Variability of Sublimation in the Upper Colorado River Basin

May 09, 2013

Morgan Phillips

Committee: William Cotton (advisor), Russ Schumacher, John Stednick (Forest, Rangeland, and Watershed Stewardship)

Abstract

Snowpack stored in mountain environments is the primary source of water for the population of much of the western United States, and the loss of water through direct evaporation is a significant factor in the amount of runoff realized from snow melt. A land surface modeling study was carried out in order to quantify the magnitude of temporal and spatial variability of sublimation over a large mountain basin in North America through the use of a spatially distributed snow-evolution model known as SnowModel. Simulations relied on forcing from high resolution atmospheric analysis data from the North American Land Data Assimilation System (NLDAS). These data were used to simulate snow sublimation for several years over a 400 by 400 km domain in the Upper Colorado River Basin at a horizontal resolution of 250 m and hourly time-steps.

Results show that total volume of sublimated water from snow varies up to 68% within the ten years of the study period. On daily timescales sublimation was found to be episodic in nature, with short periods of enhanced sublimation followed by several days of relatively low snowpack water loss. The greatest sublimation rates on the order of 3 mm/day were found to occur in high elevation regions generally above tree line in conjunction with frequent windblown snow, while considerable contributions from canopy sublimation occurred at middle elevations. Additional sensitivity runs accounting for reduced canopy leaf area index as a result of western pine beetle induced tree mortality were also carried out to test the models sensitivity to land surface characteristics. Results from this comparison show a linear decrease in domain total sublimation with reduced LAI. Model performance was somewhat satisfactory, with simulations underestimating precipitation and accumulated SWE, most likely due to biases in the precipitation forcing and errors in determining precipitation phase.