Contaminant Transport Model Research Articles

Experimental and Numerical Investigations of Using Nanoparticles in Groundwater Remediation

The efficiency of using zeolite nano-clay and silica sand in removing iron from groundwater is investigated experimentally as an application of in situ remediation technique using permeable reactive barrier (PRB). In the first stage of the study batch experiments were conducted on coarse silica sand and fine silica gravel to determine their iron removal efficiency from contaminated water. The results showed that the removal efficiency was about 51.90% for coarse silica sand while fine silica gravel failed to reduce the iron concentration in water. A mix of zeolite nano-clay and coarse silica sand with a ratio of 1:30 was tested. It was found that iron removal efficiency significantly increases to about 99.70%. The linear adsorption isotherm was found to be the most representative for the adsorption of iron onto coarse silica sand and the mix of nano-clay and coarse silica sand with distribution coefficients equal 0.0009 and 0.001, respectively. In the second stage a glass sand tank with coarse silica sand and a mix of zeolite nano-clay and coarse silica PRBs was constructed. The sand tank was used to investigate the effect of sampling time, head difference, iron concentration, nano-clay dosage, and thickness of permeable reactive barrier on the iron removal efficiency. The results indicated that increasing iron concentration and head difference decreases iron removal efficiency. The mix of zeolite nano-clay and coarse silica sand improves iron removal efficiency. Furthermore, increasing nano-clay dosage slightly increases the removal efficiency. However, increasing the thickness of filter layer (i.e., PRB) significantly improves the removal efficiency. Finally, the experimental model data were used to test the capability of a numerical contaminant transport model to predict the removal efficiency. The MT3DMS numerical model included within the Groundwater Modeling System (GMS) was used along with the different experimental data to obtain reaction rate values as calibration parameters for linear isotherm. Reaction rates that yield modeling results matching experimental data were obtained.

Experimental evaluation of vertical metal retardation in stormwater management practices as influenced by cycles of baseline and high salinity

The application of NaCl as a deicer increases salinity of stormwater runoff, which may impact the speciation and mobility of various contaminants, including metals. Salt can remain in the fill media of stormwater management practices for an extended period after application, creating annual cycles of baseline and high salinity. This study evaluated the impacts of NaCl concentration and application cycles on metal retardation in fill media via 1-D continuous flow bench-scale columns. The high salinity scenario of 0.1 M NaCl decreased retardation factors of metals when compared to baseline salinity scenario of 0.01 M NaCl. Application of cycling baseline and high NaCl caused substantial fluctuations in the effluent metal concentration. The metals that were adsorbed during the baseline salinity periods were desorbed during the high salinity periods, leading to elevated concentrations of metals in porewater and effluent. Flushing with water removed only Na from the fill media top layers, while applying cysteine, as an environmentally friendly chelator, was demonstrated to be a promising approach to mobilizing accumulated metals from top layers to deeper layers. The results suggest that incorporating seasonal changes in environmental variables such as salinity enhances accuracy of contaminant transport modeling in fill media.

Teaching Groundwater Flow and Contaminant Transport Modeling via a Sand-Tank Model

In this study, a sand-tank model as a physical analog of a real-world aquifer is presented for groundwater instruction. The sand tank is used for introducing flow nets and quantifying groundwater flow, for groundwater modeling and calibration via a spreadsheet, and for dye-transport modeling. Students learn from the sand tank through interaction and visualization, and by collecting and interpreting data. This integrates the theories from lectures into the sand-tank laboratories, enhancing students’ skills and understanding.

An Integrated Bayesian and Machine Learning Approach Application to Identification of Groundwater Contamination Source Parameters

The identification of groundwater contamination source parameters is an important prerequisite for the control and risk assessment of groundwater contamination. This study developed an innovative approach for the optimal design of observation well locations and the high-precision identification of groundwater contamination source parameters. The approach involves Bayesian theory and integrates Markov Chain Monte Carlo, Bayesian design, information entropy, machine learning, and surrogate modeling. The optimal observation well locations are determined by information entropy, which is adopted to mine valuable information about unknown groundwater contamination source parameters from measurements of contaminant concentration according to Bayesian design. After determining the optimal observation well locations, the identification of groundwater contamination source parameters is implemented through a Bayesian-based Differential Evolution Adaptive Metropolis with Discrete Sampling–Markov Chain Monte Carlo approach. However, the processes of both determination and identification are time-consuming because the original simulation model (that is, the contaminant transport model) needs to be invoked multiple times. To overcome this challenge, a machine learning approach, that is, Multi-layer Perceptron, is used to build a surrogate model for the original simulation model, which can greatly accelerate the determination and identification processes. Finally, two hypothetical numerical case studies involving homogeneous and heterogeneous cases are used to verify the performance of the proposed approach. The results show that the optimal design of observation well locations and high-precision identification of groundwater contamination source parameters can be implemented accurately and effectively by using the proposed approach. In summary, this study highlights that the integrated Bayesian and machine learning approach provides a promising solution for high-precision identification of groundwater contamination source parameters.

A new analytical model for transport of multiple contaminants considering remediation of both NAPL source and downgradient contaminant plume in groundwater

The contamination of groundwater aquifers by chlorinated solvents is a water-resource issue of great importance worldwide. Such contaminants are difficult to treat because they are often released as dense non-aqueous phase liquids (DNAPLs). Research shows that the application of remediation technologies to both the NAPL source and dissolved plume can lead to more efficient remediation, rather than to either alone. In these remediation efforts, analytical models that evaluate behavior and fate of contaminants do provide a better understanding of the performance of these remedial technologies. To the best of our knowledge, there exist no analytical model of simulating the plume migration of multiple contaminants with capabilities of accounting for both NAPL source and plume remediation simultaneously and different retardation for original chlorinated solvent contaminant and its degradation byproducts. In this study, we present a new analytical model for remediating both NAPL source and downgradient contaminant plume in groundwater at sites contaminated with chlorinated solvents and their degradation products with different retardation factors as well as considering both NAPL source and plume remediation simultaneously. A source model that accounts for the depletion of mass by the processes of dissolution or first-order decay reactions, corresponding with the removal or destruction of the source mass, is coupled to a plume reactive transport model. The source model is accounted for by relating source mass to the flux-averaged source discharge concentration through a power function. The developed analytical model considers 1-D advection, 3-D dispersion, first-order decay reactions and ingrowth as well as linear isothermal equilibrium sorption. The proposed analytical solution was derived through successive application of the Laplace transform in time and the double finite Fourier cosine transform regarding y and z. The correctness of the analytical model and its auxiliary FORTRAN computer program code are proved by showing excellent agreements between the simulated plume concentrations of all contaminants obtained from the derived analytical model and from a semi-analytical model available in the literature. Application of the proposed analytical solutions illustrates that the use of identical retardation factors for all contaminants may lead to underestimation or overestimation of the mobility of the contaminants, in cases when the retardation factors of the individual contaminants are greatly different from the identical retardation factor value adopted in all contaminants. From the experiments on six scenarios corresponding six remedial treatments, we found out that both the enhanced source decay and partial removal of source mass are main controlling factors at reducing the concentrations of all the contaminants, whereas plume decay leads to effective reduction in the concentrations of PCE, however, rather it causes unfavorable increases of the concentrations of the degradation byproducts.Ultimately, the developed model is used to better understand the impacts of various possible combinations of remedial efforts and management decisions on remediation of the subsurface contamination and quantify the benefit of a certain remediation decision.

Finite difference solver for simulating leaching process in bounded porous media: Development and application

This work, for the first time, developed an unconditionally stable, implicit numerical solution of a one-sided spatial fractional advection-dispersion equation (s-FADE) on a bounded domain to model contaminant transport through porous media during a leaching process. We used the zero-value Robin and Neumann conditions with a fractional-order derivative as the inlet and outlet boundaries, respectively, and a constant initial concentration of the contaminant in the whole domain as an initial condition. By conducting numerical analyses, we found that there is a good agreement between the results of the numerical solution and of its analytical counterpart, validating the accuracy of the numerical solution. In the case of the α variations meaningfully altered the heterogeneity degree of the porous medium, these variations significantly affected the results of the numerical solution, especially at intermediate times. Contrary to the α parameter, the numerical solution was insensitive to the spatial node number. The noisy observational data led to the maximum uncertainty in the estimated fractional dispersion coefficient. The application of the developed numerical solution to simulate sodium chloride (NaCl) leaching curves (LCs) at a laboratory scale revealed that the numerical solution described the leaching process in the homogeneous and heterogeneous sands better than COMSOL Multiphysics®, a commercial finite element software package. According to the fitting results of the developed numerical solution to the experimental data, the mean α values were 1.876 and 1.379 for the homogeneous and heterogeneous sands, respectively. The α values correctly represented the heterogeneity degrees of the used sands and the deviation rate of the transport process from the Fickian transport. Overall, the proposed numerical solution is a reliable numerical model to simulate the leaching process in homogeneous and heterogeneous porous media with bounded domains.

Hydrogeochemical processes and causative pollution sources in the highly urbanized crystalline aquifer system in Southern India

Groundwater contamination due to the disposal of untreated or partially treated domestic and industrial sewage is posing a severe threat to urban groundwater reserves in many parts of the world. The efforts made for the modelling of contaminant transport to understand these pollution transport and hydrogeochemical processes in urban areas are often challenging due to the difficulty in selecting source boundary condition locations mainly in the presence of Multiple Point Sources (MPS). The present research used Multivariate Statistical analysis (MSA) to classify the major pollution sources and to demarcate its area in the highly urbanized Hussain Sagar (HS) lake catchment situated in Hyderabad, South India. The observed monitoring data of groundwater levels and groundwater quality (pH, TDS, Ca2+, Mg2+, Na+, K+, HCO32−, Cl−, SO42−, NO3-N, total hardness) at 108 locations for eight different seasons over four years have been used for modelling. The MSA has revealed that the first component is associated with industrial pollution loads that are restricted to Kukatpally and Dulapally streams and HS lake with a total variance of up to 46% to the total pollution load. Component 2 and component 3 are associated with domestic pollution loads (HCO32−, Na+, and NO3-N) that spread across the lake catchment with a total variance of up to 37%. The approach used in this study can be applied to any local to regional scale river basins for understanding hydrogeochemical processes and to provide inputs to simulate contaminant transport.

Groundwater Contaminant Transport Solved by Monte Carlo Methods Accelerated by Deep Learning Meta-Model

Groundwater contaminant transport modeling is a vitally important topic. Since modeled processes include uncertainties, Monte Carlo methods are adopted to obtain some statistics. However, accurate models have a substantial computational cost. This drawback can be overcome by employing the multilevel Monte Carlo method (MLMC) or approximating the original model using a meta-model. We combined both of these approaches. A stochastic model is substituted with a deep learning meta-model that consists of a graph convolutional neural network and a feed-forward neural network. This meta-model can approximate models solved on unstructured meshes. The meta-model within the standard Monte Carlo method can bring significant computational cost savings. Nevertheless, the meta-model must be highly accurate to obtain similar errors as when using the original model. Proposed MLMC with the new lowest-accurate level of meta-models can reduce total computational costs, and the accuracy of the meta-model does not have to be so high. The size of the computational cost savings depends on the cost distribution across MLMC levels. Our approach is especially efficacious when the dominant computational cost is on the lowest-accuracy MLMC level. Depending on the number of estimated moments, we can reduce computational costs by up to ca. 25% while maintaining the accuracy of estimates.

ERRATUM: Contaminant transport model in transient and unsaturated conditions applied to laboratory column test with tailings

ERRATUM: Contaminant transport model in transient and unsaturated conditions applied to laboratory column test with tailings

Coupled model for consolidation and organic contaminant transport in GMB/CCL composite liner under non-isothermal distribution condition

The transport behavior of organic contaminants in the composite liner is affected by both consolidation and thermal diffusion. However, research on the coupled theory is still limited. In this study, the governing equations for consolidation and organic contaminant transport in GMB/CCL (geomembrane and compacted clay liner) composite liner are developed under non-isothermal distribution condition, and the corresponding coupled model is established. Meanwhile, the numerical method is adopted to obtain the finite difference solutions for consolidation and organic contaminant transport, respectively. Besides, the correctness of the proposed coupled model is validated by comparing the existing analytical solution with the theoretical model. Finally, the effects of different factors on the transport behaviors are discussed, in which trichloroethylene is chosen as the research object. It is found that the influence of non-isothermal distribution on the transport process is amplified when consolidation is neglected rather than considered. Moreover, the effects of consolidation on the transport behaviors are more remarkable under the non-isothermal distribution condition than under the isothermal distribution condition, where the volume compressibility coefficient plays a vital role. Overall, the coupled influences of multi-factors such as thermal diffusion and consolidation should be considered simultaneously to properly evaluate the transport characteristics of organic contaminants.

Centrifuge Modeling of Chloride Ions Completely Breakthrough Kaolin Clay Liner

The 2 m thick compacted clay liner with a permeability coefficient of 1 × 10−7 cm/s is required in the Chinese technical specifications about landfills. The processes of chloride ion completely breakthrough low permeability barriers (k ≤ 1 × 10−7 cm/s) were modeled at 50 g in a geo-centrifuge. A measuring system was used to monitor solute velocity and conductivity. The entire process of chloride ion completely breaking through 2 m Kaolin clay liner was modeled successfully, which provided a valuable testing technology for centrifuge modeling of contaminant transport through low-permeable clay. The analyses results indicated the breakthrough time of conservative pollutant for the 2 m clay liner with a hydraulic conductivity of 1.0 × 10−9 m/s under Δhw of 40 m was 1.6 years. As for strongly adsorptive pollutants, the breakthrough time t0.1 increased by 9 times when Rd increased from 1 to 10, which indicates that the effect of Rd on the performance of the liner was significant.

Development of a contaminant concentration transport model for sulfate-contaminated areas

Groundwater pollution is one of the most important challenges for human. In many parts of the world, groundwater is used for agriculture and even drinking, whereas natural and human-made groundwater contaminants have also affected the quality of these waters. Therefore, monitoring and evaluating the quantity and quality of groundwater is very important. In this research, the efficiency of finite element method (FEM) for groundwater flow and Sulfate concentration transport modeling has been investigated for a 7-year period. After finite element validation analysis, this method was employed in a hypothetical and real-case aquifer with regularly distributed nodes and square elements 200 m × 200 m. The mean error and root mean square error (RMSE) as performance criteria were used to evaluate the performance of the model. The results indicated that the FEM model with RMSE = 1.06 (m) and 1.44 (me/lit) has good skills in groundwater flow and contaminant transport modeling, respectively. Also, the results of the FEM model indicated that in the northeast of the aquifer, the groundwater level is low and the amount of Sulfate is high (higher than the standard values recommended by) which is also confirmed by real data.

Review of groundwater flow and contaminant transport modelling approaches for the Sherwood Sandstone aquifer, UK; insights from analogous successions worldwide

Sandstones are characterized by different hydraulic behaviours and need to be modelled in various ways to represent groundwater flow and contaminant transport. This review shows how sandstone aquifers within the UK Triassic Sherwood Sandstone Group can be represented using three modelling approaches: the Conduit Network, Discrete Fracture Network and Equivalent Porous Medium. The Sherwood Sandstone aquifer is dominated by matrix flow in the Eastern England Shelf, Worcester, Needwood and Staffordshire basins. Here, the aquifers are modelled as Equivalent Porous Media at different spatial scales. Fractures represent the principal flow pathways in the Cheshire Basin. In this basin, Discrete Fracture Network models that account for diffusivity in the matrix can be used where the domain scale is small. The Sherwood Sandstone aquifer across northwestern England shows evidence of intense groundwater alteration and high flow velocities in solutionally enlarged fractures. Turbulent flowing pipe-elements can be inserted in the modelling domain represented by Equivalent Porous Medium at specific sites. The review shows how the Sherwood Sandstone aquifer as well as other siliciclastic deposits across the world need to be represented using a range of modelling approaches, as they behave as matrix or fracture flow aquifers, or in specific cases show a karst-like behaviour. Thematic collection: This article is part of the Hydrogeology of Sandstone collection available at: https://www.lyellcollection.org/cc/hydrogeology-of-sandstone

Modeling Monthly Nitrate Concentration in a Karst Spring with and without Discrete Conduit Flow

Understanding the coupled continuum pipe-flow framework for modeling contaminant transport in karst systems is critical for protecting water resources therein. This study simulated point and non-point source nitrate concentration in a karst spring and investigated the results generated from the flow and transport model with and without discrete conduit flow. CFPv2 and CMT3D models were integrated to address the changes in nitrate concentration at a monthly scale in a karst spring, and the results were compared with that from an equivalent porous media (EPM) model with high-hydraulic conductivity (K) zones set in the main karstified area to represent conduits. The results show that the CFPv2+CMT3D model is able to describe well the recession of nitrate concentration in spring discharge, and the relatively larger deviation (slower nitrate recession) from the observed trend for the EPM model is probably a result of the limitation of utilizing high hydraulic conductivity cells to represent conduit. Moreover, simulated hydraulic heads in poorly karstified areas from the two models both show slight differences from the observations (the head RMSE values of calibration/validation for CFPv2 and MODFLOW models are 0.16 m/0.25 m and 0.26 m/0.17 m, respectively), indicating the inclusion of conduits may not affect the simulation considerably, and the lower the proportion of karstic area, the slight effects brought from the inclusion of conduits in the model. For highly karstified areas, the CFPv2+CMT3D model could provide more accurate results (head RMSE of calibration/validation for CFPv2 and MODFLOW are 0.22 m/0.06 and 0.52 m/0.47 m, respectively), showing the coupled continuum pipe-flow framework may be more appropriate for applying to highly and maturely karstified areas where the variations in the behavior of flow and contaminant transport are more affected by turbulent flow regime.

Contaminant transport model in transient and unsaturated conditions applied to laboratory column test with tailings

Mining is an important economic activity in the modern world. However, despite the generated benefits, mining produces tremendous volumes of tailings, an environmental liability with numerous adverse effects. Researches about contaminant transport in tailings dam are important to assess the degree of contamination and to propose preventive or remedial measures. In geotechnical practice, the flow of solutes is generally characterized by numerical solution of the Richards equation to describe water movement followed by advection-dispersion equation to describe contaminant movement. This study aimed to model and simulate contaminant transport in a laboratory column test, using a new analytical formulation and mathematical codes, through tailings in transient unsaturated conditions. The analytical solution for the Richards equation was used to simulate the variation in the volumetric water content and to determine the transient contaminant plume using the advection-dispersion equation subsequently. The models were used to calibrate experimental data from hydraulic characterization and contamination tests. Finally, the normalized contaminant plume (cw/c0) was simulated as a function of time and space. Comparisons with experimental data showed that the analytical formulations adequately expressed the process of contaminant infiltration through the unsaturated porous medium. The formulations offered effectively and are configured as a new approach to solve various contamination problems in transient unsaturated conditions, providing insights into many complex processes that occur in the lab tests and requires far less computational effort compared with current programs to modeling the solute transport using numerical solutions, as the versatile commercial Software HYDRUS.

Evaluating the movement of dissolved porewater species through a marine sediment 51 years after establishment of a pulp and paper effluent stabilization basin

Over 50 years ago, a marine estuary was converted to a wastewater stabilization basin for treatment of primarily pulp and paper effluent. As a result, the basin was immediately converted to a “freshwater” environment and subsequently accumulated a thin layer of black, organic-rich sediment containing varying amounts of dioxins and furans, metals, polycyclic aromatic hydrocarbons, and petroleum hydrocarbons. Previous studies on the site have shown that the majority of this contamination in the basin appears to have been contained within this black sediment layer and not migrated to any significant extent into the original underlying marine sediments. The purpose of this study is to examine sediment porewater chemistry changes that have occurred over 51 years of operation of the stabilization basin with the intent of better understanding why contamination has been minimal into the underlying natural marine sediments. Field and laboratory testing is presented to characterize the physical, chemical, and mineralogical sediments in the basin. Porewater chemistry profiles obtained from this work are then used in combination with a one-dimensional contaminant transport model to examine the role of diffusion, sorption, and upward groundwater flux in the porewater profiles found for the sediments.

A research and development roadmap to support applications of the enhanced BIOMASS methodology

The International Atomic Energy Agency has coordinated an international project addressing enhancements of methods for modelling the biosphere in post-closure safety assessments of solid radioactive waste disposal. This has resulted in the enhanced BIOMASS methodology that is described elsewhere in this special issue. To a large degree, the enhancements to the BIOMASS methodology arose from experience gained in applying the original methodology, both in the context of other international projects and in assessments of existing or proposed disposal facilities for solid radioactive wastes. Here, this experience is used, together with information on the status of solid radioactive waste disposal programmes worldwide, to identify opportunities for applying the enhanced methodology and for learning from those applications. This provides a basis for identifying research and development to support application of the enhanced methodology in a variety of environmental settings. These research and development requirements include aspects related to climate change under a variety of forcing scenarios, landform development in climatic regimes ranging from cold, polar to arid, tropical, modelling of groundwater flow and contaminant transport in surface-water catchments where both fractured rock and porous sediments are present, and studies of the transport of key radioisotopes of elements central to major biogeochemical cycles, such as those of carbon, chlorine, sulphur and iodine. In addition, some remarks are made on aspects of the application of the enhanced methodology that could imply review and updating of regulations and regulatory guidance, e.g. in relation to the definition of representative persons or groups to be considered in assessments and in respect of approaches to the assessment of radiological impacts on non-human biota. Furthermore, consideration is given as to how the scientific and technical experience that has been gained and methods that have been developed in the context of solid radioactive disposal facilities could support management of contaminated sites and legacy facilities that are likely to require long-term management and stewardship.

DynSus: Dynamic sustainability assessment in groundwater remediation practice

Decision-making processes for clean-up of contaminated sites are often highly complex and inherently uncertain. It depends not only on hydrological and biogeochemical site variability, but also on the associated health, environmental, economic, and social impacts of taking, or not taking, action. These variabilities suggest that a dynamic framework is required for promoting sustainable remediation. For this, the decision support system DynSus is presented here for integrating a predeveloped contaminant fate and transport model with a sustainability assessment tool. Implemented within a system dynamics framework, the new tool uses model simulations to provide remediation scenario analysis and handling of uncertainty in various data. DynSus was applied to a site in south Sweden, contaminated with pentachlorophenol (PCP). Simulation scenarios were developed to enable a comparison between alternative remediation strategies and combinations of these. Such comparisons are provided for selected sustainability indicators and remediation performance (in terms of concentration at the recipient). This leads to identifying the most critical variables to ensure that sustainable solutions are chosen. Simulation results indicated that although passive practices, e.g., monitored natural attenuation, were more sustainable at first (5–7 years after beginning remediation measures), they failed to compete with more active practices, e.g., bioremediation, over the entire life cycle of the project (from the beginning of remedial action to achieving the target concentration at the recipient). In addition, statistical tools (clustering and genetic algorithms) were used to further assess the available hydrogeochemical data. Taken together, the results reaffirmed the suitability of the simple analytical framework that was implemented in the contaminant transport model. DynSus outcomes could therefore enable site managers to evaluate different scenarios more quickly and effectively for life cycle sustainability in such a complex and multidimensional problem.

Making Waves: Modeling bioturbation in soils – are we burrowing in the right direction?

The burrowing, feeding and foraging activities of terrestrial and benthic organisms induce displacements of soil and sediment materials, leading to a profound mixing of these media. Such particle movements, called “sediment reworking” in aquatic environments and “bioturbation” in soils, have been thoroughly studied and modeled in sediments, where they affect organic matter mineralization and contaminant fluxes. In comparison, studies characterizing the translocation, by soil burrowers, of mineral particles, organic matter and adsorbed contaminants are paradoxically fewer. Nevertheless, models borrowed from aquatic ecology are used to predict the impact of bioturbation on organic matter turnover and contaminant transport in the soil. However, these models are based on hypotheses that have not been tested with adequate observations in soils, and may not necessarily reflect the actual impact of soil burrowers on particle translocation. This paper aims to (i) highlight the possible shortcomings linked to the current use of sediment reworking models for soils, (ii) identify how recent progresses in aquatic ecology could help to circumvent these limitations, and (iii) propose key steps to ensure that soil bioturbation models are built on solid foundations: more accurate models of organic matter turnover, soil evolution and contaminant transport in the soil are at stake

Development and application of a contaminant transport model for groundwater remediation and reservoir protection: a case study from India.

The upper Kodaganar basin, located in Dindigul district of Tamil Nadu, India, is composed of hard rock terrain. Groundwater is the major source of domestic and irrigation needs and it is being contaminated by tannery wastewater that is discharged into the nearby Sengulam Lake. The main aim of this work was to develop a contaminant transport model using the total dissolved solids (TDS) concentration of groundwater measured in the basin. The model was developed to predict the fate of contaminant in the aquifer. The TDS concentrations in the wells ranged from 249 to 20,120mg/L, wherein extremely high values were observed in some of the severely contaminated wells. Three scenarios were proposed to predict the fate of the contaminant and to mitigate the effect of contaminant on groundwater receptors for the year 2020: scenario I: developed with the existing discharge conditions; scenario II: developed with discharge as per the standards; scenario III: developed with zero discharge. The results of this study showed that scenario III reduced the contaminated area from 12 km2 to 6 km2. The reduction in area for different concentration contours, namely 2000mg/L, 5000mg/L, 10,000mg/L, and 15,000mg/L, was 2 km2, 0.5 km2, 0.2 km2, and 0.1 km2, respectively, and the groundwater remediation was expected to take 2050years. Hence, there is an urgent need for the application of clean and resource efficienttechnologies in process industries, and the implementation of suitable wastewater treatment technologies to prevent ground water pollution in the region.