Application of dynamic contributing area for modelling the hydrologic response of the Assiniboine River basin to a changing climate

The Prairie landscape consists of numerous pothole depressions which produce complex fill-and-spill runoff generation processes that result in intermittent hydrologic connectivity and dynamic contributing areas (DCA). We investigated the effect of including DCA in the modified version of the Soil and Water Assessment Tool (SWAT) model and its implication on future streamflow projection for the pothole dominated Assiniboine River Basin (ARB). The fill-and-spill processes that lead to DCA were captured using a physically-based approach, with a volumetric threshold to reduce the computational demand. Despite the challenges in accurately simulating prairie pothole hydrology, both in terms of timing and volume of runoff, the modified approach improved streamflow modelling performance, and reduced model uncertainty. Further, we evaluated the effects of representing DCA on projecting future streamflow by using eight statistically downscaled CMIP5 GCMs, forced with the RCP4.5 and RCP8.5 scenarios. End of century projections indicate increases in annual precipitation and temperature across the ARB, with decreasing summer precipitation relative to the 1976-2005 baseline period. Compared to the standard SWAT setup that does not allow for DCA, the modified model was found to be more responsive to climatic change with relatively larger projected increases in seasonal and annual flows at the majority of evaluated stations. This advance in DCA modelling will facilitate longer-term large basin-scale simulations that are more representative for the Prairie region. Crown Copyright (c) 2020 Published by Elsevier B.V. on behalf of International Association for Great Lakes Research. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

Automated summary

The study aimed to investigate the impact of improved hydrological modeling in prairie pothole regions on future streamflow projection. The results showed that the modified model incorporating Dynamic Contributing Areas (DCA) not only enhanced simulation performance, reduced model uncertainty, but also exhibited greater responsiveness to climatic changes, providing more accurate future streamflow predictions.