Peter F. Andersen

Remedial Action Assessment for Hazardous Waste Sites Via Numerical Simulation

Abstract A common remedial action at many hazardous waste sites consists of some type of hydraulic control which generally takes the form of one or a combination of the following: (1) drains, (2) wells and (3) permeability barriers such as walls and caps. All of these hydraulic controls have been tested in construction projects where workers need dry conditions. Under these circumstances, time frames are relatively short (a few years or less) and monitoring is very accurate (workers identifying leaks within days). For hazardous waste sites, however, design criteria for hydraulic controls must consider time frames of many years and monitoring systems that include only a few observation points. Because the design criteria for construction projects and remediation are so different, there is no assurance that hydraulic controls will work equally well for both applications. For hazardous waste sites, uncertainty in the effectiveness of hydraulic controls has led to the combined use of modelling and monitoring. This usage of modelling in assessing various remedial actions is demonstrated by presenting simulation results from four hazardous waste sites. Groundwater flow modelling is used to evaluate various combinations of drains, walls and caps at the Lipari site in New Jersey. A variably-saturated flow model is applied to various combinations of a wall, cap and drains considered for the Love Canal site in Niagara Falls, NY. A flow and transport model is applied to a purge well system to recover a chlorinated hydrocarbon spill in New England. Finally, an immiscible flow model is applied to the S-Area site, also in Niagara Falls, to evaluate the remedial action necessary to prevent the downward movement of dense non-aqueous liquid. In all four applications, emphasis is placed on the groundwater system response to the remedial action. The results of such simulations may be used in an iterative fashion to improve both remedial design and monitoring.

The Ensemble Kalman Filter for Groundwater Plume Characterization: A Case Study: The Ensemble Kalman Filter for Groundwater Plume Characterization: A Case Study

The Kalman filter is an efficient data assimilation tool to refine an estimate of a state variable using measured data and the variables correlations in space and/or time. The ensemble Kalman filter (EnKF) (Evensen, 2004, 2009) is a Kalman filter variant that employs Monte Carlo analysis to define the correlations that help to refine the updated state. While use of EnKF in hydrology is somewhat limited, it has been successfully applied in other fields of engineering (e.g. oil reservoir modeling, weather forecasting). Here, EnKF is used to refine a simulated groundwater TCE plume that underlies the Tooele Army Depot-North (TEAD-N) in Utah, based on observations of TCE in the aquifer. The resulting EnKF-based assimilated plume is simulated forward in time to predict future plume migration. The correlations that underpin EnKF updating implicitly contain information about how the plume developed over time under the influence of complex site hydrology and variable source history, as they are predicated on multiple realizations of a well-calibrated numerical groundwater flow and transport model. The EnKF methodology is compared to an ordinary kriging-based assimilation method with respect to the accurate representation of plume concentrations in order to determine the relative efficacy of EnKF for water quality data assimilation.

The Ensemble Kalman Filter for Groundwater Plume Characterization: A Case Study: J.L. Ross and P.F. Andersen Groundwater XX, no. XX: XX-XX

The Kalman filter is an efficient data assimilation tool to refine an estimate of a state variable using measured data and the variables correlations in space and/or time. The ensemble Kalman filter (EnKF) (Evensen 2004, 2009) is a Kalman filter variant that employs Monte Carlo analysis to define the correlations that help to refine the updated state. While use of EnKF in hydrology is somewhat limited, it has been successfully applied in other fields of engineering (e.g., oil reservoir modeling, weather forecasting). Here, EnKF is used to refine a simulated groundwater tetrachloroethylene (TCE) plume that underlies the Tooele Army Depot-North (TEAD-N) in Utah, based on observations of TCE in the aquifer. The resulting EnKF-based assimilated plume is simulated forward in time to predict future plume migration. The correlations that underpin EnKF updating implicitly contain information about how the plume developed over time under the influence of complex site hydrology and variable source history, as they are predicated on multiple realizations of a well-calibrated numerical groundwater flow and transport model. The EnKF methodology is compared to an ordinary kriging-based assimilation method with respect to the accurate representation of plume concentrations in order to determine the relative efficacy of EnKF for water quality data assimilation.

Continuous Improvement of a Groundwater Model over a 20-Year Period: Lessons Learned: P.F. Andersen et al. Groundwater xx, no. xx: xxx-xxx

Groundwater models developed for specific sites generally become obsolete within a few years due to changes in: (1) modeling technology; (2) site/project personnel; (3) project funding; and (4) modeling objectives. Consequently, new models are sometimes developed for the same sites using the latest technology and data, but without potential knowledge gained from the prior models. When it occurs, this practice is particularly problematic because, although technology, data, and observed conditions change, development of the new numerical model may not consider the conceptual models underpinnings. As a contrary situation, we present the unique case of a numerical flow and trichloroethylene (TCE) transport model that was first developed in 1993 and since revised and updated annually by the same personnel. The updates are prompted by an increase in the amount of data, exposure to a wider range of hydrologic conditions over increasingly longer timeframes, technological advances, evolving modeling objectives, and revised modeling methodologies. The history of updates shows smooth, incremental changes in the conceptual model and modeled aquifer parameters that result from both increase and decrease in complexity. Myriad modeling objectives have included demonstrating the ineffectiveness of a groundwater extraction/injection system, evaluating potential TCE degradation, locating new monitoring points, and predicting likelihood of exceedance of groundwater standards. The application emphasizes an original tenet of successful groundwater modeling: iterative adjustment of the conceptual model based on observations of actual vs. model response.

Continuous Improvement of a Groundwater Model Over a 20 Year Period: Lessons Learned: Continuous Improvement of a Groundwater Model Over a 20 Year Period: Lessons Learned

Groundwater models developed for specific sites generally become obsolete within a few years due to changes in: 1) modeling technology, 2) site/project personnel, 3) project funding, and 4) modeling objectives. Consequently, new models are sometimes developed for the same sites using the latest technology and data, but without potential knowledge gained from the prior models. When it occurs, this practice is particularly problematic because, although technology, data, and observed conditions change, development of the new numerical model may not consider the conceptual models underpinnings. As a contrary situation, we present the unique case of a numerical flow and Trichloroethylene (TCE) transport model that was first developed in 1993 and since revised and updated annually by the same personnel. The updates are prompted by an increase in the amount of data, exposure to a wider range of hydrologic conditions over increasingly longer timeframes, technological advances, evolving modeling objectives, and revised modeling methodologies. The history of updates shows smooth, incremental changes in the conceptual model and modeled aquifer parameters that result from both increases and decreases in complexity. Myriad modeling objectives have included demonstrating the ineffectiveness of a groundwater extraction/injection system, evaluating potential TCE degradation, locating new monitoring points, and predicting likelihood of exceedance of groundwater standards. The application emphasizes an original tenet of successful groundwater modeling: iterative adjustment of the conceptual model based on observations of actual versus model response.

Evolution of a Groundwater Model Over 20 Years

The regulatory agency overseeing cleanup actions at the Tooele Army Depot in Utah requires annual updating of the groundwater flow and solute transport model that is used as a decision tool for remedial actions. The model, which was originally developed in 1993, is now in its 20 th year of existence and use. The updates include incorporation of new data, revisions to the conceptual model, and recalibration of the numerical model. The revisions the model has gone through since its inception result from an increase in the amount of data, encountering a wider range of hydrologic conditions over a progressively longer period of time, technological advances, and changes in modeling methods. The original 3-layer, 300 ft cell width, steady-state, groundwater flow model of a 13.4 sq mi area has evolved to a 9-layer, 200 ft cell width, 70-year transient, groundwater flow and solute transport model of a 39.3 sq mi area. Revisions that have been made to the conceptual model over the years, including parameter values, are discussed along with the primary factors that elicited the revision. In general, it appears that consideration of plume trajectory, movement, and extent as well as mirroring abrupt spatial changes in water levels have constrained the model the most and hence led to revisions to the model. Technological advances have contributed to the ability to consider greater spatial resolution, a longer time frame, and analysis of a wider universe of realizations.