Retrieval of 1 km surface soil moisture from Sentinel-1 over bare soil and grassland on the Qinghai-Tibetan Plateau

Most existing soil moisture (SM) products from earth observations and land surface models over the Qinghai-Tibetan Plateau (QTP) have coarse resolutions or are mostly generated with high spatial resolutions based on downscaling methods. The former could hinder the applications in hydrological and ecological analyses at the regional scale and the performance of the latter could be limited by the intricate relationship between SM and downscaling factors in regions with complex topography. To address this issue, this paper aims to retrieve a 1 km SM product from 2017 to 2021 using Sentinel-1 Synthetic Aperture Radar (SAR) observations based on a semi-empirical method specific to the QTP region (SM_S-1) as different from the previous downscaled SM products. The main interest in our retrievals is that the semi-empirical modeling approach allows exploring the relationships between microwave backscatters and the soil and vegetation parameters spatially based on well-defined mathematics. The SM_S-1 retrievals were evaluated against the observations from five in-situ networks over the QTP and against six other existing downscaled 1 km SM products. The temporal evaluation against in-situ measurements showed that SM_S-1 retrievals performed better than most 1 km SM products obtained from Machine Learning methods (median R = 0.57, ubRMSD = 0.064 m³/m^3, RMSD = −0.107 m³/m³ and bias = −0.042 m³/m³) except for SM_Sg. Furthermore, the SM_S-1 retrievals presented reasonable spatial patterns that are consistent with the spatial distribution of the grassland-type map. Our Sentinel-1 SAR-based method can therefore potentially serve as a foundation for the advance of active microwave remote sensing SM algorithm to retrieve spatially high-resolution SM.