Bridging Hydrology, Ecology, and Reservoir Management to Address Environmental Flow Specifications from Dams in a Changing Climate

Abstract

Water resource management has altered the natural flow regime of rivers around the globe. Buffers to environmental risk and uncertainty, dams balance competing demands for water storage and release for human needs. While dams have served as a cornerstone for human development, they have historically been tied to river exploitation, jeopardizing ecological health and species richness of streams and rivers. This project seeks to assess the impacts of current reservoir management practices on downstream ecological integrity in a changing climate with a focus on rainfall distribution shifts. We assess these impacts in a ‘model-world’ that captures some of the complexities existing in natural systems while enabling various dam management scenarios to operate under controlled conditions. For this reason, a lumped three-part mathematical model was developed to represent the impacts of precipitation and dam management on the stability of a simplified food web operating downstream from the dam. First, a watershed routing model was derived to link precipitation statistics and watershed land cover properties using a prescribed unit hydrograph. Second, a nonlinear reservoir model linking inflow, outflow and storage behind the dam was used to generate distinct patterns of streamflow variability downstream of the dam. Last, the dynamics of a three species food web were coupled to the aforementioned flow downstream from the dam so as to determine whether reservoir operations can sustain the downstream food web stability. This three-part lumped model was operated under five reservoir management scenarios: Natural flow variability, run of river, minimum flow management, drought management, and flood management. Using predictions from the IPCC AR5 Report (2013), changes in precipitation frequency and depth due to long term shifts in the climate were evaluated assuming long-term annual precipitation is not altered. By simulating multiple reservoir management scenarios, it is envisaged that reservoir operators can accommodate ecological integrity explicitly. As expected, flow variability was found to decrease substantially in each of the four dammed scenarios when compared to an unregulated flow regime, with the range of flows shifting from 105-108 to 4-5 105 m3/day. With less frequent and more intense storms, the outflow from the reservoir shifted towards less frequent, higher magnitude flow rates in each scenario. None of the scenarios tested maintain populations in all trophic levels for the duration of the modeling period when faced with high variability in rainfall inter-arrival times. Presently, reservoir managers operating their dams under run of river or flood management will achieve the greatest downstream ecological integrity. However, as precipitation patterns shift from more frequent and less intense to less frequent and more intense storms, these reservoir types are most at risk to ecological degradation. The downstream food web appeared to be resilient to a changing precipitation pattern in a minimum flow management scenario, indicating that current management practices that preserve “ecological integrity” may be advantageous in an uncertain climate future. While the study’s findings support that minimum flow regulation may be one of the best management approaches in a changing climate, the top trophic level is only maintained during 33.6% of the modeling time period for said management scenario. Continued efforts should be made to optimize reservoir management practices so as to improve ecological integrity in an uncertain future. Serving as a first attempt at linking shifts in precipitation statistics, hydrology, reservoir management, and ecology, this study provides new insight into the effects of dam management on downstream food web dynamics, allowing reservoir managers to assess the impacts of their management decisions to preserve ecological integrity.