Julie Holcombe, M.S.

RESEARCH:
A Modeling Approach to Estimating Snow Cover Depletion and Soil Moisture Recharge in a Semi-arid Climate at Two NASA CLPX Sites

EDUCATION:
M.S. (Watershed Science) 2004 Colorado State University, Fort Collins, CO, USA 80523-1472
B.S. (Atmospheric Sciences) 2000 The University of North Carolina at Asheville, North Carolina, USA 28804


Holcombe, J.D., 2004. A Modeling Approach to Estimating Snow Cover Depletion and Soil Moisture Recharge in a Semi-arid Climate at Two NASA CLPX Sites. Unpublished M.S. thesis, Watershed Science, Colorado State University, Fort Collins, Colorado, USA, 98pp + appendices.

Abstract

Snow cover depletion and soil moisture recharge are small segments, but crucial hydrological components for cryospheric regions of the earth. The abilities of a one-dimensional mass and energy balance model (SNTHERM) to predict snow cover depletion and Fast All season Soil STrength (FASST) to model the evolution of soil moisture recharge based on observed data from two NASA Cold Land Processes Experiment (CLPX) sites were evaluated. The objective was to investigate both model accuracies in predicting the observed parameters at Buffalo Pass near Steamboat and Illinois River located in North Park, both of which are located in the Colorado Rocky Mountains and are known for their differences in terrain and weather conditions.

The results from SNTHERM and FASST and the model performance statistics illustrate that the models overall fit to the observations were excellent at both locations. SNTHERM predicted the snow cover depletion date two days later than the observations at Buffalo Pass and only one day prior to the observations at Illinois River. The timing of snow accumulation and melt at Illinois River was in agreement with the observations at Illinois River, but the magnitude of snow depth was incorrect. The shallow and patchy nature of snow cover and the inconsistent meteorological parameters were problematic for SNTHERM. FASST correctly predicted the magnitude of seasonal soil moisture storage at both sites, but soil moisture recharge prediction was challenging for the model. A lateral flow module and thorough soil data are thought to improve FASSTís capability to predict the timing of soil moisture change. SNTHERM and FASST prove to possess the ability to predict snow cover depletion and seasonal soil moisture storage at two radically different field sites.

Committee:
Advisor: Steven Fassnacht
Co-Advisor: Kelly Elder (USFS RMRS)
Susan Frankenstein (USACE-CRREL)
Greg Butters (Soil and Crop Science)

Last update: SRF, 2016-06-15