Predicting global change effects on reservoir sedimentation

Water availability is not uniformly distributed, and water is not available on demand in many areas of the world. Thus, artificial storage of water is essential for the sustainable management of water resources. However, reservoirs are transport-limited systems due to low flow velocities, resulting in sedimentation. Additionally, global change amplifies sedimentation because of altered hydrological conditions and sediment production of river basins. Preparedness for global change necessitates decades-long forecasting of these complex phenomena, which is computationally challenging. Sediment depositions reduce not only the available storage volume over time but may create severe safety issues, such as blockage of bottom outlets or increased flood risk. Therefore, it is essential to understand not only the trapping efficiency of a reservoir and its temporal variations but also the spatial distribution of expected sediment accumulations. To generate these insights, long-term predictions based on three-dimensional (3d) hydro-morphological models considering the changing climate are required.

The Banja reservoir, located in southeast Albania, was investigated in this study to investigate the effects of global change on reservoir sedimentation. Simulations were performed up to 90 years into the future to model characteristic sedimentation stages and to test for differences between several emission scenarios, combined with socioeconomic and climate scenarios. A 3d numerical model simulated hydrodynamics, suspended sediment transport, and sedimentation processes, considering the Devoll River as the main tributary and three smaller tributaries. To enable long-term simulations, an adaptive grid with a spatial resolution of 50 m x 50 m in the x- and y-direction, respectively, as well as up to 10 cells in the z-direction was used. Due to an implicit time discretization a time step of 5,400 seconds was chosen to achieve reasonable computational times.

The model results showed a decrease in the trapping efficiency by 2100 for all scenarios, which is associated with storage loss over time. In the high and medium emission scenarios, the reservoir experiences a substantial loss of storage volume due to increasing sediment yields. The model also showed the formation of a delta at the head of the reservoir and the progressive movement of the delta further into the reservoir. These spatial and temporal insights into future sediment deposition patterns are crucial for developing sustainable management strategies to account for global change.