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In situ chemical oxidation (ISCO) is widely used as an efficient remediation technology for groundwater pollution. However, quantitative studies of its reactive remediation process under coupled thermal desorption technology are scarce. Based on laboratory experiments and site remediation, the chemical oxidation remediation reaction process was quantified, and the apparent reaction equation of the ISCO process was constructed. And then, a numerical model coupled with Hydraulic-Thermal-Chemical (HTC) fields was built to quantitatively describe the remediation process of an actual contaminated site. The simulation results fit well with the site monitoring data, and the results indicated that thermal desorption strengthens the ISCO remediation effect. In addition, the HTC model is expanded to build a conceptual and numerical model of a coupled remediation system, including heating and remediation wells. The results showed that high-temperature conditions enhance the activity of remediation chemicals and increase the rate of remediation reaction to obtain a better remediation effect. The heating wells increase the regional temperature, accelerating the diffusion of pollutants and remediation chemicals, and promoting adequate contact and reaction. Based on this crucial mechanism, thermal desorption coupled with ISCO technology can significantly improve remediation efficiency, shorten the remediation cycle, and precisely control agent delivery with the help of numerical simulation to avoid secondary contamination., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Cong Han, Xiaobin Zhu, Guiyao Xiong, Jingxun Gao, Jianfeng Wu, Dong Wang, Jichun Wu, (Copyright © 2023. Published by Elsevier Ltd.)

Microplastics are widely detected in the soil-groundwater environment, which has attracted more and more attention. Clay mineral is an important component of the porous media contained in aquifers. The transport experiments of polystyrene nanoparticles (PSNPs) in quartz sand (QS) mixed with three kinds of clay minerals are conducted to investigate the effects of kaolinite (KL), montmorillonite (MT) and illite (IL) on the mobility of PSNPs in groundwater. Two-dimensional (2D) distributions of DLVO interaction energy are calculated to quantify the interactions between PSNPs and three kinds of clay minerals. The critical ionic strengths (CIS) of PSNPs-KL, PSNPs-MT and PSNPs-IL are 17.0 mM, 19.3 mM and 21.0 mM, respectively. Experimental results suggest KL has the strongest inhibition effect on the mobility of PSNPs, followed by MT and IL. Simultaneously, the change of ionic strength can alter the surface charge of PSNPs and clay minerals, thus affecting the interaction energy. Experimental and model results indicate both the deposition rate coefficient (k) and maximum deposition (S max ) linearly decrease with the logarithm of the DLVO energy barrier, while the mass recovery rate of PSNPs (R m ) exponentially increases with the logarithm of the DLVO energy barrier. Therefore, the mobility and associated kinetic parameters of PSNPs in complex porous media containing clay minerals can be predicted by 2D distributions of DLVO interaction energy. These findings could help to gain insight into understanding the environmental behavior and transport mechanism of microplastics in the multicomponent porous media, and provide a scientific basis for the accurate simulation and prediction of microplastic contamination in the groundwater system., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The quantification of trade-offs between social-economic and environmental effects is of great importance, especially in the semi-arid coastal areas with highly developed agriculture. The study presents an integrated multi-objective simulation-optimization (S-O) framework to evaluate the basin-scale water-environment-agriculture (WEA) nexus. First, the variable-density groundwater model (SEAWAT) is coupled to the reactive transport model (RT3D) for the first attempt to simulate the environmental effects subject to seawater intrusion (SWI) and nitrate pollution (NP). Then, the surrogate assisted multi-objective optimization algorithm is utilized to investigate the trade-offs between the net agricultural benefits and extents of SWI and NP while considering the water supply, food security, and land availability simultaneously. The S-O modeling methodology is applied to the Dagu River Basin (DRB), a typical SWI region with intensive agricultural irrigation in China. It is shown that the three-objective space based on Pareto-optimal front can be achieved by optimizing planting area in the irrigation districts, indicating the optimal evolution of the WEA nexus system. The Pareto-optimal solutions generated by multi-objective S-O model are more realistic and pragmatic, avoiding the decision bias that may often lead to cognitive myopia caused by the low-dimensional objectives. Although the net agricultural benefits in Pareto-optimal solutions are declined to some extent, the environmental objectives (the extents of SWI and NP) are improved compared to those in the pre-optimized scheme. Therefore, the proposed multi-objective S-O framework can be applied to the WEA nexus in the river basin with intensive agriculture development, which is significant to implement the integrated management of water, food, and environment, especially for the semi-arid coastal aquifers., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Rational coastal groundwater planning is of great significance to freshwater supply for sustainable social-economic development, and to environmental protection in case of seawater intrusion (SI). Quantifying the relation among groundwater quality, quantity, and the related social-economic benefits in a coastal region with intense spatio-temporal variation in groundwater abstraction is helpful to the restoration of the coastal aquifer, and the practical policymaking. However, due to the comprehensive reality involving interdisciplinary principles, it is usually difficult to integrate all the main attributes of groundwater resources into a mono-policymaking process, which might lead to biased decisions, producing a series of adverse impacts on the environment and the social economy. This study thereby develops a combined simulation-optimization model (S-O model) in the coastal part of Longkou City, China, for striking the balance among the three main attributes of groundwater, i.e., the groundwater quantity, groundwater quality or its environmental function, and its related economic yield involving the agricultural and industrial sectors. It is seen that the industrial sector contributed over 80% of the economic yield by consuming over 10% of the total groundwater resource, and the massive agricultural use of groundwater was mainly responsible for the SI. The results of the multi-objective optimization provided practical alternative schemes for groundwater abstraction in terms of maximizing economic yield and minimizing SI. Moreover, the decision discrepancy caused by partial management only considering the groundwater quantity and quality would lower the water use efficiency, and then cause unacceptable economic losses for the enterprises and the government. Our research highlights that the interdisciplinary management of groundwater resources based on the S-O model could significantly improve practicability in groundwater policymaking, and provides a typical reference for the other developing regions facing difficulty in groundwater management during coastal urban planning and economic transformation., (Copyright © 2022. Published by Elsevier Ltd.)

Coastal aquifer management (CAM) considering conjunctive optimization of pumping and injection system for seawater intrusion (SI) mitigation poses significant decision-making challenges. CAM needs to pose multiple objectives and massive decision variables to explore tradeoff strategies between the conflicting resources, economic, and environmental requirements. Here, we investigate a joint artificial injection scheme for ameliorating SI by establishing an evolutionary multi-objective decision-making framework that combines simulation-optimization (S-O) modelling with a cost-benefit analysis, and demonstrate the framework on a large-scale CAM case in Baldwin County, Alabama. First, a SI numerical model, using SEAWAT, was configured to predict the vulnerable region as an SI encroachment area with the scenarios of minimum and maximum pumping capacity. As a result, a smaller number of candidate sites were selected in the SI encroachment area for implementing groundwater injection to avoid the computationally infeasible SI optimization with an inordinate number of injection related decision variables. Second, the effective S-O methodology of niched Pareto tabu search combined with a genetic algorithm (NPTSGA), which considers the moving-well option, was applied to discover optimal pumping/injection (P/I) strategies (including P/I rates and injection well locations) between three conflicting management objectives under complicated SI constraints. Third, for practical operation of the P/I schemes, a cost-benefit analysis provides judgment criteria to allow decision-makers to implement more sustainable P/I strategies to capture the different realistic preferences. The implementation of three extreme optimization solutions for the case study indicates that, compared to the initial unoptimized scheme, a maximum increase of a factor of 3 in groundwater extraction rates, a maximum reduction of 17% in extent of SI, and a maximum 82.3 million US dollars in comprehensive benefits are specifically achieved by conjunctive P/I optimization. The robustness in the decision alternatives attributed to the uncertainty in physical parameters of hydraulic conductivity was discovered through global sensitivity analysis. The proposed framework provides a decision support system for multi-objective CAM with combined pumping control and engineering measures for SI mitigation., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

This study presents a new multiobjective evolutionary algorithm (MOEA), the elitist multiobjective tabu search (EMOTS), and incorporates it with MODFLOW/MT3DMS to develop a groundwater simulation-optimization (SO) framework based on modular design for optimal design of groundwater remediation systems using pump-and-treat (PAT) technique. The most notable improvement of EMOTS over the original multiple objective tabu search (MOTS) lies in the elitist strategy, selection strategy, and neighborhood move rule. The elitist strategy is to maintain all nondominated solutions within later search process for better converging to the true Pareto front. The elitism-based selection operator is modified to choose two most remote solutions from current candidate list as seed solutions to increase the diversity of searching space. Moreover, neighborhood solutions are uniformly generated using the Latin hypercube sampling (LHS) in the bounded neighborhood space around each seed solution. To demonstrate the performance of the EMOTS, we consider a synthetic groundwater remediation example. Problem formulations consist of two objective functions with continuous decision variables of pumping rates while meeting water quality requirements. Especially, sensitivity analysis is evaluated through the synthetic case for determination of optimal combination of the heuristic parameters. Furthermore, the EMOTS is successfully applied to evaluate remediation options at the field site of the Massachusetts Military Reservation (MMR) in Cape Cod, Massachusetts. With both the hypothetical and the large-scale field remediation sites, the EMOTS-based SO framework is demonstrated to outperform the original MOTS in achieving the performance metrics of optimality and diversity of nondominated frontiers with desirable stability and robustness., (© 2017, National Ground Water Association.)

The distribution of perfluoroalkyl acids (PFAAs), one class of persistent organic pollutants, in groundwater, especially in confined aquifers remains poorly understood. In this study, we investigated the occurrence of 12 PFAAs through a water cycle from the Huai River Basin to the Yellow Sea, including confined aquifers, unconfined aquifers, rivers, and coastal waters. We found the ubiquity of PFAAs in all types of samples, including those from confined aquifers (2.7-6.8 ng/L). Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) were the major PFAAs in all samples, accounting for an average of 49.1% (0.8-84.8%) and 33.3% (6.3-92.2%) of total PFAAs, respectively. Comparing the concentration of PFOA with that of PFOS, we found a higher concentration of PFOA in rivers and a higher concentration of PFOS in confined aquifers. Short-chain perfluoropentanoic acid accounted for an average of 10.3% (1.9-24.6%) of total PFAAs in rivers and coastal waters. Branched isomers of both PFOA and PFOS were detected in most samples (36/42 and 39/42, respectively). One-way analysis of variance indicated a significant difference in the profiles of PFAAs among the different types of water samples. Principal component analysis suggested that rainwater and recent uses of PFAAs could be the major sources of PFAAs in confined aquifers, while recent and current uses of PFAAs could be the major source of PFAAs in unconfined aquifers, rivers and coastal waters. The risk quotients of PFOA and PFOS in groundwater and rivers were 2-3 orders of magnitude lower than unity, indicating no immediate risks via drinking water consumption., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The North China Plain (NCP) is one of the most severe water shortage areas in China. Due to the scarcity of surface water in the NCP, groundwater system is seriously over-exploited and use of nitrogen fertilizers is greatly increasing year by year to improve soil fertility and crop production, causing a variety of environmental issues in the processes of abstracting groundwater. Considering that previous research was limited on approaches to assess sustainability of groundwater through flow modeling and water level decline, this study focuses on addressing the implications of groundwater contaminant for water resource sustainability in the central part of NCP. Based on the previously developed groundwater flow model, a reaction modular code for the reactive transport in three-dimensional aquifers (RT3D) is developed for simulating the reactive process of nitrogen species transport in groundwater system. The management optimization model coupled with the nitrogen reactive transport model under consideration of water quality constraints is then conducted to quantify and improve the sustainability of groundwater utilization in the study area. Thus, the optimal pumping well locations and pumping rates that lead to the maximum total yield or the minimum total management costs subjecting to a series of groundwater level constraints are obtained from the optimization models. Compared with the optimization model without water quality constraints, this study could provide a more useful tool for developing cost-effective strategies for sustainable management of groundwater resource in the NCP, and greatly improve groundwater management level and water quality., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Polyamide (PA) and bisphenol A (BPA) are selected as typical microplastic and endocrine-disrupting chemicals in this study. The adsorption of BPA on the surface of PA and the effect of PA on the transport behavior of BPA in groundwater are systematically investigated using a combination of batch experiments, column experiments and numerical models. The results of scanning electron microscope (SEM) and Fourier transform infrared spectra (FTIR) show that the surface of PA particles is changed significantly after adsorption of BPA. The isothermal adsorption process of BPA can be simulated by the Langmuir model and the Freundlich model. Kinetic adsorption, on the other hand, can be fitted by a quasi-first-order adsorption model, and the adsorption results indicate that the maximum adsorption of BPA on PA reaches 13 mg·g−1. The results of the column experiments suggest that the mass recovery rate of BPA decreases with PA content, and increases with flow velocity, while initial concentration has no apparent influence on BPA transport. In addition, due to the hydrolysis of BPA, the mass recovery rate of BPA does not change with pH under conditions of pH < 10.2 and increases substantially to 94% when pH > 10.2. Moreover, Ca2+ has a significant inhibitory effect on the transport of BPA, while Na+ has no apparent influence on the transport of BPA. The transport process of BPA in porous media is simulated using a single-point kinetic model, and the fitted mathematical relationships for the variation of kinetic parameters with environmental factors are obtained by regression analysis. [ABSTRACT FROM AUTHOR]

The environment of Bosten Lake in the Mid-Eastern Yanqi Basin (MEYB), an arid inland area in northwest China, has deteriorated greatly due to increasing groundwater exploitation and changes in the interactions between groundwater and surface water. This study intended to simulate the spatio-temporal variability of groundwater and surface water across the entire MEYB over the period 2000-2013. The applicable groundwater flow model and mass balance calculation method for river water were constructed to evaluate the change in groundwater recharged by and discharged to different segments of the Kaidu River. Simulation results show that the entire river seepage in the MEYB increased from 1.05 to 6.17 × 108 m3/year between 2000 and 2013. The increasing river seepage, induced by increasing groundwater exploitation, plays the most important role in the water level decline in the downstream reaches of the Kaidu River and in Bosten Lake. This implies that the current utilization of groundwater resources in the MEYB is unsustainable. [ABSTRACT FROM AUTHOR]

Yang, Y.; Wu, J.; Lin, J.; Wang, J.; Zhou, Z., and Wu, J., 2018. An efficient simulation–optimization approach for controlling seawater intrusion. In: Wang, D. and Guido-Aldana, P.A. (eds.), Select Proceedings from the 3rd International Conference on Water Resource and Environment (WRE2017). Journal of Coastal Research, Special Issue No. 84, pp. 10–18. Coconut Creek (Florida), ISSN 0749-0208. The management of freshwater stored in coastal aquifers involves decisions regarding not only the sustainable utilization and exploration of optimal coastal groundwater resources but also the designing of optimal strategies for controlling seawater intrusion (SI). Simultaneously optimizing pumping operation, the extent of SI, and design of mitigation measures is a challenging task because mitigating SI has become imperative for groundwater management of coastal aquifers. This study proposed a simulation-optimization framework (SWT-NPTSGA) to search Pareto-optimal solutions for estimating the optimal pumping and artificial recharge schemes under complicated SI constraints. The SWT-NPTSGA is based on a combination of a new hybrid multi-objective evolutionary algorithm, the niched Pareto tabu search combined with a genetic algorithm, and the numerical variable-density groundwater flow and transport model. Three different management scenarios, pumping only, injection only, and combined pumping and injection (P&I), were designed in a synthetic application to evaluate the efficiency of the proposed methodology. The results showed that the P&I scenario could generate comprehensive information for multi-objective decision-making. The SI mitigation measures by artificial recharge could offer the most groundwater supply and the least area of seawater intrusion. The optimization results showed the potential feasibility of the proposed methodology for managing groundwater resources and controlling SI in coastal aquifers. [ABSTRACT FROM AUTHOR]

For most of aquifers with abundant groundwater resource, quantifications of tortuosity and corresponding representative elementary volume (REV) are very essential to improve the understanding of groundwater and contaminant transfers in porous media. In this study, a mathematical model of tortuosity based on the three dimensional (3D) microstructure of regular tetrahedron (RTM) is proposed to quantify tortuosity and corresponding REV of granular porous media. The calculated tortuosity using the new 3D RTM model agrees well with the measured tortuosity in experiment, indicating that the new 3D microstructure model is more appropriate to precisely delineate the tortuosity of granular porous media. Afterward, the new model is utilized to quantify the tortuosity of heterogeneous translucent silica. Moreover, corresponding REV is estimated using a criterion of relative gradient error ( ε g i ). Results suggest minimum τ -REV sizes most distribute in 0.0–5.0 mm and the bound of cumulative frequency above 80% is larger than 3.00 mm. The REV scale of tortuosity has its own rationality and superiority over that estimated by two-dimensional (2D) tortuosity model, implying the proposed 3D tortuosity model of RTM is helpful for understanding the tortuosity of flow paths in granular porous media and corresponding REV estimation of tortuosity. [ABSTRACT FROM AUTHOR]

Groundwater can be stored abundantly in granulacomposed aquifers with high permeability. The microstructure of granular materials has important effect on the permeability of aquifers and the contaminant migration and remediation in aquifers is also influenced by the characteristics of porous media. In this study, two different microscale arrangements of sand particles are compared to reveal the effects of microstructure on the contaminant migration and remediation. With the help of fractal theory, the mathematical expressions of permeability and entry pressure are conducted to delineate granular materials with regular triangle arrangement (RTA) and square pitch arrangement (SPA) at microscale. Using a sequential Gaussian simulation (SGS) method, a synthetic heterogeneous site contaminated by perchloroethylene (PCE) is then used to investigate the migration and remediation affected by the two different microscale arrangements. PCE is released from an underground storage tank into the aquifer and the surfactant is used to clean up the subsurface contamination. Results suggest that RTA can not only cause more groundwater contamination, but also make remediation become more difficult. The PCE remediation efficiency of 60.01-99.78% with a mean of 92.52 and 65.53-99.74% with a mean of 95.83% is achieved for 200 individual heterogeneous realizations based on the RTA and SPA, respectively, indicating that the cleanup of PCE in aquifer with SPA is significantly easier. This study leads to a new understanding of the microstructures of porous media and demonstrates how microscale arrangements control contaminant migration in aquifers, which is helpful to design successful remediation scheme for underground storage tank spill. [ABSTRACT FROM AUTHOR]

Abstract: Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap‐to‐evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion‐based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD‐based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling. [ABSTRACT FROM AUTHOR]

To investigate the effect of microplastics on the transport and retention of antibiotics in subsurface environment, polypropylene (PP) and ciprofloxacin (CIP) are selected as typical microplastic and antibiotic contaminant, respectively. The key factors and main control mechanisms are systematically investigated using a combination of adsorption experiments, column experiments and numerical model. The adsorption experiments indicate the largest adsorption capacity of CIP on PP is 1.03 mg·g−1. Simultaneously, the results of column experiments and numerical model suggest that PP can significantly affect the migration behavior and retention of CIP in porous media. CIP mobility is positively correlated to flow velocity, initial concentration of CIP and ionic strength (Na+, Ca2+ and Ba2+). Moreover, compared to monovalent cation (Na+), divalent cations (Ca2+, Ba2+) have a stronger enhancement effect on CIP mobility and a stronger inhibition effect on CIP retention in saturated porous media. The transport of CIP in saturated porous media containing PP is simulated by a single-point kinetic model, and the equations of the transport kinetic parameters of CIP are obtained through regression analysis. The research could help to gain insight into understanding the environmental behavior of antibiotic in the groundwater system, and provide scientific basis for the accurate prediction and assessment of environmental risk caused by microplastic and antibiotic in the groundwater system. [Display omitted] • The adsorption capacity of CIP on PP is stronger than that on QS. • PP significantly affects the migration behavior of CIP in porous media. • Divalent cations enhance CIP mobility more than monovalent cations. • Single-point kinetic deposition model can simulate and predict the effect of PP on CIP migration. • The relationship between CIP transport kinetic parameters and environmental factors are obtained. [ABSTRACT FROM AUTHOR]

A new multi-objective optimization methodology is developed, whereby a multi-objective fast harmony search (MOFHS) is coupled with a groundwater flow and transport model to search for optimal design of groundwater remediation systems under general hydrogeological conditions. The MOFHS incorporates the niche technique into the previously improved fast harmony search and is enhanced by adding the Pareto solution set filter and an elite individual preservation strategy to guarantee uniformity and integrity of the Pareto front of multi-objective optimization problems. Also, the operation library of individual fitness is introduced to improve calculation speed. Moreover, the MOFHS is coupled with the commonly used flow and transport codes MODFLOW and MT3DMS, to search for optimal design of pump-and-treat systems, aiming at minimization of the remediation cost and minimization of the mass remaining in aquifers. Compared with three existing multi-objective optimization methods, including the improved niched Pareto genetic algorithm (INPGA), the non-dominated sorting genetic algorithm II (NSGAII), and the multi-objective harmony search (MOHS), the proposed methodology then demonstrated its applicability and efficiency through a two-dimensional hypothetical test problem and a three-dimensional field problem in Indiana (USA). [ABSTRACT FROM AUTHOR]

In this study, a novel surrogate model assisted multiobjective memetic algorithm (SMOMA) is developed for optimal pumping strategies of large-scale coastal groundwater problems. The proposed SMOMA integrates an efficient data-driven surrogate model with an improved non-dominated sorted genetic algorithm-II (NSGAII) that employs a local search operator to accelerate its convergence in optimization. The surrogate model based on Kernel Extreme Learning Machine (KELM) is developed and evaluated as an approximate simulator to generate the patterns of regional groundwater flow and salinity levels in coastal aquifers for reducing huge computational burden. The KELM model is adaptively trained during evolutionary search to satisfy desired fidelity level of surrogate so that it inhibits error accumulation of forecasting and results in correctly converging to true Pareto-optimal front. The proposed methodology is then applied to a large-scale coastal aquifer management in Baldwin County, Alabama. Objectives of minimizing the saltwater mass increase and maximizing the total pumping rate in the coastal aquifers are considered. The optimal solutions achieved by the proposed adaptive surrogate model are compared against those solutions obtained from one-shot surrogate model and original simulation model. The adaptive surrogate model does not only improve the prediction accuracy of Pareto-optimal solutions compared with those by the one-shot surrogate model, but also maintains the equivalent quality of Pareto-optimal solutions compared with those by NSGAII coupled with original simulation model, while retaining the advantage of surrogate models in reducing computational burden up to 94% of time-saving. This study shows that the proposed methodology is a computationally efficient and promising tool for multiobjective optimizations of coastal aquifer managements. [ABSTRACT FROM AUTHOR]

[Display omitted] • Groundwater vulnerability zonation investigation is conducted for GHM Greater Bay Area. • Three different perspectives are comprehensively considered in this study. • Groundwater risk, function value and contamination status are superposed using the AHP method. • Quantification and visualization of groundwater contamination prevention regionalization. • The AHP-DRASTICH model is an effective method to evaluate the groundwater risk in shallow aquifers. The groundwater contamination assessment and prevention regionalization are an important part of groundwater investigation, which is of great significance to groundwater environmental management and contamination control. Although the Guangdong-Hong Kong-Macao Greater Bay Area (GHM Greater Bay Area) has faced significant groundwater contamination since 2020, there's been no investigation into its vulnerability zonation. In this paper, groundwater in a typical area of south China was taken as the research object. We analyzed groundwater contamination risk by considering both the groundwater vulnerability and the load from contamination sources. Using the analytic hierarchy process (AHP) method, we superposed the groundwater risk, function value and contamination status, and realized the quantification and visualization of groundwater contamination prevention regionalization. Based on the DRASTIC model, the zones of low, moderate, high, and very high vulnerability are respectively 14.2 %, 24.28 %, 37.67 %, and 20.45 % of the study area. Results show that the groundwater vulnerability grade in the area is III-IV, which means it is easy to be polluted. The functional value of groundwater in the south-central part of the region is relatively high. Most of the areas with high prevention and control levels are located in plain areas and the Piedmont plain area with an area of 460 km2. The secondary control levels (key protection area) are mainly located in the middle, southwest, and northeast of the plain, with an area of 6944 square kilometers. Consequently, the ideas and contamination prevention zone maps might provide a scientific foundation for long-term planning and management and groundwater conservation in the Guangdong-Hong Kong-Macao Greater Bay Area and peripheral zones. [ABSTRACT FROM AUTHOR]

• SOM was conducted to evaluate the long-term variations of groundwater hydrochemistry. • SOM clustering results reflected the governing factors of groundwater hydrochemistry. • HFE-Diagram indicated hydrochemical facies and its evolution imposed by SI. • Groundwater pollution arose from nitrogen fertilizer, excrement, and domestic sewage. A clear identification of the hydrochemical processes in groundwater systems is critical for the management and protection of alternative water resources. The Dagu River Basin (DRB) has become one of the most concerning areas due to the typical geographical conditions and intensive human disturbance. In this study, the spatio-temporal variations of groundwater hydrochemical characteristics were discriminated based on the self-organizing maps (SOM) clustering results from 2001 to 2017. Simultaneously, their main governing factors were also identified according to the composite properties of hydrogen and oxygen isotopic evidence, hydrochemical facies evolution diagram (HFE-D), chloro-alkaline indices (CAI) values, and the enrichment of nitrogen. Analysis results indicated that the long-term evolution of hydrochemical signatures basically conformed to the trends of rising in the dry season and falling in the rainy season. Total dissolved solids (TDS) fluctuated from 187.90 mg/L to 2294.81 mg/L, with an average of 881.77 mg/L. Moreover, the nitrate concentrations in the river basin varied significantly from 0.70 mg/L to 605.32 mg/L. The unconfined aquifer beneath DRB was experiencing freshening gradually, while some other samples were still subjected to the interference of environmental pollution. Spatio-temporal variations in the respective clusters demonstrated that natural factors including precipitation infiltration, evaporation, and water–rock interactions played vital roles in the samples of Clusters I-III, V, and VIII, while the samples of Cluster VII were influenced by seawater intrusion; and those of Clusters IV and VI were mainly affected by nitrate and nitrite contamination. This study suggests that the SOM connected with stable isotope analysis, HFE-Diagram, CAI values, and correlation analysis could be successfully used to interpret nonlinear and high-dimensional multivariate systems and provide supplementary information about the dominant mechanisms controlling the regional groundwater evolution. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Classification of four soil gleyization types based on soil chemical prosperities. • Impacts of groundwater depth on soil gleyization in field and laboratory condition. • Establishing a FEFLOW model for regional groundwater depths assessment. • Implementation of model assessment under four climate change scenarios. • The GRD will suffer a significant soil gleyization due to future climate changes. Abstract Various natural and anthropogenic factors affect the formation of gleyed soil. It is a major challenge to identify the key hazard factors and evaluate the dynamic evolutionary process of soil gleyization at a regional scale under future climate change. This study addressed this complex challenge based on regional groundwater modelling for a typical agriculture region located in the Ganjiang River Delta (GRD) of Poyang Lake Basin, China. We first implemented in-situ soil sampling analysis and column experiments under different water depths to examine the statistical relationship between groundwater depth (GD) and gleyization indexes including active reducing substance, ferrous iron content, and redox potential. Subsequently, a three-dimensional groundwater flow numerical model for the GRD was established to evaluate the impacts of the historical average level and future climate change on vadose saturation and soil gleyization (averaged over 2016–2050) in the irrigated farmland. Three climate change scenarios associated with carbon dioxide emission (A1B, A2, and B1) were predicted by the ECHAM5 global circulation model published in IPCC Assessment Report (2007). The ECHAM5 outputs were applied to quantify the variation of groundwater level and to identify the potential maximum gleyed zones affected by the changes of meteorological and hydrological conditions. The results of this study indicate that GD is an indirect indicator for predicting the gradation of soil gleyization at the regional scale, and that the GRD will suffer considerable soil gleyization by 2050 due to fluctuations of the water table induced by future climate changes. Compared with the annually average condition, the climate scenario B1 will probably exacerbate soil gleyization with an 8.8% increase in total gleyed area in GRD. On average, the highly gleyed areas will increase in area by 29.7 km2, mainly on the riverside area, and the medium-slightly gleyed area will increase by 19.2 km2 in the middle region. [ABSTRACT FROM AUTHOR]

In this work, column experiments were conducted to investigate the transport characteristics of graphene oxide (GO) nanoparticles in limestone media under various electrolytes, solution pH, and humic acid (HA) concentration conditions. In the limestone media, GO exhibited relatively low mobility with the mass recovery rate lower than 65.2%, even when solution ionic strength was low. The presence of HA enhanced its mobility. In addition, the presence of S 2- , a divalent anion, also promoted GO transport in limestone media compared to Cl − under similar ionic strength conditions through neutralizing more positive charge and thus diminishing the cation bridging. Solution pH showed slight effect on the transport of GO in limestone with the mass recovery range from 40.3% to 51.7%. Over all, decreases in solution pH, HA concentration and increases in solution ionic strength reduced the mobility of GO in the limestone media under the tested conditions. These results indicated both environmental conditions and media characteristics played important roles in controlling GO fate and transport in porous media. The one-site kinetic deposition model was applied to describe the interactions between the GO and limestone media and model simulations fitted the observed experimental data very well. As limestone is an important component of aquiferous media in subsurface, findings from this study elucidated the key factors and processes controlling the fate of GO particles in limestone media, which can inform the prediction and assessment of the risks of GO in groundwater environment. [ABSTRACT FROM AUTHOR]