Ground-penetrating Radar Reflection Data Research Articles

Reconstruction of Holocene relative sea-level from beach ridges of the central west coast of India using GPR and OSL dating

The Holocene sea-level and associated shoreline regression of beach ridges in the central west coast of India have been reconstructed based on internal sedimentary architecture and luminescence chronology. For this purpose, various techniques namely ground penetrating radar (GPR), optically-stimulated luminescence (OSL) dating, and interferometry synthetic aperture radar (InSAR) have been used. The berm and beach-dune boundary of paleo beach ridges have been mapped from the high-resolution sub-surface images and converted into sea-level indicators using modern analogs and OSL ages. GPR reflection data shows a number of seaward dipping radar facies with a few landward dipping facies in paleo beach ridges. In the case of the swale, radar signal has been highly attenuated due to the presence of water and mud causing the appearance of multiple horizontal and parallel positive and negative couplets in the sedimentary layer. The results of the research reveal that the oldest beach ridge was formed around 7.7 kyr BP and sea-level was +2 m above mean sea-level. The average progradation rate of these ridges is 0.14 m/yr. From the grain size analysis, it has been found that the larger share of grain size falls into the classes of fine and moderate sand. The present displacement map of the region, which has been generated from the Sentinel-1 datasets, demonstrates that the average upliftment is 2.5 mm/yr whereas subsidence is 1 mm/yr. The fall of the Holocene relative sea-level with respect to the study region is the consequence of both global and regional events.

Structurally constrained inversion by means of a Minimum Gradient Support regularizer: examples of FD-EMI data inversion constrained by GPR reflection data

SUMMARYMany geophysical inverse problems are known to be ill-posed and, thus, requiring some kind of regularization in order to provide a unique and stable solution. A possible approach to overcome the inversion ill-posedness consists in constraining the position of the model interfaces. For a grid-based parameterization, such a structurally constrained inversion can be implemented by adopting the usual smooth regularization scheme in which the local weight of the regularization is reduced where an interface is expected. By doing so, sharp contrasts are promoted at interface locations while standard smoothness constraints keep affecting the other regions of the model. In this work, we present a structurally constrained approach and test it on the inversion of frequency-domain electromagnetic induction (FD-EMI) data using a regularization approach based on the Minimum Gradient Support stabilizer, which is capable to promote sharp transitions everywhere in the model, i.e., also in areas where no structural a prioriinformation is available. Using 1D and 2D synthetic data examples, we compare the proposed approach to a structurally constrained smooth inversion as well as to more standard (i.e., not structurally constrained) smooth and sharp inversions. Our results demonstrate that the proposed approach helps in finding a better and more reliable reconstruction of the subsurface electrical conductivity distribution, including its structural characteristics. Furthermore, we demonstrate that it allows to promote sharp parameter variations in areas where no structural information are available. Lastly, we apply our structurally constrained scheme to FD-EMI field data collected at a field site in Eastern Germany to image the thickness of peat deposits along two selected profiles. In this field example, we use collocated constant offset ground-penetrating radar (GPR) data to derive structural a priori information to constrain the inversion of the FD-EMI data. The results of this case study demonstrate the effectiveness and flexibility of the proposed approach.

Weighted Diffraction-Based Migration Velocity Analysis of Common-Offset GPR Reflection Data

Migration focusing analysis of diffractions is an increasingly important tool for estimating the large-scale subsurface velocity structure from surface-based common-offset ground-penetrating radar (GPR) reflection data. We present a weighting strategy, whose aim is to improve the reliability of estimations of the root-mean-square (rms) velocity obtained using a local semblance focusing measure. In this regard, we increase the resolution of the inferred semblance spectra through a weighting function that varies in accordance with the sensitivity of a diffraction curve to changes in velocity. The weighting function is derived from coherency and slope attributes of the diffracted wavefield components. To demonstrate the viability of our proposed method, we consider its application in two synthetic test cases and one field GPR dataset. Compared with conventional unweighted local semblance spectra, their weighted counterparts allow for a significantly increased resolution and correspondingly reduced picking uncertainty.

Estimating porosity distribution of a heterogeneous alluvial aquifer by GPU-accelerated 3D conditional stochastic inversion of common-offset GPR reflection data

Three-dimensional (3D) high-resolution and accurate characterization of the heterogeneity in an alluvial aquifer is critical to predicting the groundwater flow and contaminant transport. In this study, we extend the previous 2D conditional stochastic inversion method with respect to common-offset ground-penetrating radar (GPR) data to 3D for the estimation of 3D porosity distribution in a heterogeneous alluvial aquifer. First, 3D stochastic realizations of subsurface properties can be obtained using the fast Fourier transform moving average (FFT-MA) method, and the realizations are conditioned to borehole porosity measurements available in the 3D survey area, as well as to the geostatistical parameters derived from the borehole logs and the processed 3D GPR data. Next, the realizations are constantly modified and regenerated via a localized simulated annealing optimization strategy, which ultimately makes their corresponding synthetic data offer an acceptable fit to the GPR data. To accelerate the computational speed of 3D inversion, we design and implement the multi-GPUs multi-node parallelization of the 3D conditional stochastic inversion algorithm. The proposed 3D inversion algorithm is positively verified through the application to field GPR data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA. Our results indicate that the proposed 3D inversion method has the potential to effectively recover the fine-scale porosity distribution of a heterogeneous alluvial aquifer.

High-resolution velocity estimation from surface-based common-offset GPR reflection data

SUMMARY Surface-based common-offset ground-penetrating radar (GPR) reflection profiling is a popular geophysical exploration technique for obtaining high-resolution images of the shallow subsurface in a cost-effective manner. One drawback of this technique is that, without complementary borehole information in form of dielectric permittivity and/or porosity logs along the profile, it is currently not possible to obtain reliable estimates of the high-frequency electromagnetic velocity distribution of the probed subsurface region. This is problematic because adequate knowledge of the velocity is needed for accurate imaging and depth conversion of the data, as well as for quantifying the distribution of soil water content. To overcome this issue, we have developed a novel methodology for estimating the detailed subsurface velocity structure from common-offset GPR reflection measurements, which does not require additional conditioning information. The proposed approach combines two key components: diffraction analysis is used to infer the smooth, large-scale component of the velocity distribution, whereas the superimposed small-scale fluctuations are inferred via inversion of the reflected wavefield. We test and validate our method on two synthetic data sets having increasing degrees of complexity and realism before applying it to a field example from the Boise Hydrogeophysical Research Site, where independent control data in the form of neutron–neutron porosity logs are available for validation. The results obtained demonstrate the viability and robustness of the proposed approach. Further, due to its efficiency, both in terms of field effort and computational cost, the method can be readily extended to 3-D, which further enhances its attractiveness compared to multi-offset-based GPR velocity estimation techniques.

Ground Penetrating Radar Imaging of a Circular Patterned Ground near King Sejong Station, Antarctica

Constraints on the structure and composition of the active layer are important for understanding permafrost evolution. Soil convection owing to repeated moisture-induced freeze-thaw cycles within the active layer promotes the formation of self-organized patterned ground. Here we present the results of ground penetrating radar (GPR) surveys across a selected sorted circle near King Sejong Station, Antarctica, to better delineate the active layer and its relation to the observed patterned ground structure. We acquire GPR data in both bistatic mode (common mid-points) for precise velocity constraints and monostatic mode (common-offset) for subsurface imaging. Reflections are derived from the active layer-permafrost boundary, organic layer-weathered soil boundary within the active layer, and frozen rock-fracture-filled ice boundary within the permafrost. The base of the imaged sorted circle possesses a convex-down shape in the central silty zone, which is typical for the pattern associated with convection-like soil motion within the active layer. The boundary between the central fine-silty domain and coarse-grained stone border is effectively identified in a radar amplitude contour at the assumed active layer depth, and is further examined in the frequency spectra of the near- and far-offset traces. The far-offset traces and the traces from the lower frequency components dominant on the far-offset traces would be associated with rapid absorption of higher frequency radiowave due to the voids in gravel-rich zone. The presented correlation strategies for analyzing very shallow, thin-layered GPR reflection data can potentially be applied to the various types of patterned ground, particularly for acquiring time-lapse imaging, when electric resistivity tomography is incorporated into the analysis.

On the usage of diffractions in ground-penetrating radar reflection data: Implications for time-lapse gas migration monitoring

Time-lapse ground-penetrating radar (GPR) measurements are used to image/monitor, for example, water infiltration, water table changes, and fluid/gas flow patterns. Although crosshole GPR is often preferred over surface-reflection GPR in such studies, its application is limited by the selected borehole geometry, which may be difficult to define in an optimal way, especially in experiments in which flow pathways are difficult to predict. Surface-reflection GPR data sets are generally faster to collect over relatively large areas and are therefore more efficient for covering the volume when a fast-moving tracer (e.g., gas) may infiltrate a heterogeneous subsurface medium. We have used a diffraction imaging approach on time-lapse surface-reflection GPR data to detect changes in radar wave velocity associated with gas (CO2) injected into a heterogeneous chalk succession. We initially test and evaluate the diffraction imaging approach on synthetic GPR data. Afterward, we apply the methodology to time-lapse GPR field data, and we evaluate the robustness of using information from diffractions in light of the obtained data quality. The synthetic tests indicate that diffractions provide essential information for delimiting the area affected by gas in the heterogeneous chalk section studied. Our field experiment shows that using the diffraction information alone allows for detection of gas-affected zones and, therefore, potential flow characteristics of gas movement. We infer that the CO2 flow patterns in our study most likely are determined by small-scale fractures rather than the porosity/permeability of the rock matrix. Moreover, the approach used may serve as an initial study for future more targeted experiments or for further detail-retrieving full-waveform inversion.

3D modeling of ground-penetrating radar data across a realistic sedimentary model

Ground-penetrating radar (GPR) is an established geophysical tool to explore a wide range of near-surface environments. Today, the use of synthetic GPR data is largely limited to 2D because 3D modeling is computationally more expensive. In fact, only recent developments of modeling tools and powerful hardware allow for a time-efficient computation of extensive 3D data sets. Thus, 3D subsurface models and resulting GPR data sets, which are of great interest to develop and evaluate novel approaches in data analysis and interpretation, have not been made publicly available up to now.We use a published hydrofacies data set of an aquifer-analog study within fluvio-glacial deposits to infer a realistic 3D porosity model showing heterogeneities at multiple spatial scales. Assuming fresh-water saturated sediments, we generate synthetic 3D GPR data across this model using novel GPU-acceleration included in the open-source software gprMax. We present a numerical approach to examine 3D wave-propagation effects in modeled GPR data. Using the results of this examination study, we conduct a spatial model decomposition to enable a computationally efficient 3D simulation of a typical GPR reflection data set across the entire model surface. We process the resulting GPR data set using a standard 3D structural imaging sequence and compare the results to selected input data to demonstrate the feasibility and potential of the presented modeling studies. We conclude on conceivable applications of our 3D GPR reflection data set and the underlying porosity model, which are both publicly available and, thus, can support future methodological developments in GPR and other near-surface geophysical techniques.

Non-invasive estimation of root zone soil moisture from coarse root reflections in ground-penetrating radar images

Root zone soil moisture is an important component in water cycling through the soil-plant-atmosphere continuum. However, its measurement in the field remains a challenge, especially non-invasively and repeatedly. Here, we developed a new method that uses ground-penetrating radar (GPR) to quantify root zone soil moisture. Coarse roots were chosen as reflectors to collect GPR radargrams. An automatic hyperbola detection algorithm identified coarse root reflections in GPR radargrams and determined the velocity of GPR wave, which then was used to calculate the average soil water content of a soil profile (ASWC) and soil water content in a depth interval (ISWC). In total, GPR reflection data of 55 root samples from three computer simulation scenarios and two field experiments in sandy shrubland, one burying roots at known depths and the other under the undisturbed condition, were used to evaluate the proposed method. Both the simulated and the field collected data demonstrated the effectiveness of the proposed method for measuring root zone soil moisture with high accuracy. Even in the two field experiments, the root-mean-square errors of the estimated ASWC and ISWC relative to measurements from soil cores were as low as 0.003 and 0.012 m3·m−3, respectively. The proposed method offers a new way of quantifying root zone soil moisture non-invasively that allows repeated measurements. This study expands the application of GPR in root and soil study and enhances our ability to monitor plant-soil-water interactions.

Quantitative imaging for civil engineering by joint full waveform inversion of surface-based GPR and shallow seismic reflection data

Full waveform inversion (FWI) of ground penetrating radar (GPR) and seismic data is a promising imaging tool for the detailed characterization of latent cavities and tunnels. In this study, surface-based GPR FWI and seismic FWI are combined to quantitatively image the geometry and geophysical attributes of the subsurface. These two FWI methods are integrated into a joint procedure and linked by cross-gradient functions which can provide structural constraints between the parameters. The elastic and electromagnetic properties of the medium (P-wave velocity, permittivity, and conductivity) are linked and simultaneously inverted in the joint FWI approach. This joint FWI approach is tested using three numerical examples. In the first two examples, target objects with various shapes are contained in both homogeneous and inhomogeneous media. In the third example, two sediment-filled cavities and a fractured area are analyzed in the calcarenite layers. The results show that the joint FWI approach can integrate the common structure of models and correct the model structures that are inaccurately reconstructed in the individual FWI methods, providing a comprehensive structural interpretation of the study areas.

Apparent apertures from ground penetrating radar data and their relation to heterogeneous aperture fields

Considering fractures with heterogeneous aperture distributions, we explore the reliability of constant-aperture estimates derived from ground penetrating radar (GPR) reflection data. We generate geostatistical fracture aperture realizations that are characterized by the same mean-aperture and variance, but different Hurst exponents and cut-off lengths. For each of the 16 classes of heterogeneity considered, we generate 1000 fracture realizations from which we compute GPR reflection data using our recent effective-dipole forward model. We then use each (noise-contaminated) data set individually to invert for a single ‘apparent’ aperture, that is, we assume that the fracture aperture is homogeneous. We find that the inferred ‘apparent’ apertures are only reliable when fracture heterogeneity is non-fractal (the Hurst exponent is close to 1) and the scale of the dominant aperture heterogeneities is larger than the first Fresnel zone. These results are a direct consequence of the nonlinear character of the thin-bed reflection coefficients. As fracture heterogeneity is ubiquitous and often fractal, our results suggest that robust field-based inference of fracture aperture can only be achieved by accounting for the nonlinear response of fracture heterogeneity on GPR data.

Changes in Holocene relative sea-level and coastal morphology: A study of a raised beach ridge system on Samsø, southwest Scandinavia

Changes in relative sea-level (RSL) during the Holocene are reconstructed based on ground-penetrating radar (GPR) data collected across a raised beach ridge system on the island of Samsø, Denmark. The internal architecture of the beach ridge and swale deposits is divided into characteristic radar facies. We identify downlap points interpreted to mark the transition from the beachface to the upper shoreface and, thus, sea-level at the time of deposition. This new data set shows that beach steps can be preserved and resolved in GPR reflection data. This is important, as downlap points identified at the base of the beach steps should be corrected for beach step height in order to be used as a marker of sea-level. Identification of beach steps in combination with observed changes in dips of the interpreted beachface reflections can give information about changes in the morphodynamic conditions of beach ridge progradation through time. The vertical levels of identified downlap points are combined with an age model based on optically stimulated luminescence-dated samples to reconstruct RSL for the past c. 5000 years. Overall, the reconstruction shows that the period between c. 4800 and 3800 yr BP was characterized by relatively high RSL values around 2.3 m above DVR90 (Danish Vertical Reference 1990). A marked decrease in RSL of c. 1.3 m occurred between c. 3800 and 3600 yr BP at a rate of c. 5 mm/yr. After c. 3500 yr BP, the RSL curve shows a gradual decrease at a rate of c. 0.6 mm/yr.

Reflection waveform inversion of ground-penetrating radar data for characterizing thin and ultrathin layers of nonaqueous phase liquid contaminants in stratified media

Accurately quantifying thin-layer parameters by applying a targeted reflection waveform inversion methodology to ground-penetrating radar (GPR) reflection data may provide a useful tool for near-surface investigation and especially for contaminated site investigation where nonaqueous phase liquid (NAPL) contaminants are present. We implemented a targeted reflection waveform inversion algorithm to quantify thin-layer permittivity, thickness, and conductivity for NAPL thin ([Formula: see text] dominant wavelength [Formula: see text]) and ultrathin ([Formula: see text]) layers using GPR reflection data. The inversion used a nonlinear grid search with a Monte Carlo scheme to initialize starting values to find the global minimum. By taking a targeted approach using a time window around the peak amplitude of the reflection event of interest, our algorithm reduced the complexity in the inverse problem. We tested the inversion on three different synthetic data sets and four field data sets. In all testing, the inversion solved for NAPL-layer properties within 15% of the measured values. This algorithm provides a tool for site managers to prioritize remediation efforts based on quantitative assessments of contaminant quantity and location using GPR.

Combining EMI and GPR for non‐invasive soil sensing at the Stonehenge World Heritage Site: the reconstruction of a WW1 practice trench

SummaryIncreasingly, conventional soil sampling procedures face restrictions because of their destructive character. Hence there is a growing interest in non‐invasive techniques, on which proximal soil sensors are based. There is great interest in applying proximal soil sensing to improve the characterization of the buried heritage embedded in the soil landscape at sites such as the Stonehenge World Heritage Site, UK. Because calibration and validation procedures based on invasive practices are unconventional, we turned to the investigation of a well‐documented practice trench dug during the First World War (WW1) close to the prehistoric Stonehenge monument. A methodology was tested that would simultaneously invert frequency‐domain ground‐penetrating radar (GPR) and multi‐receiver electromagnetic induction (EMI) data, with the aim of reconstructing the trench network. This trench network could not be distinguished on the EMI apparent electrical conductivity (σa) measurements, but appeared on the apparent magnetic susceptibility (κa) data. The GPR measurements showed the trench infilling as strong reflections contrasting with the surrounding soil. However, converting the two‐way travel times to absolute depths requires knowledge of the relative permittivity (εr). Because of the preference for non‐invasive observation in this protected landscape, we developed a procedure integrating the GPR measurements with κa measurements obtained with EMI. A fitting procedure, assuming a constant susceptibility and permittivity of the sub‐surface layers, allowed us to estimate both the susceptibility of the trench fill and the surrounding soil material, and the εr value of the material above and within the trench. This provided absolute depth values for the GPR reflection data, improving the lateral and vertical reconstruction of the trench system. Moreover, these results allowed depth slices to be determined from EMI κa data. So, integrating both GPR and EMI measurements enabled the detailed reconstruction of the buried trench network at Stonehenge, offering new perspectives on the investigation of features buried within the soil of protected sites.

Joint interpretation of beach-ridge architecture and coastal topography show the validity of sea-level markers observed in ground-penetrating radar data

Geological studies of past and present sea level rely on valid and robust features marking sea level in geological sections. Present sea-level markers around the upper shoreface to beachface transition are detected in a beach-ridge plain formed in a microtidal regime. These sea-level markers identify specific relative sea levels at the time of formation. Ground-penetrating radar (GPR) data collected across the youngest part of the beach-ridge system of Feddet, Denmark are compared with independent coastal morphological and sedimentological data of the active strand plain and interpreted in relation to sea-level data. The data show consistency between dip values of the present beachface and upper shoreface compared with dip values of interpreted beachface and upper shoreface GPR reflections. A clear change in dip value is observed between beachface and upper shoreface deposits in both data sets. Within few centimetres, this break point coincides with actual sea level and is interpreted to correspond to downlap points observed in the GPR reflection data. Furthermore, our observations may indicate that downlap points of deposits, formed under both relatively high and low water levels, are preserved and may be identified in GPR reflection data. Downlap points identified in GPR data across microtidal beach-ridge systems from other localities can also constitute markers of palaeo-sea level at the time of deposition. Records of these sea-level markers can be used to reconstruct the local relative sea-level history during the Holocene.

Ground Penetrating Radar: Water Table Detection Sensitivity to Soil Water Retention Properties

We are interested in Ground Penetrating Radar (GPR) as a geophysical tool useful for determining the depth of the ground water table (GWT) and for monitoring shallow water infiltration in sandy soils. At hydrostatic equilibrium, the water content distribution in a homogeneous unsaturated soil down to the water saturated zone depends on the soil water retention function. A classical way to fit retention curve data is to use the van Genuchten continuous model. Using Finite Difference Time Domain simulations, we study the sensitivity of the GPR signal reflected by a van Genuchten type transition to the hydraulic parameters. We show a power type relationship between the reflected signal amplitude and the slope of the soil retention curve. Furthermore, for simulating GPR reflection data acquired above a transition from unsaturated to saturated soil, geophysicists often approximate the soil water retention curve by a piecewise linear model. We test the validity of such an approximation depending on the frequency of the radar signal and the abruptness of the retention curve. We illustrate our results with high resolution GPR data (1600 MHz) acquired above a fluctuating water table in a sand column at the laboratory scale.

Constraining 3-D electrical resistance tomography with GPR reflection data for improved aquifer characterization

Abstract Surface-based ground penetrating radar (GPR) and electrical resistance tomography (ERT) are common tools for aquifer characterization, because both methods provide data that are sensitive to hydrogeologically relevant quantities. To retrieve bulk subsurface properties at high resolution, we suggest incorporating structural information derived from GPR reflection data when inverting surface ERT data. This reduces resolution limitations, which might hinder quantitative interpretations. Surface-based GPR reflection and ERT data have been recorded on an exposed gravel bar within a restored section of a previously channelized river in northeastern Switzerland to characterize an underlying gravel aquifer. The GPR reflection data acquired over an area of 240 × 40 m map the aquifer's thickness and two internal sub-horizontal regions with different depositional patterns. The interface between these two regions and the boundary of the aquifer with the underlying clay are incorporated in an unstructured ERT mesh. Subsequent inversions are performed without applying smoothness constraints across these boundaries. Inversion models obtained by using these structural constraints contain subtle resistivity variations within the aquifer that are hardly visible in standard inversion models as a result of strong vertical smearing in the latter. In the upper aquifer region, with high GPR coherency and horizontal layering, the resistivity is moderately high (> 300 Ωm). We suggest that this region consists of sediments that were rearranged during more than a century of channelized flow. In the lower low coherency region, the GPR image reveals fluvial features (e.g., foresets) and generally more heterogeneous deposits. In this region, the resistivity is lower (~ 200 Ωm), which we attribute to increased amounts of fines in some of the well-sorted fluvial deposits. We also find elongated conductive anomalies that correspond to the location of river embankments that were removed in 2002.

Geostatistical inversion of seismic and ground‐penetrating radar reflection images: What can we actually resolve?

Estimation of the spatial statistics of subsurface velocity heterogeneity from surface‐based geophysical reflection survey data is a problem of significant interest in seismic and ground‐penetrating radar (GPR) research. A method to effectively address this problem has been recently presented, but our knowledge regarding the resolution of the estimated parameters is still inadequate. Here we examine this issue using an analytical approach that is based on the realistic assumption that the subsurface velocity structure can be characterized as a band‐limited scale‐invariant medium. Our work importantly confirms recent numerical findings that the inversion of seismic or GPR reflection data for the geostatistical properties of the probed subsurface region is sensitive to the aspect ratio of the velocity heterogeneity and to the decay of its power spectrum, but not to the individual values of the horizontal and vertical correlation lengths.

Ground‐penetrating radar assessment of the medieval arch bridge of San Antón, Galicia, Spain

AbstractSeveral arched masonry bridges are listed historical monuments in Spain, which are valued tourist attractions or local landmarks. They are maintained by several organizations dedicated to the cultural heritage such as the International Council on Monuments and Sites (ICOMOS). Many of these important structures are the oldest constructions still in use within the transportation infrastructure and as a result of the increase in traffic loads and their age they have undergone some structural decay. Ground‐penetrating radar (GPR) has been shown to be valuable in evaluating the state of conservation of the San Antón medieval bridge in order to help preserve its historical character. This bridge was surveyed by using the 200, 250 and 500 MHz antennas. Interpretation and analysis of GPR reflection data were supported by finite‐difference time domain numerical modelling, based on the accurate external geometry obtained with three‐dimensional laser scanning methods. Results show that GPR mapping provides valuable information for detecting an internal structural element used for reinforcement as well as a possible interior hidden arch that remains from ancient times. This information is noteworthy for archaeologists and civil engineers as it can be used to make decisions about stability and for future strengthening measures. Copyright © 2010 John Wiley & Sons, Ltd.

Time‐Lapse GPR Tomography of Unsaturated Water Flow in an Ice‐Contact Delta

Cross‐well ground penetrating radar (GPR) data sets were collected in the vadose zone of an ice‐contact delta near Oslo's Gardermoen Airport (Norway) before, during, and after snowmelt in 2005. The observed travel times were inverted using curved‐ray travel time tomography. The tomograms are in good agreement with the local geologic structure of the delta. The tomographic results were confirmed independently by surface GPR reflection data and x‐ray images of core samples. In addition to structure, the GPR tomograms also show a strong time dependency due to the snowmelt. The time‐lapse tomograms were used to estimate volumetric soil water content using Topp's equation. The volumetric soil water content was also observed independently by using a neutron meter. Comparison of these two methods revealed a strong irregular wetting process during the snowmelt. This was interpreted to be due to soil heterogeneity as well as a heterogeneous infiltration rate. The geologic structure and water content estimates obtained from the GPR tomography can be used in forward and inverse flow modeling. Finally, the water balance in the vadose zone was calculated using snow accumulation data, precipitation data, porosity estimates, and observed changes in the groundwater table. The amount of water stored in the vadose zone obtained from the water balance is consistent with the amount estimated using GPR tomography. Alternatively, the change in water storage in the vadose zone can be estimated using GPR tomography. This may then permit estimates of evapotranspiration to be made, provided other components of the water balance are known.