| Summary: | Assessing the impact of climate change on water systems often requires employing a hydrological model to estimate streamflow. However, the choice of hydrological model, process representation, input data resolution, and catchment discretization can potentially influence such analyses. This study aims to evaluate the sensitivity of climate change impact assessments to various hydrological modeling configurations in a snow-dominated headwater system in Alberta, Canada. The HBV-MTL and GR4J models, coupled with the Degree-Day and CemaNeige snowmelt modules, were utilized and calibrated using point- and grid-based climate data on lumped and semi-distributed catchment discretization. The hydrological models, in conjunction with a water allocation model, were supplied with climate model outputs to project changes in the basin. While all models revealed a unanimous increase in peak flow, the difference between their estimations could be as substantial as 42%. In contrast, their divergence was minimal in projecting median flow. Furthermore, most models projected an aggravated water supply deficit between 16% and 40%. Overall, the quantified climate change impacts were the most sensitive to the choice of snow routine module, followed by the model type, catchment discretization, and data resolution in this snow-dominant basin. Therefore, particular attention should be given to the proper representation of snowmelt processes.
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