Estimation of surface water volume using CYGNSS and radar altimetry

Surface water storage in inland water bodies is crucial for understanding water storage dynamics, which directly impact the hydrological cycle. Traditional in situ methods face limitations in capturing these dynamics, especially for smaller and remote water bodies, highlighting the need for alternative approaches. Remote sensing techniques, particularly the combination of Global Navigation Satellite System reflectometry (GNSS-R) and radar altimetry, offer significant opportunities to overcome these challenges. By leveraging the unique capabilities of  CYclone Global Navigation Satellite System (CYGNSS) and radar altimetry missions, it is possible to monitor water surface extent and elevation over time, enabling continuous estimation of surface water volume in both large and small water bodies.

This study employs the CYGNSS satellite constellation to generate water masks from Delay Doppler Maps (DDMs) for Gandhisagar reservoir, Ghaghra river in Ayodhya, and Chilka lake. CYGNSS can distinguish smooth water surfaces from rough terrestrial surfaces as the DDMs generated are dominated by coherent reflections. This makes it a valuable tool for inland water body detection. An algorithm is developed to classify DDMs into coherent, incoherent, and mixed categories using a deep convolutional neural network based on the InceptionResNetV2 architecture, achieving a classification accuracy of 97.46\%. The water masks generated by CYGNSS will be compared against Pekel Global Surface Water masks and Sentinel-1 data using a thresholding method to ascertain the performance.

The elevations of the water body are estimated from radar altimetry satellites Sentinel-3 and Sentinel-6, and also from Surface Water and Ocean Topography (SWOT) mission. These estimates are then compared with in situ Water Resources Information System India (WRIS-India) data provided by the Central Water Commission, Government of India. By combining water surface area from CYGNSS and elevation data from satellite altimetry missions surface water volume change is calculated. This approach provides a framework for assessing volumetric changes in inland water bodies by combining multiple datasets.