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Transient hydraulic tomography (THT) is a robust method of aquifer characterization to estimate the spatial distributions (or tomograms) of both hydraulic conductivity ( K ) and specific storage ( S s ). However, the highly-parameterized nature of the geostatistical inversion approach renders it computationally intensive for large-scale investigations. In addition, geostatistics-based THT may produce overly smooth tomograms when head data used to constrain the inversion is limited. Therefore, alternative model conceptualizations for THT need to be examined. To investigate this, we simultaneously calibrated different groundwater models with varying parameterizations and zonations using two cases of different pumping and monitoring data densities from a laboratory sandbox. Specifically, one effective parameter model, four geology-based zonation models with varying accuracy and resolution, and five geostatistical models with different prior information are calibrated. Model performance is quantitatively assessed by examining the calibration and validation results. Our study reveals that highly parameterized geostatistical models perform the best among the models compared, while the zonation model with excellent knowledge of stratigraphy also yields comparable results. When few pumping tests with sparse monitoring intervals are available, the incorporation of accurate or simplified geological information into geostatistical models reveals more details in heterogeneity and yields more robust validation results. However, results deteriorate when inaccurate geological information are incorporated. Finally, our study reveals that transient inversions are necessary to obtain reliable K and S s estimates for making accurate predictions of transient drawdown events. [ABSTRACT FROM AUTHOR]

Hydraulic tomography (HT) has been shown to map subsurface heterogeneity accurately through the joint interpretation of multiple pumping tests. Previous research has shown that smooth hydraulic conductivity ( K ) estimates are obtained beyond where pumping/observation data are available using the geostatistical inversion approach, when the inversion begins with a homogeneous K and when data densities are not high. However, geological data are typically available through outcrops and borehole logs to provide geological variability. Therefore, we investigate the usefulness of geological data for HT analysis at a highly heterogeneous field site by: (1) comparing calibrated geological models of two different resolutions to two homogeneous and four highly parameterized geostatistical inverse models, in terms of both model calibration and validation performances as well as correspondence of estimated K values with permeameter-estimated K profiles along boreholes; and (2) using geological models as prior information for the geostatistical inversion approach. Results reveal that the simultaneous calibration of geological models to seven pumping test data yields K values that correctly reflect the general patterns of vertical distributions of permeameter-estimated K . We also find that the geostatistical inversion approach using a geological model as prior information performs better for both model calibration and validation than using a homogenous K as a prior, and more importantly, improves the correspondence of K estimates to permeameter test results along wells, as well as in preserving geological features where drawdown measurements are lacking. Overall, our results suggest the joint use of both geological and pumping test data for HT analysis when accurate geological data are available. [ABSTRACT FROM AUTHOR]

This paper investigates the importance of geological data in Hydraulic Tomography (HT) through sandbox experiments. In particular, four groundwater models with homogeneous geological units constructed with borehole data of varying accuracy are jointly calibrated with multiple pumping test data of two different pumping and observation densities. The results are compared to those from a geostatistical inverse model. Model calibration and validation performances are quantitatively assessed using drawdown scatterplots. We find that accurate and inaccurate geological models can be well calibrated, despite the estimated K values for the poor geological models being quite different from the actual values. Model validation results reveal that inaccurate geological models yield poor drawdown predictions, but using more calibration data improves its predictive capability. Moreover, model comparisons among a highly parameterized geostatistical and layer-based geological models show that, (1) as the number of pumping tests and monitoring locations are reduced, the performance gap between the approaches decreases, and (2) a simplified geological model with a fewer number of layers is more reliable than the one based on the wrong description of stratigraphy. Finally, using a geological model as prior information in geostatistical inverse models results in the preservation of geological features, especially in areas where drawdown data are not available. Overall, our sandbox results emphasize the importance of incorporating geological data in HT surveys when data from pumping tests is sparse. These findings have important implications for field applications of HT where well distances are large. [ABSTRACT FROM AUTHOR]

• A calibrated perfect-geological model yields better flow and transport predictions. • With HT-inverted K fields, the ADE can reasonably simulate tracer plumes and BTCs. • Fusing geology into geostatistics-based HT reveals inter- and intra-layer K changes. • High-resolution K fields with geological features reproduce plume fingering vividly. Hydraulic tomography (HT) has been developed over the last two decades to image subsurface heterogeneity at high resolution that is critically important to robust solute transport predictions. In this study, HT based on two concepts (i.e., geological zonation and geostatistical inversion models) was utilized to characterize the K distribution of a laboratory sandbox aquifer at different parameter resolutions. We compared the estimated K fields for predicting independent pumping tests and solute transport using the classical advection–dispersion equation (ADE). The impact of using geological zonation models of varying accuracy for HT analyses was investigated. Results revealed that, when being calibrated to datasets from multiple pumping tests, geological zonation models that faithfully represented the true stratigraphy predicted groundwater flow satisfactorily. The deterministic K field of the calibrated reliable geological zonation models satisfactorily reproduced the preferential migration path of the observed tracer plume, and the breakthrough curves (BTCs) at sampling ports. With further resolving the inter- and intra-layer heterogeneity, the reconstructed K fields by HT better predicted both migrating plumes and BTCs for two conservative tracer tests. The estimated dispersivity values for ADE only resulted in slight improvements in the fitting between observed and simulated solute tracer data. It also demonstrated the need of integrating reliable geological information into the geostatistical inversion approach to reproduce geological structures in K fields. Our study suggested the proper consideration of geological zonation between boreholes during field implementation of HT to yield improved solute transport results. [ABSTRACT FROM AUTHOR]

• HPT pressure logs (P c) can be rapidly collected in unconsolidated deposits. • P c data provide information on sharp and gradually-varying layer boundaries. • Integrating HPT-derived hydrostratigraphy and HT yields a K field with sharp boundaries. • HPT K estimates require additional evaluations for highly heterogeneous deposits. Hydraulic tomography (HT) has been developed as a robust technique in characterizing subsurface heterogeneity over the last two decades. Hydraulic conductivity (K) and specific storage (S s) estimated by geostatistically-based HT inversion approaches are typically smooth and lack geological features when observation data density is sparse. Although integrating geological information can be helpful in adding structural features into parameter fields, costly efforts are required to obtain borehole logging through conventional coring and sampling. Also, identification of geological features such as layer boundaries from sampled materials can be a subjective process. In this study, corrected pressure (P c) logs collected during hydraulic profiling tool (HPT) surveys are utilized to derive the local hydrostratigraphic layers of the glaciofluvial deposit at the North Campus Research Site (NCRS) in Waterloo, Ontario, Canada. Site-specific geological models representing aquifer and aquitard layers are developed and calibrated to drawdown data of multiple pumping tests. Results show that estimated K fields correctly reflect the variation features of permeameter-estimated K profiles, as well as the spatial distribution of high and low K sediments. The calibrated geological models performed better than the geostatistically-based inversion approach in predicting independent pumping tests used for model validation. Moreover, by including K estimates of geological models as prior means, the estimated K fields reveal both intra- and interlayer heterogeneity, and the performances of drawdown prediction are further improved for the geostatistical inversion approach. Overall, our study suggests that, integration of stratigraphic information derived from HPT P c logs is useful for HT to capture the sharp boundaries in K fields, especially when the pumping test data is sparse. [ABSTRACT FROM AUTHOR]

• THT analysis treating S s to be homogeneous yields less accurate results. • S s heterogeneity should be considered in THT for improved mapping of K and S s fields. • Reliable geological data helps THT to improve not only K , but also S s estimates. Over the last two decades, various studies on Transient Hydraulic Tomography (THT) have shown that it is an effective approach to characterize subsurface heterogeneity. Typically, high-resolution hydraulic conductivity (K) distributions were recovered, while the spatial variability of specific storage (S s) was found to be smooth. In some studies, S s heterogeneity has been intentionally ignored due to the belief that S s is less variable than K. Therefore, one may question the importance of considering S s heterogeneity during THT and its impact on the reliability of estimated hydraulic parameters. To investigate these issues, three modeling approaches (i.e., effective parameters, geological, and geostatistics-based) were used to obtain K and S s estimates of varying spatial resolutions. The reliability of K and S s estimates were evaluated by comparing their drawdown prediction performances. The values of using different prior K and S s information for THT analyses were investigated. Our results revealed that: (1) the K distribution estimated from the geostatistics-based steady-state HT analysis accurately predicted the late time drawdowns, while further improvements in transient drawdowns were obtained only after jointly treating the S s field as heterogeneous; (2) S s heterogeneity should be considered in addition to K for THT inversions, even when the estimated S s field is smooth; and (3) using K and S s estimates from the calibrated geological model as initial mean distributions for the geostatistical inversion approach were helpful in capturing both interlayer and intralayer heterogeneity of K and S s. These findings suggested that S s heterogeneity should be properly considered during the implementation of THT. [ABSTRACT FROM AUTHOR]