Climate change is a major concern for agricultural production regions like the Canadian Prairies. Therefore, understanding the hydrologic and crop yield response to climate change is important to developing adaptative and mitigative strategies. Downscaled climate model projections from two GCMs for historical (1981-2010), midcentury (2041-2070), and late-century (2071-2100) periods under three representative concentration pathways (RCP2.6, RCP4.5, and RCP 8.5) were used as climate inputs to drive a calibrated and validated DRAINMOD model under two water management scenarios: free drainage (FD) and controlled drainage (CD). Field data, including water table depth, was collected for two canola growing seasons at the PESAI (Prairies East Sustainable Agriculture Initiative) research site in Arborg, Manitoba, Canada. The model was calibrated and validated using the 2019 and 2020 water table depth. The projected changes in the climatic variables showed a slight increase in the mean annual precipitation and the mean temperature across the seasons. DRAIN- MOD simulation results suggest that CD would significantly decrease subsurface drainage, while water loss through evapotranspiration (ET) and surface runoff are projected to increase considerably under CD and FD. Furthermore, results showed that the relative canola yield would decrease under FD and CD. Stressor analysis showed that canola yield reduction was driven by dry stress due to the projected temperature rise, which outweighs the slight increase in precipitation. Simulation results suggest that the capture, storage, and reuse of drainage water could be an adaptive and mitigative strategy to address the predicted impacts.