Sensitivity of the results of modeling of seasonal ground freezing to selection of parameterization of the snow cover thermal conductivity
https://doi.org/10.15356/2076-6734-2019-1-67-80
Abstract
The relationship between the results of calculations of the dynamics of the temperature regime of the in freezing and thawing soil profile with the heating effect of the snow cover is considered. To analyze this connection, two coupled models are used: the model of formation and degradation of snow cover in winter and the model of heat transfer and soil moisture transport in underlying vadoze zone profile. Parametrization of the influence of the snow cover, which at each calculated moment of time has the current average density and depth, on the dynamics of the temperatures of the soil profile is due to the use of its specific thermal resistance, which depends on its current depth and the thermal conductivity coefficient. The coefficient of thermal conductivity of the snow cover is related with its density using six different published empirical relationships. Modeling of heat transfer in freezing and thawing soil is carried out on the example of the field site for monitoring the thermal regime located on the territory of the Zvenigorod Biological Station of Moscow State University. It is shown that the well-known relationships give similar curves for the dynamics of the depth of seasonal freezing, including the degradation of the seasonal freezing layer in the spring period, with the same dynamics of the snow cover. However, the maximum penetration depth of the zero isotherm differs significantly for different snow conductivity-snow density relationships. The tested six relationships were divided into three groups. Minimal freezing is provided by the Sturm model and the effective medium model. The average and rather poorly differentiating freezing from each other is given by the Pavlov, Osokin et al. and Jordan relationships. The greatest value of the freezing depth is obtained with using Pavlov’s relationship with a temperature correction.
About the Authors
S. P. PozdniakovRussian Federation
S. O. Grinevskyi
Russian Federation
E. A. Dedulina
Russian Federation
E. S. Koreko
Russian Federation
References
1. Grinevskiy S.O., Pozdnyakov S.P. A retrospective analysis of the impact of climate change on groundwater resources. Vestnik Moskovskogo Universiteta. Herald of the Moscow State University. Geology Series. 2017, 2: 42–50. doi: 10.3103/S0145875217030036. [In Russian].
2. Gelfan A.N. Dinamiko-stokhasticheskoe modelirovanie formirovaniya talogo stoka. Dynamic stochastic modeling of the formation of melt flow. Moscow: Nauka, 2007: 279 p. [In Russian].
3. Gusev E.M., Nasonova O.N. Modelirovanie teplo i vlagoobmena poverkhnosti sushi s atmosferoy. Modeling of heat and moisture exchange of the land surface with the atmosphere. Moscow: Nauka, 2010: 323 p. [In Russian].
4. Pavlov A.V. Teplofizika landshaftov. Thermophysics of landscapes. Novosibirsk: Nauka, 1979: 286 p. [In Russian].
5. Shmakin A.B., Turkov D.V., Mikhailov A.Yu. Model' snezhnogo pokrova s uchetom sloistoy struktury i yeye sezonnoy evolyutsii. Model of snow cover with inclusion of layered structure and its seasonal evolution. Kriosfera Zemli. Cryosphere of the Earth. 2009, XIII (4): 69–79. [In Russian].
6. Osokin N.I., Sosnovskiy A.V., Chernov R.A. The influence of the stratigraphy of the snow cover on its thermal resistance. Led i Sneg. Ice and snow. 2013, 53 (3): 63–70. [In Russian].
7. Osokin N.I., Sosnovskiy A.V., Chernov R.A. The coefficient of thermal conductivity of snow is its variability. Kriosfera Zemli. Cryosphere of the Earth. 2017, 3: 60–68. [In Russian].
8. Sokratov S.A., Sato A., Kamata Y. Water vapor in the pore space of snow. Annals of Glaciology. 2001, 32: 51–58.
9. Sturm M., Holmgren J., Konig M., Morris K. The thermal conductivity of seasonal snow. Journ. of Glaciology. 1997, 43 (143): 26–41.
10. Sturm M., Perovich D. K., Holmgren J. Thermal conductivity and heat transfer through the snow on the ice of the Beaufort Sea. Journ. of Geophys. Research. 2002, 8043, 107 (C10): 1–17. doi: 10.1029/2000JC000409.
11. Jordan R. A one-dimensional temperature model for a snow cover technical documentation for SNTHERM.89.U.S. Army Corps of Engineers. Cold Regions Research & Engineering Laboratory. Special Report 91–16. 1991: 49 p.
12. Pozdniakov S., Tsang C.F. A self-consistent approach for calculating the effective hydraulic conductivity of a binary, heterogeneous medium. Water Resources Research. 2004, 5: 1–15. doi: 10.1029/2003WR002617.
13. Gelfan A.N., Moreido V.M. Dynamic-stochastic modeling of snow cover formation on the European territory of Russia. Led i Sneg. Ice and Snow. 2014, 2 (126): 44–52. [In Russian].
14. Dall'Amico M., Endrizzi S., Gruber S., Rigon R. A robust and energy-conserving model of freezing variably-saturated soil. The Cryosphere. 2011, 5: 469–484. https://doi.org/10.5194/tc-5-469-2011.
15. Côté J., Konrad J-M. A generalized thermal conductivity model for soils and construction materials. Canadian Geotechnical Journ. 2005, 42: 443–458. https:// doi.org/10.1139/104-106.
16. Allen R.G., Pereira S., Raes D., Smith M. Crop evapotranspiration guidelines for computing crop water requirements. FAO Irrigation and Drainage. Paper 56. Food and Agriculture Organization of the United Nations, 1998. 281 p.
17. Grinevskiy S.O., Maslov A.A., Pozdnyakov S.P. Experience in the creation and application of a complex of regime hydrogeological observations in the conditions of the Zvenigorod training ground of the Moscow State University. Inzhenernye izyskaniya. Engineering Survey. 2011, 5: 30–34. [In Russian].
18. Kalyuzhny I.L, Lavrov S.A. Effect of climate changes on the soil freezing depth in the Volga River basin. Led i Sneg. Ice and Snow. 2016, 56 (2): 207–220. [In Russian].
Supplementary files
For citation: Pozdniakov S.P., Grinevskyi S.O., Dedulina E.A., Koreko E.S. Sensitivity of the results of modeling of seasonal ground freezing to selection of parameterization of the snow cover thermal conductivity. Ice and Snow. 2019;59(1):67-80. https://doi.org/10.15356/2076-6734-2019-1-67-80
Refbacks
- There are currently no refbacks.
ISSN 2076-6734 (Print)
ISSN 2412-3765 (Online)