Douglas Hultstrand, M.S.
Geostatistical Methods for Estimating Snowmelt Contribution to the Annual Water Balance in an Alpine Watershed
M.S. (Watershed Science) 2006 Colorado State University, Fort Collins, CO, USA 80523-1472
B.A. (Geography) 2003 University of Colorado at Boulder, Boulder, Colorado 80309
Hultstrand, D.M., 2006. Geostatistical Methods for Estimating Snowmelt Contribution to the Annual Water Balance in an Alpine Watershed.
Unpublished M.S. thesis, Watershed Science, Colorado State University, Fort Collins, Colorado, USA, 104pp + 1appendix.
Spatial interpolation methods can provide accurate estimates of distributed snow water equivalent (SWE) when intensive snow depth and density observations are available.
In this study, the performance of nine spatial interpolation models was evaluated to estimate snowmelt contributions to streamflow into an alpine watershed.
In April 2005, peak accumulation snow depth and snow density measurements were collected over the West Glacier Lake (WGL) watershed.
The distribution of SWE was calculated as the product of snow depth, snow density, and snow-covered area (SCA).
Snow depths were spatially distributed throughout the watershed through spatial interpolation methods.
Snow densities were spatially distributed through multiple linear regression analysis. The nine spatial snow depth models explained 18% to 94%
of the observed variance in the measured snow depths. Co-kriging with solar radiation produced the best results explaining 94% of the observed variance in snow depth measurements.
The annual water balance, expressed as equivalent water depths was total precipitation (1,481 mm), snowpack sublimation (251 mm), and streamflow (1,000 mm), resulting in an estimate of evapotranspiration (230 mm).
Estimated SWE from the field survey data was 67% greater than precipitation gauge estimates and accounted for 85% of the annual streamflow.
Last update: SRF, 2016-06-15
Advisor: Steven Fassnacht
Co-Advisor: John Stednick (Watershed Science)
Bob Musselman (USFS RMRS)
Nolan Doesken (CIRA)