Abstract: The construction of the Jinping Ⅰ Hydropower Station has changed the hydrogeological conditions on both banks of the Xiaojin River. This leads to water immersion at the front edges of multiple slopes, posing a risk of slope instability. Using small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) technology based on ascending and descending orbit data, this study determined the surface deformation fields on both banks of the Xiaojin River in the period from December 2021 to March 2024 through inversion. On this basis, the impacts of water level and precipitation on landslide deformation were further quantified by combining remote sensing-based water level monitoring and a grey relational analysis (GRA) model. The results indicate the presence of a total of 40 wading landslides along the Xiaojin River, including six high-risk landslides. The average grey relational degree between water level and landslide deformation was 0.776, and that between precipitation and landslide deformation was 0.658. Therefore, water level was identified as a primary contributor to landslide deformation, with strong correlation and significant discrepancy identified between both. In contrast, weak correlation and insignificant discrepancy were determined between precipitation and landslide deformation. The GRA results of the Lawo landslide further confirm that water level produced a greater impact on landslide deformation than precipitation. Especially during a drop in water level, the slope stability significantly decreased, highlighting the need for intensified monitoring and prevention. This study provides important supplementary information on the triggering mechanisms of wading landslides in high-mountain and canyon areas. Furthermore, it offers a scientific basis for landslide prevention and control and for the parameter setting of the early warning systems for geologic disasters.