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Exploring the challenges posed by uncertainties in numerical modeling for hazardous material storage, this study introduces methodologies to improve monitoring networks for detecting subsurface leakages. The proposed approaches were applied to the Korea CO2 Storage Environmental Management (K-COSEM) test site, undergoing calibration, validation and uncertainty analysis through hydraulic and controlled-CO2 release tests. The calibration phase involved inter-well tracer and multi-well pumping tests, leveraging the Parameter ESTimation (PEST) model to determine the aquifer flow and solute transport properties of the K-COSEM site. To tackle uncertainties with limited observation data, we adopted Latin Hypercube simulation. Our uncertainty analysis confirmed model accuracy in simulating observed CO2 breakthrough curves. We also explored a probabilistic method to identify the environmental change point (EnCP) through correlation analysis with the distance from the CO2 injection well, revealing a linear trend and pinpointed potential preferential flow pathways by assessing detection probabilities. Evaluating CO2 detection capabilities was crucial for optimizing monitoring well placement, highlighting strategic well selection based on detection probabilities. This study advances managing uncertainties in hydrogeological modeling, underscoring the importance of sophisticated models in designing monitoring networks for hazardous leak detection in complex subsurface conditions.

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The interaction between surface water and groundwater during flood events is a complex process that has traditionally been described using simplified analytical solutions, or abstracted numerical models. To make the problem tractable, it is common to idealize the flood event, simplify river channel geometry, and ignore bank soil heterogeneity, often resulting in a model that only loosely represents the site, thus limiting its applicability to any specific river cross-section. In this study, we calibrate a site-specific fully-integrated surface and subsurface HydroGeoSphere model using flood events for a cross-section along the South River near Waynesboro, VA. The calibration approach presented in this study demonstrates the incorporation of fining direction regularization with a highly parameterized inversion driven by natural stimuli, to develop several realistic realizations of hydraulic conductivity fields that reflect the depositional history of the system. Specifically, we calibrate a model with 365 unique material zones to multiple flood events recorded in a dense well network while incorporating possible fining sequences consistent with the depositional history of the riverbank. Over 25,000 individual simulations were completed using calibration software and a cloud platform specifically designed for highly parallelized computing environments. The results of this study demonstrate the use of fining direction regularization during model calibration to generate multiple calibrated model realizations that account for the depositional environment of the system.

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Over the past several decades, different groundwater modeling approaches of various complexities and data use have been developed. A recently developed approach for mapping hydraulic conductivity (K) and specific storage (Ss ) heterogeneity is hydraulic tomography, the performance of which has not been compared to other more "traditional" methods that have been utilized over the past several decades. In this study, we compare seven methods of modeling heterogeneity which are (1) kriging, (2) effective parameter models, (3) transition probability/Markov Chain geostatistics models, (4) geological models, (5) stochastic inverse models conditioned to local K data, (6) hydraulic tomography, and (7) hydraulic tomography conditioned to local K data using data collected in five boreholes at a field site on the University of Waterloo (UW) campus, in Waterloo, Ontario, Canada. The performance of each heterogeneity model is first assessed during model calibration. In particular, the correspondence between simulated and observed drawdowns is assessed using the mean absolute error norm, (L1 ), mean square error norm (L2 ), and correlation coefficient (R) as well as through scatterplots. We also assess the various models on their ability to predict drawdown data not used in the calibration effort from nine pumping tests. Results reveal that hydraulic tomography is best able to reproduce these tests in terms of the smallest discrepancy and highest correlation between simulated and observed drawdowns. However, conditioning of hydraulic tomography results with permeameter K data caused a slight deterioration in accuracy of drawdown predictions which suggests that data integration may need to be conducted carefully.

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The coupling of hydraulic and poroelastic processes is critical in predicting processes involving the deformation of the geologic medium in response to fluid extraction or injection. Numerical models that consider the coupling of hydraulic and poroelastic processes require the knowledge of relevant parameters for both aquifer and aquitard units. In this study, we jointly estimated hydraulic and poroelastic parameters from pumping test data exhibiting "reverse water level fluctuations," known as the Noordbergum effect, in aquitards adjacent to a pumped aquifer. The joint estimation was performed by coupling BIOT2, a finite element, two-dimensional, axisymmetric, groundwater model that considers poroelastic effects with the parameter estimation code PEST. We first tested our approach using a synthetic data set with known parameters. Results of the synthetic case showed that for a simple layered system, it was possible to reproduce accurately both the hydraulic and poroelastic properties for each layer. We next applied the approach to pumping test data collected at the North Campus Research Site (NCRS) on the University of Waterloo (UW) campus. Based on the detailed knowledge of stratigraphy, a five-layer system was modeled. Parameter estimation was performed by: (1) matching drawdown data individually from each observation port and (2) matching drawdown data from all ports at a single well simultaneously. The estimated hydraulic parameters were compared to those obtained by other means at the site yielding good agreement. However, the estimated shear modulus was higher than the static shear modulus, but was within the range of dynamic shear modulus reported in the literature, potentially suggesting a loading rate effect.

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Remediation of subsurface contamination requires an understanding of the contaminant (history, source location, plume extent and concentration, etc.), and, knowledge of the spatial distribution of hydraulic conductivity (K) that governs groundwater flow and solute transport. Many methods exist for characterizing K heterogeneity, but most if not all methods require the collection of a large number of small-scale data and its interpolation. In this study, we conduct a hydraulic tomography survey at a highly heterogeneous glaciofluvial deposit at the North Campus Research Site (NCRS) located at the University of Waterloo, Waterloo, Ontario, Canada to sequentially interpret four pumping tests using the steady-state form of the Sequential Successive Linear Estimator (SSLE) (Yeh and Liu 2000). The resulting three-dimensional (3D) K distribution (or K-tomogram) is compared against: (1) K distributions obtained through the inverse modeling of individual pumping tests using SSLE, and (2) effective hydraulic conductivity (K(eff) ) estimates obtained by automatically calibrating a groundwater flow model while treating the medium to be homogeneous. Such a K(eff) is often used for designing remediation operations, and thus is used as the basis for comparison with the K-tomogram. Our results clearly show that hydraulic tomography is superior to the inversions of single pumping tests or K(eff) estimates. This is particularly significant for contaminated sites where an accurate representation of the flow field is critical for simulating contaminant transport and injection of chemical and biological agents used for active remediation of contaminant source zones and plumes.

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The main purpose of this paper was to compare three approaches for predicting solute transport. The approaches include: (1) an effective parameter/macrodispersion approach (Gelhar and Axness 1983); (2) a heterogeneous approach using ordinary kriging based on core samples; and (3) a heterogeneous approach based on hydraulic tomography. We conducted our comparison in a heterogeneous sandbox aquifer. The aquifer was first characterized by taking 48 core samples to obtain local-scale hydraulic conductivity (K). The spatial statistics of these K values were then used to calculate the effective parameters. These K values and their statistics were also used for kriging to obtain a heterogeneous K field. In parallel, we performed a hydraulic tomography survey using hydraulic tests conducted in a dipole fashion with the drawdown data analyzed using the sequential successive linear estimator code (Yeh and Liu 2000) to obtain a K distribution (or K tomogram). The effective parameters and the heterogeneous K fields from kriging and hydraulic tomography were used in forward simulations of a dipole conservative tracer test. The simulated and observed breakthrough curves and their temporal moments were compared. Results show an improvement in predictions of drawdown behavior and tracer transport when the K tomogram from hydraulic tomography was used. This suggests that the high-resolution prediction of solute transport is possible without collecting a large number of small-scale samples to estimate flow and transport properties that are costly to obtain at the field scale.

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Hydraulic conductivity (K) and specific storage (S(s)) are required parameters when designing transient groundwater flow models. The purpose of this study was to evaluate the ability of commonly used hydrogeologic characterization approaches to accurately delineate the distribution of hydraulic properties in a highly heterogeneous glaciofluvial deposit. The metric used to compare the various approaches was the prediction of drawdown responses from three separate pumping tests. The study was conducted at a field site, where a 15 m × 15 m area was instrumented with four 18-m deep Continuous Multichannel Tubing (CMT) wells. Each CMT well contained seven 17 cm × 1.9 cm monitoring ports equally spaced every 2 m down each CMT system. An 18-m deep pumping well with eight separate 1-m long screens spaced every 2 m was also placed in the center of the square pattern. In each of these boreholes, cores were collected and characterized using the Unified Soil Classification System, grain size analysis, and permeameter tests. To date, 471 K estimates have been obtained through permeameter analyses and 270 K estimates from empirical relationships. Geostatistical analysis of the small-scale K data yielded strongly heterogeneous K fields in three-dimensions. Additional K estimates were obtained through slug tests in 28 ports of the four CMT wells. Several pumping tests were conducted using the multiscreen and CMT wells to obtain larger scale estimates of both K and S(s). The various K and S(s) estimates were then quantitatively evaluated by simulating transient drawdown data from three pumping tests using a 3D forward numerical model constructed using HydroGeoSphere (Therrien et al. 2005). Results showed that, while drawdown predictions generally improved as more complexity was introduced into the model, the ability to make accurate drawdown predictions at all CMT ports was inconsistent.

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For almost 80 years, deformation-induced head changes caused by poroelastic effects have been observed during pumping tests in multilayered aquifer-aquitard systems. As water in the aquifer is released from compressive storage during pumping, the aquifer is deformed both in the horizontal and vertical directions. This deformation in the pumped aquifer causes deformation in the adjacent layers, resulting in changes in pore pressure that may produce drawdown curves that differ significantly from those predicted by traditional groundwater theory. Although these deformation-induced head changes have been analyzed in several studies by poroelasticity theory, there are at present no practical guidelines for the interpretation of pumping test data influenced by these effects. To investigate the impact that poroelastic effects during pumping tests have on the estimation of hydraulic parameters, we generate synthetic data for three different aquifer-aquitard settings using a poroelasticity model, and then analyze the synthetic data using type curves and parameter estimation techniques, both of which are based on traditional groundwater theory and do not account for poroelastic effects. Results show that even when poroelastic effects result in significant deformation-induced head changes, it is possible to obtain reasonable estimates of hydraulic parameters using methods based on traditional groundwater theory, as long as pumping is sufficiently long so that deformation-induced effects have largely dissipated.

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Dense nonaqueous phase liquids (DNAPL) are prevalent at a large number of sites throughout the world. The variable release history, unstable flow, and geologic heterogeneity make the spatial distribution of DNAPLs complex. This causes difficulties in site remediation contributing to long-term groundwater contamination for decades to centuries. We present laboratory experiments to demonstrate the efficacy of Sequential Successive Linear Estimator (SSLE) algorithm that images DNAPL source zones. The algorithm relies on the fusion of hydraulic and partitioning tracer tomography (HPTT) to derive the best estimate of the K heterogeneity, DNAPL saturation (S(N)) distribution, and their uncertainty. The approach is nondestructive and can be applied repeatedly. Results from our laboratory experiments show that S(N) distributions compare favorably with DNAPL distributions observed in the sandbox but not so with local saturation estimates from core samples. We also found that the delineation of K heterogeneity can have a large impact on computed S(N) distributions emphasizing the importance of accurate delineation of hydraulic heterogeneity.

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