Soil moisture 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 Systems Reflectometry (GNSS-R) Interference Pattern Technique (IPT) for soil moisture estimation. In these studies, soil moisture 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 soil moisture estimation beneath vegetation cover. An empirical model was developed for estimating soil moisture 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 pre- and post-harvesting. The study incorporated Normalized Differential 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 estimate soil moisture (RMSE = 0.04 m³/m³). Moreover, results show that the vegetation layer mainly attenuates the IP amplitude with a non-significant 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 soil moisture is known. In summary, this study highlights the effectiveness of the ground-based IPT for close-range sensing of soil moisture and a biomass proxy, such as NDWI.@en

Soil moisture (SM) is an important state variable in land surface models. Here, we investigate the potential of a ground-based global navigation satellite system receiver with two linearly polarized antennas that measure the interference power (IP) of direct and reflected signals in horizontal polarization (H-pol) and vertical polarization (V-pol) to estimate SM. The coefficient of determination between the IP waveforms at H-pol and V-pol ( $\boldsymbol {R}_{ \boldsymbol {v}\mathbf {/} \boldsymbol {h}}^{\mathbf {2}}$ ) was used as a predictor of SM. A coherent specular reflection model was employed to first explore the relationship between $\boldsymbol {R}_{ \boldsymbol {v}\mathbf {/} \boldsymbol {h}}^{\mathbf {2}}$ and SM for different values of soil roughness. That relationship was subsequently applied to estimate SM from $\boldsymbol {R}_{ \boldsymbol {v}\mathbf {/} \boldsymbol {h}}^{\mathbf {2}}$ determined from global positioning system (GPS) signals acquired continuously by a ground-based receiver between May and December 2022 for an area with very smooth bare soil. The results show that the proposed method can estimate the SM of the upper 10-cm layer with high accuracy (with a root-mean-square error (RMSE) of approximately 1.5 vol.%) and demonstrate the potential of the ground-based IP technique as a practical system solution for proximal remote sensing of SM over bare soils .

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