Climate and land use changes will affect the hydrological regime, and therefore hydropower. This study which aims to develop a novel modeling framework, does not only determine the changes in hydropower generation and sustainability, but also provide robust operating rules for handling uncertainty attributed to both climate and land use changes, using Xinanjiang Reservoir in Eastern China as a case study. Specifically, projections of five bias-corrected and downscaled General Circulation Models (GCMs) and three modeled land uses representing a range of tradeoffs between ecological protection and urban development are employed to drive the Soil and Water Assessment Tool (SWAT) and to predict streamflow under 15 scenarios. We then develop a set of robust rule curves to consider the potential uncertainty in reservoir inflow and to increase hydropower generation, and a baseline rule is presented for comparison. Results show that both robust and baseline rules increase hydropower generation with increasing reservoir inflows in future, but the robust rule yields better hydropower generation, sustainability and efficiency. The streamflow under the rapid urbanization scenarios differs from that under other scenarios, but there are no significant differences in hydropower among scenarios corresponding to the non-linear relationship between streamflow and hydropower change. Our findings highlight the potential to improve water resource utilization in the future, especially based on the robust operating rule considering optimization and uncertainty, and can provide references for future hydropower planning to the other existing plants.

Climate and land use/cover changes are the main factors altering hydrological regimes. To understand the impacts of climate and land use/cover changes on streamflow within a specific catchment, it is essential to accurately quantify their changes given many possibilities. We propose an integrated framework to assess how individual and combined climate and land use/cover changes impact the streamflow of Xinanjiang Basin, in East China, in the future. Five bias-corrected and downscaled General Circulation Model (GCM) projections are used to indicate the inter-model uncertainties under three Representative Concentration Pathways (RCPs). Additionally, three land use/cover change scenarios representing a range of tradeoffs between ecological protection (EP) and urban development (UD) are projected by Cellular Automata - Markov (CA-Markov). The streamflow in 2021–2050 is then assessed using the calibrated Soil and Water Assessment Tool (SWAT) with 15 scenarios and 75 possibilities. Finally, the uncertainty and attribution of streamflow changes to climate and land use/cover changes at monthly and annual scale are analyzed. Results show that while both land use/cover change alone and combined changes project an increase in streamflow, there is a disagreement on the direction of streamflow change under climate change alone. Future streamflow may undergo a more blurred boundary between the flood and non-flood seasons, potentially easing the operation stress of Xinanjiang Reservoir for water supply or hydropower generation. We find that the impacts of climate and land use/cover changes on monthly mean streamflow are sensitive to the impermeable area (IA). The impacts of climate change are stronger than those induced by land use/cover change under EP (i.e., lower IA); and land use/cover change has a greater impact in case of UD (i.e., higher IA). However, changes in annual mean streamflow are mainly driven by land use/cover change, and climate change may decrease the influence attributed to land use/cover change.