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| Titel |
What drives basin scale spatial variability of snowpack properties in northern Colorado? |
| VerfasserIn |
G. A. Sexstone, S. R. Fassnacht |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1994-0416
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| Digitales Dokument |
URL |
| Erschienen |
In: The Cryosphere ; 8, no. 2 ; Nr. 8, no. 2 (2014-03-03), S.329-344 |
| Datensatznummer |
250116071
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| Publikation (Nr.) |
 copernicus.org/tc-8-329-2014.pdf |
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| Zusammenfassung |
| This study uses a combination of field measurements and Natural Resource
Conservation Service (NRCS) operational snow data to understand the drivers
of snow density and snow water equivalent (SWE) variability at the basin
scale (100s to 1000s km2). Historic snow course snowpack density
observations were analyzed within a multiple linear regression snow density
model to estimate SWE directly from snow depth measurements. Snow surveys
were completed on or about 1 April 2011 and 2012 and combined with NRCS
operational measurements to investigate the spatial variability of SWE near
peak snow accumulation. Bivariate relations and multiple linear regression
models were developed to understand the relation of snow density and SWE
with terrain variables (derived using a geographic information system
(GIS)). Snow density variability was best explained by day of year, snow
depth, UTM Easting, and elevation. Calculation of SWE directly from snow
depth measurement using the snow density model has strong statistical
performance, and model validation suggests the model is transferable to
independent data within the bounds of the original data set. This pathway of
estimating SWE directly from snow depth measurement is useful when
evaluating snowpack properties at the basin scale, where many time-consuming
measurements of SWE are often not feasible. A comparison with a previously
developed snow density model shows that calibrating a snow density model to
a specific basin can provide improvement of SWE estimation at this scale, and
should be considered for future basin scale analyses. During both water year
(WY) 2011 and 2012, elevation and location (UTM Easting and/or UTM Northing)
were the most important SWE model variables, suggesting that orographic
precipitation and storm track patterns are likely driving basin scale SWE
variability. Terrain curvature was also shown to be an important variable,
but to a lesser extent at the scale of interest. |
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