Extensive research has shown that back diffusion of contaminants stored in zones with lower hydraulic conductivity (K) can slow aquifer recovery, greatly extending the time to reach remediation goals. The project team addressed this research gap by developing a suite of field and modeling approaches that will allow users to better characterize low-K zones in the field, more accurately simulate mass transfer between low-K and high-K zones, and evaluate the impact of these processes on the time to reach groundwater cleanup goals following source removal. Specific technical objectives included:

  1. Develop low-cost direct push (DP) methods for high-resolution characterization of hydraulic conductivity.
  2. Determine if high-resolution solute transport models, primarily calibrated using DP tools, can provide satisfactory predictions of contaminant mass transfer between high and low K zones.
  3. Develop methods to calibrate existing and new mobile-immobile zone models using high-resolution K distributions obtained with DP equipment.
  4. Develop simplified methods for estimating the impact of matrix diffusion on cleanup time.

Technical Approach

A complementary set of field and modeling methods was developed for quantifying mobile-immobile mass transfer in shallow, unconsolidated settings. The hydraulic profiling tool (HPT) is commonly used for high-resolution (1.5 cm) characterization of K in moderate to high permeability formations. The HPT system consists of a water injection port with a transducer positioned behind it and an electrical conductivity sensor array. The original system is modified to allow water injection at lower flowrates, reducing pressure buildup, and allowing K measurement in lower permeability formations. To evaluate the value of this approach, high resolution site characterizations were completed at two contaminated sites where back diffusion of chlorinated solvents from low permeability zones was expected to extend cleanup times. These results were used to calibrate high-resolution flow and solute transport models and simulate the long-term impacts of back diffusion on site cleanup time. This information was also used to evaluate the use of a new semi-analytical modeling approach developed for simulating back diffusion. Sensitivity analyses were conducted to identify the parameters that have the greatest impact on cleanup times.


The current HPT system was modified for use in low-K settings. A combination of numerical simulations, laboratory experiments and field tests were performed to facilitate the low-K HPT tool development. The existing HPT system was modified by altering the water pump and flow meter, and then evaluated in a low permeability aquifer test cell and in the field. Simulation results were used to develop a simplified relationship for estimating K from the injection flow rate, pressure, probe advancement speed, and specific storage. This simplified relationship was evaluated by comparing HPT K estimates with slug test results in adjoining monitor wells.

Detailed field characterizations were completed at two contaminated sites – Air Force Plant 3 (AFP3) in Tulsa and Former Naval Training Center Orlando, Operable Unit 2 (OU2) in Orlando. Work included HPT profiling, Cone Penetrometer Test profiling, and traditional site characterization approaches. Numerical simulations showed that at both AFP3 and OU2, large spatial variations in K had a major influence on the groundwater cleanup rate in down-gradient monitor wells. Trichloroethene (TCE) was rapidly flushed from higher K zones, but declined much more slowly in lower K zones. In long-screened monitoring wells, this gave the appearance of a slow gradual decline in TCE concentrations.

A new modeling approach (semi-analytic method) was developed and tested, that allows for simple, efficient simulation of diffusive mass transfer between high and low K zones. This semi-analytic method accurately reproduces analytical and high-resolution numerical model results for a variety of geometries. The new method has three geometrical parameters, but these can be reduced to two parameters by assuming a logical relationship between the low permeability zone volume, the interfacial area, and the characteristic diffusion length. The key matrix diffusion parameters needed for this model, the volume fraction of high permeability material and the characteristic diffusion length, can be estimated from well logs.

Sensitivity analyses were conducted with Remediation Evaluation Model for Chlorinated Solvents-MD to identify the physical parameters that have the greatest influence on the time to reach one, two and three order-of-magnitude reductions in contaminant concentrations following source removal. These results were then used to develop simplified relationships for estimating cleanup time.


This project has substantially improved the understanding of mobile-immobile mass transfer and its impacts on the fate and transport of contaminants in shallow groundwater systems. Project results include a set of tools to better characterize sites with significant low-K zones; estimate the rate, timing and duration of contaminant release from those zones; and evaluate the impact of contaminant mass stored in low K zones on long-term plume behavior. This will provide site managers with more accurate estimates of the time to reach groundwater cleanup goals following source removal.


Borden, R.C., K.Y. Cha, and G. Liu. 2020. A Physically Based Approach for Estimating Hydraulic Conductivity from HPT Pressure and Flowrate. Groundwater.  doi: 10.1111/gwat.13039

Falta, R.W. and W. Wang. 2017. A Semi-analytical Method for Simulating Matrix Diffusion in Numerical Transport Models. Journal of Contaminant Hydrology, 197:39-49.

Liu, G., R. Borden, and J.J. Butler, Jr. 2019. Simulation Assessment of Direct Push Injection Logging for High Resolution Aquifer Characterization. Groundwater, 57(4);262-574. doi: 10.1111/gwat.12826

Muskus, N. and R.W. Falta. 2018. Semi-analytical Method for Matrix Diffusion in Heterogeneous and Fractured Systems with Parent-daughter Reactions. Journal of Contaminant Hydrology, 218:94-109.