Investigating the Effects of Spatial Snow Water Equivalent Heterogeneity on Runoff Timing and Magnitude
Journal Article
Overview
abstract
ABSTRACT; Mountain snowpack spatial variability can impact snow‐driven streamflow timing and magnitude. Near‐peak, lidar‐derived snow water equivalent (SWE) data were coarsened (50 m through 1 km re‐gridding and elevation bands) and inserted into the Distributed Hydrology Soil Vegetation Model (DHSVM) to evaluate how spatial snow heterogeneity influences streamflow in the Tuolumne River, California, and Blue River, Colorado. In the Tuolumne, simulated peak streamflow from the most homogeneous snowpack representation was 36% greater than the more heterogeneous simulations. In all years, the homogeneous snowpack representation did not produce an observed snowmelt pulse in the recession limb. Streamflow during late summer was higher (up to 3.5 times) for finer‐resolution snow heterogeneity simulations. In the Blue, sensitivity to snowpack heterogeneity was less pronounced. This difference between watersheds was attributed to differences in spatial snowpack patterning and subsurface processes between the two basins. In the Blue, snowmelt infiltrated into the subsurface and was slowly released throughout summer. In the Tuolumne, mid‐winter melt and rain resulted in higher soil moisture at peak SWE. The combination of high antecedent soil moisture and the Tuolumne's subsurface characteristics contributed to flashier snowmelt runoff compared to the Blue. For both watersheds, altering snow heterogeneity had little effect (within 2%) on total end‐of‐water‐year runoff or evapotranspiration because absolute differences balanced out throughout the melt season: A more heterogeneous SWE representation produced less streamflow at peak SWE but greater streamflow afterward relative to a coarser SWE representation. Experiments isolating radiation variability demonstrated that accumulation heterogeneity at peak SWE had a stronger influence on streamflow timing than post‐peak radiation heterogeneity. These results suggest that if basin‐mean SWE is well constrained, capturing spatial heterogeneity in SWE may not be necessary for water supply forecasting on quasi‐annual timescales but may be important for simulating late summer flows, snow cover persistence, and magnitude of peak flows.
