Abstract: To address the impacts of dynamic reservoir capacity and unsteady flow propagation in the mainstream and tributaries within the reservoir area on hydropower generation scheduling for river-type reservoirs, this paper proposes a reservoir optimal power generation scheduling model coupled with a 1D river network unsteady flow model. The model is solved using an OpenMP-based parallel dynamic programming algorithm and applied to a case study of the Three Gorges Reservoir (TGR). The results show that the proposed dynamic capacity model effectively simulates the spatial-temporal variations of flow discharges and water levels along the mainstream and tributaries within the TGR area. Compared with the static capacity model, the proposed dynamic capacity model exhibit distinct differences in power generation processes across operational phases—showing more stable variations during the drawdown and flood seasons, while experiencing significantly more fluctuations during the impoundment period. Specifically, the total power generation decreases by 206 million kW·h, 129 million kW·h, and 47 million kW·h respectively during these three periods, with the most significant impact observed during the drawdown period. Furthermore, during the initial stages of the drawdown and impoundment periods, the dynamic capacity model enhances power generation by increasing outflow discharge. This study would help the refined hydropower generation scheduling simulations in river-type reservoirs.