Subsurface Contaminant Transport Research Articles

Incorporating geological structure into sensitivity analysis of subsurface contaminant transport

Incorporating geological structure into sensitivity analysis of subsurface contaminant transport

Experimental and modeling insights into mixing-limited reactive transport in heterogeneous porous media: Role of stagnant zones

The understanding of mixing-controlled reactive dynamics in heterogeneous porous media remains limited, presenting significant challenges for modeling subsurface contaminant transport processes and for designing cost-effective environmental remedial efforts. The complexity of accurately observing, measuring, and modeling mixing-limited reactive transport has led to inadequate exploration of these critical processes. This study investigates the mixing and reaction kinetics affected by stagnant zones, which are commonly found in alluvial aquifers-aquitards and fracture-matrix systems. By conducting experiments involving conservative and bimolecular reactive transport through porous media within translucent chambers filled with two sizes of glass beads and under varying flow rates, we explored the effects of grain size and hydrodynamic conditions. Using a high-resolution camera, we monitored the concentration changes of conservative and reactive tracers, with subsequent interpretation through three-dimensional numerical simulations. The outcomes revealed the emergence of distinct mixing interfaces within both mobile and stagnant zones, culminating in a bi-peaked plume formation. Notably, the mixing and reaction times in media containing stagnant zones were found to be approximately 10 times longer than in homogeneous media. These findings, through experimental and modeling efforts, advance our understanding of mixing-limited reactive transport phenomena within heterogeneous media, underscoring the significant role of stagnant zones—a topic previously underexplored.

Multiscale pore‐network reconstruction of a fine‐textured heterogeneous soil

AbstractDigital samples offer many opportunities to study subsurface fluid flow and contaminant transport processes. The pore size distribution of especially fine‐textured porous media often covers many orders of magnitude in the length scale, which makes accurate microCT scanning and modeling of the underlying processes difficult. When a single‐resolution image is not capable of capturing all relevant details of a sample, one should scan the sample, or selected parts of it, at different resolutions. Combining multiple resolutions into one single sample for subsequent pore‐scale modeling is generally not possible due to limitations in computer memory and speed, thus making it necessary to create a simpler sample containing relevant information from the parent networks. We imaged four samples using different resolutions to capture the multiscale heterogeneity of a fine‐textured soil and combined them into one overall digital sample based on the original pore networks. The parent networks were characterized using their geometrical properties, correlations between these properties, and connectivity functions describing the network topologies. Our approach creates stochastic networks of arbitrary size with the same flow properties as the parent network. The method, implemented using the PoreStudio pore network model, repeatedly integrates information at two subsequent scales, with the resulting digital sample having the same hydraulic properties as the original samples. The procedure leads to more useful three‐dimensional digital models, facilitating basic analyses of underlying pore size distributions. Porosity calculations were compared with direct measurements, while those for the hydraulic conductivity were compared with estimates based on the particle size distribution and nearby field data.

Contaminant Transport Modeling and Source Attribution With Attention‐Based Graph Neural Network

AbstractGroundwater contamination induced by anthropogenic activities has long been a global issue. Characterizing and modeling contaminant transport processes is crucial to groundwater protection and management. However, challenges still exist in process complexity, data constraint, and computational cost. In the era of big data, the growth of machine learning has led to new opportunities in studying contaminant transport in groundwater systems. In this work, we introduce a new attention‐based graph neural network (aGNN) for modeling contaminant transport with limited monitoring data and quantifying causal connections between contaminant sources (drivers) and their spreading (outcomes). In five synthetic case studies that involve varying monitoring networks in heterogeneous aquifers, aGNN is shown to outperform LSTM‐based (long‐short term memory) and CNN‐ based (convolutional neural network) methods in multistep predictions (i.e., transductive learning). It also demonstrates a high level of applicability in inferring observations for unmonitored sites (i.e., inductive learning). Furthermore, an explanatory analysis based on aGNN quantifies the influence of each contaminant source, which has been validated by a physics‐based model with consistent outcomes with an R2 value exceeding 92%. The major advantage of aGNN is that it not only has a high level of predictive power in multiple scenario evaluations but also substantially reduces computational cost. Overall, this study shows that aGNN is efficient and robust for highly nonlinear spatiotemporal learning in subsurface contaminant transport, and provides a promising tool for groundwater management involving contaminant source attribution.

Engineering properties of microcapsules self-healing geopolymer cutoff wall backfill under dry-wet cycles

Vertical cutoff wall has been employed for decades to control groundwater flow and subsurface contaminant transport. Environmental stress fluctuations induced by alternating dry and wet conditions impair the permeability and durability of the cutoff wall, leading to the dispersion of contaminants. The objective of this study is to incorporate self-healing microcapsules into existing geopolymer cutoff wall backfill (GCWB) to form self-healing geopolymer cutoff wall backfill (SHGCWB) that hold promise for better durability and performance. The in-situ polymerization method was used to develop single-walled and double-walled microcapsules. The microcapsules use sodium silicate as the healing agent encapsulated in single-walled polyurethane (PU) and double-walled polyurethane/melamine-formaldehyde (PU/MF) microcapsules. The effect of microcapsules on the unconfined compressive strength (UCS) and hydraulic conductivity of SHGCWB were elaborated. The durability and hydraulic conductivity variation of SHGCWB in dry-wet cycle was thoroughly investigated by Scanning Electron Microscopy (SEM) test for understanding the self-healing mechanism. The overall performance demonstrated the significant potential of the use microcapsules as a self-healing approach for cutoff walls.

Influence of karst conduit’s geometry and morphology on 3D flow and transport processes: Insights from 3D tracer tests and numerical modelling

In karst, the characterization of subsurface solute and contaminant transport is a major issue that has been widely investigated due to the high vulnerability of these hydrosystems. In former studies, several researchers addressed these needs with different approaches such as laboratory experiments, field experiments, or groundwater flow and transport simulations. The objective of such approaches is to improve knowledge of transport processes in karst hydrosystems, and propose solutions to limit the downstream hydrogeological risks (contamination of water resources). In this study, we performed the 3D mapping of the karst conduit, which outlet is the Lez spring (southern France) to get the precise geometry and morphology of this fully water-filled karst conduit. Then we injected a dye in the water-filled karst conduit and performed a continuous monitoring of dye tracer recovery at three different cross-sections located downstream the injection spot, at a distance of 40 m, 90 m and 160 m, respectively. In each cross-section, five submersible fluorometer probes were positioned at different locations (top, right, down, left and central parts) along the cross-section of the karst conduit. Experimental data allowed to reconstruct the transient spatial distribution of concentration for each cross-section, which allowed assessing the propagation and evolution of solute plume over time. Monitored data also provided information about dye mixing along the karst conduit and were used to investigate the effect of karst conduit geometry, flow turbulences and velocity profiles on the mixing processes and propagation of solute plume along the conduit with numerical models. Modelling results showed that the consideration of 3D mapped karst conduit geometry and morphology allows a much better reproduction of observed transport processes and breakthrough curves, than the one obtain when considering simplified conduit geometry and morphology.

Durability of geopolymer cutoff wall backfill incorporating reactive MgO particles under dry-wet cycles

Vertical cutoff wall has been employed for decades to control groundwater flow and subsurface contaminant transport. The barrier performance of cutoff wall material may significantly deteriorate under dry-wet cycles due to precipitation, drought, and groundwater fluctuation. This study adopted active magnesium oxide (MgO) particles to enhance the durability of geopolymer cutoff wall backfill (GCWB) under dry-wet cycles. The influence of particle size and proportion of MgO on the unconfined compressive strength (UCS), hydraulic conductivity, self-healing capacity and durability of GCWB were comprehensively examined. The results indicate that the incorporation of active MgO particles hindered the geopolymerization process of GCWB to a certain extent, leading to an increase in hydraulic conductivity and a decrease in UCS. But the overall performance of GCWB was still favorable. The hydraulic conductivity of samples with MgO gradually increased to more than 1 × 10−8 m/s after at least two dry-wet cycles. In the subsequent cycles, the samples with MgO exhibited a pattern of first gradually declining then ascending in hydraulic conductivity. This is due to hydration and carbonization of the remained MgO in matrix during the dry-wet cycles, which converts into oxygen-rich carbonates, forming well-ramified networks and reducing the proportion of macropores. Thus, the durability of GCWB with MgO is significantly more favorable than that devoid of MgO. In particular, large particle size MgO can exert more persistent self-healing effect, endowing the samples with superior durability under the prolonged dry-wet cycles.

MODELS FOR ASSESSING AND PREDICTING THE SUBSURFACE TRANSPORT OF CONTAMINANTS FROM THE WASTEWATER IN THE EFFLUENT CHANNEL OF KCM AD - PLOVDIV, SOUTHERN BULGARIA

Until the end of the 20th century, the uncontrolled discharge of highly polluted emissions from the non-ferrous metals companies in Bulgaria was the cause of heavy contamination in vast areas around these industrial sites. In the last two decades, after the introduction of good environmental practices and the closure of polluting industries, a deceleration of the negative processes and a gradual cleaning of the already polluted waters and soils are observed. In order to evaluate and predict these processes, numerical 2D models of the conditions for the subsurface transport of contaminants from the wastewater in the effluent channel of KCM AD-Plovdiv are developed using the VS2DI computer programme. The scheme of convection-diffusion mass-transport is applied, taking into account the concomitant processes of reversible elimination, mechanical dispersion and mixing. Employing the developed models, the fate and transport of pollutants typical for this type of industrial sites – sulphate ions and cadmium (SO4 and Cd) are studied, taking into account their concentration in the wastewater before and after the application of modern technologies and equipment for remediation of contaminated water. The computer simulation encompasses the period from the construction of the effluent channel till 2035.

Reduced Accessible Air–Water Interfacial Area Accelerates PFAS Leaching in Heterogeneous Vadose Zones

AbstractPer‐ and polyfluoroalkyl substances (PFAS) are surface‐active contaminants experiencing strong retention in vadose zones due to adsorption at air–water and solid–water interfaces. Leaching of PFAS through vadose zones poses great risks of groundwater contamination. Prior PFAS transport studies have focused on homogenous or layered vadose zones that significantly underrepresented the impact of preferential flow caused by soil heterogeneities—a primary factor known to dominantly control the subsurface transport of many contaminants. We conduct numerical simulations to investigate the impact of preferential flow on PFAS leaching in stochastically generated heterogeneous vadose zones. The simulations show that while shorter‐chain PFAS experience accelerated leaching similar to non‐surfactant solutes, the accelerated leaching of more surface‐active longer‐chain PFAS is uniquely amplified by 1.1–4.5 times due to reduced accessible air–water interfacial areas along preferential flow pathways. Our study highlights the criticality of characterizing soil heterogeneities for accurately predicting the leaching of long‐chain PFAS in vadose zones.

Physics-Guided Data-Driven Seismic Inversion: Recent progress and future opportunities in full-waveform inversion

The goal of seismic inversion is to obtain subsurface properties from surface measurements. Seismic images have proven valuable, even crucial, for a variety of applications, including subsurface energy exploration, earthquake early warning, carbon capture and sequestration, estimating pathways of subsurface contaminant transport, etc. These subsurface properties (such as wave speed, density, and elastic velocities) influence the transmission of seismic waves through the subsurface media, and well-understood physics models (so-called “forward models”) can be used to predict what surface measurements would be made for any given subsurface configuration.

Subsurface Contaminant Transport Analysis for Flowpath Direction in Katni Watershed, Madhya Pradesh, India Using GIS and Groundwater Modeling Approach

The current study aims to identify the pathways of pollutants and travel time of contamination using Remote Sensing and GIS approach. In sight of this, to evaluate hazard, groundwater contaminant transport is analyzed by using the ground water model in Katni River watershed. Darcy flow and velocity have been used for contaminant transport analysis, which is one of the components of Arc GIS in Groundwater module extension. Modeling tools such as Kriging, Darcy Flow/Velocity and Linear Directional Mean were used to identify the groundwater path lines and travel time. The analysis was done by taking into account of vulnerable areas, the location of contaminant sources and infected wells and their well field. The hydro-geological properties of underlying rocks along with surface and groundwater elevation are also considered by simulations, found that flow lines intersect with the Katni River in numerous places and flow lines converge towards wells in the study area, implying contaminated water is carried to these areas from all directions. Consequentially, the quality of the surface and groundwater is determining the quality of water in the wells Keywords: Contaminant Transport Analysis, Pathways and Travel Time, Groundwater Flow Model, Darcy Flow, GIS, Kriging

Numerical analysis on the applicability of sorption isotherm models in aquifers and its correlation with recharged water movement

ABSTRACT Sorption is a necessary process influencing the subsurface solute or contaminant transport. There are many adsorption isotherms, and selecting one to represent the system is likely to remain an elusive goal. Also, the lack of observed data and its associated certainty may hinder the determination of sorption parameters. This study investigated the influence of different isotherms – linear adsorption assumption, Freundlich isotherm, Langmuir isotherm, and Redlich – Peterson isotherm, on chloride concentrations. The numerical model also gauged the extent of recharged waters migrating from the injection well. Temporal analysis of groundwater resident volumes helped to understand better the change in chloride concentrations with the selected isotherm. The residual solute concentrations from the isotherms followed the order: Redlich – Peterson < Freundlich < Langmuir. The results highlighted the importance of obtaining a range of sorption values rather than a single value from one fitted isotherm for the productive aid in groundwater decision making.

Vertical Barriers for Land Contamination Containment: A Review.

Soil pollution is one of the major threats to the environment and jeopardizes the provision of key soil ecosystem services. Vertical barriers, including slurry trench walls and walls constructed with soil mix technology, have been employed for decades to control groundwater flow and subsurface contaminant transport. This paper comprehensively reviewed and assessed the typical materials and mechanical and permeability properties of soil–bentonite, cement–bentonite and soil mix barriers, with the values of mix design and engineering properties summarized and compared. In addition, the damage and durability of barrier materials under mechanical, chemical, and environmental stresses were discussed. A number of landmark remediation projects were documented to demonstrate the effectiveness of the use of barrier systems. Recent research about crack-resistant and self-healing barrier materials incorporating polymers and minerals at Cambridge University and performance monitoring techniques were analyzed. Future work should focus on two main areas: the use of geophysical methods for non-destructive monitoring and the optimization of resilient barrier materials.

Theory-guided full convolutional neural network: An efficient surrogate model for inverse problems in subsurface contaminant transport

Identification of the location and strength of a contaminant source in an aquifer is a challenging but crucial task. Efficient surrogate models can be constructed to replace traditional time-consuming simulators while solving this inverse problem. In recent years, with the rapid development of machine learning (ML) algorithms, the artificial neural network (ANN) has been proven to be an efficient way for surrogate modeling. However, it may be difficult for ANN-based algorithms to learn the convection-dispersion equation and predict the contaminant concentration field due to their point-to-point learning scheme. Because of their strong localized features, the concentration fields can be seen as images. In contrast, the convolutional neural network (CNN) can extract spatial information better due to its convolutional structure. Herein, a theory-guided full convolutional neural network (TgFCNN) model is proposed to solve inverse problems in subsurface contaminant transport. TgFCNN can construct robust and reliable surrogate models with limited training realizations, and be further utilized for inverse modeling tasks. The loss function of TgFCNN comprises the residual of governing equations of contaminant transport, as well as data mismatch. Moreover, the iterative ensemble smoother (IES) method is employed to update the parameters while solving the inverse problems. The proposed TgFCNN model is evaluated in four scenarios. The results demonstrate that the TgFCNN model possesses strong generalization and extrapolation abilities, and satisfactory accuracy when estimating unknown contaminant source parameters, as well as the permeability field. The time consumption of the TgFCNN surrogate model for inverse tasks is also greatly reduced compared to using traditional simulators directly.

Stratigraphic identification with airborne electromagnetic methods at the Hanford Site, Washington

Stratigraphic units can influence the fate and transport of subsurface contaminants within groundwater. Units having coarse-grained sediments act as preferential flow pathways, and therefore can accelerate the transport of contaminants to reach human and ecological receptors. At legacy waste sites, detailed knowledge of subsurface stratigraphy can be used for effective monitoring and remediation planning to help minimize risk to human health and the environment. Airborne electromagnetic (AEM) methods can non-invasively provide information on kilometer-scale or larger subsurface stratigraphic features and fill informational gaps in directly sampled data from sparsely located boreholes. In this paper, we present inversion results of a 412 line-km frequency-domain AEM survey to delineate subsurface stratigraphic features at the Hanford Site, located in southeastern Washington State. The inversion was performed using a massively parallel 3D electromagnetic modeling and inversion code, where the modeling is based on solving frequency-domain Maxwell's equations using an unstructured-mesh finite-element method and the inversion employs a Gauss-Newton optimization scheme. The results are compared to an underlying geologic framework model (GFM), built by interpolating contact depths of stratigraphic units interpreted from site borehole datasets. In areas with good borehole coverage, the inversion results show a good match with the GFM to a depth of about 60 m. Outside of these areas, the inversion results exhibit inconsistencies from the assumptions made to create the GFM, demonstrating that the AEM survey results can be used to improve the understanding of the geological conceptual model.

Mechanisms of bentonite colloid aggregation, retention, and release in saturated porous media: Role of counter ions and humic acid

In the subsurface environment, colloids play an important role in pollutant transport by acting as the carriers. Understanding colloid release, transport, and deposition in porous media is a prerequisite for evaluating the potential role of colloids in subsurface contaminant transport. In this work, the aggregation, retention, and release of bentonite colloid in saturated porous sand media were investigated by kinetic aggregation and column experiments, the correlation and mechanism of these processes were revealed by combining colloid filtration theory, interaction energy calculation and density functional theory. The results showed that the retention and release of colloids were closely related to the dispersion stability and filtration effect. Multivalent cations with higher mineral affinity reduced the colloid stability, and the dispersion stability and mobility of the colloid were greatly improved by humic acid due to the enhancement of electrostatic repulsion and steric hindrance effects. The primary minimum interaction was found to contribute more to irreversible colloid retention in a Ca2+ system, while the secondary energy minimum was found to be responsible for colloid release with the occurrence of transient solution chemistry. The deposited colloid aggregates could be redistributed and released when the solution chemistry became favorable towards dispersion. These findings provide essential insight into the environmental colloid fate as well as a vital reference for the risk of colloid-driven transport of contaminants in the subsurface aquifer environment.

Groundwater characterization and monitoring at a complex industrial waste site using electrical resistivity imaging

A contaminated industrial waste site in Washington State (USA) containing buried, metallic-waste storage tanks, pipes, and wells, was evaluated to determine the feasibility of monitoring groundwater remediation activities associated with an underlying perched aquifer system using electrical resistivity tomography. The perched aquifer, located ~65 m below ground surface and ~10 m above the regional water table, contains high concentrations of nitrate, uranium, and other contaminants of concern from past tank leaks and intentional releases of wastes to surface disposal sites. The extent of the perched water aquifer is not well known, and the effectiveness of groundwater extraction for contaminant removal is uncertain, so supplemental characterization and monitoring technologies are being evaluated. Numerical simulations of subsurface flow and contaminant transport were performed with a highly resolved model of the hydrogeologic system and waste site infrastructure, and these simulations were used as the physical basis for electrical resistivity tomography modeling. The modeling explicitly accounted for metallic infrastructure at the site. The effectiveness of using surface electrodes versus surface and horizontal subsurface electrodes, for imaging groundwater extraction from the perched water aquifer, was investigated. Although directional drilling is a mature technology, its use for electrode emplacement in the deep subsurface under a complex industrial waste site via horizontal wells has not yet been demonstrated. Results from this study indicate that using horizontal subsurface electrode arrays could significantly improve the ability of electrical resistivity tomography to image deep subsurface features and monitor remediation activities under complex industrial waste sites.

The impact of stress orientation and fracture roughness on the scale dependency of permeability in naturally fractured rocks

The equivalent permeability of layered fractured rocks plays an important role in hydrocarbon recovery, underground energy storage, waste disposal management, groundwater hydrology, and subsurface contaminant transport. Borehole data contain some uncertainties/sampling bias during collection and interpretation. This sampling effect may lead to an inaccurate characterization of the fractured media. Studies show that long fractures with high permeability, which are rarely seen in borehole images, dominate the flow pattern and affect the overall permeability of the fractured system. This means that samples taken at any scale smaller than the scale of interest result in imprecise permeability upscaling.To understand this sampling problem, we have established an efficient sampling method to study the existence of the representative elementary volume (REV) in naturally fractured rocks. We selected a collection of outcrop data represented by discrete fracture and matrix (DFM) models in which fracture apertures are mechanically constrained. A finite-element-finite-volume approach is utilized to characterize the flow behavior of DFM models. Multiscale random sampling is combined with flow-based upscaling to determine the equivalent permeability tensor and its anisotropy by considering the variable orientation of the stress state and fracture roughness.Our findings indicate a convergence towards a scale-invariant equivalent permeability and fracture density with increasing sample size, and the equivalent permeability itself has a multimodal distribution. The spatial variation of the permeability tensor and the change in the degree of anisotropy with sample size reflect the inhomogeneity of the fracture patterns.

Comparison of chemical sediment analyses and field oiling observations from the Shoreline Cleanup Assessment Technique (SCAT) in heavily oiled areas of former mangrove in Bodo, eastern Niger Delta

Trial pitting, borehole drilling, and soil, sediment and groundwater sampling are important components of oil spill response and contaminated land assessment. These investigations provide detailed information on the subsurface geology and contaminant occurrence and transport but have disadvantages including worker safety hazards, cost and time required for completion, and may cause cross-contamination among aquifers. An alternative to such investigations applied in oil spill response is the Shoreline Cleanup Assessment Technique (SCAT) approach, which relies heavily on direct visual observations to assess the severity of oil contamination and guide cleanup efforts. Here, we compare SCAT observations of oil type, surface coverage and pit oiling with collected surface and subsurface sediment samples taken concurrently and analysed for a suite of hydrocarbon constituents. Results indicate that although limited sampling and analysis is required to chemically characterize the contamination, SCAT observations can be calibrated using limited sediment sampling and are sufficient to steer physical cleanup methods. This is particularly evident as even closely spaced chemical samples show high variability. A coarser direct visual observation is fit-for-purpose considering the wide variability in contaminant distribution at even local levels. In this contribution, we discuss the limitations of the different methods. Supplementary material: The modified SCAT data collection form, figures showing subsurface versus ground surface total petroleum hydrocarbons (TPH) and a variogram of TPH measured in the ground surface and subsurface samples, and data tables are available at https://doi.org/10.6084/m9.figshare.c.4534682 Thematic collection: This article is part of the Measurement and monitoring collection available at: https://www.lyellcollection.org/cc/measurement-and-monitoring

A new model approach for reactive solute transport in dual-permeability media with depth-dependent reaction coefficients

In this study, we developed a one-dimensional mobile-mobile model (MM) for contaminant transport in subsurface with depth-dependent reaction coefficients. Two local systems at micro-scale level are involved in this model: a micro-pore system and a less permeable pore system. The breakthrough curves (BTCs) obtained from the MM with depth-dependent coefficients were thoroughly analyzed, where the case with constant coefficients was used as the reference system. The effects of different parameters on BTCs were studied, and a parameter analysis was also performed to illustrate the effects of adsorption coefficient and degradation coefficient on BTCs. Results show that the BTC patterns for the depth-dependent reactions, in which the reaction rate decreases with increasing depth, vary between the two extreme cases with constant-rate reactions in the topsoil and observation depth. The mass transfer coefficient (α) plays a significant role in defining the BTC pattern. The double peak changes to a single peak when the value of α is large enough. In addition, the velocity of the main flow determines the shape of the BTCs while the velocity of the SVD defines the pattern of the dual peaks in BTCs which also tends to be represented by a single peak as the velocity decreases. Finally, we tested the applicability of the proposed model (MM-FD) in the leaching experiments of both field herbicide and conservative tracer in an agricultural area of northeastern Greece, and compared its performance with that of the advection-dispersion equation (ADE) model by Gao et al. (2013), both of which have depth-dependent coefficients. The results showed that the proposed mobile-mobile model with depth-dependent reaction coefficients was able to satisfactorily capture the evolution of metolachlor concentration both at upper and lower depths.