Estimating infiltration front depth using time-lapse multioffset gathers obtained from ground-penetrating-radar antenna array

Non-destructive and non-invasive visualization and quantification of dynamic subsurface hydrological processes are needed. Using a ground penetrating radar (GPR) antenna array, time-lapse common-offset gather (COG) and common mid-point (CMP) data can be collected by fixing the antenna at a given location when scanning subsurface. This study aims to determine wetting front depths continuously during a field infiltration experiment by estimating electromagnetic (EM) wave velocities at given elapsed times using ground penetrating radar (GPR) antenna array data. A surface GPR antenna array system, consisting of 10 transmitters (Tx) and 11 receivers (Rx), that can scan each Tx-Rx combination in 10 s at a millisecond scale was used to acquire all 110 Rx-Tx combinations in approximately 1.5 s. The field infiltration experiment was conducted at an experimental field near the Tottori Sand Dunes in Japan. Using the estimated EM wave velocity from the CMP data, the depth to the wetting front was computed every minute. The estimated wetting front arrival time agreed with the time at which a sudden increase in the moisture sensor output was observed at a depth from 20 cm and below. This study demonstrated that time-lapsed CMP data collected with the GPR antenna array system could be used to estimate EM wave velocities continuously during the infiltration. The GPR antenna array was capable of accurate and quantitative tracking of the wetting front.

Determining optimum wave velocity from sparse CMP automatically by coupling POCS interpolation and NMO correction: application to array antenna GPR data collected during in-situ infiltration test

<p>As an array antenna ground penetrating radar (GPR) system electronically switches any antenna combinations sequentially in milliseconds, multi-offset gather data, such as common mid-point (CMP) data, can be acquired almost seamlessly. However, due to the inflexibility of changing the antenna offset, only a limited number of scans can be obtained. The array GPR system has been used to collect time-lapse GPR data, including CMP data during the field infiltration experiment (Iwasaki et al., 2016). CMP data obtained by the array GPR are, however, too sparse to obtain reliable velocity using a standard velocity analysis, such as semblance analysis. We attempted to interpolate the sparse CMP data based on projection onto convex sets (POCS) algorithm (Yi et al., 2016) coupled with NMO correction to automatically determine optimum EM wave velocity. Our previous numerical study showed that the proposed method allows us to determine the EM wave velocity during the infiltration experiment.</p><p>The main objective of this study was to evaluate the performance of the proposed method to interpolate sparse array antenna GPR CMP data collected during the in-situ infiltration experiment at Tottori sand dunes. The interpolated CMP data were then used in the semblance analysis to determine the EM wave velocity, which was further used to compute the infiltration front depth. The estimated infiltration depths agreed well with independently obtained depths. This study demonstrated the possibility of developing an automatic velocity analysis based on POCS interpolation coupled with NMO correction for sparse CMP collected with array antenna GPR.</p>

Estimate of hydrodynamic parameters with a coupled hydrogeophysical inversion using GPR surveys

<p>We develop a methodology to estimate soil hydrodynamic parameters from a water infiltration experiment monitored with a GPR (Ground Penetrating Radar). Such an experiment, carried out on both controlled and natural site, consists in applying a water charge in a tank on the soil surface. During the water infiltration, the water layer thickness above the soil surface in the tank and the GPR response on the infiltration water front are monitored. The infiltration experiment is then modelled numerically using hydrogeological parameters which describe the constitutive relationships between water content, pressure and hydraulic conductivity. In that goal, we use the WAMOS-1D code which combines the 1D Richards equation and the Mualem – van Genuchten model. From the hydrogeological models outputs and petrophysical relationships, corresponding GPR velocity models are created to generate the resulting GPR signals. Then, an inversion algorithm couples both the hydrogeological and the geophysical models to seek the optimal hydrodynamic parameters. The inverse problem objective function is calculated from the estimated arrival time of the GPR waves reflected by the water infiltration front and compared to the measured ones. Preliminary inversion tests explore the hydrodynamic parameters space using synthetic data. First results show that the saturated hydraulic conductivity parameter can be estimated. Further tests are performed to improve both our experimental set-up and methodology and allow an estimation of the other hydrodynamic parameters. An emerging idea is to complete the objective function by analyzing the arrival time corresponding to additional reflectors to the water infiltration front.</p>

Using GPR surveys and infiltration experiments for assessing soil physical quality of an agricultural soil

<p>Time-lapse ground penetrating radar (GPR) surveys in conjunction with automated single-ring infiltration experiments can be used for non-invasive monitoring of the spatial distribution of infiltrated water and for generating 3D representations of the wetted zone. In this study we developed and tested a protocol to quantify and visualize water distribution fluxes under unsaturated and saturated conditions into layered soils. We carried out a gridded GPR survey on a 0.3-m thick sandy clay loam layer underlain by a restrictive limestone layer at the Ottava experimental station of the University of Sassari (Sardinia, IT). We firstly established a survey grid (1 m × 1 m), consisting of six horizontal and six vertical parallel survey lines with 0.2 m intervals between them. The field survey then consisted of six steps, including <strong>i)</strong> a first GPR survey, <strong>ii)</strong> a tension infiltration experiment conducted within the grid and aimed at activating only the soil matrix, <strong>iii)</strong> a second GPR survey aimed at highlighting the amplitude fluctuations between repeated GPR radargrams of the first and second surveys, due to the infiltrated water moving within the matrix flow region, <strong>iv)</strong> a single-ring infiltration experiment of the Beerkan type carried out within the grid on the same infiltration surface using a solution of brilliant blue dye (E133) and aimed to activate the whole pore network, <strong>v)</strong> a third GPR survey aimed to highlight the amplitude fluctuations between repeated GPR radargrams of the first and third surveys, due to the infiltrated water moving within the whole pore network (both matrix and fast-flow regions), and <strong>vi)</strong> the excavation of the soil to expose the wetted region. The shapes of the 3D diagrams of the wetted zones facilitated the interpretation of the infiltrometer data, allowing us to resolve water infiltration into the layered system. Finally, we used the infiltrometer data in conjunction with the Beerkan estimation of soil transfer parameter (BEST) method to determine the following capacitive indicators of soil physical quality of the upper soil layer: air capacity <em>AC</em> (m<sup>3</sup> m<sup>–3</sup>), plant-available water capacity <em>PAWC</em> (m<sup>3</sup> m<sup>–3</sup>), relative field capacity <em>RFC</em> (–), and soil macroporosity <em>p<sub>MAC</sub></em> (m<sup>3</sup> m<sup>–3</sup>). Results showed that the investigated soil was characterized by high soil aeration and macroporosity (i.e., <em>AC</em> and <em>p<sub>MAC</sub></em>) along with low values for indicators associated with microporosity (i.e., <em>PAWC</em> and <em>RFC</em>). These findings suggest that the upper soil layer facilitates root proliferation and quickly drains excess water towards the underlying limestone layer, and, on the contrary, has limited ability to store and provide water to plant roots. In addition, the 3D diagram allowed the detection of non-uniform downward water movement through the restrictive limestone layer. The detected difference between the two layers in terms of hydraulic conductivity suggests that surface ponding and overland flow generation occurs via a saturation-excess mechanism. Indeed, percolating water may accumulate above the restrictive limestone layer and form a shallow perched water table that, in case of extreme rainfall events, could rise causing the complete saturation of the soil profile.</p>

NUMERICAL SIMULATION OF A SINGLE RING INFILTRATION EXPERIMENT WITH hp-ADAPTIVE SPACE-TIME DISCONTINUOUS GALERKIN METHOD

We present a novel hp-adaptive space-time discontinuous Galerkin (hp-STDG) method for the numerical solution of the nonstationary Richards equation equipped with Dirichlet, Neumann and seepage face boundary conditions. The hp-STDG method presented in this paper is a generalization of a hp-STDG method which was developed for time dependent non-linear convective-diffusive problems. We describe the method and the single ring experiment, and then we present a numerical experiment which clearly demonstrates the superiority of the hp-STDG method over a discontinuous Galerkin method based on a static fine mesh.

Time-Lapse Seismic and Electrical Monitoring of the Vadose Zone during a Controlled Infiltration Experiment at the Ploemeur Hydrological Observatory, France

The vadose zone is the main host of surface and subsurface water exchange and has important implications for ecosystems functioning, climate sciences, geotechnical engineering, and water availability issues. Geophysics provides a means for investigating the subsurface in a non-invasive way and at larger spatial scales than conventional hydrological sensors. Time-lapse hydrogeophysical applications are especially useful for monitoring flow and water content dynamics. Largely dominated by electrical and electromagnetic methods, such applications increasingly rely on seismic methods as a complementary approach to describe the structure and behavior of the vadose zone. To further explore the applicability of active seismics to retrieve quantitative information about dynamic processes in near-surface time-lapse settings, we designed a controlled water infiltration experiment at the Ploemeur Hydrological Observatory (France) during which successive periods of infiltration were followed by surface-based seismic and electrical resistivity acquisitions. Water content was monitored throughout the experiment by means of sensors at different depths to relate the derived seismic and electrical properties to water saturation changes. We observe comparable trends in the electrical and seismic responses during the experiment, highlighting the utility of the seismic method to monitor hydrological processes and unsaturated flow. Moreover, petrophysical relationships seem promising in providing quantitative results.