Use of distributed snow measurements to test and improve a snowmelt model for predicting the effect of forest clear-cutting

Modeling the effect of forest clear-cutting with a distributed hydrological model can be used to detect hydrologic changes as an alternative to paired-catchment studies, and also to estimate the hydrologic sensitivity of a catchment to assist in forest management decisions. To model the effect of clear-cutting in a snow dominated forested watershed, a model needs to be able to simulate effects of all of the main controls on snow accumulation and melt. However, most studies that used a distributed modeling approach relied on one or a few sites for model testing. In this study, we employ a stratified nested sample layout that was specifically designed to test distributed models, involving measurement of snow water equivalent (SWE) under forest and in clearcuts over a range of elevations and aspects. To test the ability of a model to simulate the main controls on the spatial distribution of SWE, spatial gradients of observed and simulated SWE in relation to topographic and vegetation controls are computed using regression analysis. Comparison of observed and simulated gradients helps to highlight model weaknesses. The approach is applied to evaluate the snow algorithms in the distributed hydrology soil and vegetation model (DHSVM) using data collected in Cotton Creek, a snow dominated forested watershed in south-eastern British Columbia. SWE measurements were made from 2005 to 2008, covering peak snow accumulation and snow melt.