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Accurate estimation of water balance components at the river basin scale is essential for sustainable water resources management, particularly in regions experiencing increasing climatic variability and growing anthropogenic pressures. The Cauvery River Basin, one among the major river basins of peninsular India is taken up in this study. This study presents a comprehensive water balance analysis of the Cauvery River Basin using the Variable Infiltration Capacity (VIC) model integrated with satellite based remote sensing datasets. Meteorological forcing from the India Meteorological Department (IMD), MODIS-derived vegetation parameters, and Shuttle Radar Topography Mission (SRTM) topographic data were used to capture the spatial heterogeneity of the basin. Long term simulations were performed for the period 1951–2019 to assess the spatial and temporal variability of surface and subsurface components. The results indicate pronounced interannual variability in rainfall, which strongly influences runoff generation, while evapotranspiration remains a relatively stable and dominant loss component across the basin. Reduced rainfall during the late 1990s and early 2000s resulted in diminished runoff and increased hydrological stress, whereas post 2005 conditions show partial recovery in basin water availability. The runoff-to-rainfall coefficient and evapotranspiration ratio for the basin are estimated as 0.26 and 0.68, respectively. Reservoir representations were incorporated to analyze inflow dynamics for major reservoirs. Model performance evaluation demonstrated overall good agreement between simulated and observed discharge, with stronger performance at Hemavathy (r = 0.93, NSE = 0.87, KGE = 0.93; RMSE = 72.68 m3/s, MAE = 37.43 m3/s, PBIAS = -4.47%) compared to Krishna Raja Sagara (r = 0.85, NSE = 0.68, KGE = 0.13; RMSE = 116.26 m3/s, MAE = 68.99 m3/s, PBIAS = 23.33%). Overall, the integration of remote sensing datasets with the VIC framework provides a robust approach for basin scale hydrological assessment and supports informed water resources planning and management.
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Saravanan et al. (2026) studied this question.
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