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

Geophysics ◽  
2021 ◽  
pp. 1-37
Author(s):  
Hirotaka Saito ◽  
Seiichiro Kuroda ◽  
Toshiki Iwasaki ◽  
Jacopo Sala ◽  
Haruyuki Fujimaki
Keyword(s):  
Antenna Array ◽  
Ground Penetrating Radar ◽  
Sand Dunes ◽  
Time Lapse ◽  
Sudden Increase ◽  
Wetting Front ◽  
Moisture Sensor ◽  
Wave Velocities ◽  
Ground Penetrating ◽  
Infiltration Experiment

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.

scholarly journals Multi-offset ground-penetrating radar imaging of a lab-scale infiltration test

2012 ◽  
Vol 16 (11) ◽  
pp. 4009-4022 ◽  
Author(s):  
A. R. Mangel ◽  
S. M. J. Moysey ◽  
J. C. Ryan ◽  
J. A. Tarbutton
Keyword(s):  
Water Content ◽  
Ground Penetrating Radar ◽  
Time Lapse ◽  
Volumetric Water Content ◽  
Data Cube ◽  
Sand Layer ◽  
Wetting Front ◽  
One Dimensional ◽  
Ground Penetrating ◽  
Infiltration Experiment

Abstract. A lab scale infiltration experiment was conducted in a sand tank to evaluate the use of time-lapse multi-offset ground-penetrating radar (GPR) data for monitoring dynamic hydrologic events in the vadose zone. Sets of 21 GPR traces at offsets between 0.44–0.9 m were recorded every 30 s during a 3 h infiltration experiment to produce a data cube that can be viewed as multi-offset gathers at unique times or common offset images, tracking changes in arrivals through time. Specifically, we investigated whether this data can be used to estimate changes in average soil water content during wetting and drying and to track the migration of the wetting front during an infiltration event. For the first problem we found that normal-moveout (NMO) analysis of the GPR reflection from the bottom of the sand layer provided water content estimates ranging between 0.10–0.30 volumetric water content, which underestimated the value determined by depth averaging a vertical array of six moisture probes by 0.03–0.05 volumetric water content. Relative errors in the estimated depth to the bottom of the 0.6 m thick sand layer were typically on the order of 2%, though increased as high as 25% as the wetting front approached the bottom of the tank. NMO analysis of the wetting front reflection during the infiltration event generally underestimated the depth of the front with discrepancies between GPR and moisture probe estimates approaching 0.15 m. The analysis also resulted in underestimates of water content in the wetted zone on the order of 0.06 volumetric water content and a wetting front velocity equal to about half the rate inferred from the probe measurements. In a parallel modeling effort we found that HYDRUS-1D also underestimates the observed average tank water content determined from the probes by approximately 0.01–0.03 volumetric water content, despite the fact that the model was calibrated to the probe data. This error suggests that the assumed conceptual model of laterally uniform, one-dimensional vertical flow in a homogenous material may not be fully appropriate for the experiment. Full-waveform modeling and subsequent NMO analysis of the simulated GPR response resulted in water content errors on the order of 0.01–0.03 volumetric water content, which are roughly 30–50% of the discrepancy between GPR and probe results observed in the experiment. The model shows that interference between wave arrivals affects data interpretation and the estimation of traveltimes. This is an important source of error in the NMO analysis, but it does not fully account for the discrepancies between GPR and the moisture probes observed in the experiment. The remaining discrepancy may be related to conceptual errors underlying the GPR analysis, such as the assumption of uniform one-dimensional flow, a lack of a sharply defined wetting front in the experiment, and errors in the petrophysical model used to convert dielectric constant to water content.

scholarly journals Multi-offset ground-penetrating radar imaging of a lab-scale infiltration test

2011 ◽  
Vol 8 (6) ◽  
pp. 10095-10123 ◽  
Author(s):  
A. R. Mangel ◽  
S. M. J. Moysey ◽  
J. C. Ryan ◽  
J. A. Tarbutton
Keyword(s):  
Water Content ◽  
Ground Penetrating Radar ◽  
Data Cube ◽  
Wetting Front ◽  
Hydrologic Processes ◽  
Infiltration Test ◽  
Relative Errors ◽  
Ground Penetrating ◽  
Discrete Moments ◽  
Infiltration Experiment

Abstract. A lab scale infiltration experiment was conducted to evaluate the use of transient multi-offset ground-penetrating radar (GPR) data for characterizing dynamic hydrologic events in the vadose zone. A unique GPR data acquisition setup allowed sets of 21 traces at different offsets to be recorded every 30 s during a 3 h infiltration experiment. The result is a rich GPR data cube that can be viewed as multi-offset gathers at discrete moments in time or as common offset images that track changes in the GPR arrivals over the course of the experiment. These data allows us to continuously resolve the depth to soil boundaries while simultaneously tracking changes in wave velocity, which are strongly associated with soil water content variations. During the experiment the average volumetric water content estimated in the tank ranged between 10–30% with discrepancies between the GPR results, moisture probe data, and 1-D numerical modeling on the order of 3–5% (vol vol−1), though the patterns of the estimated water content over time were consistent for both wetting and drying cycles. Relative errors in the estimated depth to a soil boundary located 60 cm from the surface of the tank were typically on the order of 2% over the course of the experiment. During the period when a wetting front migrated downward through the tank, however, errors in the estimated depth of this boundary were as high as 25%, primarily as a result of wave interference between arrivals associated with the wetting front and soil boundary. Given that our analysis assumed one-dimensional, vertical infiltration, this high error could also suggest that more exhaustive GPR data and comprehensive analysis methods are needed to accurately image non-uniform flow produced during periods of intense infiltration. Regardless, we were able to track the movement of the wetting front through the tank and found a reasonably good correlation with in-situ water content measurements. We conclude that transient multi-offset GPR data are capable of quantitatively monitoring dynamic soil hydrologic processes.

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

2021 ◽  
Author(s):  
Koki Oikawa ◽  
Hirotaka Saito ◽  
Seiichiro Kuroda ◽  
Kazunori Takahashi
Keyword(s):  
Wave Velocity ◽  
Convex Sets ◽  
Numerical Study ◽  
Sand Dunes ◽  
Time Lapse ◽  
Array Antenna ◽  
Velocity Analysis ◽  
Nmo Correction ◽  
Infiltration Experiment

<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>

scholarly journals Reflection tomography of time-lapse GPR data for studying dynamic unsaturated flow phenomena

2020 ◽  
Vol 24 (1) ◽  
pp. 159-167 ◽  
Author(s):  
Adam R. Mangel ◽  
Stephen M. J. Moysey ◽  
John Bradford
Keyword(s):  
Data Collection ◽  
Water Content ◽  
Unsaturated Flow ◽  
Time Lapse ◽  
New Method ◽  
Wetting Front ◽  
Empirical Estimates ◽  
Flow Phenomena ◽  
Ground Penetrating ◽  
Reflection Tomography

Abstract. Ground-penetrating radar (GPR) reflection tomography algorithms allow non-invasive monitoring of water content changes resulting from flow in the vadose zone. The approach requires multi-offset GPR data that are traditionally slow to collect. We automate GPR data collection to reduce the survey time significantly, thereby making this approach to hydrologic monitoring feasible. The method was evaluated using numerical simulations and laboratory experiments that suggest reflection tomography can provide water content estimates to within 5 % vol vol−1–10 % vol vol−1 for the synthetic studies, whereas the empirical estimates were typically within 5 %–15 % of measurements from in situ probes. Both studies show larger observed errors in water content near the periphery of the wetting front, beyond which additional reflectors were not present to provide data coverage. Overall, coupling automated GPR data collection with reflection tomography provides a new method for informing models of subsurface hydrologic processes and a new method for determining transient 2-D soil moisture distributions.

scholarly journals Quantitative high-resolution observations of soil water dynamics in a complicated architecture using time-lapse ground-penetrating radar

2015 ◽  
Vol 19 (3) ◽  
pp. 1125-1139 ◽  
Author(s):  
P. Klenk ◽  
S. Jaumann ◽  
K. Roth
Keyword(s):  
High Resolution ◽  
Water Content ◽  
Soil Water ◽  
Ground Penetrating Radar ◽  
Time Lapse ◽  
Test Site ◽  
Water Dynamics ◽  
Soil Water Dynamics ◽  
Capillary Fringe ◽  
Ground Penetrating

Abstract. High-resolution time-lapse ground-penetrating radar (GPR) observations of advancing and retreating water tables can yield a wealth of information about near-surface water content dynamics. In this study, we present and analyze a series of imbibition, drainage and infiltration experiments that have been carried out at our artificial ASSESS test site and observed with surface-based GPR. The test site features a complicated but known subsurface architecture constructed with three different kinds of sand. It allows the study of soil water dynamics with GPR under a wide range of different conditions. Here, we assess in particular (i) the feasibility of monitoring the dynamic shape of the capillary fringe reflection and (ii) the relative precision of monitoring soil water dynamics averaged over the whole vertical extent by evaluating the bottom reflection. The phenomenology of the GPR response of a dynamically changing capillary fringe is developed from a soil physical point of view. We then explain experimentally observed phenomena based on numerical simulations of both the water content dynamics and the expected GPR response.

scholarly journals Detecting infiltrated water and preferential flow pathways through time-lapse ground-penetrating radar surveys

2020 ◽  
Vol 726 ◽  
pp. 138511 ◽  
Author(s):  
Simone Di Prima ◽  
Thierry Winiarski ◽  
Rafael Angulo-Jaramillo ◽  
Ryan D. Stewart ◽  
Mirko Castellini ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Preferential Flow ◽  
Time Lapse ◽  
Flow Pathways ◽  
Preferential Flow Pathways ◽  
Ground Penetrating

scholarly journals UWB Vivaldi Antenna Array Lower Band Improvement for Ground Penetrating Radar Applications

2019 ◽  
Vol 27 (1) ◽  
pp. 92-98 ◽  
Author(s):  
M. Biancheri-Astier ◽  
A. Diet ◽  
Y. le Bihan ◽  
M. Grzeskowiak
Keyword(s):  
Antenna Array ◽  
Ground Penetrating Radar ◽  
Lower Band ◽  
Radar Applications ◽  
Vivaldi Antenna ◽  
Ground Penetrating
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