[1] Hydraulic tomography is a cost-effective technique for characterizing the heterogeneity of hydraulic parameters in the subsurface. During hydraulic tomography surveys a large number of hydraulic heads (i.e., aquifer responses) are collected from a series of pumping or injection tests in an aquifer. These responses are then used to interpret the spatial distribution of hydraulic parameters of the aquifer using inverse modeling. In this study, we developed an efficient sequential successive linear estimator (SSLE) for interpreting data from transient hydraulic tomography to estimate threedimensional hydraulic conductivity and specific storage fields of aquifers. We first explored this estimator for transient hydraulic tomography in a hypothetical onedimensional aquifer. Results show that during a pumping test, transient heads are highly correlated with specific storage at early time but with hydraulic conductivity at late time. Therefore reliable estimates of both hydraulic conductivity and specific storage must exploit the head data at both early and late times. Our study also shows that the transient heads are highly correlated over time, implying only infrequent head measurements are needed during the estimation. Applying this sampling strategy to a well-posed problem, we show that our SSLE can produce accurate estimates of both hydraulic conductivity and specific storage fields. The benefit of hydraulic tomography for ill-posed problems is then demonstrated. Finally, to affirm the robustness of our SSLE approach, we apply the SSLE approach to a hypothetical three-dimensional heterogeneous aquifer.

[1] Traditional analysis of aquifer tests uses the observed drawdown at one well, induced by pumping at another well, for estimating the transmissivity (T) and storage coefficient (S) of an aquifer. The analysis relies on Theis' solution or Jacob's approximate solution, which assumes aquifer homogeneity. Aquifers are inherently heterogeneous at different scales. If the observation well is screened in a low-permeability zone while the pumping well is located in a high-permeability zone, the resulting situation contradicts the homogeneity assumption in the traditional analysis. As a result, what does the traditional interpretation of the aquifer test tell us? Using numerical experiments and a first-order correlation analysis, we investigate this question. Results of the investigation suggest that the effective T and S for an equivalent homogeneous aquifer of Gaussian random T and S fields vary with time as well as the principal directions of the effective T. The effective T and S converge to the geometric and arithmetic means, respectively, at large times. Analysis of the estimated T and S, using drawdown from a single observation well, shows that at early time both estimates vary with time. The estimated S stabilizes rapidly to the value dominated by the storage coefficient heterogeneity in between the pumping and the observation wells. At late time the estimated T approaches but does not equal the effective T. It represents an average value over the cone of depression but influenced by the location, size, and degree of heterogeneity as the cone of depression evolves.

[1] Hydraulic tomography is a method that images the hydraulic heterogeneity of the subsurface through the inversion of multiple pumping or cross-hole hydraulic test data. Transient hydraulic tomography is different from steady state hydraulic tomography in that it utilizes transient hydraulic head records to yield the distribution of hydraulic conductivity (K) as well as specific storage (S s ) of an aquifer. In this paper we demonstrate the robustness of transient hydraulic tomography through the use of hydraulic head data obtained from multiple cross-hole pumping tests conducted in a laboratory sandbox with deterministic heterogeneity. We utilize the algorithm developed by Zhu and Yeh (2005) to conduct the transient inversions and validate the K and S s tomograms using a multimethod and multiscale validation approach previously proposed by Illman et al. (2006). Validation data consist of cross-hole tests not used in the inversion as well as other hydraulic tests that provided local (core, single-hole tests) as well as large-scale (unidirectional flow-through tests) estimates of hydraulic parameters. Results show that the algorithm is able to yield consistent estimates that agree with independently collected local as well as large-scale hydraulic parameter data. In addition, we find that the transient hydraulic tomography requires a fewer number of pumping tests to estimate a similar quality K tomogram when compared with steady state hydraulic tomography, as the former approach utilizes more data from each pumping test. Overall, we find that transient hydraulic tomography is a robust subsurface characterization technique that can delineate the subsurface heterogeneity in both K and S s from multiple pumping or crosshole hydraulic tests.

[1] Groundwater modeling has become a vital component to water supply and contaminant transport investigations. An important component of groundwater modeling under steady state conditions is selecting a representative hydraulic conductivity (K) estimate or set of estimates which defines the K field of the studied region. Currently, there are a number of characterization approaches to obtain K at various scales and in varying degrees of detail, but there is a paucity of information in terms of which characterization approach best predicts flow through aquifers or drawdowns caused by some drawdown inducing events. The main objective of this paper is to assess K estimates obtained by various approaches by predicting drawdowns from independent cross-hole pumping tests and total flow rates through a synthetic heterogeneous aquifer from flow-through tests. Specifically, we (1) characterize a synthetic heterogeneous aquifer built in the sandbox through various techniques (permeameter analyses of core samples, single-hole, cross-hole, and flow-through testing), (2) obtain mean K fields through traditional analysis of test data by treating the medium to be homogeneous, (3) obtain heterogeneous K fields through kriging and steady state hydraulic tomography, and (4) conduct forward simulations of 16 independent pumping tests and six flowthrough tests using these homogeneous and heterogeneous K fields and comparing them to actual data. Results show that the mean K and heterogeneous K fields estimated through kriging of small-scale K data (core and single-hole tests) yield biased predictions of drawdowns and flow rates in this synthetic heterogeneous aquifer. In contrast, the heterogeneous K distribution or "K tomogram" estimated via steady state hydraulic tomography yields excellent predictions of drawdowns of pumping tests not used in the construction of the tomogram and very good estimates of total flow rates from the flowthrough tests. These results suggest that steady state groundwater model validation is possible in this laboratory sandbox aquifer if the heterogeneous K distribution and forcing functions (boundary conditions and source/sink terms) are characterized sufficiently.