Abstract
This study introduces the Modified Water Balance Model (MWBM), leveraging Google Earth Engine (GEE) and high-resolution remote sensing data to enhance Groundwater Recharge (GWR) estimations in West Bengal. Utilizing MODIS land surface temperature and CHIRPS precipitation data, the MWBM provides precise and spatially extensive GWR estimates. The study area, encompassing diverse climatic and geological conditions, reveals significant variations in GWR influenced by factors such as the Himalayan foothills, urban infrastructure, and soil types. Key findings indicate high GWR values in districts like Alipurduar and Jalpaiguri due to heavy rainfall, while areas such as Bankura and Purba Bardhhaman show lower, more stable GWR due to less permeable laterite layers. The MWBM's integration of satellite data and advanced computational tools marks a substantial advancement in groundwater management, providing critical insights for sustainable water resource planning. Future research should focus on incorporating dynamic meteorological data and assessing the impact of anthropogenic activities on groundwater recharge.