Testing a Blowing Snow Model Against Distributed Snow Measurements at Upper Sheep Creek

Table of Contents

Testing a Blowing Snow Model Against Distributed Snow Measurements at Upper Sheep Creek

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Objectives

Comparison Methods

Reynolds Creek

Tollgate SnowTran-3D study area

Observed SWE

SnowTran-3D

Scenario’s Modeled

Full SnowTran-3D simulation Upper Sheep Creek Precipitation LANDSAT vegetation

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Visual comparison

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Upper Sheep Creek Average Snow Water Equivalence

3/3/93 Upper Sheep Creek SWE analysis by zones

Drift factor approach that assumes linearity

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Evaluation of wind model derived drift factors, Upper Sheep Creek, 3/3/1993.

Conclusions

Acknowledgements

Email: dtarb@cc.usu.edu

Home Page: http://www.neng.usu.edu/dtarb

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Abstract
In this paper a physically-based numerical snow transport model (SnowTran-3D) was used to simulate snow drifting over a 30 m grid, and was compared to detailed snow water equivalence 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 snow, (2) visual comparisons of the spatial maps, (3) comparisons of the basinwide average, (4) comparisons of zonal averages in accumulation and scour zones, and (5) comparisons of distribution functions.  We found that the basin average modeled snow water equivalence was in reasonable agreement with observations, and that visually the spatial pattern of snow accumulation was well represented except for a small pattern shift.  In spite of the overall model success, pointwise comparisons between the modeled and observed snow water equivalence maps displayed significant errors. Observation-based drift factors were obtained from calibration using measured snow water equivalence maps and a physically-based snow melt model.  The distributions of SnowTran-3D modeled drift factors from two precipitation scenarios on three dates were compared with the distribution of observation-based drift factors to evaluate the assumption of linearity.  In comparisons against the observation-based drift factors the fraction of explained variance reduced from 90% to 75% when precipitation was increased 79%.  This 15% reduction in the explained variance indicates reasonable linearity and supports the idea that drift factors estimated separately from a blowing snow model may be used to simply parameterize wind redistribution of snow in distributed hydrologic modeling.