Electromagnetic Inversion of GPR Signals and Subsequent Hydrodynamic Inversion to Estimate Effective Vadose Zone Hydraulic Properties

Lambot, Sébastien; Antoine, Michaël; Bosch, I. van den; Slob, Evert; Vanclooster, Marnik

doi:10.2113/3.4.1072

Cited by 49 publications

(34 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both phase and amplitude information is inherently used for model inversion, thereby maximizing information retrieval from the available radar data, both in terms of quantity and quality. The technique has been successfully validated in a series of hydrogeophysical applications (Lambot et al, 2004a(Lambot et al, , b, 2005(Lambot et al, , 2006a. Recently, we integrated the method with hydrodynamic modeling to retrieve the soil hydraulic properties from otherwise (Lopera et al, 2007a, b).…”

Section: The Model Includes Internal Antenna and Antenna-soil Interacmentioning

confidence: 99%

“…In (Lambot et al, 2004a), we applied that GPR approach to monitor water content as a function of time and depth during a free drainage event in a 2-m high laboratory sand column (see Figure 6). The sand column was also equipped for this specific inverse problem, and the stability of the inverse solution with respect to actual modeling and measurement errors.…”

Section: Model Validation and Applicationsmentioning

confidence: 99%

“…Figure 6. GPR monitoring of water content as a function of time at two different depths of a laboratory lysimeter subject to free drainage (Lambot et al, 2004a). Markers represent GPRderived soil moisture at two different depths and solid lines represent modeled moisture time series using hydrodynamic modeling.…”

Section: Model Validation and Applicationsmentioning

confidence: 99%

See 2 more Smart Citations

Soil Chemical Pollution, Risk Assessment, Remediation and Security

Simeonov¹,

Sargsyan²

2008

NATO Science for Peace and Security Series C: Environmental Security

View full text Add to dashboard Cite

Plant ecophysiology Effects of pollutants (ozone, UV-B, metals, acidic deposition, and surfactants)and climate change (drought, frost) on forests and trees (gas exchange, water relations, cuticles, roots, ectomycorrhizas, growth and pollen) biomonitoring, moss biomonitoring, raptor biomonitoring, heavy metal contamination, cellular localization of metals, hydrological fluxes of forest canopies. expertise in sustainable development, particularly in the following areas: environmental services, ecology and biogeochemistry of ecosystems and agroecosystems, bioenergy, biofuels, biochar, remote sensing, and electron microscopy applied to nanotechnology, electronics and automation, climate change adaptation and mitigation of greenhouse gases emissions.

show abstract

Section: The Model Includes Internal Antenna and Antenna-soil Interacmentioning

confidence: 99%

Section: Model Validation and Applicationsmentioning

confidence: 99%

See 1 more Smart Citation

Soil Chemical Pollution, Risk Assessment, Remediation and Security

Simeonov¹,

Sargsyan²

2008

NATO Science for Peace and Security Series C: Environmental Security

View full text Add to dashboard Cite

show abstract

“…Sequentially coupling a globally convergent search algorithm, e.g., the global multilevel coordinate search algorithm (GMCS, Huyer and Neumaier, 1999) with the gradient-free locally convergent Nelder-Mead simplex algorithm (NMS, Nelder and Mead, 1965), was successfully applied to estimate hydraulic material properties from GPR measurements (e.g., Lambot et al, 2004;Busch et al, 2012;Moghadas et al, 2014). The NMS was further developed to the shuffled complex evolution (SCE-UA, Duan et al, 1992) which has become a standard tool in hydrology and was also applied on GPR measurements (e.g., Jadoon et al, 2012;Léger et al, 2014Léger et al, , 2015.…”

Section: Introductionmentioning

confidence: 99%

Soil hydraulic material properties and layered architecture from time-lapse GPR

Jaumann

Roth

2018

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Quantitative knowledge of the subsurface material distribution and its effective soil hydraulic material properties is essential to predict soil water movement. Groundpenetrating radar (GPR) is a noninvasive and nondestructive geophysical measurement method that is suitable to monitor hydraulic processes. Previous studies showed that the GPR signal from a fluctuating groundwater table is sensitive to the soil water characteristic and the hydraulic conductivity function. In this work, we show that the GPR signal originating from both the subsurface architecture and the fluctuating groundwater table is suitable to estimate the position of layers within the subsurface architecture together with the associated effective soil hydraulic material properties with inversion methods. To that end, we parameterize the subsurface architecture, solve the Richards equation, convert the resulting water content to relative permittivity with the complex refractive index model (CRIM), and solve Maxwell's equations numerically. In order to analyze the GPR signal, we implemented a new heuristic algorithm that detects relevant signals in the radargram (events) and extracts the corresponding signal travel time and amplitude. This algorithm is applied to simulated as well as measured radargrams and the detected events are associated automatically. Using events instead of the full wave regularizes the inversion focussing on the relevant measurement signal. For optimization, we use a global-local approach with preconditioning. Starting from an ensemble of initial parameter sets drawn with a Latin hypercube algorithm, we sequentially couple a simulated annealing algorithm with a Levenberg-Marquardt algorithm. The method is applied to synthetic as well as measured data from the ASSESS test site. We show that the method yields reasonable estimates for the position of the layers as well as for the soil hydraulic material properties by comparing the results to references derived from ground truth data as well as from time domain reflectometry (TDR).

show abstract

“…This includes internal antenna and antenna-soil interaction propagation effects through frequency dependent, complex scalar transfer functions and solves exactly the three-dimensional (3-D) Maxwell's equations for wave propagation in multilayered media. The proposed method was validated in laboratory conditions for identifying both the dielectric permittivity and electrical conductivity of a sandy soil subject to a range of water contents [7], to monitor the dynamics of water in a laboratory sand column and subsequently derive the soil hydraulic properties using hydrodynamic inverse modeling [8], to map the soil surface water content in field conditions [9], [10], and to estimate soil hydraulic properties from integrated hydrogeophysical inversion of time-lapse off-ground GPR data [11], [12].The exact location of the phase center of double ridged horns depends on the dimensions of the horn, specially on its flare angle and tapper, and on the frequencies of operation. Significant variation can be observed in the phase center with frequency, when the pattern angles extend across the main beam [3].…”

mentioning

confidence: 99%

Investigation of the frequency dependent antenna transfer functions and phase center position for modeling off-ground GPR

Jadoon

Lambot

Slob

et al. 2010

Proceedings of the XIII Internarional Conference on Ground Penetrating Radar

View full text Add to dashboard Cite

maximizing information retrieval from a single GPR measurement. Both phase (travel time) and amplitude information are inherently exploited. The technique relies on an accurate and computationally effective radar forward model. This includes internal antenna and antenna-soil interaction propagation effects through frequency dependent, complex scalar transfer functions and solves exactly the three-dimensional (3-D) Maxwell's equations for wave propagation in multilayered media. The proposed method was validated in laboratory conditions for identifying both the dielectric permittivity and electrical conductivity of a sandy soil subject to a range of water contents [7], to monitor the dynamics of water in a laboratory sand column and subsequently derive the soil hydraulic properties using hydrodynamic inverse modeling [8], to map the soil surface water content in field conditions [9], [10], and to estimate soil hydraulic properties from integrated hydrogeophysical inversion of time-lapse off-ground GPR data [11], [12].The exact location of the phase center of double ridged horns depends on the dimensions of the horn, specially on its flare angle and tapper, and on the frequencies of operation. Significant variation can be observed in the phase center with frequency, when the pattern angles extend across the main beam [3]. For large flare angles and/or high frequencies the phase center is closer to the apex and for small flare angles and/or low frequencies, the phase center moves toward the aperture of the horn [2]. Historically, the work of Walton et al.[13] on the double-ridged horn was important, and it is still used today for the design of these horns. Such horn antennas have recently been analyzed numerically [14]- [17], but the effect of frequency on the phase center position has not been quantified in these studies. Antenna analysis is nevertheless necessary for precise measurements of the source point above the ground and correctly parameterize the forward electromagnetic radar model.In this paper, we compared different methods for estimating the double ridged horn antenna phase center, namely, by extrapolation of peak-to-peak reflection values in the time domain (ψ c ) and by frequency-domain full-waveform inversion assuming frequency dependent phase centers (ψ c ( f )). For Abstract-We compared different methods to estimate the phase center of an ultra wideband ground penetrating radar (GPR) horn antenna operating off-ground, namely, (1) extrapolation of peak-to-peak reflection values in the time domain and assuming a fixed phase center, and (2), frequency-domain full-waveform inversion assuming a frequency dependent phase center. For that purpose, we performed radar measurements at different heights above a perfect electrical conductor (PEC). A double ridged horn antenna operating in the frequency range 0.8 -5.2 GHz was used. In the limits of the antenna geometry, we observed that antenna modeling results were not significantly affected by the position of the phase center, even when considering frequency d...

show abstract

Electromagnetic Inversion of GPR Signals and Subsequent Hydrodynamic Inversion to Estimate Effective Vadose Zone Hydraulic Properties

Cited by 49 publications

References 53 publications

Soil Chemical Pollution, Risk Assessment, Remediation and Security

Soil Chemical Pollution, Risk Assessment, Remediation and Security

Soil hydraulic material properties and layered architecture from time-lapse GPR

Investigation of the frequency dependent antenna transfer functions and phase center position for modeling off-ground GPR

Contact Info

Product

Resources

About