Location: Watershed Management ResearchTitle: Assessing the sensitivities of distributed snow models to forcing data resolution Author
|Marks, Daniel - Danny|
Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/5/2013
Publication Date: 5/16/2014
Citation: Winstral, A.H., Marks, D.G., Gurney, R. 2014. Assessing the sensitivities of distributed snow models to forcing data resolution. Journal of Hydrometeorology. 15(4):1366-1383. Interpretive Summary: Research evaluates how the detail and scale of a snow simulation model impacts the resulting estimates of the timing and magnitude of snow melt over a mountain basin. Evaluation includes wind, snow redistribution, precipitation, solar and thermal radiation. Results indicate that a model scale of about 100m is required for simulation of snow deposition and melt, but that radiation could be scaled to 250m and still produce acceptable results. The combination of radiation scaling and wind-precipitation scaling may indicate that courser scale model simulations may be provide adequate results if carefully configured.
Technical Abstract: Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns, local ecology, and ultimately the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically-based distributed snow model requires appropriately scaled model structures. This work looks at how model scale – particularly the scales at which the forcing processes are represented – affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwest Idaho, USA. In this region where there is a negative correlation between snow accumulation and melt rates, overall increases in model scale across all processes pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region – wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation – were also independently rescaled to test process-specific spatio-temporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100m. Wind and wind-affected precipitation – the primary influence on snow distribution – required similar resolution. Thermal radiation scaled with the vegetation structure (~100m), while solar radiation was adequately modeled with 250m resolution. Spatio-temporal sensitivities to scale were found that allowed for further savings in computational costs. Solar and thermal radiation in combination with the vegetation structure often exhibited spatially consistent counteracting effects on snowmelt (e.g. thermally-enhanced fluxes under the solar-shaded canopy). These compensating scale effects – at least in this catchment – could be exploited to further reduce computational costs.