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We present an integrated hydrogeophysical inversion approach that uses time-lapse off-ground ground-penetrating radar (GPR) data to estimate soil hydraulic parameters, and apply it to a dataset collected in the field. Off-ground GPR data are mainly sensitive to the near-surface water content profile and dynamics, and are thus related to soil hydraulic parameters, such as the parameters of the hydraulic conductivity and water retention functions. The hydrological simulator HYDRUS 1-D was used with a two-layer single- and dual-porosity model. To monitor the soil water content dynamics, time-lapse GPR and time domain reflectometry (TDR) measurements were performed, whereby only GPR data was used in the inversion. The dual porosity model provided better results compared to the single porosity model for describing the soil water dynamics, which is supported by field observations of macropores. Furthermore, the GPR-derived water content profiles reconstructed from the integrated hydrogeophysical inversion were in good agreement with TDR observations. These results suggest that the proposed method is promising for non-invasive characterization of the shallow subsurface hydraulic properties and monitoring water dynamics at the field scale. [ABSTRACT FROM PUBLISHER]

We used a new integrated modeling procedure for analyzing near-field ground-penetrating radar (GPR) and electromagnetic induction (EMI) data for reconstructing the electrical properties of multilayered media. Both GPR and EMI systems are set up using vector network analyzer technology and operate with the antennas on the ground or in near-field conditions. The antennas are modeled using a set of infinitesimal dipoles and characteristic, frequency-dependent, global reflection and transmission coefficients. Wave propagation and diffusion in the medium are described using a set of three-dimensional multilayered media Green's functions. GPR and EMI antennas were calibrated using measurements collected at different heights over water of know electrical conductivity. The GPR and EMI models were then validated for measurements collected over water subject to different salinity levels. The models showed a high degree of accuracy for reproducing the observed data and model inversion provided good estimates of the medium electrical properties, though discrepancies between measured and estimated water electrical conductivity values were observed in some cases due to a lack of sensitivity. The proposed approach is in particular promising for joint analysis of GPR and EMI data in an inverse data fusion framework, especially as the calibration and modeling procedures are identical for both instruments. [ABSTRACT FROM PUBLISHER]

A new near-field ground-penetrating antenna model was applied for characterization of soil moisture in an agricultural transect in central Belgium. The measurement system consists of a vector network analyzer connected with a horn antenna and a differential GPS mounted on a motorcycle for quick data acquisition. Numerical experiments show that near-field GPR data are more sensitive to the soil dielectric properties than far-field data due to nearer distance between the antenna and medium. For the field measurements, the modeled GPR data from far-field and near-field configurations agree very well with the measured ones. However, soil water content estimated from near-field data is higher and more in agreement with Theta Probe measurements than far-field owning to the deeper penetration depth, smaller foot print and larger sensitivity with soil permittivity of near-field data. The results also show that the spatial pattern of the soil moisture is mainly controlled by the topography, while temporal variability is influenced by the rainfall intensity and time lag between rainfall event and experiment. The proposed approach shows a promising potential for temporal and spatial characterization of soil moisture at the field scale. [ABSTRACT FROM PUBLISHER]

Characterization of the electrical properties of a medium using ground-penetrating radar (GPR) appeals to inverse modeling, which has remained a major challenge in applied geophysics in particular due to antenna modeling limitations. In this paper, we propose a new near-field radar modeling approach for wave propagation in layered media. Radar antennas are modeled using an equivalent set of infinitesimal electric dipoles and characteristic, frequency-dependent, global reflection and transmission coefficients. These coefficients determine, through a plane wave decomposition, wave propagation between the radar reference plane, point sources, and field points. The interactions between the antenna and the medium are thereby inherently accounted for. The fields are calculated using three-dimensional Green's functions. We validated the model using both time and frequency domain radars. The antennas were calibrated using measurements at different heights above a copper plane. The proposed model provided unprecedented results for describing near-field radar data collected over water, whose frequency-dependent electrical properties were described using the Debye model. Very good agreements were also obtained for measurements collected over water as validating medium for the inversions. The proposed modeling approach is fast and shows great promise for digital soil mapping or non-destructive material characterization. [ABSTRACT FROM PUBLISHER]