HR: 0800h
AN: C31A-0306    [Abstracts]
TI: Snow-Elk Interactions In The Northern Elk Winter Range, Yellowstone National Park
AU: * Anderson, C
EM: cranders@colorado.edu
AF: Institute of Arctic and Alpine Research, University of Colorado-Boulder CB 450, Boulder, CO 80309 United States
AU: * Anderson, C
EM: cranders@colorado.edu
AF: Department of Geography, University of Colorado-Boulder, University of Colorado-Boulder CB 260, Boulder, CO 80309 United States
AU: Williams, M
EM: markw@snobear.colorado.edu
AF: Institute of Arctic and Alpine Research, University of Colorado-Boulder CB 450, Boulder, CO 80309 United States
AU: Williams, M
EM: markw@snobear.colorado.edu
AF: Department of Geography, University of Colorado-Boulder, University of Colorado-Boulder CB 260, Boulder, CO 80309 United States
AU: Crabtree, R
AF: Yellowstone Ecological Research Center, 2048 Analysis Drive, Suite B, Bozeman, MT 59718 United States
AB: Distributed estimates of snowpack properties and the processes that control them are important for gaining a more comprehensive understanding of complex ecosystems. The Northern Elk Winter Range, located in the Greater Yellowstone Ecosystem, is an exemplar of such a complex ecosystem. Ungulates, specifically elk (Cervus Elaphus), are a key biotic component of the Northern Elk Winter Range. Migration, predation, forage utilization strategies and herd distribution of elk are all greatly influenced by the heterogeneous distribution of snowpack properties. This study developed an approach to model the spatial and temporal distribution of snowpack properties for two basins within the Northern Elk Winter Range in an attempt to better understand the energetic expenditures of elk with respect to variable snowpack conditions. Our approach used SNTHERM, a process based energy and mass balance model, to predict snowpack properties for the 2004 winter season. SNTHERM takes initial snowpack conditions and observed meteorological conditions over a given time period, and using mathematical equations based on known physical processes, calculates melt and other snowpack fluxes. We spatially distributed the model by classifying the study area into zones of similar physical characteristics and running the model for each classification region.. Discrete classification regions were derived using combinations of elevation, aspect and landcover type. The performance of the distributed SNTHERM model was tested by comparing the predicted versus measured snow depth, snow density, snow water equivalences, snowpack temperatures, and snowpack stratigraphy. This poster presents the results from these measured versus modeled comparisons and assesses the major sources of uncertainty in the modeling process. Ultimately, this research looks to provide insights into the complexities of snow/elk interactions as well as making a contribution to the development and improvement of spatially distributed snow models within the field of snow hydrology.
DE: 1863 Snow and ice (1827)
SC: Cryosphere [C]
MN: 2004 AGU Fall Meeting