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au=bales and au=molotch
HR: 1340h
AN: H13H-1404
TI: Local-scale
controls on snow distribution in the Rio Grande headwaters: implications for evaluating
spatially distributed snowpack estimates
AU: * Molotch, N P
EM: molotch@cires.colorado.edu
AF: Cooperative Institute for Research in
Environmental Sciences, University of Colorado at Boulder, 216 UCB, Boulder,
CO 80309-0216 United States
AU: Bales, R C
EM: rbales@ucmerced.edu
AF: Division of Engineering, University of
California, Merced, 4225 N. Hospital Road, Bldg 1200, Atwater, CA 95301
United States
AB: The spatial distribution of snow water
equivalent (SWE) within 16-, 4-, and 1-km2 grid elements
surrounding six snow telemetry (SNOTEL) stations in the Rio Grande headwaters
was characterized using field observations of snowpack properties, satellite
data, binary regression tree models, and a spatially distributed net
radiation / temperature-index snowpack mass balance model. In some cases
SNOTEL SWE values were 200% greater than mean grid-element SWE. Analyses
designed to identify the optimal location for measuring mean grid-element SWE
accumulation indicated that only 2.4% of each grid element satisfied the
criteria of optimality. Similar analyses for the ablation season showed that
point SWE and mean grid-element SWE were highly correlated (r = 0.73) in
areas with relatively persistent snow cover. These locations did not overlap
in space with areas deemed optimal at maximum accumulation; areas with
persistent snow cover have relatively high accumulation rates. Therefore
future observations may need to be placed with the specific objective of
representing either accumulation or ablation season processes. These results
have implications for large-scale studies that require ground observations
for updating purposes; we show an example of this utility using the SWE
product of the National Operational Hydrologic Remote Sensing Center.
Furthermore, the relatively consistent spatial patterns of snow accumulation
and melt has implications for future observation network design in that
results from short-term studies (e.g. 2 years) can be used to design
long-term observation networks.
DE: 1839 Hydrologic scaling
DE: 1847 Modeling
DE: 1855 Remote sensing (1640)
DE: 1863 Snow and ice (0736, 0738, 0776, 1827)
SC: Hydrology [H]
MN: Fall Meeting 2005
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