What resolution snow model is needed for accurate streamflow timing and volume simulation?

The spatial heterogeneity of snow influences the onset and timing of snowmelt and resulting streamflow in snow-dominated watersheds. However, it is unclear how much streamflow will change by accounting for incrementally-finer scale physical processes using incrementally-finer spatial representations to resolve snow’s spatial heterogeneity. In this study we attempt to quantify the impact of various snow processes, ranging from very fine resolutions (e.g. wind redistribution, ~3 – 30m) to coarser-scale processes (e.g. orographic enhancement, ~1km), on streamflow simulations. We attempt to identify where and when such processes have a significant impact on streamflow simulations and conversely identify instances where and when such processes can be neglected in the model.

To begin answering this question, we use the Distributed Hydrology and Soil Vegetation Model (DHSVM) set up at a 30-m spatial resolution over the East River Watershed, Colorado and the Upper Tuolumne River Watershed, California. We directly insert near peak-SWE snow water equivalent data from the Airborne Snow Observatory at different spatial resolutions while maintaining the 30-m spatial resolution within DHSVM. This ensures the same volume of snow across simulations and that differences between streamflow simulations are only related to the spatial variability of snow as a result of differences in snow accumulation. DHSVM simulates differences in snowmelt timing and rates at a 30-m resolution even if the direct insertion was done using a 1-km resolution SWE field. Therefore we address how the variability at near peak SWE influences streamflow simulations.

Preliminary results show that in both a high and low snow year, streamflow simulations were nearly identical between direct insertions of near peak-SWE at 30-m spatial resolution and 1-km spatial resolution (0-6% difference) throughout the year. These results suggest the importance of soil moisture and its ability to buffer streamflow simulations by holding on to snowmelt and slowly releasing it into the stream. Future results will use an improved calibrated hydrologic model that more accurately simulates evapotranspiration and groundwater, explore the influence of snow heterogeneity within smaller areas of the watershed, and explore the influence of different snow distribution patterns in other snow climates (e.g. Tuolumne, California).