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<p>The Surface Water and Ocean Topography (SWOT) mission, equipped with a Ka-band radar interferometer, is designed to detect global hydrological fluxes through high-precision water elevation measurements. This study assessed SWOT observation characteristics and uncertainties across Indian inland waterbodies, including rivers, reservoirs, glacial lakes, and hydraulic structures. The performance evaluation was carried out during calibration-validation (cal/val) fast-sampling and science orbits using in-situ and altimetry datasets. SWOT-derived Water Surface Elevation (WSE) evaluation showed root mean square error (RMSE) ranging from 0.32 to 1.25&#xa0;m for rivers and 0.09 to 1.51&#xa0;m for reservoirs. These metrics align with the accuracy of conventional radar altimeters, however, after the selection of optimized data quality filters and outlier removal. Spatiotemporal variations in water surface slope (WSS), strong backscatter from permanent water in river channels facilitating river width estimation and WSE offer unique simultaneous measurements for hydrological models, enhancing our understanding of the terrestrial water cycle from regional to global scales.</p>

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SWOT Mission with Wide-Swath Altimetry: Observations and Insights into India’s Inland Waterbodies

  • 期刊论文

  • 发表日期：

    2025年6月5日

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  • Pankaj R. Dhote,
  • Praveen K. Thakur,
  • Kartikeya Gaur,
  • Vaibhav Garg,
  • Pramod Kumar,
  • Raghavendra P. Singh

摘要

The Surface Water and Ocean Topography (SWOT) mission, equipped with a Ka-band radar interferometer, is designed to detect global hydrological fluxes through high-precision water elevation measurements. This study assessed SWOT observation characteristics and uncertainties across Indian inland waterbodies, including rivers, reservoirs, glacial lakes, and hydraulic structures. The performance evaluation was carried out during calibration-validation (cal/val) fast-sampling and science orbits using in-situ and altimetry datasets. SWOT-derived Water Surface Elevation (WSE) evaluation showed root mean square error (RMSE) ranging from 0.32 to 1.25 m for rivers and 0.09 to 1.51 m for reservoirs. These metrics align with the accuracy of conventional radar altimeters, however, after the selection of optimized data quality filters and outlier removal. Spatiotemporal variations in water surface slope (WSS), strong backscatter from permanent water in river channels facilitating river width estimation and WSE offer unique simultaneous measurements for hydrological models, enhancing our understanding of the terrestrial water cycle from regional to global scales.