Responses of River-Lake Interaction to Future Morphological Evolution: A Numerical Investigation of the Jing River–Dongting Lake System, Middle Yangtze River, China

The Jing River–Dongting Lake (DTL), a critical river–lake complex system in the Middle Yangtze River, China, plays a vital role in flood regulation and ecological sustainability. Recent decades have experienced significant morphology adjustments due to upstream reservoir operations; however, the long-term high-resolution hydro-morphodynamic evolution and its impacts on river–lake interactions remain insufficiently quantified. To address this gap, a two-dimensional hydro-morphodynamic model based on HEC-RAS was employed to simulate three decades of hydro-morphology evolution under projected flow–sediment conditions. The model was validated against observed data and reproduced erosion–deposition trends consistent with previous numerical studies. The results indicate sustained channel incision in the Jing River, with a cumulative erosion volume of 462 million m 3 , in contrast to net deposition in the DTL area totaling 276 million m 3 over three decades. A comparison of results under a sediment reduction regulation shows that the overall spatial pattern of erosion and deposition remains largely consistent, although local areas, particularly the confluence of the three major inlets feeding the lake, exhibit pronounced sensitivity to sediment variations. Furthermore, continuous mainstream incision intensifies a draining effect on the lake during dry seasons, leading to declines in both water levels and surface area in the DTL. This effect is most pronounced in the eastern lake area, with reductions being markedly greater in dry periods than in wet periods. Finally, the lake’s storage capacity progressively decreases, with an average annual loss of approximately 36.5 million m 3 in the wet periods, underscoring significant impairment of its flood-regulation function. This study provides a validated modeling framework and critical insights for predicting morphological evolution and informing adaptive management in large river–lake systems.