Reservoir water level fluctuations and rainfall are primary contributors to the destabilization and damage of landslides in the Three Gorges Reservoir area (TGRA). Consequently, the investigation of the landslide deformation mechanism in the TGRA has gained significant attention since the implementation of the Three Gorges Reservoir. By utilizing recent monitoring data and focusing on the stepwise evolution of displacement, this study establishes a hydraulic calculation model for the Liangshuijing landslide. The research incorporates long-term data on reservoir water level fluctuations and rainfall to investigate the seepage field, stability, and displacement patterns under the combined influence of reservoir water level fluctuations and rainfall. Additionally, the study explores the intrinsic deformation mechanism of the Liangshuijing landslide. The results indicate that the seepage field in the front and back of the landslide is primarily influenced by the reservoir water level and rainfall, respectively, while the middle part is affected by the combination of both. The stability coefficient exhibits periodic changes corresponding to the rise and fall of the reservoir water level, and rainfall further diminishes the overall landslide stability. The surface displacement demonstrates an incremental trend, with a decrease in reservoir water level causing the displacement to increase incrementally, while an increase in reservoir water level tends to stabilize the displacement. Overall, the deformation of the Liangshuijing landslide is primarily caused by the reservoir water level fluctuations and rainfall, which subsequently impact the underground seepage field and hydraulic conditions, resulting in deformation. Generally, the current deformation is primarily concentrated at the foot of the slope, gradually extending towards the rear. The stabilization of deformation is observed in the middle and rear regions. Changes in the reservoir water level have a more pronounced impact on landslide deformation, and during years with greater fluctuations in the reservoir water level, it is crucial to enhance early warning monitoring of the deformation.