|Garen, David - NRCS|
Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 15, 2005
Publication Date: December 15, 2005
Citation: Garen, D.C., Marks, D. 2005. Spatially distributed energy balance snowmelt modelling in a mountainous river basin: Estimated of inputs and verification of model results. Journal of Hydrology, 315:126-153 Interpretive Summary: An uncalibrated, physically-based snowmelt model coupled to a hydrologic model has been applied to the Boise River basin (2150 km2), ID, USA, to simulate the accumulation and melt of the snowpack, and streamflow from the basin for the years 1998–2000. The results were verified in terms of both snow water equivalent (SWE) and depth at several NRCS Snotel sites within the basin, against a time-series of satellite-derived snow covered area (SCA) images, and against measured stream discharge from the basin. The close agreement between simulated and measured data showed that it is possible to accurately simulate both the accumulation and melting of the seasonal snowcover over a large basin. The snowmelt model was coupled to a hydrologic model so that the distributed input of meltwater could be used to estimate streamflow from the basin, which closely matched measured streamflow for all three years. This research demonstrates that uncalibrated, physically-based hydrologic models can be applied to large basins to improve forecasts of water supplies in the intermountain western US. The models used in this study will be the foundation of the next generation of water supply forecasting models used by resource management agencies such as NRCS.
Technical Abstract: A spatially distributed energy balance snowmelt model has been applied to a 2150 km2 drainage basin in the Boise River, ID, USA, to simulate the accumulation and melt of the snowpack for the years 1998–2000. The simulation was run at a 3 h time step and a spatial resolution of 250 m. Spatial field time series of meteorological input data were obtained using various spatial interpolation and simulation methods. The variables include precipitation, air temperature, dew point temperature, wind speed, and solar and thermal radiation. The goal was to use readily available data and relatively straightforward, yet physically meaningful, methods to develop the spatial fields. With these meteorological fields as input, the simulated fields of snow water equivalent, snow depth, and snow covered area reproduce observations very well. The simulated snowmelt fields are also used as input to a spatially distributed hydrologic model to estimate streamflow. This gives an additional verification of the snowmelt modelling results as well as provides a linkage of the two models to generate hydrographs for water management information. This project is a demonstration of spatially distributed energy balance snowmelt modelling in a large mountainous catchment using data from existing meteorological networks. This capability then suggests the potential for developing new spatial hydrologic informational products and the possibility of improving the accuracy of the prediction of hydrologic processes for water and natural resources management.