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National Aeronautics and Space Administration&#x0027;s soil moisture active&#x2013;passive (SMAP) mission potential to produce high-resolution soil moisture suffered adversely due to its L-band synthetic-aperture radar (SAR) failure. Other satellite-based L-&#x002F;C-band SAR observations can be used within the SMAP active&#x2013;passive algorithm. In this article, we evaluated the capability of ingesting ISRO&#x0027;s Radar Imaging Satellite-1 (RISAT-1) C-band SAR observations in the SMAP active&#x2013;passive algorithm to obtain soil moisture at 1, 3, and 9 km over the agricultural region dominant by paddy that experiences seasonal flooding. We also improved the SMAP mission active&#x2013;passive algorithm with a dynamic surface water bodies (ponding conditions) masking approach using the native RISAT-1 observations. The article shows that the use of surface water masks helps in mitigating the negative impact of surface water bodies in the active&#x2013;passive disaggregation process. The SMAP&#x2013;RISAT soil moisture retrievals at 1 and 3 km resolutions are found to have high unbiased root-mean-square error (ubRMSE) greater than 0.06 m3&#x002F;m3 during very wet and high vegetative conditions. However, at low and moderate soil moisture states, the ubRMSE is below 0.06 m3&#x002F;m3. Comparison of soil moisture retrievals at 9 km resolution with upscaled ground-based soil moisture measurements shows ubRMSE less than 0.04 m3&#x002F;m3. This article is a precursor for estimating soil moisture for the upcoming RISAT-1A dataset over India. The findings will further help in the implementation of a microwave active&#x2013;passive algorithm to retrieve soil moisture for future satellite missions involving radiometer-SAR instruments, and challenging geophysical conditions (i.e., dynamic surface water bodies).

Soil Moisture Retrieval Using SMAP L-Band Radiometer and RISAT-1 C-Band SAR Data in the Paddy Dominated Tropical Region of India