Predicting the dissolution rates of immiscible contaminants in groundwater is crucial for developing environmental remediation strategies, but quantitative modeling efforts are inherently subject to multiple uncertainties. These include unknown residual amounts of non-aqueous phase liquids (NAPL) and source zone dimensions, inconsistent historical monitoring of contaminant mass discharge, and the mathematical simulation of field-scale mass transfer processes. Effective methods for simulating NAPL dissolution must therefore be able to assimilate a variety of data through physical and scalable mass transfer parameters to quantify and reduce site-specific uncertainties. This investigation coupled upscaled and numerical mass transfer modeling with uncertainty analyses to understand and develop data-assimilation and parameter-scaling methods for characterizing NAPL source zones and predicting depletion timeframes.
Parameters of key interest regulating kinetic NAPL persistence and contaminant fluxes are residual mass and saturation, but neither can be measured directly at field sites. However, monitoring and characterization measurements can constrain source zone dimensions, where NAPL mass is distributed. This work evaluated the worth of source zone delineation and dissolution monitoring for estimating NAPL mass and mass transfer coefficients at multiple scales of spatial resolution. Mass transfer processes in controlled laboratory and field experiments were analyzed by simulating monitored dissolved-phase concentrations through the parameterization of explicit and lumped system properties in volume-averaged (VA) and numerical models of NAPL dissolution, respectively. Both methods were coupled with uncertainty analysis tools to investigate the relationship between data availability and model design for accurately constraining system parameters and predictions. The modeling approaches were also combined for reproducing experimental bulk effluent rates in discretized domains, explicitly parameterizing mass transfer coefficients at multiple grid scales.
Research findings linked dissolved-phase monitoring signatures to model estimates of NAPL persistence, supported by source zone delineation data. The accurate characterization of source zone properties and kinetic dissolution rates, governing NAPL longevity, was achieved by adjusting model parameterization complexity to data availability. While multistage effluent rates accurately constrained explicit-process parameters in VA models, spatially-varying lumped-process parameters estimated from late dissolution stages also constrained unbiased predictions of NAPL depletion. Advantages of the numerical method included the simultaneous assimilation of bulk and high-resolution monitoring data for characterizing the distribution of residual NAPL mass and dissolution rates, whereas the VA method predicted source dissipation timeframes from delineation data alone. Additionally, comparative modeling analyses resulted in a methodology for scaling VA mass transfer coefficients to simulate NAPL dissolution and longevity at multiple grid resolutions. This research suggests feasibility in empirical constraining of lumped-process parameters by applying VA concepts to numerical mass transfer and transport models, enabling the assimilation of monitoring and source delineation data to reduce site-specific uncertainties. / Doctor of Philosophy / Predicting the dissolution rates of immiscible contaminants in groundwater is crucial for developing environmental restoration strategies, but quantitative modeling efforts are inherently subject to multiple uncertainties. These include unknown mass and dimensions of contaminant source zones, inconsistent groundwater monitoring, and the mathematical simulation of physical processes controlling dissolution rates at field scales. Effective simulation methods must therefore be able to leverage a variety of data through rate-limiting parameters suitable for quantifying and reducing uncertainties at contaminated sites. This investigation integrated mathematical modeling with uncertainty analyses to understand and develop data-driven approaches for characterizing contaminant source zones and predicting dissolution rates at multiple measurement scales.
Parameters of key interest regulating the lifespan of source zones are the distribution and amount of residual contaminant mass, which cannot be measured directly at field sites. However, monitoring and site characterization measurements can constrain source zone dimensions, where contaminant mass is distributed. This work evaluated the worth of source zone delineation and groundwater monitoring for estimating contaminant mass and dissolution rates at multiple measurement scales. Rate-limiting processes in controlled laboratory and field experiments were analyzed by simulating monitored groundwater concentrations through the explicit and lumped representation of system properties in volume-averaged (VA) and numerical models of contaminant dissolution, respectively. Both methods were coupled with uncertainty analysis tools to investigate the relationship between data availability and model design for accurately constraining system parameters and predictions. The approaches were also combined for predicting average contaminant concentrations at multiple scales of spatial resolution.
Research findings linked groundwater monitoring profiles to model estimates of contaminant persistence, supported by source zone delineation data. The accurate characterization of source zone properties and contaminant dissolution rates was achieved by adjusting model complexity to data availability. While monitoring profiles indicating multi-rate contaminant dissolution accurately constrained explicit-process parameters in VA models, spatially-varying lumped parameters estimated from late dissolution stages also constrained unbiased predictions of source mass depletion. Advantages of the numerical method included the simultaneous utilization of average and spatially-detailed monitoring data for characterizing the distribution of contaminant mass and dissolution rates, whereas the VA method predicted source longevity timeframes from delineation data alone. Additionally, comparative modeling analyses resulted in a methodology for scaling estimable VA parameters to predict contaminant dissolution rates at multiple scales of spatial resolution. This research suggests feasibility in empirical constraining of lumped parameters by applying VA concepts to numerical models, enabling a comprehensive data-driven methodology to quantify environmental risk and support groundwater cleanup designs.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/115551 |
| Date | 27 June 2023 |
| Creators | Prieto Estrada, Andres Eduardo |
| Contributors | Civil and Environmental Engineering, Widdowson, Mark A., Grant, Stanley, Burbey, Thomas J., Stewart, Lloyd "Bo" |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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