alps. Journal of Hydrology, 2009, 378(1–2): 161-167

[25]

Kondo J, Yamazaki T. A prediction model for snowmelt, snow surface temperature and freezing depth using a heat balance method. Journal of Applied Meteorology, 1990, 29(5): 375-384

[26]

Kustas WP, Rango A, Uijlenhoet R. A simple energy budget algorithm for the snowmelt runoff model. Water Resources Research, 1994, 30(5): 1515-1527

[27]

Larson LW, Peck EL. Accuracy of precipitation measurements for hydrologic modeling. Water Resources Research, 1974, 10(4): 857-863

[28]

Li Y, Wang K, Wu G, Mao Y. Proportion and distribution of rain and snow in China from 1960 to 2018. Journal of Hydrometeorology, 2022, 23(2): 225-238

[29]

Male DH, Gray DM. Problems in developing a physically based snowmelt model. Canadian Journal of Civil Engineering, 1975, 2(4): 474-488

[30]

McCreight JL, Small EE. Modeling bulk density and snow water equivalent using daily snow depth observations. The Cryosphere, 2014, 8(2): 521-536

[31]

Mo HM, Dai LY, Fan F, Che T, Hong HP. Extreme snow hazard and ground snow load for China. Natural Hazards, 2016, 84(3): 2095-2120

[32]

Mo HM, Ye W, Hong HP. Estimating and mapping snow hazard based on at-site analysis and regional approaches. Natural Hazards, 2022, 111(3): 2459-2485

[33]

Mo, H.M., X.L. Cao, H.P. Hong, and F. Fan. 2022. Development of a relation between return period values of annual maximum snow load and snow depth and its implication in structural reliability for northeastern China. Journal of Structural Engineering 148(8): Article 04022100.

[34]

MOHURD (Ministry of Housing and Urban-Rural Development of the People’s Republic of China) Load code for the design of building structures, GB 50009–2012, 2012, Beijing: China Architecture & Building Press (in Chinese)

[35]

Nitu, R., Y.A. Roulet, M. Wolff, M. Earle, A. Reverdin, C. Smith, J. Kochendorfer, S. Morin et al. 2018. WMO Solid Precipitation Intercomparison Experiment (SPICE) (2012–2015). Instruments and Observing Methods Report No. 131. Geneva: World Meteorological Organization.

[36]

NRCC (National Research Council of Canada) National Building Code of Canada, 2015, Ottawa: Institute for Research in Construction, National Research Council of Canada

[37]

Rasmussen R, Baker B, Kochendorfer J, Meyers T, Landolt S, Fischer AP, Black J, Theriault JM How well are we measureing snow—The NOAA/FAA/NCAR winter precipitation test bed. Bulletin of the American Meteorological Society, 2012, 93(6): 811-829

[38]

Ren Z, Li M. Errors and correction of precipitation measurements in China. Advances in Atmospheric Sciences, 2007, 24(3): 449-458

[39]

Sanpaolesi L. Snow loading: Scientific basis, problems and challenges. Progress in Structural Engineering and Materials, 1998, 1(4): 443-451

[40]

Sevruk B, Ondras M, Chvila B. The WMO precipitation measurement intercomparisons. Atmospheric Research, 2009, 92(3): 376-380

[41]

Sturm M, Holmgren J. Differences in compaction behavior of three climate classes of snow. Annals of Glaciology, 1998, 26: 125-130

[42]

Sturm M, Taras B, Liston GE, Derksen C, Jonas T, Lea J. Estimating snow water equivalent using snow depth data and climate classes. Journal of Hydrometeorology, 2010, 11(6): 1380-1394

[43]

Tarboton DG, Luce CH. Utah energy balance snow accumulation and melt model (UEB)—Computer model technical description and users guide, 1996, Logan, UT: Utah Water Research Laboratory and USDA Forest Service Intermountain Research Station

[44]

Wang YH, Broxton P, Fang Y, Behrangi A, Barlage M, Zeng X, Niu GY. A wet-bulb temperature-based rain-snow partitioning scheme improves snowpack prediction over the drier western United States. Geophysical Research Letters, 2019, 46: 13825-13835

[45]

Wei W, Qin D, Liu M. Properties and structure of the seasonal snow cover in the continental regions of China. Annals of Glaciology, 2001, 32: 93-96

[46]

Yang DQ, Shi YF, Kang ES, Zhang YS, Yang XY. Results of solid precipitation measurement intercomparison in the alpine area of Urumqi basin. Chinese Science Bulletin, 1991, 36(13): 1105-1109.

[47]

Yang D, Zhang Y, Zhang Z. A study on the snow density in the head area of Urumqi river basin. Acta Geographica Sinica, 1992, 59(3): 260-266 (in Chinese)

[48]

Yang DQ, Wang CZ, Zhang YS, Zhang ZZ. Distribution of seasonal snow cover and variation of snow density on the headwaters of Urumqi river basin. Geographical Research, 1992, 11(4): 86-96 (in Chinese)

[49]

Yang D, Goodison BE, Metcalfe JR, Golubev VS, Elomaa E, Gunther T, Bates R, Pangburn T Accuracy of tretyakov precipitation gauge: Result of WMO intercomparison. Hydrological Processes, 1995, 9(8): 877-895

[50]

Ye BS, Yang D, Ding Y, Han T, Koike T. A bias-corrected precipitation climatology for China. Journal of Hydrometeorology, 2004, 5(6): 1147-1160

[51]

Zeinivand H, De Smedt F. Prediction of snowmelt floods with a distributed hydrological model using a physical snow mass and energy balance approach. Natural Hazards, 2010, 54(2): 451-468

[52]

Zhang Y, Ren Y, Ren G, Wang G. Bias correction of gauge data and its effect on precipitation climatology over mainland China. Journal of Applied Meteorology and Climatology, 2019, 58(10): 2177-2196

[53]

Zhou X, Zhang Y, Gu M, Li J. Simulation method of sliding snow load on roofs and its application in some representative regions of China. Natural Hazards, 2013, 67(2): 295-320

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