Aditya Sati (Indian Institute of Technology, Kanpur, India); Balaji Devaraju (Indian Institute of Technology, Kanpur, India)

Reservoirs are artificial water bodies controlled by human operations, unlike natural lakes or rivers driven primarily by climate and catchment processes. Their levels, storage, release, and seasonal behavior make separate analysis essential for understanding their behavior and impact. Satellite radar altimetry provides water surface elevation (WSE) estimates, but factors such as altimetry pass location, variability in surface water area, and topographic conditions can influence accuracy. The Surface Water and Ocean Topography (SWOT) mission introduces co-located observations of WSE, surface water area, and derived storage changes, offering a framework for integrated reservoir monitoring. This study presents a workflow to estimate reservoir storage change using data from Sentinel-6, Sentinel-3A/3B, and SWOT (nadir) altimetry missions, combined with surface water extent derived from Sentinel-1 Synthetic Aperture Radar (SAR) imagery. The workflow includes the selection of virtual stations based on altimetry track distribution, dynamic surface masking using auxiliary datasets, and integration of multi-mission altimetry for WSE estimation. Storage change is calculated by combining the WSE and the area time series. We apply this workflow to five Indian reservoirs: Gandhisagar, Nathsagar, Shivajisagar, Somasila, and Ukai, which differ in shape, size, and topography. The results are compared against the SWOT Level 2 Lake Single-Pass Vector Data Product (SWOT_L2_HR_LakeSP), evaluating WSE, area, and storage estimates. The analysis examines the consistency between SWOT observations and multi-mission satellite-based methods and assesses the ability of SWOT to capture spatial and temporal changes in reservoirs.