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Rapid agricultural expansion, urbanization, and increasing anthropogenic water demands are exerting significant pressure on surface and groundwater resources, necessitating robust hydrological assessments, particularly in ungauged basins. This study quantifies groundwater recharge and surface runoff in the Yamuna–Krishni interfluve of Northern India using the SWAT model. Due to unavailability of observed streamflow data, MODIS-based evapotranspiration data was employed for model calibration and validation. During the calibration period, the model achieved an NSE of 0.73 and an R² of 0.77, while the validation results demonstrated consistent predictive capability, with corresponding NSE and R² values of 0.71 and 0.72, respectively confirming a good statistical agreement. Simulated groundwater recharge ranged from 104.71 to 201.25 mm (14.67–23.88% of rainfall), while surface runoff varied between 8.15 and 14.86% supported by Groundwater Estimation Committee norms as well as hydrological model outcomes from adjacent basins. The results highlight the effectiveness of remote sensing–driven SWAT modeling for hydrological assessment in ungauged basins, providing a scientific basis for sustainable water resource management and infrastructure planning.
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Kumar et al. (2026) studied this question.
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