Abstract
Monitoring soil moisture (SM) on individual crop fields is of great interest for agricultural applications. Synthetic aperture radar (SAR) systems such as Sentinel-1 provide sensitivity to surface SM at a spatial resolution compatible with crop-field monitoring. Different algorithms have been proposed to relate SAR backscattering to SM, yet most overlook soil texture as a modulating factor. This study investigated the influence of soil texture, closely related to soil hydrological properties, on the relationship between Sentinel-1 C-band backscattering and surface SM using extensive data from the agricultural sites of the COSMOS-UK monitoring network. Our results evidenced the semi-empirical first-order relationship between SM and field-averaged VV backscattering, and found that the gradient of their linear regression was indicative of soil texture. For instance, in sandy loam soil the S1 response showed high sensitivity to SM with a change of 1.69% SM per dB; this compared with the lower sensitivity of a clayey soil at a change of 4.81% SM per dB. These findings lay the ground for the retrieval of field-scale soil hydrological properties from backscatter temporal patterns, when used in synergy with rainfall data and process-based soil-moisture models.