Abstract

The looming impacts of changing climate and ever increasing water and energy demands make it important to quantify expected water and energy availabilities and develop strategies to mitigate expected shortfalls. Keeping these aspects in mind, in this paper, hydrological modeling is performed on the Upper Yangtze River Basin (UYRB) to simulate the inflows to the Three Gorges Reservoir (TGR) based on the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) model and a Multiple-input single-output Linear Systematic Model (MLSM). These models are derived for historical (1960–2005) and future (near: 2021–2050 and far: 2061–2090) time periods using bias corrected climate projections from an ensemble of 6 RCMs available through the COordinated Regional Downscaling EXperiment in East Asia (CORDEX-EA) under Representative Concentration Pathway (RCP) 4.5 and 8.5. Simulating with and without snow, hydrological responses to both the historical and future climates are fed into a daily reservoir simulation model where the operation of the TGR follows the designed operating rule curves which can be regarded as a standard operating policy (SOP). The results indicate marginal reduction in mean annual precipitation, inflow and hydropower generation and mean hydropower generation reliability for the future scenarios under RCP 8.5 with the decreases for far future being more prominent than those for near future. The inflow decreases strongly reduce the hydropower generation of the TGR in November and May and have limited impact on other months because of the regulation ability of the SOP. Hydropower generation responses to extreme variations in annual inflow are projected to aggravate the water and energy security stress of the TGR. The without snow projections alter the inflow patterns as well as the hydropower generation patterns of the TGR with respect to the with snow projections and are likely to have positive impact on the waterimpounding and hydropower generation for both the historical and future time periods.

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