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Simulating accumulation and melt of snow for RUSLE2 databases

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2007 ASAE Annual Meeting  072263.(doi:10.13031/2013.23044)
Authors:   Donald K McCool, Hanxue Qiu, Todd R Anderson
Keywords:   Erosion, Runoff, Snow, Accumulation, Melt, SPAW, RUSLE2

Lack of a method to properly account for snowmelt runoff and erosion in the Revised Universal Soil Loss Equation Version 2 (RUSLE2) hampers its use in areas where there is a period of melting of snow accumulated during the winter. This also adversely affects the performance of other models that use RUSLE2 as the driver for hill slope erosion. Because RUSLE2 relies on input data sets to drive the erosion process, we sought models that could effectively estimate snow accumulation and melt and provide data from which snowmelt erosivity databases could be developed. The Soil-Plant-Air-Water (SPAW) model was tested for ability to simulate accumulation and melt of snow. Model tests were based on daily climate data collected over a forty-one-year period from selected weather stations in cold or high elevation cropland areas of the western U S, the Northern Great Plains, and the northeastern U S. Snow depths predicted with SPAW default parameters are generally less than observed and the snow pack is predicted to melt before observed records indicate. Adjusting the accumulation and melt temperatures allows for a better match to the observed data. Density of falling snow is an important issue that needs to be considered in snow depth prediction and snow accumulation because new snow density is highly variable. After converting observed snow density to the constant value used in SPAW, the model fitting evidently improved. The model performance also indicated that ET and air temperature need to be well handled to achieve better prediction. When RUSLE2 average climate data is used in SPAW, the model is insensitive to the input accumulation and melting temperature for stations with low winter temperature and heavy snow. However, the model is sensitive to these input temperatures for stations where winter temperature is high and snowfall is light. Here, snow accumulation is less likely to be a winter long event; rather, snow accumulates and melts frequently during the winter.

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