Soil surface water content estimation by full-waveform GPR signal inversion in the presence of thin layers

We analyzed the effect of shallow thin layers on the estimation of soil surface water content using full-waveform inversion of off-ground ground penetrating radar (GPR) data. Strong dielectric contrasts are expected to occur under fast wetting or drying weather conditions, thereby leading to constructive and destructive interferences with respect to the surface reflection. First, synthetic GPR data were generated and subsequently inverted considering different thin-layer model configurations. The resulting inversion errors when neglecting the thin layer were quantified, and then, the possibility to reconstruct these layers was investigated. Second, laboratory experiments reproducing some of the numerical experiments configurations were conducted to assess the stability of the inverse solution with respect to actual measurement and modeling errors. Results showed that neglecting shallow thin layers may lead to significant errors on the estimation of soil surface water content ($\Delta\theta$ > 0.03 $m^3/m^3$), depending on the contrast. Accounting for these layers in the inversion process strongly improved the results, although some optimization issues were encountered. In the laboratory, the proposed full-waveform method permitted to reconstruct thin layers with a high resolution up to 2 cm and to retrieve the soil surface water content with an rmse less than 0.02 $m^3/m^3$, owing to the full-waveform inverse modeling. These results suggest that the proposed GPR approach is promising for field-scale mapping of soil surface water content of nondispersive soils with low electrical conductivity and for instances when soil layering is encountered

Effects of the Conductivity/Permittivity Ratio on the Dispersion and Attenuation of Radar Signals

Introduction In modelling and processing of Ground Penetrating Radar (GPR) data, the distortion of the radar signal as it propagates through the ground is often neglected, see e.g. Davis and Annan, 1989. In the frequency range of interest for GPR applications, 10 MHz to 1 GHz, the loss mechanism in the ground is usually described by an exponential damping factor along the path of propagation. To study the transmission effects of GPR signals through the earth, we have modelled the response of 2D homogeneous media. The study is specifically aimed at determining the amount of distortion of transient radar-type signals in conductive media. Calculations are performed in the space-time domain for an analytic source-wavelet and models which vary in the electric permittivity (") and conductivity (oe). The Electric Wavefield For a two-dimensional setup, Maxwell's equations can be combined to a Helmholtz equation for the electric field i

Quasi-analytical method for frequency-to-time conversion in CSEM applications

Frequency-to-time transformations are of interest to controlled-source electromagnetic methods when time-domain data are inverted for a subsurface resistivity model by numerical frequency-domain modeling at a selected, small number of frequencies whereas the data misfit is determined in the time domain. We propose an efficient, Prony-type method using frequency-domain diffusive-field basis functions for which the time-domain equivalents are known. Diffusive fields are characterized by an exponential part whose argument is proportional to the square root of frequency and a part that is polynomial in integer powers of the square root of frequency. Data at a limited number of frequencies suffice for the transformation back to the time. In the exponential part, several diffusion-time values must be chosen. Once a suitable range of diffusion-time values are found, the method is quite robust in the number of values used. The highest power in the polynomial part can be determined from the source and receiver type. When the frequency-domain data are accurately approximated by the basis functions, the timedomain result is also accurate. This method is accurate over a wider time range than other methods and has the correct late-time asymptotic behavior. The method works well for data computed for layered and 3D subsurface models.Geoscience & TechnologyCivil Engineering and Geoscience

Filtering soil surface and antenna effects from GPR data to enhance landmine detection

The detection of antipersonnel landmines using ground-penetrating radar (GPR) is particularly hindered by the predominant soil surface and antenna reflections. In this paper, we propose a novel approach to filter out these effects from 2-D off-ground monostatic GPR data by adapting and combining the radar antenna subsurface model of Lambot et al. with phase-shift migration. First, the antenna multiple reflections originating from the antenna itself and from the interaction between the antenna and the ground are removed using linear transfer functions. Second, a simulated Green's function accounting for the surface reflection is subtracted. The Green's function is derived from the estimated soil surface dielectric permittivity using full-wave inversion of the radar signal for a measurement taken in a local landmine-free area. Third, off-ground phase-shift migration is performed on the 2-D data to filter the effect of the antenna radiation pattern. We validate the approach in laboratory conditions for four differently detectable landmines embedded in a sandy soil. Compared to traditional background subtraction, this new filtering method permits a better differentiation of the landmine and estimation of its depth and geometrical properties. This is particularly beneficial for the detection of landmines in low-contrast conditions

Non-invasive estimation of moisture content in tuff bricks by GPR

Measuring water content in buildings of historical value requires non-invasive techniques to avoid the damage that sample taking or probe insertion may cause to the investigated walls. With this aim, a stepped frequency ground penetrating radar (GPR) system was tested to assess its applicability in moisture measurements of porous masonry elements. The technique was tested on a real scale wall made with yellow Neapolitan tuff bricks, a material commonly found in historical buildings of Campania (Southern Italy). First, the antenna was calibrated to find its characteristic transfer functions. Then 64 GPR acquisitions, coupled with gravimetric measurements of the volumetric water content, were performed on the tuff wall in laboratory controlled conditions. A full inverse modelling of the GPR signal on tuff was used to retrieve dielectric permittivity and electrical conductivity of tuff at various water contents. By linking these characteristic electromagnetic parameters to the water content, the calibration relationships specific for yellow Neapolitan tuff are defined, which can be used for moisture measurements by GPR in real case studies. The experimental results lead to a robust identification of clearly defined monotonic relationships for dielectric permittivity and electrical conductivity. These are characterized by high values of the correlation coefficient, indicating that both parameters are potentially good proxies for water content of tuff. The results indicate that GPR represents a promising indirect technique for reliable measurements of water content in tuff walls and, potentially, in other porous building materials