A Model of Snowpack Formation and Snowmelt Model for the Volga-Kama Cascade Watershed

2020 ◽  
Vol 54 (2) ◽  
pp. 186-188
Author(s):  
S. E. Bednaruk ◽  
E. M. Klenov ◽  
A. V. Mastryukova ◽  
V. V. Chukanov
Keyword(s):  
2013 ◽  
Vol 10 (12) ◽  
pp. 15071-15118 ◽  
Author(s):  
J. You ◽  
D. G. Tarboton ◽  
C. H. Luce

Abstract. \\label{sec:abstract} Snow surface temperature is a key control on energy exchanges at the snow surface, particularly net longwave radiation and turbulent energy fluxes. The snow surface temperature is in turn controlled by the balance between various external fluxes and the conductive heat flux, internal to the snowpack. Because of the strong insulating properties of snow, thermal gradients in snow packs are large and nonlinear, a fact that has led many to advocate multiple layer snowmelt models over single layer models. In an effort to keep snowmelt modeling simple and parsimonious, the Utah Energy Balance (UEB) snowmelt model used only one layer but allowed the snow surface temperature to be different from the snow average temperature by using an equilibrium gradient parameterization based on the surface energy balance. Although this procedure was considered an improvement over the ordinary single layer snowmelt models, it still resulted in discrepancies between modeled and measured snowpack energy contents. In this paper we examine the parameterization of snow surface temperature in single layer snowmelt models from the perspective of heat conduction into a semi-infinite medium. We evaluate the equilibrium gradient approach, the force-restore approach, and a modified force-restore approach. In addition, we evaluate a scheme for representing the penetration of a refreezing front in cold periods following melt. We also introduce a method to adjust effective conductivity to account for the presence of ground near to a shallow snow surface. These parameterizations were tested against data from the Central Sierra Snow Laboratory, CA, Utah State University experimental farm, UT, and Subnivean snow laboratory at Niwot Ridge, CO. These tests compare modeled and measured snow surface temperature, snow energy content, snow water equivalent, and snowmelt outflow. We found that with these refinements the model is able to better represent the snowpack energy balance and internal energy content while still retaining a parsimonious one layer format.


2011 ◽  
Vol 66 (5) ◽  
pp. 1423-1429 ◽  
Author(s):  
Mupenzi Jean de la Paix ◽  
Li Lanhai ◽  
Ge Jiwen ◽  
Habumugisha Jean de Dieu ◽  
Nzayisenga Theoneste

2013 ◽  
Vol 28 (26) ◽  
pp. 6320-6336 ◽  
Author(s):  
Vinod Mahat ◽  
David G. Tarboton
Keyword(s):  

2009 ◽  
Vol 376 (1-2) ◽  
pp. 94-106 ◽  
Author(s):  
Georg Jost ◽  
R. Dan Moore ◽  
Markus Weiler ◽  
David R. Gluns ◽  
Younes Alila
Keyword(s):  

Author(s):  
Masashi Satoh ◽  
Mikio Sasaki ◽  
Takahiro Takeuchi

In this study, two models for snow and snowmelt were extended. Using those models, the calculation of water flowing in river was carried out. The results were compared with the observations. The outflow estimated by using the snow model in winter is in good agreement with the observations, and the snowmelt runoff predicted by using the snowmelt model in spring, April, May and June, is also at the good accuracy. The snowmelt runoff starts increasing from the early April, and it reaches the peak in the early May.


2014 ◽  
Vol 18 (12) ◽  
pp. 5061-5076 ◽  
Author(s):  
J. You ◽  
D. G. Tarboton ◽  
C. H. Luce

Abstract. Snow surface temperature is a key control on and result of dynamically coupled energy exchanges at the snow surface. The snow surface temperature is the result of the balance between external forcing (incoming radiation) and energy exchanges above the surface that depend on surface temperature (outgoing longwave radiation and turbulent fluxes) and the transport of energy into the snow by conduction and meltwater influx. Because of the strong insulating properties of snow, thermal gradients in snow packs are large and nonlinear, a fact that has led many to advocate multiple layer snowmelt models over single layer models. In an effort to keep snowmelt modeling simple and parsimonious, the Utah Energy Balance (UEB) snowmelt model used only one layer but allowed the snow surface temperature to be different from the snow average temperature by using an equilibrium gradient parameterization based on the surface energy balance. Although this procedure was considered an improvement over the ordinary single layer snowmelt models, it still resulted in discrepancies between modeled and measured snowpack energy contents. In this paper we evaluate the equilibrium gradient approach, the force-restore approach, and a modified force-restore approach when they are integrated as part of a complete energy and mass balance snowmelt model. The force-restore and modified force-restore approaches have not been incorporated into the UEB in early versions, even though Luce and Tartoton have done work in calculating the energy components using these approaches. In addition, we evaluate a scheme for representing the penetration of a refreezing front in cold periods following melt. We introduce a method to adjust effective conductivity to account for the presence of ground near to a shallow snow surface. These parameterizations were tested against data from the Central Sierra Snow Laboratory, CA, Utah State University experimental farm, UT, and subnivean snow laboratory at Niwot Ridge, CO. These tests compare modeled and measured snow surface temperature, snow energy content, snow water equivalent, and snowmelt outflow. We found that with these refinements the model is able to better represent the snowpack energy balance and internal energy content while still retaining a parsimonious one layer format.


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