Abstract

The Elbow River watershed, located in the foothills of the Rocky Mountains, has experienced several extreme hydrological events such as droughts and floods over the last century. It is therefore critical to understand the future possible responses of the hydrological processes to changes in climate and land-use/land-cover (LULC) since they can induce considerable stress to the watershed along with economic and social costs. Very little attention has been given so far in the literature to the combined impact of climate and LULC change on hydrological processes at the watershed scale, which might result in an over- or under-estimation of the responses. This study was undertaken to investigate the responses of hydrological processes to the combined impact of climate and LULC change in the watershed in the 2020s and 2050s. The physically-based, distributed MIKE SHE/MIKE 11 model was coupled with a LULC cellular automata model to simulate hydrological processes using two extreme GCM-scenarios and two LULC change scenarios. Results reveal that LULC change is the dominant factor affecting the majority of the hydrological processes, especially streamflow, and that it plays a key role in amplifying a rise in flow discharge in the Elbow River. Evapotranspiration and infiltration are more strongly affected by both climate and LULC change in winter while streamflow is more impacted in the spring. The separated impacts of climate and LULC change on streamflow are positively correlated in winter and spring, which intensifies their influence. This is particularly the case in spring when the combined impact of climate and LULC results in a significant rise in streamflow, which may increase the vulnerability of the watershed to floods in this season. The flow duration curves (FDC) indicate that LULC change has a greater contribution to peak flows than climate change in both the 2020s and 2050s. This study highlights the importance of investigating the combined impact of climate and LULC change to avoid underestimating or overestimating water storage in the watershed.

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