Title

Testing a Blowing Snow Model Against Distributed Snow Measurements at Upper Sheep Creek, Idaho, United States of America

Document Type

Article

Journal/Book Title/Conference

Water Resources Research

Volume

37

Issue

5

Publisher

Wiley

Publication Date

5-1-2001

First Page

1341

Last Page

1356

DOI

10.1029/2000WR900317

Abstract

In this paper a physically based snow transport model (SnowTran-3D) was used to simulate snow drifting over a 30 m grid and was compared to detailed snow water equivalence (SWE) surveys on three dates within a small 0.25 km2 subwatershed, Upper Sheep Creek. Two precipitation scenarios and two vegetation scenarios were used to carry out four snow transport model runs in order to (1) evaluate the blowing snow model, (2) evaluate the sensitivity of the snow transport model to precipitation and vegetation inputs, and (3) evaluate the linearity of snow accumulation patterns and the utility of the drift factor concept in distributed snow modeling. Spatial comparison methods consisted of (1) pointwise comparisons of measured and modeled SWE, (2) visual comparisons of the spatial maps, (3) comparisons of the basin-wide average SWE, (4) comparisons of zonal average SWE in accumulation and scour zones, and (5) comparisons of distribution functions. We found that the basin average modeled SWE was in reasonable agreement with observations and that visually the spatial pattern of snow accumulation was well represented except for a pattern shift. Pointwise comparisons between the modeled and observed SWE maps displayed significant errors. The distribution functions of SnowTran-3D-modeled drift factors from two precipitation scenarios on three dates were compared with the distribution function of observation-based drift factors obtained previously by calibration to evaluate the assumption of linearity. We found only a 14% reduction in explained variance in the distribution function of drift factors for a 69% increase in precipitation, suggesting that the simplification provided by the use of drift factor distributions will result in errors that are tolerable in many cases.

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