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Regional patterns of snow water equivalent in the Colorado River Basin using snowpack telemetry (SNOTEL) data

Date

2008

Authors

Derry, Jeffrey Edward, author
Fassnacht, Steven R., advisor
Doesken, Nolan J., committee member
Stednick, John D., committee member

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Abstract

Identifying regions of homogeneity of precipitation data is often a crucial preliminary step in natural resource investigations. Previous clustering of station based snow water equivalent (SWE) data has typically grouped stations based on spatial proximity, political boundaries, or watershed boundaries, and has been restricted due to the temporal resolution of snow course data. This investigation utilized daily data from 216 snowpack telemetry (SNOTEL) stations located in and around the Colorado River Basin over a 15-year period (1991-2005) to cluster stations, i.e., identify regions of homogeneity, based on the patterns and variability of SWE. To achieve this, data were submitted to a selforganizing map (SOM), a particular application of artificial neural networks. This methodology represents a learning algorithm that is non-linear, non-parametric, unsupervised, and learns through an iterative training process.

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Department Head: Michael J. Manfredo.

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