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An Energy Budget Algorithm for a Snowpack-Snowmelt Calculation

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An Energy Budget Algorithm for a Snowpack-Snowmelt Calculation
Other Titles
스노우팩-융설 계산을 위한 에너지수지 알고리즘
Lee, Jeonghoon
Energy budget; Snowmelt; Rain-on-snow experiment; Diel variation; Intrinisic permeability
Issue Date
Lee, Jeonghoon, KO, KYUNG-SEOK. 2011. "An Energy Budget Algorithm for a Snowpack-Snowmelt Calculation". Korean Society Of Soil And Groundwater Environment, 16(5): 82-89.
Understanding snowmelt movement to the watershed is crucial for both climate change and hydrological studies because the snowmelt is a significant component of groundwater and surface runoff in temperature area. In this work, a new energy balance budget algorithm has been developed for melting snow from a snowpack at the Central Sierra Snow Laboratory (CSSL) in California, US. Using two sets of experiments, artificial rain-on-snow experiments and observations of diel variations, carried out in the winter of 2002 and 2003, we investigate how to calculate the amount of snowmelt from the snowpack using radiation energy and air temperature. To address the effect of air temperature, we calculate the integrated daily solar radiation energy input, and the integrated discharge of snowmelt under the snowpack and the energy required to generate such an amount of meltwater. The difference between the two is the excess (or deficit) energy input and we compare this energy to the average daily temperature. The resulting empirical relationship is used to calculate the instantaneous snowmelt rate in the model used by Lee et al. (2008a;2010), in addition to the net-short radiation. If for a given 10 minute interval, the energy obtained by the melt calculation is negative, then no melt is generated. The input energy from the sun is considered to be used to increase the temperature of the snowpack. Positive energy is used for melting snow for the 10-minute interval. Using this energy budget algorithm, we optimize the intrinsic permeability of the snowpack for the two sets of experiments using one-dimensional water percolation model, which are 52.5 × 10^(10) ㎡ and 75 × 10^(10) ㎡ for the ar tificial rain-on-snow experiments and observations of diel variation, respectively.
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