Campus Units

Geological and Atmospheric Sciences

Document Type

Article

Publication Version

Published Version

Publication Date

1-2011

Journal or Book Title

Advances in Water Resources

Volume

34

Issue

1

First Page

14

Last Page

127

DOI

10.1016/j.advwatres.2010.10.002

Abstract

The National Weather Service (NWS) uses the SNOW17 model to forecast snow accumulation and ablation processes in snow-dominated watersheds nationwide. Successful application of the SNOW17 relies heavily on site-specific estimation of model parameters. The current study undertakes a comprehensive sensitivity and uncertainty analysis of SNOW17 model parameters using forcing and snow water equivalent (SWE) data from 12 sites with differing meteorological and geographic characteristics. The Generalized Sensitivity Analysis and the recently developed Differential Evolution Adaptive Metropolis (DREAM) algorithm are utilized to explore the parameter space and assess model parametric and predictive uncertainty. Results indicate that SNOW17 parameter sensitivity and uncertainty generally varies between sites. Of the six hydroclimatic characteristics studied, only air temperature shows strong correlation with the sensitivity and uncertainty ranges of two parameters, while precipitation is highly correlated with the uncertainty of one parameter. Posterior marginal distributions of two parameters are also shown to be site-dependent in terms of distribution type. The SNOW17 prediction ensembles generated by the DREAM-derived posterior parameter sets contain most of the observed SWE. The proposed uncertainty analysis provides posterior parameter information on parameter uncertainty and distribution types that can serve as a foundation for a data assimilation framework for hydrologic models.

Comments

This article is published as He, Minxue, Terri S. Hogue, Kristie J. Franz, Steven A. Margulis, and Jasper A. Vrugt. "Characterizing parameter sensitivity and uncertainty for a snow model across hydroclimatic regimes." Advances in Water Resources 34, no. 1 (2011): 114-127. doi: 10.1016/j.advwatres.2010.10.002.

Rights

Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.

Language

en

File Format

application/pdf

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