We combined a full-waveform ground-penetrating radar (GPR) model with a roughness model to retrieve surface soil moisture through signal inversion. The proposed approach was validated under laboratory conditions with measurements performed above a sand layer subjected to seven different water contents and four different surface roughness conditions. The radar measurements were performed in the frequency domain in the range of 1–3 GHz and the roughness amplitude standard deviation was varied from 0 to 1 cm. Two inversion strategies were investigated: (1) Full-waveform inversion using the correct model configuration, and (2) inversion focused on the surface reflection only. The roughness model provided a good description of the frequency-dependent roughness effect. For the full-waveform analysis, accounting for roughness permitted us to simultaneously retrieve water content and roughness amplitude. However, in this approach, information on soil layering was assumed to be known. For the surface reflection analysis, which is applicable under field conditions, accounting for roughness only enabled water content to be reconstructed, but with a root mean square error (RMS) in terms of water content of [Formula: see text] compared to an RMS of [Formula: see text] for an analysis where roughness is neglected. However, this inversion strategy required a priori information on soil surface roughness, estimated, e.g., from laser profiler measurements.
Evaluation and systematic selection of significant multi-scale surface roughness parameters (SRPs) as process monitoring index