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.     

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.     

Assessing Lakebed Hydraulic Conductivity and Seepage Flux by Potentiomanometer

Potentiomanometers (PMs) are commonly used to determine flux directions across interfaces between surface waters and aquifers. We describe a complementary function: estimating small‐scale hydraulic conductivity (K) in a lakebed, using the constant‐head injection test (CHIT) by Cardenas and Zlotnik (2003) with the PM designed by Winter et al. (1988). A piezometer with a small screen is inserted into the lakebed. Local head potential is obtained by measuring the head difference between the test point and the aquifer interface. The piezometer is then used for water injection. This technique is illustrated by measurements taken from Alkali Lake in the Sand Hills, Nebraska, United States. Lakebed K and seepage fluxes ranged from 0.037 to 0.090 m/d and Darcy velocities ranged from 0.004 to 0.027 m/d. Results were consistent with the supplementary data gathered using a modified CHIT and a cone penetrometer. The compact size of the device and the small volumes used for injection enable this method to estimate lakebed K values as low as 0.01 to 0.1 m/d, a range seldom explored in lake‐aquifer interface systems.     

Determining Hydraulic Conductivity Using Pumping Data from Low-Flow Sampling

Hydraulic conductivity values computed using the steady-state discharge and drawdown attained while low-flow sampling were evaluated to determine if they were equivalent to those determined from slug testing. Based on testing 12 wells, it was found that the results were statistically equivalent. Conductivity values computed using low-flow sampling parameters were also evaluated as to their reproducibility in actual practice by analyzing consultant data for three wells sampled over three quarterly monitoring periods by four field technicians. The results were found to be reproducible within about a factor of 2 or better. Since the method is based on only one pair of parameters, diligence is required in attaining steady state and in accurately measuring the flow rate and drawdown. Conductivity values computed using this approach can enhance the use of low-flow data gathered in water quality sampling, avoid the need for slug testing in a subsequent phase of investigation, and help reduce the cost of characterizing sites when multilevel samplers are used. Given the practical range of discharge in low-flow sampling, the method was found to be applicable at conductivity values somewhat greater than 10⁻⁶ cm/s. Given the typical accuracy of water level meters and pressure transducers and a maximum discharge of 1 L/min, as mandated by regulatory guidance, the method has a calculated upper conductivity limit in the range of 10⁻³ to 10⁻² cm/s.     

A Falling-Head Method for Measuring Intertidal Sediment Hydraulic Conductivity

This paper presents an in situ falling-head method for measuring hydraulic conductivity of beach sediments in tidal environment. A polyvinyl chloride (PVC) standpipe was vertically pushed into the submerged beach sediments so that its lower part was filled by a sediment column. During the experiment, the sediments were submerged by sea water and the standpipe top was higher than the sea level. The pipe was fully filled with sea water at the beginning of the experiment. Then the water level time series inside and outside the standpipe were recorded. Analytical solutions were derived to describe the relation among the sediment's hydraulic conductivity and the water levels inside and outside the standpipe and used to analyze the experiment data obtained from the intertidal zone of Puqian Bay, Haikou, Hainan Province, China. The water levels predicted by the analytical solution agreed very well with all the experiment data. Experiments for horizontal hydraulic conductivity estimation were also conducted using L-shaped standpipe which bends from vertical to horizontal in the beach sediments. The averaged hydraulic conductivity anisotropy ratio at the study area is about 2.9. After each in situ experiment, the sediments in the standpipe were stored in a plastic box and transported to university laboratory to measure the hydraulic conductivity using falling-head method. It is found that the in situ hydraulic conductivity averages one order of magnitude greater than the laboratory one, indicating that the original beach surface sediments were loose due to tidal and wave actions and that the samples were significantly compacted during the transportation to laboratory.     

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.     

Approximation of van Genuchten Parameter Ranges from Hydraulic Conductivity Data

The use of retention function and relative conductivity function is essential for the calculation of flow in a variably saturated media using the Richards equation. A widely used mathematical model for this is the Mualem-van Genuchten model which requires the shape parameters and . These, however, are difficult to obtain. When data is scarce, and are often taken from literature and may deviate largely from actual values. The current study presents a novel mathematical model for the approximation of $$ and $$ and for the further estimation of realistic value ranges, which may be used as parameter space, for example, for the calibration of a numerical model. The model was developed for cases where data is scarce and only values of saturated hydraulic conductivity are available. It is based on a large data set from literature and it is demonstrated that the model estimates mean values from that data set with a good accuracy. In order to show the applicability of the model, a second data set has been compiled anew (provided as Supporting Information). The model is incorporated into the current version of the freeware computer program HYPAGS, which enables easy usage.     

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.