Praveen K. Thakur (Indian Institute of Remote Sensing, Indian Space Research Organisation, Dehradun, India); Vaibhav Garg (Indian Institute of Remote Sensing, Indian Space Research Organisation, Dehradun, India); Hind Oubanas (G-EAU, INRAE, Montpellier, France, France); Pierre-Olivier Malaterre (G-EAU, INRAE, Montpellier, France, France); Shubhangam Garg (Indian Institute of Remote Sensing, Indian Space Research Organisation, Dehradun, India); Kartikeya Gaur (Indian Institute of Remote Sensing, Indian Space Research Organisation, Dehradun, India); Kshiitij Srivastava (Indian Institute of Remote Sensing, Indian Space Research Organisation, Dehradun, India); Harish Karnataka (Indian Institute of Remote Sensing, Indian Space Research Organisation, Dehradun, India); Pramod Kumar (Indian Institute of Remote Sensing, Indian Space Research Organisation, Dehradun, India); Raghavendra P Singh (Indian Institute of Remote Sensing, Indian Space Research Organisation, Dehradun, India)

Monitoring inland water bodies is essential for understanding the hydrological cycle, as well as broader environmental and atmospheric processes within the Earth system. Accurate estimation of river discharge plays a key role in water resource management, ecosystem sustainability, and hydrological modeling. With a global decline in in-situ monitoring stations, remote sensing techniques are increasingly being adopted for estimating river, lake, and reservoir fluxes. The Surface Water and Ocean Topography (SWOT) mission, equipped with a Ka-band radar interferometer, aims to capture global hydrological fluxes through high-precision water surface elevation (WSE) measurements. This study evaluates the characteristics and uncertainties of SWOT observations over diverse Indian inland water bodies—including rivers, reservoirs, glacial lakes, and hydraulic structures—during both calibration-validation (cal/val) and science orbit phases, using in-situ and satellite altimetry datasets. Our findings indicate that the SWOT node product generally yields slightly more accurate WSE estimates compared to the raster product when validated against GNSS, in-situ, and radar altimetry data, although quality filtering reduces the temporal resolution. Conversely, the raster product captures two-dimensional WSE variability, improving spatial representation in wide river cross-sections. To further harness SWOT’s potential, we developed a geo-portal to monitor water level and storage changes across major Indian reservoirs. The mission’s ability to simultaneously capture spatiotemporal variations in water surface slope (WSS), strong backscatter from permanent river channels for river width estimation, and WSE provides a valuable dataset for hydrological modeling. Our analysis underscores SWOT’s significant potential for inland hydrodynamic applications, while also emphasizing the need for continued evaluation in complex riverine and reservoir systems.