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Knowledge of the geologic structure at a field site is a useful piece of information for hydrologic modeling since it can serve as more site-specific prior information about the hydraulic parameter patterns at the site than generic spatial statistics. Widely accepted electrical resistivity tomography (ERT) survey for mapping subsurface anomalies could be a viable tool for acquiring this information. However, their ability to delineate geologic structures has not been thoroughly investigated. In this study, two-dimensional ERT numerical experiments were first conducted to study the effects of boundary conditions on the dipole-dipole and pole-pole array configurations. An ERT setup subsequently was implemented in a sandbox consisting of complex layers of different sands. A continuous copper wire was installed along the sides of the sandbox to impose potential boundaries. Using data collected with the pole-pole array in the sandbox under different degrees of drainage and the Successive Linear Estimator (SLE) algorithm, we show that ERT yields electrical conductivity estimates of complex layer structures with small uncertainties. In addition, using SLE with physically meaningful correlation scales as prior information can lead to an electrical conductivity field that is consistent with visually observed layer structures. The correlation scale concept also was demonstrated to provide guidance to the design of the electrode spacing in the surveys. Moreover, the estimated field was validated by predicting electrical potential fields from two independent ERT surveys using electrodes at different locations. Results of this study suggest that the combination of ERT and SLE is a viable geophysical survey tool for mapping geologic layer structures. Research Significance This study develops a method to implement prescribed potential boundaries for enhancing the pole-pole ERT survey, illustrates the importance of correlation scales and develops an approach for validating ERT results.

Pump-and-treat (P&T) is a widely adopted technology for groundwater containment/remediation. Over the past decades, we have recognized that mapping aquifer heterogeneity, especially the low hydraulic conductivity (K) zones, has become an urgent need in remediation efforts. Meanwhile, many studies have proved that hydraulic tomography (HT) utilizing groundwater responses from a series of cross-hole pumping tests is a viable technology for detailing hydraulic heterogeneity (high and low K zones) of aquifers. At a P&T field site, operation of pumping and injection wells often vary, creating changes in flow fields analogous to those in HT surveys. Therefore, collecting groundwater monitoring data and analyzing them is tantamount to a cost-effective large-scale HT survey during P&T operations. To demonstrate this idea, water level data was collected at 41 wells for one year at the U.S. Air Force Plant 44 (AFP44) P&T site in Tucson, Arizona, where the pumping and injection rates of the P&T system were changed many times during the year. This dataset was analyzed with a geostatistical inverse model to estimate the hydraulic property distribution, which can reasonably predict the pressure responses of the site under different conditions. Moreover, we showed that large-scale geological information, built based on 245 borehole logs at the site, could improve the model calibration performance through a two-step calibration procedure. Additionally, we used synthetic experiments to verify that the use of a larger variety of P&T configurations can yield non-redundant HT information, and enhance site characterization. Overall, we demonstrated that the proper scheduling of pumping and injection operations at a P&T site and collecting corresponding groundwater responses are equivalent to conducting a large-scale HT survey, with minimal additional costs.

Over the past decades, a new aquifer test technology (sequential pumping tests or hydraulic tomography, HT) has been developed and successfully applied to many field sites to delineate the spatial distributions of hydraulic properties (e.g., transmissivity (T) and storage coefficient (S)). Yet, the reproducibility of its estimated T and S fields and the predictive capabilities of the estimates for different flow scenarios at different time periods remain unexplored. That is to say, if the estimated fields based on sequential pumping tests conducted during different years are the same since the geologic formation and processes may have undergone changes. In order to answer this important question, this study first compares the drawdown-time behaviors from the sequential pumping tests (SPTs) conducted in 2010 with those conducted in 2012 at a field site and then finds they are similar but different in detail. It then uses these data to estimate the T and S fields and checks the reproducibility of the estimates. The estimated heterogeneity patterns are found to be generally reproducible in spite of uncertainties. In addition, the estimates from each year are capable of predicting the observed drawdowns, induced by independent pumping tests during the corresponding year (i.e., self-validation). Moreover, the estimated fields are cross-validated. That is, this study uses the estimates obtained from the 2010 pumping tests to predict the observed drawdowns of the independent pumping tests conducted in 2012. Likewise, it uses the estimates from 2012 pumping tests to forecast the drawdowns of the independent pumping tests of 2010. The results of both self-validation and cross-validation indicate that the estimated T and S fields based on the test in one year can be used to predict bulk flow behavior in the other year. Differences in detailed behaviors may be attributed to changes in the processes, omitted in the depth-averaged flow model.

This paper investigates the effectiveness of different oscillatory hydraulic tomography (OHT) frequencies for estimating heterogeneous fields. The analysis first formulates the effects of uncharacterized aquifer responses, T, and S fields as the ensemble mean residual flux and residual storage terms in the stochastic unconditional and conditional mean equations. These terms persist unless the T, S, or head fields are specified everywhere. We then conducted OHT to estimate the T and S fields using Monte Carlo experiments. The experiments show that using the heads in response to periodic pumping with different frequencies or multifrequency, the estimates' performance metrics vary from one realization to others. The mean performance metrics over many realizations are, however, indistinguishable, despite the frequency. We attribute the variation in the performance metrics to the lack of parameter or state variable ergodicity. Lastly, we emphasize the importance of dense monitoring networks and a cost-effective data collection strategy to improve the resolution of characterizing aquifer heterogeneity.

Strategic Environmental Research and Development Program (SERDP) [ER-1365]; Environmental Security, and Technology Certification Program (ESTCP) [ER201212]; NSF EAR from the United State [1014594]; Jilin University from Department of Education, China; Global Expert award through Tianjin Normal University from the Thousand Talents Plan of Tianjin City from China; Taiwan Typhoon and Flood Research Institute, National Applied Research Laboratories; Natural Science Foundation of China [51409029]

This study first discusses the conditional mean, realizations, and effective hydraulic conductivity in a theoretical framework. It then introduces Monte Carlo simulation (MCS) algorithms for constraining the outcome by either hydraulic conductivity (K) samples or hydraulic head (h) measurements from the hydraulic tomographic survey (HT). It demonstrates that kriging using K measurements leads to a conditional mean K field, while inverse modeling using successive linear estimator (SLE) with head measurements of HT yields the conditional effective K field. The effects of conditioning using K measurements are different from those using heads. Besides, the conditional effective K leads to the unbiased prediction of the head that honors the observed head at measurement locations. More importantly, the study reveals that the harmonic and geometric means of conditional realizations of K fields of MCS, given head measurements, are equivalent to the conditional effective K in one- and two-dimensional flows, respectively. The first-order approximation in the SLE results in a conditional covariance similar to that from MCS with smaller magnitudes. Despite the difference, all approaches predict unbiased conditional mean head behaviors.

This study exploits aquifer responses to the reduction of pumping rates at different locations in a synthetic groundwater basin as basin-scale hydraulic tomography (HT) surveys to estimate transmissivity (T) and storage coefficient (S) fields. This experiment mimics the situation of groundwater exploitation reduction in a pilot area of groundwater-overexploitation control in the North China Plain. The results of the study show that taking advantage of the groundwater exploitation reduction as HT surveys is a viable approach for basin-scale parameter estimations. Results also suggest that HT analysis should use accurate mean values of T and S for geological zones as initial guesses for the inversion of parameters. Further, we show that the T and S fields estimated from HT yield accurate predictions of the groundwater flow velocities and breakthrough curves (BTCs). However, the BTCs based on kriged and zonal mean fields are inaccurate. The predicted BTCs using homogeneous fields fail to capture the true trend of solute concentration over time. We advocate that utilizing aquifer responses induced by groundwater exploitation reduction could be a new paradigm for basin-scale aquifer characterization.