Site characterization at the Groundwater Remediation Field Laboratory

Clement, William P.; Cardimona, Steven; Endres, Anthony L.; Kadinsky‐Cade, Katharine

doi:10.1190/1.1437538

Cited by 12 publications

(7 citation statements)

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“…It is generally assumed that variations in dielectric constant at vertical spacings of less than l/4-l/3 will not be individually resolved (Annan et al, 1991;Huggenberger, 1993). However, layers thinner than l/4 have been resolved on GPR profiles where the reflection coefficient is large (Clement et al, 1997;Van Dam et al, 2003). Chan and Knight (2001) proposed two different methods to determine the depth-averaged vertical variation in k depending on the ratio of layer thickness (t) to signal wavelength (l).…”

Section: Gpr Backgroundmentioning

confidence: 98%

Soil moisture content estimation using ground-penetrating radar reflection data

Lunt

Hubbard

Rubin

2005

Journal of Hydrology

272

144

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Section: Gpr Backgroundmentioning

confidence: 98%

Soil moisture content estimation using ground-penetrating radar reflection data

Lunt

Hubbard

Rubin

2005

Journal of Hydrology

272

144

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“…After crosscorrelation, however, the vibrator data are nominally zero phase, and events correspond to the peak in the reflection wavelets. The seismic event at ∼42 ms (e.g., Figure 5, south end) and the 225-ns reflection (e.g., Figure 5, south end) in the radar profiles correspond to a depth of ∼12 m. Seismic refraction data indicate a velocity increase at a depth of 8 m (Clement et al, 1997), corresponding to the water table in the monitoring well at the GRFL. However, high-frequency (50, 100, and 200 MHz) PEIV radar profiles do not record a water table reflection across the survey area (Clement et al, 1997).…”

Section: Resultsmentioning

confidence: 93%

Seismic reflection and ground‐penetrating radar imaging of a shallow aquifer

1998

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In 1995 and 1996, researchers associated with the US Air Force's Phillips and Armstrong Laboratories took part in an extensive geophysical site characterization of the Groundwater Remediation Field Laboratory located at Dover Air Force Base, Dover, Delaware. This field experiment offered an opportunity to compare shallowreflection profiling using seismic compressional sources and low-frequency ground-penetrating radar to image a shallow, unconfined aquifer. The main target within the aquifer was the sand-clay interface defining the top of the underlying aquitard at 10 to 14 m depth. Although the water table in a well near the site was 8 m deep, cone penetration geotechnical data taken across the field do not reveal a distinct water table. Instead, cone penetration tests show a gradual change in electrical properties that we interpret as a thick zone of partial saturation. Comparing the seismic and radar data and using the geotechnical data as ground truth, we have associated the deepest coherent event in both reflection data sets with the sand-clay aquitard boundary. Cone penetrometer data show the presence of a thin lens of clays and silts at about 4 m depth in the north part of the field. This shallow clay is not imaged clearly in the low-frequency radar profiles. However, the seismic data do image the clay lens. Cone penetrometer data detail a clear change in the soil classification related to the underlying clay aquitard at the same position where the nonintrusive geophysical measurements show a change in image character. Corresponding features in the seismic and radar images are similar along profiles from common survey lines, and results of joint interpretation are consistent with information from geotechnical data across the site. Presented at the 66th Annual International Meeting, Society of Exploration Geophysicists, as Coincident ground-penetrating radar and seismic imaging of an aquitard boundary. Manuscript

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“…Similar tools to measure ϵ r in situ in soils have been presented by, for example, Shinn et al [1998], Vaz and Hopmans [2001], and Lin et al [2006]. Studies linking DP ϵ r log analysis to GPR data interpretation include, for example, Clement et al [1997], Majer et al [2001], and Schmelzbach et al [2011b].…”

Section: Introductionmentioning

confidence: 94%

High‐resolution water content estimation from surface‐based ground‐penetrating radar reflection data by impedance inversion

Schmelzbach

Tronicke

Dietrich

2012

Water Resources Research

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1] Mapping hydrological parameter distributions in high resolution is essential to understand and simulate groundwater flow and contaminant transport. Of particular interest is surface-based ground-penetrating radar (GPR) reflection imaging in electrically resistive sediments because of the expected close link between the subsurface water content and the dielectric permittivity, which controls GPR wave velocity and reflectivity. Conventional tools like common midpoint (CMP) velocity analysis provide physical parameter models of limited resolution only. We present a novel reflection amplitude inversion workflow for surface-based GPR data capable of resolving the subsurface dielectric permittivity and related water content distribution with markedly improved resolution. Our scheme is an adaptation of a seismic reflection impedance inversion scheme to surface-based GPR data. Key is relative-amplitude-preserving data preconditioning including GPR deconvolution, which results in traces with the source-wavelet distortions and propagation effects largely removed. The subsequent inversion for the underlying dielectric permittivity and water content structure is constrained by in situ dielectric permittivity data obtained by direct-push logging. After demonstrating the potential of our novel scheme on a realistic synthetic data set, we apply it to two 2-D 100 MHz GPR profiles acquired over a shallow sedimentary aquifer resulting in water content images of the shallow (3-7 m depth) saturated zone having decimeter resolution.Citation: Schmelzbach, C., J. Tronicke, and P. Dietrich (2012), High-resolution water content estimation from surface-based ground-penetrating radar reflection data by impedance inversion, Water Resour. Res., 48, W08505,

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Site characterization at the Groundwater Remediation Field Laboratory

Cited by 12 publications

References 0 publications

Soil moisture content estimation using ground-penetrating radar reflection data

Soil moisture content estimation using ground-penetrating radar reflection data

Seismic reflection and ground‐penetrating radar imaging of a shallow aquifer

High‐resolution water content estimation from surface‐based ground‐penetrating radar reflection data by impedance inversion

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