A Simple Field Method for Assessing Near‐Surface Saturated Hydraulic Conductivity

This technical note describes an effective and inexpensive field technique for measuring the saturated hydraulic conductivity of both undisturbed cores and repacked soil samples. The method requires no specialized equipment; everything that is required can be obtained in a hardware store. The method is a straightforward field implementation of the widely used falling‐head laboratory analysis directly derived from Darcy's law. As such, it sidesteps the need for empirical assumptions about soil texture and the relationship between saturated and unsaturated flow components which many permeameter‐based methods rely upon. The method is shown to produce results that are consistent with K values obtained elsewhere in the same homogeneous sand formation. Furthermore, the proposed method is useful for measuring hydraulic conductivity in drill cuttings obtained from direct push or auguring drill techniques, which cannot be done with any other field method. The range of hydraulic conductivity values that this test is appropriate for is on the order of 1E ? 7 m/s to 1E ? 3 m/s.     

Assessing the Hydraulic Conductivity Anisotropy and Skin-Effect Based on Data of Slug Tests in Partially Penetrating Wells

Water Resources - A semianalytic and approximate analytical solution is given to the problem of slug test in a partially penetrating well in a confined or unconfined anisotropic aquifer. An...     

Surfactant-Induced Reductions in Soil Hydraulic Conductivity

Surfactant solutions are being proposed for in situ flushing of organic contaminants from soils and aquifers. The feasibility of surfactant additives in remediation may depend in large part on how these chemicals affect the hydraulic conductivity of the porous media. While there is evidence in the literature of conductivity loss during surfactant flushing (Miller et al. 1975; Nash et al. 1987), there has been little research on quantifying the process for unconsolidated sediments. Surfactant-affected hydraulic conductivity reductions were measured in two soils (Teller loam and Daugherty sand). Testing was done with eight surfactants at a variety of concentrations (10^-5 to 10^-l mole/kg), surfactant mixtures, and added solution electrolytes. The Teller was also tested with its organic matter removed. Maximum hydraulic conductivity decreases were 47 percent for the sand and more than two orders of magnitude for the loam. Surfactant concentrations, surfactant mixtures, soil organic content, and added solution electrolytes all affected the degree of conductivity reduction. Results indicate that surfactant-affected hydraulic conductivity losses should be considered prior to in situ remediation and may preclude surfactant use in some fine grain soils.     

Assessing TCE Source Bioremediation by Geostatistical Analysis of a Flux Fence

Mass discharge across transect planes is increasingly used as a metric for performance assessment of in situ groundwater remediation systems. Mass discharge estimates using concentrations measured in multilevel transects are often made by assuming a uniform flow field, and uncertainty contributions from spatial concentration and flow field variability are often overlooked. We extend our recently developed geostatistical approach to estimate mass discharge using transect data of concentration and hydraulic conductivity, so accounting for the spatial variability of both datasets. The magnitude and uncertainty of mass discharge were quantified by conditional simulation. An important benefit of the approach is that uncertainty is quantified as an integral part of the mass discharge estimate. We use this approach for performance assessment of a bioremediation experiment of a trichloroethene (TCE) source zone. Analyses of dissolved parent and daughter compounds demonstrated that the engineered bioremediation has elevated the degradation rate of TCE, resulting in a two‐thirds reduction in the TCE mass discharge from the source zone. The biologically enhanced dissolution of TCE was not significant (～5%), and was less than expected. However, the discharges of the daughter products cis‐1,2, dichloroethene (cDCE) and vinyl chloride (VC) increased, probably because of the rapid transformation of TCE from the source zone to the measurement transect. This suggests that enhancing the biodegradation of cDCE and VC will be crucial to successful engineered bioremediation of TCE source zones.     

Simple Hydraulic Conductivity Estimation by the Kalman Filtered Double Constraint Method

This paper presents the Kalman Filtered Double Constraint Method (DCM‐KF) as a technique to estimate the hydraulic conductivities in the grid blocks of a groundwater flow model. The DCM is based on two forward runs with the same initial grid block conductivities, but with alternating flux‐head conditions specified on parts of the boundary and the wells. These two runs are defined as: (1) the flux run, with specified fluxes (recharge and well abstractions), and (2) the head run, with specified heads (measured in piezometers). Conductivities are then estimated as the initial conductivities multiplied by the fluxes obtained from the flux run and divided by the fluxes obtained from the head run. The DCM is easy to implement in combination with existing models (e.g., MODFLOW). Sufficiently accurate conductivities are obtained after a few iterations. Because of errors in the specified head‐flux couples, repeated estimation under varying hydrological conditions results in different conductivities. A time‐independent estimate of the conductivities and their inaccuracy can be obtained by a simple linear KF with modest computational requirements. For the Kleine Nete catchment, Belgium, the DCM‐KF yields sufficiently accurate calibrated conductivities. The method also results in distinguishing regions where the head‐flux observations influence the calibration from areas where it is not able to influence the hydraulic conductivity.     

Estimating Tortuosity Coefficients Based on Hydraulic Conductivity

While the tortuosity coefficient is commonly estimated using an expression based on total porosity, this relationship is demonstrated to not be applicable (and thus is often misapplied) over a broad range of soil textures. The fundamental basis for a correlation between the apparent diffusion tortuosity coefficient and hydraulic conductivity is demonstrated, although such a relationship is not typically considered. An empirical regression for estimating the tortuosity coefficient based on hydraulic conductivity for saturated, unconsolidated soil is derived based on results from 14 previously reported diffusion experiments performed with a broad range of soil textures. Analyses of these experimental results confirm that total porosity is a poor predictor for the tortuosity coefficient over a large range of soil textures. The apparent diffusion tortuosity coefficient is more reliably estimated based on hydraulic conductivity.     

A Method to Estimate the Hydraulic Conductivity of the Ground by TRT Analysis

The knowledge of hydraulic properties of aquifers is important in many engineering applications. Careful design of ground‐coupled heat exchangers requires that the hydraulic characteristics and thermal properties of the aquifer must be well understood. Knowledge of groundwater flow rate and aquifer thermal properties is the basis for proper design of such plants. Different methods have been developed in order to estimate hydraulic conductivity by evaluating the transport of various tracers (chemical, heat etc.); thermal response testing (TRT) is a specific type of heat tracer that allows including the hydraulic properties in an effective thermal conductivity value. Starting from these considerations, an expeditious, graphical method was proposed to estimate the hydraulic conductivity of the aquifer, using TRT data and plausible assumption. Suggested method, which is not yet verified or proven to be reliable, should be encouraging further studies and development in this direction.     

Changes in Entrapped Gas Content and Hydraulic Conductivity with Pressure

Water table fluctuations continuously introduce entrapped air bubbles into the otherwise saturated capillary fringe and groundwater zone, which reduces the effective (quasi‐saturated) hydraulic conductivity, K_quasi, thus impacting groundwater flow, aquifer recharge and solute and contaminant transport. These entrapped gases will be susceptible to compression or expansion with changes in water pressure, as would be expected with water table (and barometric pressure) fluctuations. Here we undertake laboratory experiments using sand‐packed columns to quantify the effect of water table changes of up to 250 cm on the entrapped gas content and the quasi‐saturated hydraulic conductivity, and discuss our ability to account for these mechanisms in ground water models. Initial entrapped air contents ranged between 0.080 and 0.158, with a corresponding K_quasi ranging between 2 and 6 times lower compared to the K_s value. The application of 250 cm of water pressure caused an 18% to 26% reduction in the entrapped air content, resulting in an increase in K_quasi by 1.16 to 1.57 times compared to its initial (0 cm water pressure) value. The change in entrapped air content measured at pressure step intervals of 50 cm, was essentially linear, and could be modeled according to the ideal gas law. Meanwhile, the changes in K_quasi with compression–expansion of the bubbles because of pressure changes could be adequately captured with several current hydraulic conductivity models.     

Hydraulic Tomography: 3D Hydraulic Conductivity,Fracture Network,and Connectivity in Mudstone

We present the first demonstration of hydraulic tomography (HT) to estimate the three-dimensional (3D) hydraulic conductivity (K) distribution of a fractured aquifer at high-resolution field scale (HRFS), including the fracture network and connectivity through it. We invert drawdown data collected from packer-isolated borehole intervals during 42 pumping tests in a wellfield at the former Naval Air Warfare Center, West Trenton, New Jersey, in the Newark Basin. Five additional tests were reserved for a quality check of HT results. We used an equivalent porous medium forward model and geostatistical inversion to estimate 3D K at high resolution (K blocks <1 m³), using no strict assumptions about K variability or fracture statistics. The resulting 3D K estimate ranges from approximately 0.1 (highest-K fractures) to approximately 10⁻¹³ m/s (unfractured mudstone). Important estimated features include: (1) a highly fractured zone (HFZ) consisting of a sequence of high-K bedding-plane fractures; (2) a low-K zone that disrupts the HFZ; (3) several secondary fractures of limited extent; and (4) regions of very low-K rock matrix. The 3D K estimate explains complex drawdown behavior observed in the field. Drawdown tracing and particle tracking simulations reveal a 3D fracture network within the estimated K distribution, and connectivity routes through the network. Model fit is best in the shallower part of the wellfield, with high density of observations and tests. The capabilities of HT demonstrated for 3D fractured aquifer characterization at HRFS may support improved in situ remediation for contaminant source zones, and applications in mining, repository assessment, or geotechnical engineering.     

NMR Logging to Estimate Hydraulic Conductivity in Unconsolidated Aquifers

Nuclear magnetic resonance (NMR) logging provides a new means of estimating the hydraulic conductivity (K) of unconsolidated aquifers. The estimation of K from the measured NMR parameters can be performed using the Schlumberger‐Doll Research (SDR) equation, which is based on the Kozeny–Carman equation and initially developed for obtaining permeability from NMR logging in petroleum reservoirs. The SDR equation includes empirically determined constants. Decades of research for petroleum applications have resulted in standard values for these constants that can provide accurate estimates of permeability in consolidated formations. The question we asked: Can standard values for the constants be defined for hydrogeologic applications that would yield accurate estimates of K in unconsolidated aquifers? Working at 10 locations at three field sites in Kansas and Washington, USA, we acquired NMR and K data using direct‐push methods over a 10‐ to 20‐m depth interval in the shallow subsurface. Analysis of pairs of NMR and K data revealed that we could dramatically improve K estimates by replacing the standard petroleum constants with new constants, optimal for estimating K in the unconsolidated materials at the field sites. Most significant was the finding that there was little change in the SDR constants between sites. This suggests that we can define a new set of constants that can be used to obtain high resolution, cost‐effective estimates of K from NMR logging in unconsolidated aquifers. This significant result has the potential to change dramatically the approach to determining K for hydrogeologic applications.