<p>Rainfall serves as an indirect trigger for landslides, while groundwater plays a direct role in controlling their stability. Transitioning from empirical early warning systems based on rainfall thresholds to physical early warning systems that rely on groundwater levels represents a promising approach to enhancing the reliability of landslide prediction. This study examines the Baimatan, Tanjiahe, Pailou, and Tanjiawan landslides within the Three Gorges Reservoir Area, analyzing the relationship between groundwater dynamics and landslide deformation. Furthermore, it elucidates the deformation mechanisms influenced by both exogenous factors, such as rainfall and groundwater, and endogenous factors, including the geological environment and geotechnical damage. Studies indicate that groundwater serves as a critical variable linking exogenous and endogenous factors. The groundwater level threshold early warning method is applicable to large-scale isolated landslides, where initial deformation is primarily influenced by rainfall and subsequently dominated by groundwater dynamics. Groundwater levels result from the dynamic equilibrium between recharge and discharge, while the geological environment regulates this process through its permeability and structural characteristics, thereby controlling the deformation state of landslides. The rise in groundwater level acts as both an exogenous disturbance and a trigger for endogenous damage, creating a positive feedback mechanism that exacerbates deformation. The step-like evolution of landslides follows a chain mechanism: exogenous triggering → coupled acceleration of exogenous and endogenous factors → endogenous damage sustaining decelerated creep. Furthermore, this study reveals the dynamic competition mechanism between rainfall recharge and groundwater discharge, and proposes a groundwater level prediction model represented by the equation <i>dh/dt</i> = <i>aR</i>_<i>eff</i>(<i>t</i>) − <i>bh</i>(<i>t</i>). The parameters of this model reflect the equivalent permeability characteristics of the landslide area, necessitating only initial water level and rainfall data to facilitate short-term predictions of groundwater levels. By quantifying both recharge and discharge rates, this model offers a quantitative basis for mechanism analysis and early warning of large isolated landslides.</p>