Cordilleran Section - 97th Annual Meeting, and Pacific Section, American Association of Petroleum Geologists (April 9-11, 2001)

Paper No. 0
Presentation Time: 1:00 PM-5:00 PM

USING GIS TO PREDICT THE SPATIAL DISTRIBUTION OF PERENNIAL SNOW AND ICE UNDER MODERN AND PLEISTOCENE CONDITIONS IN THE SPRING MOUNTAINS, NEVADA


VAN HOESEN, John G., Univ Nevada - Las Vegas, PO Box 454010, Las Vegas, NV 89154-4010 and ORNDORFF, Richard L., Department of Geoscience, Univ of Nevada, Las Vegas, 4505 Maryland Parkway, Las Vegas, NV 89154-4010, jgv@nevada.edu

The Spring Mountains of southern Nevada rise to an elevation of 3650 m above sea level and lie along the western edge of the Las Vegas Valley. Glacially-derived sediment, located at approximately 2590 m, supports the hypothesis of Pleistocene glaciation in the Spring Mountains, and the range therefore represents the southernmost extent of glaciation in the Great Basin during the last Ice Age. This study is significant because it estimates climatic thresholds necessary to initiate and maintain perennial snow and ice in the Spring Mountains, providing insight into the dynamic system present in southern Nevada during the late Pleistocene. We use ArcView GIS (Geographic Information System) to aid in the prediction of the distribution of snow and ice based on topography and solar radiation. We perform a series of surface operations on a DEM (digital elevation model) with 30-meter grid cell spacing. Slope aspect and shading control the amount of insolation received by a surface; we compute shading effects and seasonal variability based on the sun’s position at the summer and winter solstices. We derive slope and curvature (the slope of the slope) from the DEM to estimate stability and accumulation of snow. Using the computer model ELApse, we predict the spatial distribution of perennial snow and ice and the positions of the equilibrium line altitude (ELA) and nivation threshold altitude (NTA) for specified climatic boundary conditions. Modern climate station data is perturbed to reflect estimated paleoclimatic conditions in the Spring Mountains; we then create temperature and precipitation grids using a bivariate regression of climate variables on elevation and latitude. Raster overlays of slope, curvature, and shading created in ArcView to simulate alpine microclimates are incorporated into ELApse to estimate the climatic thresholds needed to initiate perennial snow and eventual glaciation