Articles | Volume 14, issue 6
https://doi.org/10.5194/hess-14-991-2010
https://doi.org/10.5194/hess-14-991-2010
22 Jun 2010
 | 22 Jun 2010

Prediction of snowmelt derived streamflow in a wetland dominated prairie basin

X. Fang, J. W. Pomeroy, C. J. Westbrook, X. Guo, A. G. Minke, and T. Brown

Abstract. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a prairie hydrological model for Smith Creek Research Basin (~400 km2), east-central Saskatchewan, Canada. Physically based modules were sequentially linked in CRHM to simulate snow processes, frozen soils, variable contributing area and wetland storage and runoff generation. Five "representative basins" (RBs) were defined and each was divided into seven hydrological response units (HRUs): fallow, stubble, grassland, river channel, open water, woodland, and wetland. Model parameters were estimated using field survey data, LiDAR digital elevation model (DEM), SPOT 5 satellite imageries, stream network and wetland inventory GIS data. Model simulations were conducted for 2007/2008 and 2008/2009. No calibration was performed. The model performance in predicting snowpack, soil moisture and streamflow was evaluated against field observations. Root mean square differences (RMSD) between simulation and observations ranged from 1.7 to 25.2 mm and from 4.3 to 22.4 mm for the simulated snow accumulation in 2007/2008 and 2008/2009, respectively, with higher RMSD in grassland, river channel, and open water HRUs. Spring volumetric soil moisture was reasonably predicted compared to a point observation in a grassland area, with RMSD of 0.011 and 0.009 for 2008 and 2009 simulations, respectively. The model was able to capture the timing and magnitude of peak spring basin discharge, but it underestimated the cumulative volume of basin discharge by 32% and 56% in spring 2008 and 2009, respectively. The results suggest prediction of Canadian Prairie basin snow hydrology is possible with no calibration if physically based models are used with physically meaningful model parameters that are derived from high resolution geospatial data.