Effective Surface Roughness Impact in Polarimetric GNSS-R Soil Moisture Retrievals

Single-pass soil moisture retrieval from a single instrument and without using much ancillary data has been one key objective of Global Navigation Satellite System – Reflectometry (GNSS-R) for the last decade. Achieving this goal will allow small satellites with GNSS-R payloads to perform independent land monitoring without the need for additional dynamic measurements. Effective surface roughness retrieval is key to soil moisture estimations. The surface roughness attenuation derived from the Kirchhoff Approximation needs to be properly modeled to estimate soil moisture using either L-band radiometers, GNSS-R, or L-band Synthetic Aperture Radar (SAR). In the present work, the effective surface roughness is modeled by retrieving the surface correlation length of the soil using soil moisture data retrieved by the Soil Moisture Active Passive (SMAP) mission, and reflectometry measurements collected by the SMAP radar receiver (SMAP-Reflectometry or SMAP-R). The effective surface roughness is retrieved for a single-polarization approach, useful for single-polarization GNSS-R instruments, and then for dual-polarization instrument approach, where the ratio between two orthogonal polarizations is evaluated with respect to the soil moisture model. Differences between different polarizations and approaches are evaluated, and the theoretical soil moisture error with varying effective surface roughness is analyzed. Our results show a 1-sigma soil moisture error 0.08 cm3/cm3 for the dual-polarization case.