Abstract:We want to develop a dialogue between geophysicists and hydrologists interested in synergistically advancing process based watershed research. We identify recent advances in geophysical instrumentation, and provide a vision for the use of electrical and magnetic geophysical instrumentation in watershed scale hydrology. The focus of the paper is to identify instrumentation that could significantly advance this vision for geophysics and hydrology during the next 3-5 years. We acknowledge that this is one of a number of possible ways forward and seek only to offer a relatively narrow and achievable vision. The vision focuses on the measurement of geological structure and identification of flow paths using electrical and magnetic methods. The paper identifies instruments, provides examples of their use, and describes how synergy between measurement and modelling could be achieved. Of specific interest are the airborne systems that can cover large areas and are appropriate for watershed studies. Although airborne geophysics has been around for some time, only in the last few years have systems designed exclusively for hydrological applications begun to emerge. These systems, such as airborne electromagnetic (EM) and transient electromagnetic (TEM), could revolutionize hydrogeological interpretations. Our vision centers on developing nested and cross scale electrical and magnetic measurements that can be used to construct a three-dimensional (3D) electrical or magnetic model of the subsurface in watersheds. The methodological framework assumes a 'top down' approach using airborne methods to identify the large scale, dominant architecture of the subsurface. We recognize that the integration of geophysical measurement methods, and data, into watershed process characterization and modelling can only be achieved through dialogue. Especially, through the development of partnerships between geophysicists and hydrologists, partnerships that explore how the application of geophysics can answer critical hydrological science questions, and conversely provide an understanding of the limitations of geophysical measurements and interpretation.

[1] Hydraulic tomography is a promising approach for obtaining information on variations in hydraulic conductivity on the scale of relevance for contaminant transport investigations. This approach involves performing a series of pumping tests in a format similar to tomography. We present a field-scale assessment of hydraulic tomography in a porous aquifer, with an emphasis on the steady shape analysis methodology. The hydraulic conductivity (K) estimates from steady shape and transient analyses of the tomographic data compare well with those from a tracer test and direct-push permeameter tests, providing a field validation of the method. Zonations based on equal-thickness layers and cross-hole radar surveys are used to regularize the inverse problem. The results indicate that the radar surveys provide some useful information regarding the geometry of the K field. The steady shape analysis provides results similar to the transient analysis at a fraction of the computational burden. This study clearly demonstrates the advantages of hydraulic tomography over conventional pumping tests, which provide only large-scale averages, and small-scale hydraulic tests (e.g., slug tests), which cannot assess strata connectivity and may fail to sample the most important pathways or barriers to flow.Citation: Bohling, G. C., J. J. Butler Jr., X. Zhan, and M. D. Knoll (2007), A field assessment of the value of steady shape hydraulic tomography for characterization of aquifer heterogeneities, Water Resour. Res., 43, W05430,

[1] We have investigated the potential of combining cross-hole georadar velocity and attenuation tomography as a method for characterizing heterogeneous alluvial aquifers. A multivariate statistical technique, known as k-means cluster analysis, is used to correlate and integrate information contained in velocity and attenuation tomograms. Cluster analysis allows us to identify objectively the major common trends in the tomographic data and thus to ''reduce'' the information to a limited number of characteristic parameter combinations. The application of this procedure to two synthetic data sets indicates that it is a powerful tool for converting the complex relationships between the tomographically derived velocity and attenuation structures into a lithologically and hydrologically meaningful zonation of the probed region. In addition, these synthetic examples allow us to evaluate the reliability of further petrophysical parameter estimates. We find that although absolute values of the tomographically inferred petrophysical parameters often differ significantly from the actual parameters, the clustering approach enables us to reliably identify the major trends in the petrophysical properties. Finally, we have applied the approach to a cross-hole georadar data set collected in a well-studied alluvial aquifer. A comparison of the clustered tomographic section with well-log data demonstrates that our approach delineates the hydrostratigraphic zonation.

To quantify performance of 3D time-lapse electrical resistivity tomography (ERT), a sequential injection/withdrawal experiment was designed for monitoring the pump-and-capture remediation of a conductive solute in an unconfined alluvial aquifer. Prior information is incorporated into the inversion procedure via regularization with respect to a reference model according to three protocols: (1) independent regularization involving a single reference model, (2) background regularization involving a reference model obtained via inversion of preinjection data, and (3) time-lapse regularization involving an evolving reference model obtained via inversion of data from previous experimental stages. Emplacement and sequential withdrawal of the solute is clearly imaged for all protocols. Time-lapse regularization results in greater amounts of model structure, while providing signifi-cant computational savings. ERT-estimated electrical conductivity is used to predict solute concentration and solute mass in the aquifer. At any experimental stage, we are able to estimate total solute mass in the aquifer with a maximum accuracy of 60%–85% depending on regularization protocol and survey geometry. We also estimate the withdrawn solute mass for every experimental stage (the change in mass between experimental stages). Withdrawn mass estimates are more reliable than total mass estimates and do not exhibit systematic underprediction or dependence on regularization protocol. Withdrawn mass estimates are accurate for changes in mass below [Formula: see text] of potassium bromide [Formula: see text] for horizontal and vertical dipole-dipole surveys, respectively. Estimating the withdrawn solute mass does not require background subtraction and, thus, does not require background data.

S U M M A R YLimitations of imaging using electrical resistivity tomography (ERT) arise because of the difficulty of quantifying the reliability of tomographic images. A major source of uncertainty in tomographic inversion is data error. Data error due to electrode mislocations is characterized by the sensitivity of electrical potential to both source and receiver positions. This sensitivity is described by a scattering-type equation and, therefore, depends not only on source-receiver separation, but also on the location and magnitude of contrasts in electrical conductivity. At the overlapping scales of near-surface environmental and engineering geophysical surveys, for which electrodes may be close to the target and experiment dimensions may be on the same order as those of the target, errors associated with electrode mislocations can significantly contaminate the ERT data and the reconstructed electrical conductivity. For synthetic experiments, variations in the data due to electrode mislocation are comparable in magnitude to typical experimental noise levels and, in some cases, may overwhelm variations in the data due to changes in material properties. Furthermore, the statistical distribution of electrode mislocation errors can be complicated and multimodal such that bias may be introduced into the ERT data. The resulting perturbations of the reconstructed electrical conductivity field due to electrode mislocations can be significant in magnitude with complex spatial distributions that are dependent both on the model and the experiment.

To obtain the highest-resolution ray-based tomographic images from crosshole ground-penetrating radar (GPR) data, wide angular ray coverage of the region between the two boreholes is required. Unfortunately, at borehole spacings on the order of a few meters, high-angle traveltime data (i.e., traveltime data corresponding to transmitter-receiver angles greater than approximately 50° from the horizontal) are notoriously difficult to incorporate into crosshole GPR inversions. This is because (1) low signal-to-noise ratios make the accurate picking of first-arrival times at high angles extremely difficult, and (2) significant tomographic artifacts commonly appear when high- and low-angle ray data are inverted together. We address and overcome thesetwo issues for a crosshole GPR data example collected at the Boise Hydrogeophysical Research Site (BHRS). To estimate first-arrival times on noisy, high-angle gathers, we develop a robust and automatic picking strategy based on crosscorrelations, where reference waveforms are determined from the data through the stacking of common-ray-angle gathers. To overcome incompatibility issues between high- and low-angle data, we modify the standard tomographic inversion strategy to estimate, in addition to subsurface velocities, parameters that describe a traveltime ‘correction curve’ as a function of angle. Application of our modified inversion strategy, to both synthetic data and the BHRS data set, shows that it allows the successful incorporation of all available traveltime data to obtain significantly improved subsurface velocity images.

Solution appraisal is difficult for large 3D, nonlinear inverse problems such as electrical resistivity tomography (ERT). We construct the volume of investigation index (VOI) as the sensitivity of the inversion result to a variable-reference model. This limited exploration of the model space provides an efficient and pragmatic method of appraisal for a particular data set and a 3D model domain. We present a synthetic example to demonstrate the applicability of the VOI as a tool for characterizing model reliability for 3D ERT and as a method of survey design. We show how the VOI provides a measure of model resolution and how insight gained from VOI analysis cannot be gained through similar examination of the average sensitivity distributions. In the context of ERT monitoring of an injection/withdrawal experiment, we utilize the VOI for judging the degree of reliability of hydrogeological interpretations that stem from features observed in the estimated electrical-conductivity models. We employ the VOI for the experimental data as a comparative measure of survey performance. For this experiment, the VOI shows that a larger, more artifact-free region of reliability is achieved using a circulating vertical dipole-dipole survey geometry, as opposed to a horizontal dipole-dipole survey geometry. The experimental VOI distributions exhibit dependence on the borehole infrastructure and the actual earth model.

We tested a prototype capacitive-conductivity borehole tool in a shallow, unconfined aquifer with coarse, unconsolidated sediments and very-low-conductivity water at the Boise Hydrogeophysical Research Site ͑BHRS͒. Examining such a high-resistivity system provides a good test for the capacitive-conductivity tool because the conventional induction-conductivity tool ͑known to have limited effectiveness in high-resistivity systems͒ did not generate expressive well logs at the BHRS. The capacitive-conductivity tool demonstrated highly repeatable, low-noise behavior but poor correlation with the induction tool in the lower-conductivity portions of the stratigraphy where the induction tool was relatively unresponsive. Singular spectrum analysis of capacitive-conductivity logs reveals similar vertical-length scales of structures to porosity logs at the BHRS. Also, major stratigraphic units identified with porosity logs are evident in the capacitive-conductivity logs. However, a previously unrecognized subdivision in the upper portion of one of the major stratigraphic units can be identified consistently as a relatively low-conductivity body ͑i.e., an electrostratigraphic unit͒ between the overlying stratigraphic unit and the relatively high-conductivity lower portion -despite similar porosity and lithology in adjacent units. The high repeatability and resolution and the wide dynamic range of the capacitive-conductivity tool are demonstrated here to extend to high-resistivity, unconsolidated sedimentary aquifer environments.