Regional Patterns of Snow Water Equivalent in the Colorado River Basin Using Snowpack Telemetry (SNOTEL) Data
M.S. (Watershed Science) 2008 Colorado State University, Fort Collins, CO, USA 80523-1472
B.A. (Geography) 1993 University of Colorado, Colorado Springs, Colorado 80918
The number of clusters can be specified to the SOM based on the level of generalization desired. A SOM consisting of a 4, 6, 9, and 16-cluster were constructed from daily values as well as a 6-cluster derived from snowpack descriptor variables (peak SWE, length of snow season, etc.) and physical variables (elevation, aspect, distance to moisture source, etc.) for each station. Areas of homogeneity derived from daily SWE values, annual peak SWE, and physiography were used for multivariate regression analysis to determine the physical variables that best explain variability in peak SWE.
Results showed an unbiased clustering of stations defined not by station location, but by each station's specific SWE variability over the period of study. The established snow climatologies derived from daily values show general homogenous coarse-scale clusters along a north/south gradient with spatial coherence improving at finer resolutions, but overall there are no definitive spatial patterns to the climatologies, indicating that complex local-scale variables dominate variability of daily SWE. Climatologies derived from descriptor variables showed improved spatial coherence which reflected larger scale influences. Descriptor variables that best represent daily time-step classifications were peak SWE (50% similarity), April 1st SWE (43% similarity), and physical variables (41% similarity).
Regression results showed a consistent increase in predictability as cluster size went from more general (4-cluster) to less general (16-cluster). Key physical variables are elevation, southwest barrier height, regional northness, and southwest shield height. These key variables were consistently used in the regression model, although the degree of importance of the variable depends on resolution and general location of the climatology.
Advisor: Steven Fassnacht
John Stednick (Watershed Science)
Nolan Doesken (CIRA)