Evaluating the impact of back diffusion on groundwater cleanup time.

Back diffusion of groundwater contaminants from low permeability (K) zones can be a major factor controlling the time to reach cleanup goals in downgradient monitor wells. We identify the aquifer and contaminant characteristics that have the greatest influence on the time (TOoM) after complete source removal for contaminant concentrations to decline by 1, 2 and 3 Orders-of-Magnitude (T1, T2 and T3). Two aquifer configurations are evaluated: (a) layered geometry (LG) with finite thickness low K layers; and (b) boundary geometry (BG) with thick semi-infinite low K boundaries. A semi-analytical modeling approach (Muskus and Falta, 2018) is used to simulate the concentration decline following source removal for a range of conditions and generate ≈21,000 independent values of T1, T2 and T3. Linear regression is applied to interpret this large dataset and develop simple relationships to estimate TOoM from three characteristic parameters - the mass residence time (TM), diffusion time (TD), and ratio of low K to high K mass storage (γ). TM is most important predictor of T1, T2 and T3 for both geometries and is equal to the combined high and low K contaminant mass divided by the mass flux, at the end of the loading period (TL). For LG, T3 is strongly influenced by TD = RLLD2/(4D*), where RL is the low K retardation factor, LD is the half-thickness of the embedded low K layers, and D* is the effective diffusion coefficient. For BG, T3 is strongly influenced by γ. Contaminant decay in low K zones can significantly reduce cleanup times when λLTD > 0.01, where λL is the effective first order decay rate in the low K zone. The 1st Damköhler (Da), equal to TM/TD, provides a useful indicator of the relative importance of back diffusion on TOoM. Back diffusion impacts are greatest on T3 when 0.01 > Da > 0.1, then decrease with increasing Da. Back diffusion has less impacts on T2, with limited influence on T1. The results are summarized in a simple conceptual model to aid in evaluating the impact of back diffusion on the time for concentrations to decline by 1-3 OoM.

A Physically Based Approach for Estimating Hydraulic Conductivity from HPT Pressure and Flowrate.

The hydraulic profiling tool (HPT) is widely used to generate profiles of relative permeability vs. depth. In this work, prior numerical modeling results are used to develop a relationship between probe advance rate V (cm/s), probe diameter D (cm), water injection rate Q (mL/min), corrected pressure Pc (psi), and hydraulic conductivity K (feet/d) [Formula: see text] where E is an empirically derived hydraulic efficiency factor. The relationship is validated by 23 HPT profiles that, after averaging K vertically, were similar to slug test results in adjoining monitoring wells. The best fit value of E for these profiles was 2.02. This equation provides a physically based approach for generating hydraulic conductivity profiles with HPT tooling.

Screening-level estimates of mass discharge uncertainty from point measurement methods.

The uncertainty of mass discharge measurements associated with point-scale measurement techniques was investigated by deriving analytical solutions for the mass discharge coefficient of variation for two simplified, conceptual models. In the first case, a depth-averaged domain was assumed, consisting of one-dimensional groundwater flow perpendicular to a one-dimensional control plane of uniformly spaced sampling points. The contaminant flux along the control plane was assumed to be normally distributed. The second case consisted of one-dimensional groundwater flow perpendicular to a two-dimensional control plane of uniformly spaced sampling points. The contaminant flux in this case was assumed to be distributed according to a bivariate normal distribution. The center point for the flux distributions in both cases was allowed to vary in the domain of the control plane as a uniform random variable. Simplified equations for the uncertainty were investigated to facilitate screening-level evaluations of uncertainty as a function of sampling network design. Results were used to express uncertainty as a function of the length of the control plane and number of wells, or alternatively as a function of the sample spacing. Uncertainty was also expressed as a function of a new dimensionless parameter, Ω, defined as the ratio of the maximum local flux to the product of mass discharge and sample density. Expressing uncertainty as a function of Ω provided a convenient means to demonstrate the relationship between uncertainty, the magnitude of a local hot spot, magnitude of mass discharge, distribution of the contaminant across the control plane, and the sampling density.

Impact of injection system design on ISCO performance with permanganate--mathematical modeling results.

In situ chemical oxidation (ISCO) using permanganate (MnO(4)(-)) can be a very effective technique for remediation of soil and groundwater contaminated with chlorinated solvents. However, many ISCO projects are less effective than desired because of poor delivery of the chemical reagents to the treatment zone. In this work, the numerical model RT3D was modified and applied to evaluate the effect of aquifer characteristics and injection system design on contact and treatment efficiency. MnO(4)(-) consumption was simulated assuming the natural oxidant demand (NOD) is composed of a fraction that reacts instantaneously and a fraction that slowly reacts following a 2nd order relationship where NOD consumption rate increases with increasing MnO(4)(-) concentration. MnO(4)(-) consumption by the contaminant was simulated as an instantaneous reaction. Simulation results indicate that the mass of permanganate and volume of water injected has the greatest impact on aquifer contact efficiency and contaminant treatment efficiency. Several small injection events are not expected to increase contact efficiency compared to a single large injection event, and can increase the amount of un-reacted MnO(4)(-) released down-gradient. High groundwater flow velocities can increase the fraction of aquifer contacted. Initial contaminant concentration and contaminant retardation factor have only a minor impact on volume contact efficiency. Aquifer heterogeneity can have both positive and negative impacts on remediation system performance, depending on the injection system design.