ASSESSMENT AND POTENTIAL ADJUSTMENTS TO THE SNOW-RELATED ALGORITHMS IN BIOME-BGC, v4.2
Many watersheds throughout the mountain west are snow-melt dominated. Recent studies suggest that climatic shifts throughout the 20th century have diminished snowpack around the west, a trend that may accelerate in the future. Loss of critical snowpack could negatively affect the ecosystems and communities that have come to depend on it. Process models offer a way to illuminate the effects of climate change on snowpack. BIOME-BGC, a well established eco-system process model, contains a simple snow melt model for predicting daily snow water equivalent (SWE). The model requires standard daily meteorological data and can, therefore, be extrapolated over long periods of record. This research evaluated the effectiveness of BIOME-BGC (v4.2) at predicting SWE, snowpack evolution, and soil temperature. Then, several physically based algorithms were incorporated into current model logic and model behavior was evaluated. Finally, a new degree-day algorithm was presented and assessed for inclusion into future versions of BIOME-BGC. The study concluded that the new degree-day algorithm should be investigated further as it offered the best results.
Advisor:Joel Harper; Faith Ann Heinsch; Anna Klene; Ulrich Kamp
School:The University of Montana
School Location:USA - Montana
Source Type:Master's Thesis
Date of Publication:01/26/2009