In the context of climate change and the subsequent pressure from geological structures, there is a pressing need to analyse hydroclimatic trend events on dam stability and establish a clear correlation between reservoir surface water and groundwater levels in the Bagré Dam. Hydrodynamic variables (evaporation, inflow, irrigation, spillage, water level, rainfall) collected in and around the Bagré dam were analysed, using the singular spectrum analysis algorithm to delineate trends and variability over the 1993–2022 period. Machine learning models were developed to predict the impact of surface water on groundwater level over groundwater data that spans 2002–2022. There is an observed increasing trend of spillage due to increasing inflow; evaporation and irrigation trends are also increasing, while rainfall has been decreasing since 2012. The prediction shows an increasing groundwater level due to an increasing available reservoir water level. Consistent inflow rise will affect dam stability, while a spill over might lead to flooding downstream. The increasing trend of irrigation benefits farmers, while consistent availability of reservoir surface water would enable the groundwater level to increase via recharge. Regular monitoring of hydrodynamic trends will enable dam stability, maintenance, and contribute to groundwater and surface water availability for agricultural activities amidst climate change.