Importance of temporal resolution of meteorological forcings for physics-based snow modeling

Abstract:

In alpine regions, snow delays hydrological responses to precipitation and controls initiation and length of the growing season. Therefore, precise simulations of snow accumulation and melt are crucial for understanding hydrological dynamics and predicting hydrologic response from watersheds. These predictions are important for water resource management and for ecological studies of vegetation distribution, growth and for wildlife habitat. Snow models require fine temporal resolution of meteorological inputs to capture diurnal changes. However, lack of meteorological data at fine-temporal resolution may force the use of coarser than hourly data. The objective of this work is to understand what sort of information can be lost over the watershed depending on the temporal resolution of meteorological inputs, for a range of hydroclimatic and topographic conditions. To address this goal, a spatially distributed and physics-based snow model (iSnobal) was run using 1-, 3- and 6-hourly meteorological inputs for a wet, average and a dry year over Boise River Basin (BRB), Idaho, USA. Simulated snow variables such as Snow Water Equivalent (SWE) and Surface Water Input (SWI – melt draining from the snowcover plus rain on bare ground) were averaged over 3 elevation bands including rain dominated (≤1400m), rain-snow transition (>1400 and ≤1900m) and snow dominated (>1900m). Except at the rain dominated band, using 6-hr inputs causes considerable overestimation of SWE and SWI, particularly in the wet year. The results show that at the rain-snow transition and snow dominated bands at least 3-hr meteorological data are necessary for snow modeling, due to strong diurnal changes in meteorological variables at these elevations. However, using course temporal resolution data for the rain dominated band made only a small difference in results.