Effects of Averaging and Separating Soil Moisture and Temperature in the Presence of Snow Cover in a SVAT and Hydrological Model for a Southern Ontario, Canada, Watershed

Abstract

The energy and water balances at the earth's surface are dramatically influenced by the presence of snow cover. Therefore, soil temperature and moisture for snow-covered and snow-free areas can be very different. In computing these soil state variables, many land surface schemes in climate models do not explicitly distinguish between snow-covered and snow-free areas. Even if they do, some schemes average these state variables to calculate grid-mean energy fluxes and these averaged state variables are then used at the beginning of the next time step. This latter approach introduces a numerical error in that heat is redistributed from snow-free areas to snow-covered areas, resulting in a more rapid snowmelt. This study focuses on the latter approach and examines the sensitivity of soil moisture and streamflow to the treatment of the soil state variables in the presence of snow cover by using WATCLASS, a land surface scheme linked with a hydrologic model. The model was tested for the 1993 snowmelt period on the Upper Grand River in Southern Ontario, Canada. The results show that a more realistic simulation of streamflow can be obtained by keeping track of the soil states in snow-covered and snow-free areas.