Groundwater Flow Model Research Articles

Simulation and prediction of land subsidence in Decheng District under the constraint of InSAR deformation information

Land subsidence, marked by a decline in surface elevation, poses a significant threat to urban infrastructure and safety. Accurate subsidence information and a reliable prediction model are crucial for prevention and control. In this study, we used persistent scatterer interferometric synthetic aperture radar (PS-InSAR) technology to obtain long-term land subsidence data and analyzed subsidence characteristics in Decheng District. By integrating hydrogeological and groundwater data, we developed a three-dimensional groundwater flow and one-dimensional compaction model through numerical simulation. Furthermore, the subsidence data monitored by PS-InSAR were used to further constrain and validate the model. The evolution trend of land subsidence under different groundwater exploitation scenarios was predicted and analyzed. The results showed that from May 2017 to December 2021, the cumulative maximum subsidence in Decheng District reached −173 mm. The subsidence area is mainly concentrated in the northern area, and its subsidence center is near Qiaoyuan Town. According to the Land Subsidence Prevention and Control Plan of Dezhou City, Shandong Province (2018–2025), we set up different groundwater mining scenarios with the goal that the rate of land subsidence in the key prevention and control area is less than 35 mm/yr in 2025.The Fluid-solid coupled model prediction analysis results indicated that a 30% reduction in groundwater exploitation is reasonable.

Effects of grid resolution on regional modelled groundwater salinity and salt fluxes to surface water

Coastal fresh groundwaters face growing threats from rising withdrawals and climate change, with salinization of surface and groundwater as notable impacts. Recent developments in parallel variable-density modelling enable studying these threats at unexplored resolutions and extents. To improve the understanding of ground- and surface water salinization processes, we designed an experiment to measure how spatial resolution affects both groundwater salinity distribution and salt loads to surface waters. An existing parallelized coupled variable-density groundwater flow and salt transport (VD-GWT) model is applied to a region in the Netherlands whereby the surface water drainage network is parameterized at grid resolutions between 10 and 250 m. The results show a strong dependency between resolution and the salinity distribution in shallow groundwater while simulated salt loads are affected by imperfect flux scaling. The computational resources needed for this test suggest that regional high-resolution VD-GWT models are feasible using HPC environments, albeit not practical.

A rigorous formulation of drain boundary conditions for groundwater flow modeling in geotechnical engineering

A rigorous formulation of drain boundary conditions for groundwater flow modeling in geotechnical engineering

Optimal Exploitation Strategies of Sustainable Utilization of Egypt's Fossil Groundwater Reserves

Groundwater-dependent areas in Egypt are being reclaimed as a result of the impending food crisis. Thus, the national project for land reclamation aims to turn vast tracts of desert land into productive agricultural land. Even while this kind of rural development is desperately needed, relying solely on fossil groundwater sources is a dangerous course of action. Therefore, it is crucial to use these groundwater resources quite carefully. Selecting a safe pumping schedule to prevent aquifer depletion and/or seawater intrusion is just one of the goals. However, using groundwater simulation models based on optimal approaches would introduce exploitation plans that, at the same time, guarantee the aquifers' sufficiency for continued development and maximize the agricultural investment. Thus, a groundwater flow model was generated using the FEFLOW software to explore the Moghra aquifer’s potential for extensive rural development. The maximum pumping regime that coincides with the regulation rule that was set by the MWRI for the next 100 years has been concluded. There is a potential for sustainable exploitation of this water resource to irrigate a total area of 85,715 acres (34,687 ha). The resulting drawdown is expected to reach 95.4 m. Furthermore, a few mitigating techniques are suggested as efficient ways to stop or impede the saltwater intrusion, such as the installation of subterranean barriers and brackish water scavenger wells. Without a doubt, the intended findings would serve as the foundation for wise local water management choices that might strike a balance between the socioeconomic welfare of our nation and environmental preservation. The outcomes of the project can be used by decision making and stakeholder to achieve sustainable water resources management in the new lands for reclamation projects in the northwestern of Nile Delta, Egypt.

Modeling for sustainable groundwater management: Interdependence and potential complementarity of process-based, data-driven and system dynamics approaches

Groundwater systems are vast natural water reservoirs used to support human water demands and ecosystem services. Various modeling approaches have been developed to help manage these complex highly-dynamic systems. This paper discusses the strengths and limitations of three modeling approaches, namely: process-based, data-driven and system dynamics modeling. For demonstration purposes, the three modeling approaches are applied to the Konya Closed Basin, a large agricultural region with semi-dry climate located in central Turkey. Process-based modeling is grounded in the theory-based representation of the governing processes but is somewhat limited by the computational effort and the difficulty of defining the required input parameters that characterize the heterogeneous aquifer system. Process-based models are shown to be powerful tools for resource management purposes provided climatic and water demand scenarios are accurately defined. Data-driven models are efficient tools for the management of groundwater resources but are highly dependent on the availability of large training data sets encompassing the spectrum of possible system responses. The high efficiency of surrogate modeling approaches makes them ideal tools for incorporation into applications such as real-time decision support systems and digital twin platforms. System dynamics modeling examines the groundwater exploitation problem within a socio-economic context that involves multiple stakeholders and their decision making. It combines groundwater flow models with socio-economics and endogenous decision rules to conduct scenario analysis and support policy development. The analyses and model demonstrations presented in this paper underscore the interconnectedness and complementarity of these three modeling approaches and the need for more integrated use of these modeling approaches for enhanced multi-sectoral management of groundwater systems.

Groundwater flow paths using combined self-potential, electrical resistivity, and induced polarization signals

SUMMARY The dam of Lampy (Black Mountain, Aude, France) is considered as one of the oldest dams in France. A geophysical survey is performed to better understand the pattern of groundwater flow downstream of this dam in the granitic substratum. Induced polarization is first used to image both electrical conductivity and normalized chargeability. Eight core samples of granite from this site are measured and analysed in the laboratory. Their electrical conductivity and normalized chargeability are expressed as a function of the porosity and cation exchange capacity (CEC). The field data and the petrophysical results are used to image the water content, the CEC and the permeability distribution of the substratum. Then, self-potential is used as a complementary passive geophysical technique, which, in absence of metallic bodies, is directly sensitive to groundwater flow through the so-called streaming potential effect. Indeed, the excess of electrical charges in the vicinity of the solid grains, in the so-called double layer, is dragged by the ground water flow generating in turn an electrical (streaming) current and therefore an electrical field. A map of the resulting self-potential signals is done over the area covered by the induced polarization profiles. This map shows a large positive anomaly with an amplitude of ∼80 mV possibly associated with upwelling groundwater in an area where the soil is water-saturated. A groundwater flow simulation is performed to model this anomaly. This is done in two steps. A preliminary groundwater flow model is built using the permeability and water content distributions obtained from the induced polarization data. Then, this groundwater flow model is updated using the information contained in the self-potential data including the electrical conductivity distribution obtained through resistivity tomography. The algorithm for the inversion of the self-potential data is validated through a 2-D numerical test. This analysis yields a groundwater flow model with the flow being focused through a high permeability zone. This study shows how three geoelectrical methods (self-potential, induced polarization and electrical resistivity) can be efficiently combined to image groundwater flow in the vicinity of a dam.

Simulation of coupled groundwater flow and contaminant transport using quintic B-spline collocation method

PurposeThe purpose of this study is to introduce a new numerical scheme with no stability condition and high-order accuracy for the solution of two-dimensional coupled groundwater flow and transport simulation problems with regular and irregular geometries and compare the results with widely acceptable programs such as Modular Three-Dimensional Finite-Difference Ground-Water Flow Model (MODFLOW) and Modular Three-Dimensional Multispecies Transport Model (MT3DMS).Design/methodology/approachThe newly proposed numerical scheme is based on the method of lines (MOL) approach and uses high-order approximations both in space and time. Quintic B-spline (QBS) functions are used in space to transform partial differential equations, representing the relevant physical phenomena in the system of ordinary differential equations. Then this system is solved with the DOPRI5 algorithm that requires no stability condition. The obtained results are compared with the results of the MODFLOW and MT3DMS programs to verify the accuracy of the proposed scheme.FindingsThe results indicate that the proposed numerical scheme can successfully simulate the two-dimensional coupled groundwater flow and transport problems with complex geometry and parameter structures. All the results are in good agreement with the reference solutions.Originality/valueTo the best of the authors' knowledge, the QBS-DOPRI5 method is used for the first time for solving two-dimensional coupled groundwater flow and transport problems with complex geometries and can be extended to high-dimensional problems. In the future, considering the success of the proposed numerical scheme, it can be used successfully for the identification of groundwater contaminant source characteristics.

Stable Isotopic Evidence of Paleorecharge in the Northern Gulf Coastal Plain (USA)

Stable isotope abundances (δ18O and δ2H) in regional aquifers can provide important paleoclimate information. However, identifying paleoclimate signals can be complicated by cross-formational mixing and, potentially, by isotopic diffusion between aquifers and confining units. We examine controls on δ18O and δ2H distributions in the Wilcox aquifer of the northern Gulf Coastal Plain (USA). We sampled groundwater for δ18O, δ2H, Cl−, and 36Cl along a ~300 km downgradient transect. We developed a simplified, 1D numerical model of groundwater flow and 18O transport to assess the possible importance of isotopic diffusion between the aquifer and its confining units. Along the inferred flowpath, δ18O and δ2H values were depleted by as much as 1.3 and 8.2‰, respectively, as the Wilcox aquifer transitioned from unconfined to confined. However, they then gradually rose farther downgradient by up to 1.1 and 8.6‰. Chlorine-36 analyses and 14C analyses (from other studies) indicate that groundwater ages range from ~103 yr to ~8 × 105 yr. Modeling results indicate that the effect of diffusion on isotopic abundances is limited, whereas Cl− data indicate that cross-formational flow is limited. Therefore, we posit that confined groundwater in our study reflects a Pleistocene paleorecharge signal.

Modelling approach integrating climate projections for coastal groundwater management

Climate change and excessive groundwater extraction are major contributors to rising groundwater salinization due to seawater intrusion in coastal aquifers. This study aims to define a wide-applicable approach in which hydrological balance, boundary conditions, and irrigation water demand, defined over time considering climate change predictions, can integrated into a numerical model of the groundwater system. The approach was tested in a selected coastal aquifer. The approach spans from the past, used to define steady or almost natural conditions for calibration purposes (1950–2000 in the test), to the future (2100), divided in decade steps. The water balance analysis is based on an inverse hydrogeological water balance approach. The future climate change predictions are used to assess variations in boundary conditions of the groundwater model concerning salinity and sea level, recharge, and inflow from upstream aquifers. The approach considers changes in agricultural activities, groundwater demand, and river stage. The regional model is generated using the MODFLOW code for the groundwater flow model and the SEAWAT code for the salt transport model. The test concerns the Metaponto coastal plain, in which a porous aquifer is at salinization risk due to seawater intrusion. In this way, different influences of climate change and human activities are combined to define a 3d view of groundwater depletion and salinization effects. Quantifying these potential effects or risks, adaptation scenarios with numerical assessments are outlined in this study.

Understanding Climate Change and Anthropogenic Impacts on the Salinization of Low‐Lying Coastal Groundwater Systems

AbstractFresh coastal groundwater is a valuable water resource of global significance, but its quality is threatened by saltwater intrusion. Excessive groundwater abstraction, sea‐level rise (SLR), land subsidence and other climate‐related factors are expected to accelerate this process in the future. The objective of this study is to (a) quantify the impact of projected climate change and (b) explore the role of individual hydrogeological boundaries on groundwater salinization of low‐lying coastal groundwater systems until 2100 CE. We employ numerical density‐dependent groundwater flow and salt transport modeling for this purpose, using Northwestern Germany as a case. Separate model variants are constructed and forced with climate data, that is, projected SLR and groundwater recharge, as well as likely ranges of other hydrogeological boundaries, including land subsidence, abstraction rates and drain levels. We find that autonomous salinization in the marsh areas, resulting from non‐equilibrium of the present‐day groundwater salinity distribution with current boundary conditions, is responsible for >50% of the salinization increase until 2100 CE. Sea‐level rise, land subsidence and drain levels are the other major factors controlling salinization. We further show that salinization of the water resources is a potential threat to coastal water users, including water suppliers and the agrarian sector, as well as coastal ecosystems. Regional‐scale uplifting of drain levels is identified as an efficient measure to mitigate salinization of deep and shallow groundwater in the future. The presented modeling approach highlights the consequences of climate change and anthropogenic impacts for coastal salinization, supporting the timely development of mitigation strategies.

Theoretical evaluation of high-permeability wellbore skin effect on aquifer response under pumping

Skin zones with distinct hydraulic properties often form around wellbores during drilling operations. Conventional skin-factor models, developed for low-permeability (positive) skin, assume discontinuous hydraulic heads between the wellbore and aquifer. However, these models may be inadequate for high-permeability (negative) skin scenarios resulting from intensive well development. This study derives a new skin-factor approach for negative skin approaches based on the two-zone model approach. We derive a new skin-factor approach that maintains continuous heads between the wellbore and aquifer while allowing for discontinuous fluxes. Using Laplace and finite cos-Fourier transformations, we develop a groundwater flow model for aquifer pumping under a partially penetrating well, incorporating this new approach. An asymptotic expansion method is employed to obtain a large-time solution. The proposed model is also compared to the existing two-zone model. Sensitivity analysis reveals that high-permeability skin significantly affects drawdown, particularly when there is a sudden increase in porosity within the skin zone. This revised approach provides a more accurate framework for modeling various skin effects, offering valuable insights for groundwater management and well hydraulic modeling in both hydrogeology and petroleum engineering applications.

Adaptive machine learning surrogate based multiobjective optimization for scavenging residual saltwater behind subsurface dams

High-fidelity physically based groundwater flow and solute transport models have been limited for seawater intrusion remediation design because of computationally intensive evolutionary algorithms. Data-driven machine learning approaches are promising to substitute expensive-cost groundwater numerical models within optimization due to computing efficiency. However, machine learning surrogates may accumulate error of forecasting and thereby result in infeasible optimal solutions. To achieve desired fidelity level, this study proposes a novel adaptive machine learning surrogate based multiobjective optimization method for coastal aquifer desalination. An adaptive modeling algorithm is newly introduced to iteratively retrain poorly-performed machine learning models and enhance predicting accuracy. The method is demonstrated to seek optimal extraction and injection strategies for scavenging residual saltwater trapped in an upstream aquifer behind a subsurface dam. Two conflicting objectives of minimizing the total extraction-injection rate and maximizing saltwater removal effectiveness are considered. Three machine learning models including artificial neural network (ANN), Gaussian process (GP) and response surface regression model (RSR) are developed to replace a high-fidelity seawater intrusion model for predicting chloride concentration and salinity mass. Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to derive Pareto fronts. Pareto optimal solutions obtained from machine learning models are compared against those from the seawater intrusion model. Results indicate that the developed machine learning models do not only have strong predicting capability, but also maintain good quality of Pareto optimal solutions, while achieving substantial computational saving up to 95%. Especially, the adaptively retrained RSR model inhibits error accumulation of forecasting and accelerates correct convergence to the true Pareto front. The proposed method is found superior performance in accurate convergence, widely-spread diversity as well as high computing efficiency than conventional methods.

Modeling Contaminant Transport from a Red Mud Pond – A Case Study from South India

The present study focused on impact assessment of redmud pond on groundwater using numerical groundwater flow and contaminant transport modeling using pertinent data including water quality and 2D electrical resistivity imaging data. The observed groundwater depths range from 1.2 to 25.8 meters below ground level with deeper levels observed in upstream and higher elevated regions in the study area. Elevated pH and electrical conductivity (>3000 μS/cm) characterize the Redmud ponds, while other groundwater samples meet BIS drinking water standards. Major ion concentrations contouring indicates high total dissolved solids (TDS) around Redmud ponds due to leakage and in the downstream due to domestic sewage pollution. Most locations adhere to BIS drinking water limits except for one downstream site. The resistivity data indicated hard formations (>18 m depth) with resistivity >500 Ohm.m, weathered basalt (12-18 m, 60-150 Ohm.m), and saturated water (12 m, 1-5 Ohm.m). Contaminated aquifers (<1 Ohm.m) are detected up to 3 m depth, and noticed accumulating contaminated water (27 m depth) in the NW corner of the Redmud pond from seepage. Predominant groundwater flow from the Redmud pond towards public water bodies and streams is highlighted by simulated contaminant transport model. Collaboration and comprehensive management are recommended to protect the watershed’s environmental integrity and public health.

Physics‐Informed Convolutional Decoder (PICD): A Novel Approach for Direct Inversion of Heterogeneous Subsurface Flow

AbstractWe propose a physics‐informed convolutional decoder (PICD) framework for inverse modeling of heterogenous groundwater flow. PICD stands out as a direct inversion method, eliminating the need for repeated forward model simulations. The framework combines data‐driven and physics‐driven approaches by integrating monitoring data and domain knowledge into the inversion process. PICD utilizes a convolutional decoder to effectively approximate the spatial distribution of hydraulic heads, while Karhunen–Loève expansion (KLE) is employed to parameterize hydraulic conductivities. During the training process, the stochastic vector in KLE and the parameters of the convolutional decoder are adjusted simultaneously to minimize the data‐mismatch and the physical violation. The final optimized stochastic vectors correspond to the estimation of hydraulic conductivities, and the trained convolutional decoder can predict the evolution and distribution of hydraulic heads. Various scenarios of groundwater flow are examined and results demonstrate the framework's capability to accurately estimate heterogeneous hydraulic conductivities and to deliver satisfactory predictions of hydraulic heads, even with sparse measurements.

Shoreline barriers may amplify coastal groundwater hazards with sea-level rise

Subsurface barriers have been proposed to protect coastal aquifers from sea-level rise induced seawater intrusion, but the potential for groundwater emergence near subsurface barriers remains unknown. Here, we investigated how emergence changes groundwater flow conditions and influences the protective performance of subsurface barriers with sea-level rise. We tested the subterranean consequences of sea-level rise for cutoff walls and subsurface dams with cross-shore groundwater flow and salt transport models, investigating how barrier design, aquifer properties, and hydrological conditions control the potential for emergence, groundwater partitioning at the barrier, and seawater intrusion with sea-level rise. We find that most subsurface infrastructure cannot prevent seawater intrusion and emergence simultaneously. Subsurface dams spanning more than half of the aquifer thickness created emergence hazards and subsequent groundwater partitioning for all scenarios tested. Cutoff walls were less effective at reducing seawater intrusion for all opening sizes but could reduce the emergence potential compared to similarly sized subsurface dams. Our results demonstrate the challenging trade-offs in mitigating the coastal groundwater hazards of seawater intrusion and emergence with sea-level rise, where groundwater flooding inland of protective infrastructure would require combinations of subsurface impoundments and other mitigation techniques, such as pumping or drains.

Assessing the impact of surface water and groundwater interactions for regional-scale simulations of water table elevation

Groundwater flow models are increasingly considered for the regional scale simulation of hydraulic heads and water table elevation. In the most complete configuration, models explicitly simulate two-way interactions between surface water (SW) and groundwater (GW) to reproduce and forecast both SW and GW water levels. In most regional scale groundwater models, however, SW-GW interactions are represented by simplified boundary conditions that only allow one-way interaction from SW to GW, neglecting most of the dynamic exchange fluxes between SW and GW. To evaluate the potential consequences of such simplifications on the simulation of regional GW levels, we compare two models on a 36,900 km2 regional aquifer system in Southern Quebec. One model explicitly simulates both SW and GW flow with two-way SW-GW feedback and the other model only simulates GW flow with a surface boundary flux to represent a one-way interaction with the land surface. Both models are developed with the same numerical code to ensure that the only differences are the representation of SW water flow and SW-GW feedback. The one-way model simulates overall deeper water tables because it removes all exfiltrated groundwater from the system once it exits the subsurface, therefore not allowing exfiltrating groundwater to re-infiltrate. This effect is most pronounced in areas where the water table is close to the surface and for low-flow periods. The inclusion of two-way feedback also reduces the sensitivity of simulated GW levels to the magnitude of the hydraulic conductivity. This result highlights the need for additional data on other system states to improve the calibration of regional scale models that explicitly simulate two-way SW-GW interactions.

Estimating natural groundwater recharge taking into consideration temporal and spatial variability for arid unconfined aquifer

ABSTRACT Water scarcity is one of the major critical affecting arid climate countries. In addition, population growth and climate change are threatening the sustainable development of water resources in the upcoming decades. Therefore, managing groundwater can solve water scarcity such that sustainable development is ensured for future generations. Hence, it is crucial to assess the current quantity of groundwater by analyzing groundwater variables. Thus, natural groundwater recharge could be utilized as an indicator to assess groundwater quantity conditions. This study aims to estimate natural groundwater recharge in an arid unconfined aquifer. El-Qaa plain in Sinai, Egypt was chosen as a case study. Recharge was estimated taking into consideration spatial and temporal variability. To accomplish this, the WetSpass (Water and Energy Transfer between Soil, Plants, and Atmosphere under quasi-Steady State) model was applied. The model was run using morphological, landuse – land cover and climate data from 1986 to 2015 with a monthly time step. To calibrate the model, the isotope signature of δ18O and δ2 H of water was analyzed to determine the natural groundwater recharge of the aquifer. The obtained recharge value was utilized as a reference value for the calibration process. The results were validated using a finite-difference groundwater flow model (MODFLOW). The recharge values were imported to MODFLOW followed via a transient run from 2000 to 2011. The validation was conducted by comparing the simulated groundwater level with the observed ones. After validation process, the inter-annual and seasonal variability of recharge were determined, and a relationship between recharge and other hydrological parameters was deduced. In addition, the recharge distribution was mapped to depict the recharge spatial variability. The results show that the current recharge rate ranges from approximately 8.10 to 16.62 mm/yr, with a mean annual recharge rate of nearly 12.36 mm/yr. The study might be useful for hydrogeologists for determining potential recharge in the study area, groundwater modelers for developing a reliable groundwater flow model, and decision-makers for planning appropriate future sustainable development through water resources management.

Isogeochemical Characterization of Mountain System Recharge Processes in the Sierra Nevada, California

AbstractMountain System Recharge processes are significant natural recharge pathways in many arid and semi‐arid mountainous regions. However, Mountain System Recharge processes are often poorly understood and characterized in hydrologic models. Mountains are the primary water supply source to valley aquifers via lateral groundwater flow from the mountain block (Mountain Block Recharge) and focused recharge from mountain streams contributing to focused Mountain Front Recharge at the piedmont zone. Here, we present a multi‐tool isogeochemical approach to characterize mountain flow paths and Mountain System Recharge in the northern Tulare Basin, California. We used groundwater chemistry data to delineate hydrochemical facies and explain the chemical evolution of groundwater from the Sierra Nevada to the Central Valley aquifer. Stable isotopes and radiogenic groundwater tracers validated Mountain System Recharge processes by differentiating focused from diffuse recharge, and estimating apparent groundwater age, respectively. Novel application of End‐Member Mixing Analysis using conservative chemical components revealed three Mountain System Recharge end‐members: (a) evaporated Ca‐HCO3 water type associated with focused Mountain Front Recharge, (b) non‐evaporated Ca‐HCO3 and Na‐HCO3 water types with short residence times associated with shallow Mountain Block Recharge, and (c) Na‐HCO3 groundwater type with long residence time associated with deep Mountain Block Recharge. We quantified the contribution of each Mountain System Recharge process to the valley aquifer by calculating mixing ratios. Our results show that deep Mountain Block Recharge is a significant recharge component, representing 31%–53% of the valley groundwater. Greater hydraulic connectivity between the Sierra Nevada and Central Valley has significant implications for parameterizing groundwater flow models. Our framework is useful for understanding Mountain System Recharge processes in other snow‐dominated mountain watersheds.

Exploring Urban Sustainability: The Role of Geology and Hydrogeology in Numerical Aquifer Modelling for Open-Loop Geothermal Energy Development, the Case of Torino (Italy)

This research examines the integration of geological and hydrogeological data in numerical aquifer model simulations, with a particular focus on the urban area of Torino, Italy. The role of groundwater resources in urban sustainability is analysed. The objective is to integrate open-loop geothermal plants into the district heating network of IREN S.p.A. Two case studies are examined: the Torino Nord area and the Moncalieri area, both of which host district heating plants. The work entails the collection and analysis of data from a variety of sources, including geognostic surveys and permeability tests, in order to construct a three-dimensional numerical model of the surface aquifer. Models were built using the public MODFLOW 6 (model of groundwater flow) code and calibrated using PESTHP (High Performance of Model Independent Parameter Estimation and Uncertainty Analysis). Results indicate the potential of urban aquifers as renewable energy sources and the necessity of comprehensive geological and hydrogeological assessments for optimal ground water heat pump (GWHP) system installation. This paper emphasises the significance of sustainable water management in the context of climate change and urbanisation challenges.

Determination of Contaminant Transport Parameters for a Local Aquifer by Numerical Modeling of Two Plumes: Trichloroethylene and Hexavalent Chromium

The municipal wellfield in Collierville, Tennessee, is contaminated with trichloroethylene (TCE) and hexavalent chromium (Cr (VI)) due to industrial operations dating back to the 1970s and 1980s. This study aims to elucidate the aquifer’s contaminant transport mechanisms by determining longitudinal and transverse dispersivities through inverse modeling. Utilizing MT3DMS for contaminant transport simulation, based on a well-calibrated groundwater flow model, and leveraging Python’s multiprocessing library for efficiency, the study employs a trial-and-error methodology. Key findings reveal that longitudinal dispersivity values range from 5.5 m near the source to 20.5 m further away, with horizontal and vertical transverse dispersivities between 0.28 m and 3.88 m and between 0.03 m and 0.08 m, respectively. These insights into the aquifer’s dispersivity coefficients, which reflect the scale-dependent nature of longitudinal dispersivity, are crucial for optimizing remediation strategies and achieving cleanup goals. This study underscores the importance of accurate parameter estimation in contaminant transport modeling and contributes to a better understanding of contaminant dynamics in the Collierville wellfield.