3D full-waveform inversion of time-lapse horizontal borehole GPR data to map soil water content variability

Abstract:

Soil moisture is a key state variable that controls water and mass fluxes in soil-plant systems and is variable in space and time. Over the last year’s, hydrogeophysical methods such as ground penetrating radar (GPR) have been used to determine electromagnetic properties as proxies for soil water content (SWC). Here, we combined zero-offset-profiles (ZOP) GPR measurements within multiple horizontal minirhizotubes at different depths to determine the spatial and temporal variability of SWC under a winter wheat stand at the Selhausen test site (Germany). We studied spatio-temporal variations of SWC under three different treatments: rainfed, irrigated and sheltered. We acquired 15 time-lapse ZOP GPR dataset during the growing season of the wheat in the rhizotron facility using horizontal boreholes with a separation of 0.75m and a length of 6m at six depths between 0.1-1.2m. The obtained radar velocities were converted to SWC using the 4-phase volumetric complex refractive index model. SWC values obtained using standard ray-based processing methods were not reliable close to the surface (0.1-0.2m depth) because of the inference of the critically refracted air wave and the direct wave through the subsurface. Therefore, we implemented a full-waveform inversion that uses accurate 3D forward modeling of GPRMax that incorporates the air and soil interactions. The shuffled complex evolution (SCE) method allowed us to retrieve quantitative medium properties that explained the measured data with a R² of at least 0.95, and improved SWC estimates at all depths. The final SWC distributions for wet and dry conditions showed that the vertical variability is significantly larger than the lateral variability caused by strong influence of precipitation and irrigation events.

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