Synergistic Use of Ground-Based GNSS-R and Sentinel-2 Imagery for Soil Moisture Estimation Across an Irrigated Grassland

Soil moisture (SM) plays a central role in water cycle dynamics and land-atmosphere interactions, acting across local and regional scales. Few studies have explored the use of the ground-based global navigation satellite system reflectometry (GNSS-R) interference pattern technique (IPT) for SM estimation. In these studies, SM was estimated from the GPS elevation angle where lower reflectivity occurs (notch), which is difficult to determine in real GNSS-R interference power (IP) acquisitions. This study introduces the use of IP amplitude at vertical polarization (V-pol), readily extracted from the IP oscillations, as an alternative for SM estimation beneath vegetation cover. An empirical model was developed for estimating SM in irrigated grassland using a GNSS-R receiver with a linearly polarized antenna. The experiment, conducted between June 6 and August 8, 2022, covered the grassland’s growth phase and preharvesting and postharvesting. The study incorporated normalized difference water index (NDWI) from the Sentinel-2 satellite to account for vegetation’s impact on IP amplitude. Results indicated that the IP amplitude at V-pol accurately estimates SM (RMSE =0.04 m3/m3). Moreover, the results show that the vegetation layer mainly attenuates the IP amplitude with a nonsignificant scattered contribution to the IP, allowing for the simplification of the empirical model by ignoring the scattered contribution of vegetation. The simplified empirical model can be numerically resolved to estimate the NDWI if the SM is known. In summary, this study highlights the effectiveness of the ground-based IPT for close-range sensing of SM and a biomass proxy, such as NDWI.