This study investigates the potential of assimilating satellite-derived surface soil moisture to improve the representation of surface water–groundwater interactions through enhanced groundwater recharge estimates generated by the Soil and Water Assessment Tool (SWAT). The Tombigbee River Basin in the southeastern United States was used as a test case. A baseline SWAT model was first developed to simulate surface hydrologic processes and groundwater recharge, followed by an enhanced modeling framework that assimilated the Soil Moisture Active Passive (SMAP) Enhanced L3 Radiometer Global Daily 9 km soil moisture product (SPL3SMP_E). To assess the influence of spatial representation on surface water-groundwater connectivity, soil moisture assimilation was implemented using both subbasin-level and hydrologic response unit (HRU)-level discretization schemes. Model performance was evaluated against a spatially explicit 1 km monthly recharge dataset from the U.S. Geological Survey. Results show that the enhanced SWAT models substantially improved recharge estimates (R² = 0.70; NSE = 0.63; p < 0.0001), indicating a more realistic simulation of surface-to-subsurface fluxes. Variations in interannual recharge across HRU-based simulations underscore the importance of spatially explicit calibration when quantifying surface water–groundwater interactions. Overall, this framework strengthens the linkage between surface hydrologic states and groundwater processes, offering a transferable approach for integrated surface water–groundwater studies across multiple temporal scales.