This study examines hydraulic connectivity in Warna region of Maharashtra by analyzing rainfall, reservoir, and groundwater levels. Correlation analysis and entropy measures were employed to investigate this connectivity, which is notably influenced by rainfall and reservoir water level on groundwater. The findings reveal significant seasonal variability in rainfall, with peaks occurring during the monsoon season (June-September). The Warna Reservoir's water levels respond significantly to monsoon rainfall, with notable increases of approximately 20 m during peak monsoon periods, indicating a strong interaction between rainfall and reservoir levels. Groundwater levels show variable correlations with both rainfall and reservoir water levels. The Marleswar well, for example, demonstrates a strong negative correlation with rainfall (- 0.82), indicating a rise in groundwater levels with increased rainfall, which persists during the monsoon, with a correlation of - 0.77. Correlations with reservoir water levels are more varied; the Ukalu well exhibits the strongest negative correlation, suggesting a significant relationship with reservoir water level fluctuations. Phase-segmented data analysis reveals strong cross-correlations between reservoir and groundwater levels in some wells, with the Ukalu well showing the highest connectivity during the peak monsoon period, which indicates effective reservoir recharge. Entropy and transinformation analysis for the Ukalu well indicate a substantial correlation between groundwater and reservoir levels, with transinformation averaging 54%, reflecting notable seasonal and phase variations. The variability in hydraulic connectivity appears to be influenced by geological conditions. The Ukalu well, located nearer to the Warna reservoir, shows better connectivity compared to wells situated in the Western Ghats. The basaltic terrain and associated fractures likely affect groundwater flow and connectivity, influencing well responses to variations in reservoir levels and rainfall. This study highlights the non-linear interactions and feedback mechanisms that traditional methods may not fully capture, presenting valuable insights for similar hydrogeological conditions.
