Snowpack Patterns in the East River, Colorado: Interannual Consistency and Relative Hierarchy of Contributing Physical Processes

In temperate high-elevation mountain catchments, spatial and temporal patterns of snow accumulation and melt exert a dominant control on hydrologic and biogeochemical flows and on ecological processes. Snowfall and wind interact with terrain and vegetation to create highly variable patterns of snow accumulation, in turn influences snowmelt rates, the snow surface energy balance, and snow disappearance timing. Despite large interannual changes in snowfall, snow depth patterns can exhibit broad consistency between wet and dry years. However, more local deviations in snow patterns are apparent and likely depend on year-specific changes in snow accumulation and ablation dynamics.

Focusing on the ~300 km² Watershed Function SFA (WFSFA) in the East River, Colorado, we quantify interannual patterns in snow water equivalent (SWE) near peak snowpack accumulation across multiple water years (2016-2019). The scope of activities in the WFSFA presents an unparalleled opportunity to improve quantitative and predictive understanding of the role of snow dynamics in watershed function in a well-instrumented and integrated study environment. We applied the physically-based SnowModel at a high-resolution (50 m) over the WFSFA, integrated with airborne lidar surveys of snow depth from the Airborne Snow Observatory taken near peak snow accumulation in three of the years (near-average 2016, dry 2018, and wet 2019). We first normalized the modeled SWE patterns and compared them to each other to map areas of interannual consistency and identified areas of similarity and dissimilarity. To examine the relative roles of orographic precipitation vs. other effects (preferential deposition and wind redistribution), we developed an accumulation index to map each model grid cell relative to other similar areas (elevation and proximity) to identify anomalies in SWE. We characterize and map the patterns in wind-scoured areas (anomalously low accumulation indices), wind-deposition areas (anomalously high accumulation indices), and wind-neutral areas (i.e., areas assumed to match the prevailing orographic precipitation). Using the annual maps of snow accumulation indices, we attempt to explain deviations in interannual snow patterns in the dry, average, and wet years.