Groundwater Pollution Sources Research Articles

Analysis of Nitrogen and Phosphorus Flows in a Rice-Growing Basin: The Case of the Maga Production Basin (Cameroon)

The availability of irrigation water has favored the development of agriculture in the Maga area, located in the Far North of Cameroon, with rice growing as the dominant agricultural activity. This activity is, however, known as a source of groundwater pollution through the infiltration of substances contained in inputs used for soil fertilization. The present study is a contribution to the analysis of the sources of contamination of the waters of the Maga rice basin by nitrogen and phosphate mineral compounds as well as the spatial distribution of these compounds. The monitoring of a network of fifteen wells and boreholes covering the rice-growing area during six campaigns made it possible to carry out the physicochemical characterization of subsurface and groundwater. The results obtained reveal that nitrates (NO3−) are present in water in low quantities, with averages per campaign ranging from 9.01 mg/L to 20.31 mg/L. On the other hand, ammonium (NH4+) and phosphates (PO43−) are in significant concentration. Their averages are of the order of 2.62 mg/L to 4.51 mg/L and then 0.65 mg/L to 5.58 mg/L for ammonium and phosphates, respectively. Mineral fertilizers used for soil amendment and degradation of organic matter, as well as the hydrolysis of minerals contained in the soil, contribute to the mineralization of water in the study area.

Shallow Groundwater Quality Assessment and Pollution Source Apportionment: Case Study in Wujiang District, Suzhou City

Groundwater serves as a crucial resource, with its quality significantly impacted by both natural and human-induced factors. In the highly industrialized and urbanized Yangtze River Delta region, the sources of pollutants in shallow groundwater are more complex, making the identification of groundwater pollution sources a challenging task. In this study, 117 wells in Wujiang District of Suzhou City were sampled, and 16 groundwater quality parameters were analyzed. The fuzzy synthetic evaluation method was used to assess the current status of groundwater pollution in the study area; the principal component analysis (PCA) was employed to discern the anthropogenic and natural variables that influence the quality of shallow groundwater; and the absolute principal component scores–multiple linear regression (APCS-MLR) model was applied to quantify the contributions of various origins toward the selected groundwater quality parameters. The results indicate that the main exceeding indicators of groundwater in Wujiang District are I (28%), NH4-N (18%), and Mn (14%); overall, the groundwater quality is relatively good in the region, with localized heavy pollution: class IV and class V water are mainly concentrated in the southwest of Lili Town, the north of Songling Town, and the south of Qidu Town. Through PCA, five factors contributing to the hydrochemical characteristics of groundwater in Wujiang District were identified: water–rock interaction, surface water–groundwater interaction, sewage discharge from the textile industry, urban domestic sewage discharge, and agricultural non-point source pollution. Additionally, the APCS-MLR model determined that the contributions of the three main pollution sources to groundwater contamination are in the following order: sewage discharge from the textile industry (10.63%) > urban domestic sewage discharge (8.69%) > agricultural non-point source pollution (6.26%).

Spatial variability, source identification, and partitioning of groundwater constituents in a typical lakeside plain on Yungui Plateau

The fragile ecological balance of lakeside plains on plateau makes groundwater hydrochemical composition highly susceptible to human disturbances. This research investigates a typical plain on Yunnan Plateau to quantitatively identify the potential sources of groundwater pollution in lakeside plains on plateau by combining receptor models with risk assessment models. Receptor models show there are three potential pollution sources for groundwater including water-rock interactions, agricultural pollution, and domestic sewage/manure discharge. Groundwater hydrochemical composition is predominantly shaped by natural water-rock interactions, accounting for an average of 50.12 % of the influence. This is followed by agricultural non-point source pollution, which contributes 10.79 %, and the discharge of domestic sewage and manure, which accounts for 10.61 %. Groundwater in the current plain could pose a minor non-carcinogenic risk for long-term drinking, with the total hazard index (THI) for adults varying between 0.015 and 1.089, and for children between 0.024 and 1.737. Notably, 4.35 % of groundwater samples have a THI exceeding the safe threshold of 1. NO3- (72 %) is the primary contributor to non-carcinogenic risks, accounting for 72 %, trailed by Mn (13 %), NH4+ (9 %), Fe (6 %) and NO2- (1 %). The non-carcinogenic risks are predominantly attributed to agricultural non-point source pollution (71.6 %) and the discharge of domestic sewage and manure (26.9 %). A conceptual model has been developed to encapsulate the dynamics of groundwater quality formation in lakeside plains on plateau. This research will aid residents in safeguarding against groundwater contamination and enhancing agricultural practices in present plain and similar lakeside plain worldwide.

Three-dimensional solute transport in finite and curved porous media with surface input sources

In this paper, an analytical solution for three-dimensional solute transport in porous media between two curved surfaces is investigated. It is assumed that the groundwater velocity and dispersion coefficient vary with time and position. Groundwater velocity is not considered to be horizontal. The components of dispersion coefficient along the axes are considered to be proportional to the square of corresponding the position variable. The dispersion coefficient components along axes are proportional to the corresponding component of groundwater velocity in temporal aspects while former is squarely proportional to letter one in position components. It is assumed that the sources originate from two curved surfaces. The nature of the source on the two surfaces is the same, but there may be a variation in potential. Initially, the aquifer's domain is supposed to be uniformly polluted. The Laplace Integral Transformation Technique (LITT) is used to obtain analytical solutions. Numerical examples are given to demonstrate the effects of various factors on the solute concentration profile in a system where advection and dispersion play important roles.In addition, the sub-case of horizontal flow is also discussed. The model is extremely useful in analyzing and dealing with widespread surface sources of groundwater pollution in simulated agricultural fields or urban dumping areas.

Groundwater Pollution Source and Aquifer Parameter Estimation Based on a Stacked Autoencoder Substitute

A concurrent heuristic search iterative process (CHSIP) is used for estimating groundwater pollution sources and aquifer parameters in this work. Frequent calls to carry out a numerical simulation of groundwater pollution have generated a huge calculated load during the CHSIP. Therefore, a valid means to mitigate this is building a substitute to emulate the numerical simulation at a low calculated load. However, there is a complicated nonlinear correlativity between the import and export of the numerical simulation on account of the large quantity of variables. This leads to a poor approach accuracy of the substitute compared to the simulation when using shallow learning methods. Therefore, we first built a stacked autoencoder substitute, using the deep learning method, to boost the approach accuracy of the substitute compared to the numerical simulation. In total, 400 training samples and 100 testing samples for the substitute were collected by employing the Latin hypercube sampling method and running the numerical simulator. The CHSIP was then employed for estimating the groundwater pollution sources and aquifer parameters, and the estimated outcome was obtained when the CHSIP was terminated. The data analysis, including interval estimation and point estimation, was implemented on the MATLAB platform. A relevant hypothetical case is set to verify our approaches, which shows that the CHSIP is helpful for estimating the groundwater pollution source and aquifer parameters and that the stacked autoencoder method can effectively boost the approach precision of the substitute for the simulator.

Intelligent enhanced particle filter with deep residual network surrogate for accurate groundwater pollution source characterization

Accurate groundwater pollution source characterization (GPSC) is crucial for environmental protection and water resource management. Although the particle filter (PF) algorithm is widely employed for GPSC, it suffers from particle degradation and loss of diversity. To address this challenge, this study proposes an intelligent enhanced particle filter (IEPF) method to enhance GPSC’s accuracy and efficiency. First, this method optimizes the resampling process by defining a weight threshold while introducing an information transmission mechanism. This mechanism enables low-weight particles to update their positions by leveraging information from high-weight particles and neighboring particles, thereby enhancing information exchange among particles and improving the algorithm’s global search capability. Crossover and mutation operations are introduced to further increase the particle diversity, effectively preventing particles from concentrating on local optimal solutions. Furthermore, this study employs a deep residual network (ResNet) as a surrogate model for the simulation model. The ResNet has strong feature learning and expression capabilities and efficiently captures nonlinear relationships in data, thus significantly improving computational efficiency while ensuring accuracy. The results demonstrate that the IEPF method significantly enhances GPSC accuracy. In summary, the proposed IEPF method combined with the ResNet surrogate model provides an efficient and accurate approach to GPSC, with considerable benefits for groundwater pollution management.

Preliminary Validation of Persulfate Delivery Through Porous Pipe in the Vadose Zone: A Two-Dimensional Sandbox Experiment

ABSTRACT When remediating contamination in the vadose zone, which is a potential source of continuous groundwater and surface water pollution, technical challenges are often encountered. In this study, the feasibility of delivering sodium persulfate (SPS) oxidant to unsaturated soils was explored by integrating porous pipes, commonly used in agriculture, with in-situ chemical oxidation (ISCO). An evaluation of the operating characteristics of the pipe determined a recommended influent rate of < 0.1 L min−1 and an initial influent water pressure < 20 kPa to prevent percolation pore enlargement. Two-dimensional sandbox experiments revealed that pulse infiltration at an influent rate of 0.05 L min−1 was effective in creating matrix flow and lateral movement, minimizing preferential flow induced by continuous infiltration. Application of SPS (10% by wt.) under these conditions resulted in approximately 90% wetting of the sandbox area SPS flow at the experimental time that infiltrated from the pipe. After a 14-d post infiltration resting state, residual SPS concentrations ranged from 6,000 -12,000 mg/kg in soil, with soil pH levels of 3–4, ORP around 600 mV, and 40–60% decreases in soil organic carbon. This developed method helps retain the oxidant and promote chemical reactions, making ISCO a viable option for remediating unsaturated soil contamination.

Unraveling the hydrogeochemical characteristics and pollution sources of groundwater in an intensive industrial area, East China.

It is challenging to interpret hydrogeochemical datasets with complex natural and anthropogenic genesis in intensive industrial areas. This paper elucidates the hydrogeochemical characteristics and pollution sources of groundwater in an industrial park, East China, combining the self-organizing map (SOM), hydrochemical graphs, and correlation analysis. The results show that the total dissolved solids of groundwater range from 73.45 to 997.92mg/L and can be regarded as freshwater. The pH varies greatly from 6.44 to 9.90, most of samples belonging to weakly acidic-weakly alkaline. The groundwater can be classified into five clusters by SOM, representing the non- or least-polluted groundwater (cluster D), high salt groundwater (cluster A), high NH4+-N and HCO3- groundwater (cluster B), high Fe and Mn groundwater (cluster C), and high pH groundwater (cluster E), which were contaminated by industrial salts, historical agriculture activity, industrial reducing substances, and industrial alkali, respectively. The natural evolution of groundwater (cluster D) in the study area is mainly controlled by mineral weathering/dissolution. The contributions of calcite, dolomite, gypsum, halite, and silicate mineral to groundwater solute are 55.8-66.3%, 15.1-18.0%, 9.0-10.7%, 2.5-10.1%, and 2.3-9.4%, respectively, based on the mass conservation. The contaminated groundwaters (all other clusters except for cluster D) have different hydrochemical characteristics associated with the pollution sources. In addition, the relatively reductive environment in quaternary flu-lacustrine sediments favored the formation of high level of Fe, Mn, and NH4+-N in groundwater. This study provides a new insight into the characteristic contaminants and their distributions in groundwater and the associated pollution sources based on the large datasets in an intensive industrial area. The data evaluation methods and results of this study could be useful to the groundwater usage management and pollution control in this area and other industrial areas.

Arsenic-contaminated groundwater of the Western Banat (Pannonian basin): Hydrogeochemical appraisal, pollution source apportionment, and Monte Carlo simulation of source-specific health risks.

Due to rapid urbanization and industrial growth, groundwater globally is continuously deteriorating, posing significant health risks to humans. This study employed a comprehensive methodology to analyze groundwater in the Western Banat Plain (Serbia). Using Piper and Gibbs plots, hydrogeochemistry was assessed, while the entropy-weighted water quality index (EWQI) was used to evaluate groundwater quality. Pollution sources were identified using positive matrix factorization (PMF) accompanied by Pearson correlation and hierarchical cluster analysis, while Monte Carlo simulation assessed health risks associated with groundwater consumption. Results showed that groundwater, mainly Ca-Mg-HCO3 type, is mostly suitable for drinking. Geogenic pollution, agricultural activities, and sewage were major pollution sources. Consumption of contaminated groundwater poses serious non-carcinogenic and carcinogenic health risks. Additionally, arsenic from geogenic source was found to be the main health risks contributor, considering its worryingly elevated concentration, ranging up to 364 μg/L. These findings will be valuable for decision-makers and researchers in managing groundwater vulnerability. PRACTITIONER POINTS: Groundwater is severely contaminated with As in the northern part of the study area. The predominant hydrochemical type of groundwater in the area is Ca-Mg-HCO3. The PMF method apportioned three groundwater pollution sources. Monte Carlo identified rock dissolution as the primary health risk contributor. Health risks and mortality in the study area are positively correlated.

Informed Search Strategy for Synchronous Recognition of Groundwater Pollution Sources and Aquifer Parameters Based on an Improved DCN Substitute

Informed Search Strategy for Synchronous Recognition of Groundwater Pollution Sources and Aquifer Parameters Based on an Improved DCN Substitute

Evaluation of groundwater quality with multi-source pollution based on source identification and health risks

Groundwater is a crucial water supply source in Chengdu City, western China, a region experiencing significant water scarcity. The sources of inorganic pollutants in groundwater and their potential health risks are of great concern. In this study, based on 156 groundwater samples collected in 2021 in the study area were analyzed for hydrochemical characterization and controlling factors. The Positive Matrix Factorization (PMF) model was used for contaminant source analysis, and Monte Carlo Simulation (MCS) combined with the Health Risk Evaluation Model (HREM) was used to quantify the health risks. The results indicate that the groundwater in the study area is predominantly of the Ca·Na-SO4·HCO3, Ca·Na-HCO3·SO4 and Ca-HCO3·SO4 types, mainly influenced by the combination of evaporation-concentration-crystallization and rock leaching-weathering. K+, Na+, and Cl− mainly originate from the weathering and dissolution of potassium feldspar and rock salt, while Ca2+, Mg2+, HCO3−, and SO42− primarily come from the weathering and dissolution of sulfate minerals. The main sources of groundwater pollution and their contributions are as follows: domestic pollution (25.6 %), dissolution-filtration-evaporation-concentration action (22.8 %), hydrogeochemical evolution (15.8 %), water-rock interactions (12.8 %), primary geologic context (12.1 %), and agricultural non-point source pollution (11.0 %). Cl− and As are the primary contributors to non-carcinogenic and carcinogenic risks, respectively. Non-carcinogenic risks are below USEPA standards, while the average carcinogenic risk for arsenic exceeded the maximum acceptable risk level thresholds by 23 and 109 times for adults and children, respectively. Non-carcinogenic and carcinogenic health risks were mainly influenced by pollutant concentrations. The primary geological background and domestic pollution contributed the most to the non-carcinogenic risk for adults (50.3 %) and children (77.1 %), and 38.2 % and 10.3 %, respectively. This study highlights the necessity of establishing a comprehensive groundwater pollution monitoring system, enhancing industrial waste management practices, and raising public awareness to mitigate contamination and ensure the sustainable use of groundwater resources in Chengdu City.

Methodological principles of searching for disposal sites of radioactively contaminated materials by geophysical methods

This article is devoted to radiometric studies at one of the sites of the Chornobyl nuclear power plant (the “Sandy Plateau” site), which is located on the south-eastern outskirts of the city of Pripyat. Radioactive substances, both artificial and natural, resulting from incidents and disasters at nuclear facilities pose the greatest danger. The disposal sites for radioactively contaminated materials considered in this work are sources of groundwater pollution. Currently, there is a problem of searching for their location for reburial in specialized stationary burial grounds, to solve which detailed complex geophysical studies are used. Various geophysical methods are considered, including micro-sensing and radiometric studies, to determine the location of burials. Particular attention is paid to the analysis and interpretation of geophysical data, as well as the economic and practical aspects of the application of these methods. As a result of the study, it was established: that when searching and studying burial sites of radioactively contaminated materials, the use of surface gamma photography makes it possible to assess the level of radioactive contamination of the upper layers of the soil (to a depth of 0.8-1 m). However, if the thickness of buried radioactively contaminated materials exceeds a certain level, which leads to weak contamination of rocks at a depth of more than 1-1.5 m, then burial objects may go undetected when using only gamma-ray imaging. In such cases, microgamma probing becomes an effective method. Increased values of exposure dose rate and the nature of microgamma sounding curves serve as indicators of the presence (increase in exposure dose rate with depth) or absence (sharp decrease in exposure dose rate with depth) of radioactively contaminated materials in the studied area.

Groundwater Quality Assessment in the Middle-Upper Pleistocene Aquifer

The study was conducted to assess groundwater quality and identify the main pollution sources of groundwater in Hau Giang province, Vietnam. Groundwater samples were collected at five locations (GW1-GW5) at qp2-3 aquifer in May and October 2022. Principal component analysis (PCA), cluster analysis (CA), water pollution index (WPI), and groundwater quality index (GWQI) were applied in the study. The results revealed that the groundwater quality was influenced by TDS, NH4+-N, permanganate index, and Fe. On the basis of WPI, GW2 and GW3 had the lowest water quality, exceeding a value of 1. The results of GWQI showed that groundwater quality was divided into three categories (excellent, poor, and unsuitable for drinking) in May and four categories (good, poor, very poor, and unsuitable for drinking) in October. The study also revealed seasonal variations in groundwater quality, particularly in GW5 (Vi Thuy district, Hau Giang, Vietnam). The CA results formed four water quality groups in both periods based on the similarity of groundwater parameters. PCA results presented that the three PCs explained 79.55% of the variation in groundwater quality. Three potential sources of pollution are derived from the discharge of wastewater (domestic, industrial, and agricultural), landfilling, and seawater intrusion. Doi: 10.28991/CEJ-2024-010-07-018 Full Text: PDF

Identification of groundwater pollution sources based on optimal layout of groundwater pollution monitoring network

Identification of groundwater pollution sources based on optimal layout of groundwater pollution monitoring network

Environmental and Health Impact of Heavy Metal Accumulation in (Hair - Nails) of Scavenger Workers at Some Landfill Sites in Baghdad City-Iraq

Background: Heavy metals are considered one of the most dangerous environmental pollutants due to their high toxicity, even at low concentrations, and their accumulation in various body tissues. Landfills contain various wastes rich in heavy metals, such as batteries, paints, and household and hospital waste, making them a major source of air, soil, and groundwater pollution. Objective: To analyze the level of accumulation of heavy metals in hair and nail samples of waste collectors. Material and method: Five main landfill sites in the city of Baghdad were chosen to collect hair and nail samples from waste collectors of both sexes for the winter and summer seasons to analyze the levels of metal concentrations (lead, cadmium, nickel, zinc, and copper). And the use of atomic absorption spectrometry (AAS). Results: Higher concentrations of lead, copper, and nickel were found in nail samples during the summer compared to the winter, indicating an increased risk of exposure to them. While zinc accumulation was much greater in winter samples. Conclusions The results highlight the health risks faced by landfill workers. A need to develop tailored strategies to control exposure to these emissions based on weather conditions and priority metals of concern identified through regular biological monitoring.

Joint identification of groundwater pollution source information, model parameters, and boundary conditions based on a novel ES-MDA with a wheel battle strategy

Groundwater pollution source identification (GPSI) is an important prerequisite for pollution remediation and risk assessment. However, an accurate GPSI is usually difficult to achieve due to the need to simultaneously consider practical problems and theoretical research. For practical problems, the boundary conditions, especially the concentration boundary, are often given as known constants through prior information. However, in most practical situations, the boundary conditions are complex and cannot be accurately estimated in advance, which leads to the distortion of the final identification results. Therefore, this study focused on the concentration boundary, and first proposed to jointly identify three types of unknown variables (source information, model parameters, and boundary conditions) to ensure that the identification results had more practical value. For theoretical research, as the number of unknown variable types increases, the difficulty of solving the inverse problem often increases, which may lead to inaccurate inversion results. Thus, a novel ensemble smoother with multiple data assimilation (ES-MDA) with a wheel battle strategy was proposed, enhancing the identification accuracy. We designed two cases to verify the effectiveness and practicality of the above ideas: a low-dimensional Case 1 (including four different synthetic scenarios: three scenarios with unknown boundary conditions under three concentration boundary modes and a scenario with known boundary conditions) and a high-dimensional complex Case 2. Identifying the boundary conditions in GPSI was found to be of great significance. Compared to the standard ES-MDA method, the ES-MDA with a wheel battle strategy proposed here could improve the inversion accuracy, and had certain effectiveness and practicality.

Hydrochemical characteristics and sources of groundwater pollution in Soubré and Gagnoa counties, Côte d’Ivoire

For many years, groundwater has been widely used to meet a variety of human needs. As a result of increased urbanization, industrial use, and agriculture, groundwater is inextricably affected by various threats, resulting in groundwater pollution. This current study was carried out to determine the hydrochemical characteristics of groundwater in Gagnoa and Soubré counties as well as the main sources of pollution and their impact on groundwater chemistry and quality. A total of thirty (30) groundwater samples were collected from boreholes in September 2020. The following physicochemical and chemical parameters were analyzed: Na, Ca, K, Mg, SO4, NO3–N, HCO3, Cl, pH, EC and TDS. The results showed that groundwater was acidic with a pH range from 5.22 to 6.84, fresh and moderately mineralized with a TDS range from 55.96 to 744.46 mg/l. Hydrogeochemical characterization based on the Piper diagram and Gibbs plot was used to identify the groundwater types and the main mechanism controlling the groundwater mineralization. Five (5) water types were identified with the dominance of hydrogen carbonate facies and showed the presence of silicate weathering and carbonate dissolution in the area. This is consistent with the results inferred from Gibbs plot showing that groundwater chemistry is governed by rock-water interaction. The spatial distribution map of major ions showed the different locations where each ion is dominant.According to WHO standards, the parameters show values within the threshold limit except for some of them of which their values exceed the limit. Principal component analysis and ionic ratio plots showed that the high values of nitrate as nitrogen and sulfate observed are due to the influence of natural sources such as carbonate dissolution and anthropogenic activities such as sewage-manure and chemical fertilizers.Therefore, mitigation measures should be adopted to reduce the impact of human activities contributing to groundwater pollution to protect the groundwater quality and human health.

Photocatalytic activity of rare earth elements (Gd and ce) co-doped ZnO nanostructured films

Organic dyes, which are one of the main sources of surface and groundwater pollution, cause health problems as well as environmental hazards. For this reason, ZnO, which stands out among the promising semiconductor photocatalysts in wastewater treatment due to its advantages, was preferred. In particular, Gd–Ce co-doped ZnO nanostructured films, which have been studied for the first time in the literature, were produced by ultrasonic spray pyrolysis (USP) technique and photocatalytic degradation of Methylene blue (MB) dye was carried out. Ultraviolet–Visible Spectrophotometry (UV–Vis) and Field Emission Scanning Electron Microscopy (FESEM) were used to obtain the transmittance and morphology of thin films. According to the FESEM analysis results, morphological changes in the type of nanostructure were observed after the doping. While the photocatalytic degradation percentage of the ZnO film with Gd doping was 65.84 %, when both Gd and Ce were doped, the degradation percentage increased significantly, reaching 91.58 %. Photocatalytic studies revealed that Gd–Ce co-doped ZnO films exhibited better photocatalytic efficiency compared to only Gd doped ZnO films. Therefore, when all the results are evaluated, it is concluded that ZnO:Gd:Ce photocatalysts may have a significant potential application in environmental remediation.

Assessment of Groundwater Quality Using the Pollution Index of Groundwater (PIG), Nitrate Pollution Index (NPI), Water Quality Index (WQI), Multivariate Statistical Analysis (MSA), and GIS Approaches: A Case Study of the Mnasra Region, Gharb Plain, Morocco

Groundwater, an invaluable resource crucial for irrigation and drinking purposes, significantly impacts human health and societal advancement. This study aims to evaluate the groundwater quality in the Mnasra region of the Gharb Plain, employing a comprehensive analysis of thirty samples collected from various locations, based on thirty-three physicochemical parameters. Utilizing tools like the Pollution Index of Groundwater (PIG), Nitrate Pollution Index (NPI), Water Quality Index (WQI), Irrigation Water Quality Index (IWQI), as well as Multivariate Statistical Approaches (MSA), and the Geographic Information System (GIS), this research identifies the sources of groundwater pollution. The results revealed Ca2+ dominance among cations and Cl− as the primary anion. The Piper and Gibbs diagrams illustrated the prevalent Ca2+-Cl− water type and the significance of water–rock interactions, respectively. The PIG values indicated that 86.66% of samples exhibited “Insignificant pollution”. NPI showed notable nitrate pollution (1.48 to 7.06), with 83.33% of samples rated “Good” for drinking based on the WQI. The IWQI revealed that 80% of samples were classified as “Excellent” and 16.66% as “Good”. Spatial analysis identified the eastern and southern sections as highly contaminated due to agricultural activities. These findings provide valuable insights for decision-makers to manage groundwater resources and promote sustainable water management in the Gharb region.

Research progress on nitrate isotope coupled multi-tracer tracing groundwater nitrate pollution

Nitrate pollution in groundwater has become a global concern. One of the most important issues in controlling the nitrate pollution of groundwater is to identify the pollution source quickly and accurately. In this review, we firstly summarized the isotopic background values of potential sources of nitrate pollution in groundwater in 17 provinces (cities, autonomous regions) and 29 study areas in China, which could provide the fundamental database for subsequent research. Secondly, we reviewed the research progress of nitrate isotopes combined with multiple tracers for tracing nitrate in groundwater, and discussed their applicable conditions, advantages, and disadvantages. We found that halides and microorganisms combined with nitrate isotopes could accurately trace the pollution sources of domestic sewage, excrement and agricultural activities. The combination of Δ17O and nitrate isotopes could effectively distinguish the source of atmospheric deposition of nitrate in groundwater. The combination of groundwater age and nitrate isotopes could further determine the time scale of nitrate pollution. In addition, we summarized the application cases and compared the characteristics of mass balance mixing model, IsoSource model, Bayesian isotope mixing model, and EMMTE model for quantitative identification of nitrate pollution in groundwater. For the complexity and concealment of groundwater pollution sources, the coupling of nitrate isotopes with other chemical and biological tracing methods, as well as the application of nitrate isotope quantitative models, are effective tools for reliably identifying groundwater nitrate sources and transformation processes.