Monitoring reservoir dynamics in India is critical for addressing regional water scarcity, resolving interstate water-sharing disputes, and optimising hydropower generation. We quantify emerging trends in 145 reservoirs using ground-based observations, provide an early diagnostic assessment of SWOT-derived water surface elevation (WSE) and storage observations over Indian reservoirs, and develop a continuous long-term time series by integrating ancillary multi-mission satellite altimetry data from DAHITI. Based on storage capacities, reservoirs were categorized into small (<400 MCM), medium (400–1000 MCM), and large (>1000 MCM) reservoirs to evaluate classification-based performance. Results demonstrated generally good agreement between SWOT-derived and in-situ WSE observations, with large reservoirs achieving a mean Pearson r of 0.90 and a mean ubRMSE of 1.87 m. For the storage estimates, medium reservoirs showed satisfactory performance (mean Pearson r = 0.83 and mean KGE = 0.50), whereas large reservoirs exhibited a PBIAS of 10.87%. Small reservoirs showed strong temporal agreement and relatively low absolute WSE errors, although these findings remain preliminary due to the limited sample size (n = 2) for this specific class. Corroborating inferences from explicit investigation in three selected reservoirs revealed that SWOT accurately captures observed reservoir dynamics while illustrating the integration of SWOT with historical satellite altimetry and in-situ observations (r=0.91 to 0.99 for WSE and PBIAS=1.40% to −21.90% for storage). Results highlight the practical potential of SWOT for reservoir monitoring and development of dynamic reservoir operation strategies in data-scarce reservoirs in India and beyond. The multi-source approach offers a transparent and practical framework that provides actionable data to better inform and devise long-term water management strategies amid a changing climate.
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Chauhan et al. (2026) studied this question.
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