Abstract Title: Measuring and modeling snow cover variability across a range of vegetation zones and climate regimes in Glacier National Park, Montana, USA
Author(s):
Mr. David Selkowitz - Oregon State University
Anne Nolin - Oregon State University
Dan Fagre - USGS Northern Rocky Mountain Science Center, Glacier Field Station
Abstract:
A two year study examining the relationships between snow cover and landscape vegetation structure is currently underway in Glacier National Park. Nine snow survey transects, each consisting of 30 survey points spaced at 30 meter intervals, were installed in a variety of landscape types ranging from dense high-elevation forests to forest-grassland mosaics to standing burnt forest. Results from the first season of snow survey measurements indicate that while distinct differences in landscape structure (e.g. forests vs meadows) produce distinct differences in snow cover, more subtle differences in landscape structure, such as differences in canopy density, do not always result in statistically significant differences in snow cover, at least at the scale of this experiment. Canopy gap fraction measured above each snow survey point varies in its ability to explain snow depth and snow water equivalent on the ground, depending on the width of the cone used to calculate gap fraction, the type of landscape, and the time of the year. Further research into the relationship between ground-based measurements of gap fraction and high spatial resolution satellite imagery products will pave the way for high spatial resolution modeling of snow accumulation and ablation in the Crown of the Continent Ecosystem. Including the effects of vegetation structure in spatially distributed snow models is essential in understanding potential changes in hydrology that will likely accompany predicted shifts in vegetation associated with changing climate.
