An Intercomparison of Model Performance and Uncertainty in Forcing Data for the Mackenzie River Basin

Wednesday, 17 December 2014
Gonzalo Sapriza Azuri1, Vanessa Pedinotti1, Kwok Pan Chun1, Bruce Davison2, Alain Pietroniro2 and Howard S Wheater1, (1)University of Saskatchewan, Saskatoon, SK, Canada, (2)Environment Canada, Saskatoon, SK, Canada
The Mackenzie River Basin (MRB) in Canada has been the focus of many large scale hydrological models. Significant modelling challenges arise, due to the complexities of the cold region hydrology and the current manifestations of climate warming, including permafrost thaw, increased streamflow, tundra shrub expansion, among other processes. Robust large-scale predictive models are necessary for regional and global impacts assessment, along with proper validation and uncertainty estimation of model structure and forcing data. We present an intercomparison of global model performance on the MRB and analysis of the impact of uncertainty in forcing data. With that purpose, we have implemented for the MRB a large-scale model using the Modélisation Environmentale Communautaire – Surface and Hydrology (MESH) model driven with several gridded forcing data sets. We compare the model performance with the Joint UK Land Environment Simulator (JULES), the Weather Research and Forecasting (WRF) and the Variable Infiltration Capacity (VIC) models. Results will be presented to illustrate the comparative performance of water balance components and streamflow simulations. As for the uncertainty in forcing data, precipitation has the major impact, especially the rainfall spatial variability.