Snow courses that measure snow water equivalent (SWE) are clustered and limited in areal coverage in Idaho. This study used a cell-based geographic information system and multiple regression models to construct SWE surfaces from the snow course data by month (January to May) and by watershed. SWE was the dependent variable and location and topographic variables derived from a digital elevation model were used as the independent variables. Multiple regression performed better than the traditional interpolation methods for SWE estimation. The estimated SWE surface can be displayed at different spatial scales through neighbourhood operations, or used directly as a map layer for hydrologic modelling.
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Chang et al. (2000) studied this question.