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Abstract Determining situation of groundwater vulnerability plays a crucial role in studying the groundwater resource management. Generally, the preparation of reliable groundwater vulnerability maps provides targeted and practical scientific measures for the protection and management of groundwater resources. In this study, in order to evaluate the groundwater vulnerability of Kerman–Baghin plain aquifer, two developed indicators including composite DRASTIC index (CD) and nitrate vulnerability index (NVI) based on DRASTIC index were considered. Soft computing methods, including Gene Expression Programming (GEP), Evolutionary Polynomial Regression (EPR), Multivariate Adaptive Regression Spline (MARS), and M5 Model Tree (MTM5) have been used to provide formulations for prediction of NVI. Soft computing techniques were fed nine input parameters: depth to water level, net recharge, aquifer environment, soil environment, topography, effect of unsaturated area, hydraulic conductivity, land use, and potential risk related to land use. After calculating the vulnerability by soft computing methods, the results showed that the EPR model with Correlation Coefficient (R) of 0.9999 and Root Mean Square Error (RMSE) = 0.2105 has the best performance in the testing stage in comparison with MARS (R = 0.9966 and RMSE = 2.408), M5MT (R = 0.9956 and RMSE = 2.988), and GEP (R = 0.9920 and RMSE = 3.491). Although the EPR and GEP models have more complex mathematical computations than other soft computing models, the MARS and MT model that have quadratic polynomial and multivariable linear structures respectively, can be considered as the best alternative. According to the MARS model, the vulnerability of the region is divided into two categories: very low vulnerability (73.06%) and low vulnerability (26.94%). Overall, the statistical results of soft computing techniques were indicative of effective formulations for evaluating the DRASTIC index.

Introduction: In the past few decades, nitrate contamination in water resources has become a global environmental problem often caused by urban and agricultural activities. In the past two decades, the capital of Afghanistan, Kabul has experienced rapid urbanization. This rapid urbanization has caused groundwater storage depletion and contamination of nitrate in the Kabul Plain. In the Kabul Plain, groundwater is the only source of drinking water for Kabul city residents. This study aims to determine the different sources of nitrate pollution, investigate the nitrogen transformation processes, and estimate the proportional contribution of various sources of nitrate pollution in groundwater of the Eastern Kabul Plain. Material and Methods: Eighteen groundwater samples were collected from the Eastern Kabul Plain aquifer in November 2020. In-situ parameters such as electrical conductivity (EC), pH, dissolved oxygen (DO), and temperature were measured in the sampling sites. The collected samples for analysis of nitrate and nitrate were transported to the Green Tech Laboratory in less than six hours, and the concentrations of mentioned ions were measured on the same day. The collected samples for analysis of major ions were transported to the Regional Water Organization Laboratory of Tehran, Iran. Nitrate samples for isotopic analysis were shipped to the UFZ laboratory in Germany, where isotopic measurements were carried out using the bacterial denitrifier method. The proportional contribution of nitrate sources was determined using the BSIMM model. Results and Discussion: Kabul city does not have a central sewage collection system, and sewage is disposed of mostly through septic and absorption wells. The groundwater nitrate concentration varied from 4 mg/L to 120.4 mg/L with an average value of 21 mg/L. The values ​​of δ15N-NO3̄ varied from 4.8 ‰ to 20.8 ‰ and the values ​​of δ18O-NO3̄ varied from 0.7 ‰ to 18.6 ‰. The composition diagram of δ18O-NO3̄ and δ15N-NO3̄ was employed to determine the main sources of nitrate in the aquifer. Considering that most of the samples are plotted on sewage and manure area, therefore, urban sewage plays a major role in increasing the concentration of nitrate in the groundwater of Eastern Kabul Plain. Since chloride is a conservative ion and is not affected by environmental factors, the diagram of NO3̄/Cl‾ molar ratio versus Cl‾ was used to identify potential sources of nitrate in the Kabul Plain aquifer. The plot indicated that urban sewage is the primary source of nitrate in the aquifer. The high concentration of dissolved oxygen and nitrate in the groundwater samples indicated the dominance of aerobic conditions in the aquifer and the absence of denitrification. Sewage plays a major role in nitrate pollution of groundwater. Therefore, the rapid urbanization and population growth in the Kabul Plain in the past two decades have caused groundwater nitrate pollution. The uncertainty in nitrate sources estimation has been quantitatively assessed using the uncertainty index (UI90). The results of this study display a relatively high uncertainty for the contribution of nitrate sources, particularly sewage and manure (0.49) and soil organic nitrogen (0.44). Conclusion: Sewage and manure, soil organic nitrogen, and chemical fertilizers are potential sources of nitrate in the Kabul Plain. The Bayesian stable isotope mixing model showed that sewage and manure (69.5%) are the main sources of nitrate pollution in the aquifer. The results indicated that nitrification is the main biogeochemical nitrogen transformation process in the Kabul Plain.

Groundwater nitrate contamination is a worldwide water environment problem with few phased summaries in this field. Here, 14 407 articles were selected from the Web of Science database for the years 1968—2022 to analyze the development trends and current hotspots in the field of groundwater nitrate contamination research with bibliometric visualization analysis software (VOS viewer). The results showed that: (1) The number of relevant publications has been exponentially increasing. The published journals are mainly related to environmental science and water resources, indicating an important role in this field. (2) The results from the publication institutions and funding institutions show that more than half of the total number of articles from the top ten publication institutions and funding institutions are from the United States and China. (3) The main issues in groundwater nitrate contamination research can be summarized as four subsets: source tracing, migration and transformation mechanisms, pollution remediation, and risk assessment. Among them, pollution remediation has the most keywords, demonstrating the importance of this research area. (4) From 1990 to 2014, the research hotspots in groundwater nitrate research were mainly focused on source tracing and migration and transformation mechanisms. Specifically, the main topic was the identification of nitrate pollution sources during the stage from 1990 to 1998, while the focus shifted to the methods for identifying nitrate pollution sources from 1999 to 2014, with isotopes and models being particularly effective. For the recent stage from 2015 to 2022, the research hotspots have shifted to risk assessment. The bibliometric analysis results in the field of groundwater nitrate pollution can provide some reference for the direction of this field.

In order to identify and effectively control the impact of NO3− pollution on human health, on the basis of investigation, sampling, analysis and testing, statistical analysis software (SPSS19), groundwater pollution analysis software, Nemera comprehensive index method, correlation analysis method and human health risk assessment model are applied for analysis and research. The results indicate that the groundwater in the study area is mainly Class II water, with overall good water quality. The main influencing factors for producing Class IV are NO3−, Fe, F− and SO42−. The use of agricultural fertilizers is the main source of NO3− exceeding standards in groundwater in this area. There are significant differences in the health hazards caused by NO3− pollution in groundwater among different populations, and infants and young children are more susceptible to nitrate pollution. The division of pollution areas and high-risk groups plays an important guiding role in preventing health risks. The new achievements will help people improve their awareness of risk prevention, caring for the environment, respecting nature and implementing precise policies, promoting society to step onto the track of scientific and healthy development. HIGHLIGHTS Scientific evaluation of groundwater quality was conducted and the main factors affecting water quality were analyzed.; Scientific evaluation was conducted on NO3− pollution in the research area and the main sources of NO3− were identified.; The significant differences in the health hazards of NO3− pollution were identified.; The research results have an important guiding role in preventing health risks.;

Nitrate pollution in groundwater is a global environmental problem that poses risks to human health. We investigate the health risks of nitrate in rural drinking groundwater in Rucun Township and surrounding areas of Wutai County, and provide a basis for healthy drinking water. By using statistical analysis software (SPSS19) and hydrogeochemical analysis software (AqQA), a qualitative and quantitative evaluation of nitrate health risks was conducted among populations of different ages and genders through water sample collection, chemical analysis, and construction of a human health risk model (HHRA). Through research, it was found that the average concentration of nitrate in the study area is 43.99 mg/L. Groundwater is severely polluted by NO3−, and nitrate pollution areas are mainly concentrated in the main human activity areas, especially in the main agricultural production areas. The Quaternary loess layer, as a permeable layer, cannot prevent groundwater from being polluted by NO3−. Through evaluation, it is believed that there is a health risk of nitrate pollution in rural drinking groundwater in Rucun Township and surrounding areas. Health risk level: infants>children>adult females>adult males. The discovery and evaluation results can provide a basis for the prevention and control of nitrate pollution in groundwater. HIGHLIGHTS This study determined the distribution pattern of nitrate in rural drinking groundwater in Rucun Township and surrounding areas.; The chemical characteristics of groundwater in the study area were reflected and described through the Durov diagram.; HHRA for the first time in Rucun Township and surrounding areas was established to assess the level of health risks in the study area.;

The continued input of nitrate (NO3) into groundwater is a global problem, mainly associated to excess fertilizer and improper disposal of human and livestock waste. Nitrate accumulation in oxic aquifers of semiarid areas makes these zones especially susceptible to pollution. Nitrate in Meoqui- Delicias aquifer, located in an important irrigation district in Chihuahua, Mexico, was quantified in 2021 in 63 drinking water wells. Samples collected were analyzed in laboratory and results were compared to 2003 and 2006 data available for those wells. Nitrate values varied from 0.7 to 23.2 mg/L and 22 % of the wells contained NO3 above drinking water guidelines (10 mg NO3-N/L). A low to moderate nitrate pollution index (NPI) and a slight NO3-N variation with time was observed for most wells. Values of NO3-N/Cl < 1.0 support an anthropogenic origin of nitrate. No association was found between NO3-N and well depth. The most susceptible areas to nitrate contamination were identified as those areas with high NO3-N and increasing concentration with time. The lack of a pattern of contamination suggested leakage of manure leachate at a few points as the most likely contamination source. The consistently high NO3-N content (>10 mg/L) in three deep wells constitutes a serious concern. DOI: https://doi.org/10.54167/tch.v18i1.1415

Because of the excessive use of nitrogen fertilizers, most of the groundwater resources are contaminated in the upstream of the Zayandehrud basin. This study set out to investigate the effect of different levels of water and nitrogen on yield, soil nitrogen, as well as water productivity indices of winter wheat and barley. The experimental treatments were of three nitrogen levels: no nitrogen fertilizer (N0), 50 kg N ha−1 (N1), and 150 kg N ha−1 (N2), as well as two irrigation levels containing deficit irrigation (I1) and full irrigation (I2). Each treatment was repeated three times. Wheat yield for I2 was 5,640 kg ha−1 and for I1 was 3,720 kg ha−1. The yield for barley was 5,620 and 3,850 kg ha−1 for I1 and I2, respectively. The irrigation water productivity (WPi) was increased by 55% for wheat and 83% for barley under deficit irrigation level. We recommend the use of 50 kg ha−1 (instead of 150 kg ha−1), knowing that it reduces the yield and water productivity for wheat by 11.7 and 10.9%, and by 14.5 and 12.6% for barley, respectively. In contrast, the soil nitrogen residual for wheat and barley was reduced by 56.6 and 66.1%, respectively, thus greatly reducing the risk of contamination of groundwater resources. HIGHLIGHTS NO3− concentration in water from 120 wells was measured.; Using high N fertilizer by farmers caused the increase in nitrate in groundwater.; Deficit irrigation is a good strategy to increase WP in a water-scarce arid area, for wheat and barley.; Using 50 kg N ha−1 instead of 150 kg N ha−1 is a good strategy to protect the environment; however, it may slightly reduce yields.;

This study retains the basic structure of DRASTIC model and obtains more specific evaluation results by adding land-use type and groundwater resource yield parameters, modifying the rating scale and weight of nine parameters. Comparison of the modified DRASTIC-LY vulnerability map with the map of the original DRASTIC-LY method revealed differences in 40.49% of the study area. The risk map shows that the very high vulnerability area decreased from 2.79 to 1.67%, while the high vulnerability area increased from 18.70 to 28.86%. Areas with low vulnerability increased by 10.15%, while areas with medium vulnerability decreased by 15.01%. The areas with very high groundwater vulnerability are mainly distributed in the Hanbin area on the north bank of the Han River, the areas with high are mainly concentrated on both sides of the Fujia River, while the areas with low are distributed in most areas in the west of the basin. The Pearson's correlation factor was 0.0583 in the original DRASTIC model, 0.1113 in the DRASTIC-LY method and 0.8291 in the modified DRASTIC-LY model, which indicated that the revised DRASTIC-LY model was more appropriate than the original model. The results can help the government with the protection of water resources. HIGHLIGHTS Improve the DRASTIC model.; Determine the weight, grade and category of each parameter.; Based on the sensitivity analysis and model validation results, construct the best model suitable for groundwater vulnerability assessment.; The results of this study will help government managers improve the composition of water use and strengthen the protection of vulnerable aquifers.;

In order to investigate the health risks of NO3− in rural drinking groundwater in Suihua, China and provide a basis for healthy drinking water, 40 sets of groundwater samples were collected in the Suihua area, and the average concentration of nitrate in the study area was 71.66 mg/L, statistical analysis software (SPSS19), Hydrogeochemical Analysis Software (AqQA) and groundwater pollution analysis software were used. Through water sample collection, chemical analysis and construction of human health risk model (HHRA), a qualitative and quantitative assessment of NO3− health risk was carried out for people of different ages and sexes, and it was concluded that there was NO3− pollution health risk in rural drinking groundwater in Suihua. Health risk level: infants > children > adult females > adult males. The evaluation provides a scientific basis for the prevention and control of NO3− pollution in groundwater and new ideas for preventing human health risks. HIGHLIGHTS The study identified the distribution pattern of nitrate in rural drinking groundwater in the Suihua area, providing a basis for preventing excessive use of fertilizers and pesticides.; The chemical characteristics of groundwater in the study area were reflected and described through the Durov plot.; A HHRA was first constructed in the Suihua area to evaluate the level of health risk in the study area.;

In order to investigate the main factors that caused the Nitrate increasement in Huixian Wetland, 15N-NO3 and 18O-NO3 analysis were conducted. SIAR model was applied to quantitatively test the contribution proportions of kinds of pollutants. Health risk assessment (HRA) was taken to study ten heavy metals of 96 groups samples in the four main waters in Huixian Wetland: Surface River, Subterranean Stream, Blue Hole and Well Water. The main sources of Nitrate were domestic sewage and animal feces, chemical fertilizer, and soil, with the contribution proportions of 39.1%, 32.2%, and 28.5%, respectively. The heavy metals concentration order is that of Mn > Al > Cr > Zn > As > Pb > Cu > Fe > Cd > Hg. The HRA showed that the average annual total health risks-through drinking and skin penetration-order was: Well Water > Blue Hole > Subterranean Stream > Surface River. The drinking water from Well and Blue Hole can cause the cancer risks in children of 7.08 × 10−5 a−1 and 7.01 × 10−5 a−1, respectively. Both were higher than the recommendation standard (5.0 × 10−5 a−1) from ICRP. As the main element contributed to the health risk of adults and children, the Cr in all the four waters were also over the standard (1 × 10−6 a−1) recommended by the Swedish Environmenta1 Protection Agency and the Dutch Ministry of Construction and Environment and the British Royal Society. The health risk levels of non-carcinogenic metals were 1 × 10−16–1 × 10−10, which were 5–11 order of magnitude lower than the acceptable level.

Abstract Groundwater (GW) is an important source of freshwater in arid and semiarid areas. Some important industrial activities, such as coal mining, also consume GW. There have been few studies evaluating GW quality in the Selian coal mining area of Inner Mongolia. This study aimed to identify the hydrochemical phases and the sources of main ions in the GW of the Selian coal mining area. Water quality analysis was performed on 20 shallow GW samples collected from the study area. Statistical correlation analysis was performed on these water quality data. The quality of irrigation water was evaluated based on water quality indices such as the sodium absorption rate and sodium percentage. The risk of nitrate pollution in the study area to human health was evaluated by GW nitrate content. The results show that the dominant GW chemistry types in the study area are the mixed and Ca–HCO3 types. Correlation analysis indicates that rock weathering and leaching are the main natural drivers of GW hydrochemistry in this area. The irrigation risk analysis shows that GW in this area can be used for irrigation, although some caution is needed. The human health risk assessment shows that GW nitrate pollution poses more risk to children than to adults by a factor of 1.168. It is recommended that centralized treatment of drinking water is the optimal approach to managing this risk. The results of this study can act as a reference for the rational use of GW and for control of nitrate pollution in this area.

A comprehensive hydrogeological report was conducted to determine the origin, occurrence and processes affecting nitrogen in a Mediterranean coastal aquifer-lagoon system. Water levels, hydrochemical and isotopic data was gathered during a 4-year period in the La Pletera salt marsh area (NE Spain). They were collected from the alluvial aquifer, two natural lagoons and four other permanent lagoons excavated during a restoration process (in 2002 and 2016), two watercourses (the Ter River and the Ter Vell artificial channel), 21 wells (considering six of them for groundwater sampling) and the Mediterranean Sea. Potentiometric surveys were carried out seasonally, however twelve-monthly campaigns (from November 2014 to October 2015), and nine seasonal campaigns (from January 2016 to January 2018) were conducted for hydrochemical and environmental isotopes analyses. The evolution of the water table was analysed for each well, and potentiometric maps were plotted to determine the relationship between the aquifer and the lagoons, sea, watercourses, and groundwater flow. Hydrochemical data included physicochemical data measured in situ (temperature, pH, Eh, dissolved oxygen, and electrical conductivity), major and minor ions (HCO3−, CO32−, Cl−, SO42−, F−, Br−, Ca2+, Mg2+, Na+, and K+), and nutrients (NO2−, NO3−, NH4+, Total Nitrogen (TN), PO43−, and Total Phosphorus (TP)). Environmental isotopes included stable water isotopes (δ18O and δD), nitrate (δ15NNO3 and δ18ONO3) and sulphate isotopes (δ34SSO4 and δ18OSO4). Water isotopes were analysed for all campaigns, however, nitrate and sulphate isotopes water samples were only analysed in some particular surveys (November and December 2014; January, April, June, July and August 2015). Additionally, two more surveys for sulphate isotopes were conducted in April and October of 2016. The data generated through this research may be used as a starting point to analyse the evolution of these recently restored lagoons, and their future responses to global change. In addition, this dataset may be used to model the hydrological and hydrochemical behaviour of the aquifer.

Abstract Monitoring groundwater quality and analyzing geochemical processes are very crucial in dry environments, especially in areas with intense agriculture and inadequate irrigation management systems. A total of forty-one groundwater samples were collected from the study area and analyzed for major ions chemistry. The results of the geochemical analyses are used to investigate the geochemical processes and make groundwater assessments. The hydrogeochemical characteristics of the groundwater samples revealed a highly mineralized Na+–Cl− water type, implying that the majority of the samples are chemically unfit for human consumption. Based on the water quality parameters analyzed for the groundwater samples collected in this study, such as sodium adsorption ratio (SAR), soluble sodium percentage (SSP), residual sodium carbonate (RSC), magnesium hazard (MH), permeability index (PI), and Kelley's ratio (KR), the suitability of groundwater samples for irrigation purposes is good to moderately good. Also they may reflect some alkaline hazard threats to the soil as indicated by the SSP and KR. The salinity hazard is recognized as high and expected to increase with the expansion of irrigation; hence, special salinity control management for groundwater in the study area is required. Nitrate is widely recognized as a contaminant in the study area. The nitrate concentrations range from 0.1 to 256.8 mg/L, with more than 30% of the samples exceeding the safe drinking water limit of 50 mg/L. The main concern is that the average nitrate concentration will likely continue to increase in the groundwater of the study area. Groundwater monitoring, in terms of both quality and quantity, is essential for sustainable groundwater management.

The Ingul megablock of the Ukrainian Shield contains a number of endogenous deposits of the sodium-uranium formation, which have been developed for more than 55-60 years. With the exception of the Kirovograd uranium ore region, the deposits of which are controlled by discontinuities in the fault zone of the same name, the Vatutinske and Novokostiantynivske ore fields occupy positions within the Novoukrainsky granite-gneiss dome and in close proximity to the later geostructural formation, the Korsun-Novomyrgorod pluton. Paying attention to the high degree of saturation of the Ingul megablock with endogenous uranium deposits, it is emphasized that they also contain an increased content of thorium minerals and, in combination with uranium, they produce ascending gas flows of radon. Therefore, studies of the dynamics of the upper horizons of the lithosphere and the closely related dynamics of the hydrosphere (underground and surface), as well as the gas sphere, are especially relevant both in the regions of uranium ore fields and in areas adjacent to mining enterprises. Beyond the direct influence on the radioecological situation of uranium mining enterprises, special attention should be paid to the study of the dynamics of the lithospheric surface, including fault-block structures and the kinematics of ruptures, affecting the spread of groundwater and, as a result, surface waters contaminated with uranium in the environment. In the areas of uranium ore fields, the kinematic characteristics of disjunctivals contribute to a more correct forecast of radon accumulation in natural weakly insulated underground decompressed structures and the accumulation of more long-lived products of its decay Po, Bi, and Pb with long periods of removal of biological objects from organisms. It is emphasized that in the mine workings of mining enterprises, the technological process is accompanied by nitrate pollution of groundwater due to the use of nitrate-based explosives. Thus, for the predictive assessment of radiation and nitrate pollution of the environment of industrial sites of mining enterprises and adjacent territories, the technological process of which also affects the dynamics of the litho-hydro- and gas sphere, the structural-geological, paleogeomorphological, lithological, hydrogeological, hydrographic and topographic features of the Vatutinske and Novokostiantynivske uranium ore fields. The directions of the advancement of the groundwater fronts from directly uranium mines to the nearest drains have been established. The levels of uranium pollution of surface and underground (well) waters within the Novokostiantynivske uranium ore field, as the most promising for increasing uranium mining in the coming decades, have been determined. The proposed areas and terms of complex radioecological monitoring of the Novokostiantynivske uranium ore field in order to take preventive measures to prevent the withdrawal of existing local recreational areas and water areas into the category of ecologically hazardous. On the example of the Novokostiantynivske uranium deposit, as one of the richest endogenous deposits in Ukraine, through the production shafts, which is planned to rise to the surface of uranium ore from the same type of deposits of the uranium ore field of the same name (Lisne, Litniy and Dokuchaivske) by transporting it by main drifts, the proposed optimal complex of geodynamic studies in the system of radio and general ecological monitoring of the state of the environment of such territories.

Due to rapid economic growth and over-exploitation of groundwater, nitrate pollution in groundwater has become very serious. The main objective of this study is to modify the DRASTIC model to identify groundwater vulnerability to nitrate pollution. The DRASTIC model was firstly used to analyze the intrinsic vulnerability. The DRASTIC model with the inclusion of a land-use factor (DRASTIC-LU) was put forward to map the specific vulnerability of groundwater. Furthermore, the support vector machine (SVM) was introduced to avoid the drawback of the overlay and index methods, and the improved integrated models of DRASTIC + SVM and DRASTIC-LU + SVM were built. Moreover, 103 groundwater samples were collected for building and validating the models. The Root Mean Squared Error (RMSE) of DRASTIC, DRASTIC-LU, DRASTIC + SVM, and DRASTIC-LU + SVM was found to be 0.853, 0.755, 0.631, and 0.502, respectively. The model DRASTIC-LU was more precise than the original one. The results also showed that the integrated model using SVM exhibited better correlation between the vulnerability value and the nitrate pollution. The study indicated that the modified models including the land-use factor as well as SVM in the DRASTIC model were more suitable to assess the groundwater vulnerability to nitrate. HIGHLIGHTS The improved DRASTIC-LU model was put forward to delineate groundwater specific vulnerability.; Support vector machine was introduced to further build the novel integrated model to analyze the intrinsic and specific vulnerability of groundwater.;

The Songnen Plain in Northeast China is the only remaining black soil agricultural area in the world and is an important food base for China. The groundwater resources in this area are abundant, but human activities have caused them polluted. This paper established a groundwater vulnerability assessment to characterize the influence of human activities which used an entropy weight method. The index was tested using the nitrate pollution distribution in the groundwater to verify the effectiveness of this method. The results showed that areas with high specific vulnerability were distributed in the northern and eastern parts of the Songnen Plain and were consistent with areas that showed serious nitrate pollution of the groundwater. The correlation coefficient between these areas was 0.2536, which greatly improved the vulnerability assessment without superimposing human activities in the model. The results clearly showed that human activities increased groundwater vulnerability on the Songnen Plain. The evaluation method provided a reference for similar evaluations and a basis for the protection and management of groundwater resources in this region. HIGHLIGHTS Establishing a groundwater vulnerability assessment method to characterize the influence of human activities using an entropy weight method.; Entropy weight method coupled with an improved DRASTIC model to evaluate the special vulnerability of groundwater for water management.;

Nitrate (NO3−) pollution of surface and groundwater bodies is a global problem of increasing concern, which has stimulated significant research interest. Nitrogen is crucial for life as a macronutrient for living organisms on Earth, but the global nitrogen cycle has been seriously altered by intensification of human activities, leading to eutrophication and hypoxic conditions of aquatic ecosystems. Due to nitrogen overfertilization, intensive agricultural practices generate huge nitrate fluxes that inadvertently deteriorate water quality. Different industrial processes also contribute to NO3− pollution in the environment. There are multiple technologies capable of achieving effective denitrification of waterbodies to ensure safe NO3− levels. Either separation-based or transformation-based denitrification technologies must address the challenges of by-product generation, increased energy demand, and reduced environmental footprint. This paper highlights the most used approaches, along with some promising alternatives for remediation of nitrate-polluted waters.

Commission Directive 91/676/EC introduced water protection from nitrates from agricultural sources. The Puglia Region approved its ‘Nitrate Action Plan’ (NAP) in 2013, establishing nitrate-vulnerable zones (NVZs), with restrictions on agronomic management and administrative obligations based on territorial studies. However, those aims require appropriate feedback through monitoring activities to identify the real sources of nitrate contamination. The DEMETRA-DSS project arises from a synergy between ICT companies, research institutes and agricultural organizations. The project aims at supporting local institutions in territorial monitoring and management of contamination sources and introduces innovations capable of mitigating the agronomic impact on the territory.

Groundwater nitrate pollution is nowadays one of the most important environmental issues with significant effect on human and environment health. Due to the importance of this vital water source, methods have been developed for purifying the groundwater contaminated with nitrate. One of the effective and long-lasting purification methods for groundwater contaminated with agricultural drains is the in-situ method of denitrification wall. The general concept of this technology is placing a denitrification wall with carbon material across the nitrate-contaminated groundwater pathway so that it can block the nitrate pollution as nitrate masses pass through the wall due to the groundwater natural hydraulic gradient. Despite widespread acceptance, there are still many unresolved issues regarding the long-term performance of denitrification walls which requires more understanding on the behavior, principles of design and construction methods of such walls. Accordingly the aim of this study was to fully investigate the technology and implementation of denitrification walls in all aspects. The method of this study was library type and the content, explored in simple expressions in different sections, is based on a descriptive-analytical approach to experimental and scientific experiences of this method on contaminated sites. Results showed that denitrification wall can be drilled underground either in form of funnel and gate or continuous configuration and the choice depends on the hydrological characteristics of the site and the cost of materials used in the wall. Also, when water flow contaminated with nitrate passes through the denitrification wall, nitrate pollution is treated with either adsorption or biological removal mechanisms or a combination of them. The right application of the denitrification wall can be economically efficient and the success of the system depends on the use of appropriate tools and solutions for accurate formulation of the problem in the real aquifer environment with its large dimensions and complexity. In this regard, numerical modeling and laboratory studies can help to achieve a detailed understanding of the problem in a real environment.

Application of chemical fertilizers, especially urea, causes groundwater pollution. Therefore, to decrease environmental pollution, biological fertilizers may be employed. In order to investigate the effect of irrigation levels, Azospirillum and nitrogen levels on rice yield and its components, an experiment was conducted in the north of Iran during the crop season in 2013. The experiment was arranged in a split-split plot based on a completely randomized block design with 3 replications in which irrigation level was the main factor. The levels of factors used were: I1= continuous submergence and I2 = 11 days’ irrigation interval; A1 = application and A2= no application of Azospirillum as the sub factor; and nitrogen fertilizer levels as a sub-sub factor includingN1 = 0, N2 = 30, N3 = 60 and N4 = 90 kg ha-1. Continuous submergence and 11 days’ irrigation interval produced 4247 and 2720 kg ha-1, while the application of Azospirillum and the treatment without it produced 4064 and 2903 kg ha-1, respectively. Moreover, N4, N3, N2 and N1 produced 3950, 3800, 3225 and 2700 kg ha-1, while I1A1N4 and I1A1N3 had maximum and I2A2N1 had minimum mean values with 5381, 5330 and 1882 kg ha-1, respectively. Therefore, it is concluded that the application of a balanced nitrogen fertilizer with Azospirillum could prevent the indiscriminate use of chemical fertilizers and reduce nitrate pollution, leading towards more sustainable agriculture in the north of Iran.

The groundwater resource is crucial to the urbanization and industrialization in the Guangdong coastal area; the rapid development of Daya Bay has presented a challenge for the management of the groundwater quantity and quality. Therefore, a novel approach to hydrochemical analysis, which, combined with the health risk model and the water quality index (WQI), was used to explain the hydrochemistry characteristics and risks to human health of groundwater in the Guangdong coastal areas in addition to investigating the factors controlling groundwater quality. The results showed that the average concentration of total dissolved solids (TDS) in groundwater was 1935.26 mg/L and the quality of water was weakly alkaline. The dominant hydrochemical types of groundwater were identified to be Mg-HCO3 and Na-Cl·HCO3. The main factor influencing the hydrochemical composition was rock weathering, while the result of principal component analysis (PCA) shows seawater intrusion and anthropogenic inputs also have an effect on the water quality. The conclusions of the water quality assessment indicated that most of the groundwater samples were acceptable for drinking. However, both WQI and the non-carcinogenic hazard quotient (HQ) values indicated unacceptable risks in any area of Maoming, Zhanjiang and Shantou, and, according to the hazard index (HI) value, children in the study area are at more danger to health risks than adults. It is suggested that both groundwater salinization and nitrate pollution should be paid attention to when improving groundwater quality and exploring the sustainable utilization of groundwater resources.

Bioremediation of polluted groundwater is one of the most difficult actions in environmental science. Nonetheless, the clean-up of nitrate polluted groundwater may become increasingly important as nitrate concentrations frequently exceed the EU drinking water limit of 50 mg L–1, largely due to intensification of agriculture and food production. Denitrifiers are natural catalysts that can reduce increasing nitrogen loading of aquatic ecosystems. Porous aquifers with high nitrate loading are largely electron donor limited and additionally, high dissolved oxygen concentrations are known to reduce the efficiency of denitrification. Therefore, denitrification lag times (time prior to commencement of microbial nitrate reduction) up to decades were determined for such groundwater systems. The stimulation of autotrophic denitrifiers by the injection of hydrogen into nitrate polluted regional groundwater systems may represent a promising remediation strategy for such environments. However, besides high costs other drawbacks, such as the transient or lasting accumulation of the cytotoxic intermediate nitrite or the formation of the potent greenhouse gas nitrous oxide, have been described. In this article, we detect causes of incomplete denitrification, which include environmental factors and physiological characteristics of the underlying bacteria and provide possible mitigation approaches.

Several groundwater vulnerability methodologies have been implemented throughout the years to face the increasing worldwide groundwater pollution, ranging from simple rating methodologies to complex numerical, statistical, and hybrid methods. Most of these methods have been used to evaluate groundwater vulnerability to nitrate, which is considered the major groundwater contaminant worldwide. Together with dilution, the degradation of nitrate via denitrification has been acknowledged as a process that can reduce reactive nitrogen mass loading rates in both deep and shallow aquifers. Thus, denitrification should be included in groundwater vulnerability studies and integrated into the various methodologies. This work reviewed the way in which denitrification has been considered within the vulnerability assessment methods and how it could increase the reliability of the overall results. Rating and statistical methods often disregard or indirectly incorporate denitrification, while numerical models make use of kinetic reactions that are able to quantify the spatial and temporal variations of denitrification rates. Nevertheless, the rating methods are still the most utilized, due to their linear structures, especially in watershed studies. More efforts should be paid in future studies to implement, calibrate, and validate user-friendly vulnerability assessment methods that are able to deal with denitrification capacity and rates at large spatial and temporal scales.

Introduction: World's population growth and limited water resources and needing to more food production led to interest farmers to use nitrogen fertilizer more than soil requires and subsequently Nitrate leaching causes groundwater and environmental pollution. Therefore, researches has concentrated on improvement of nitrogen use efficiency, which numerical simulation is the effective solutions to optimize the management of water and fertilizer in the field in order to achieve the maximal yield and minimal nitrate pollution of soil, groundwater and drainage in water deficiency crisis condition. For this reason, the evaluation of new user friendly models in correct estimation of soil moisture and nitrogen content distribution and recognition of water and solutes movement in the soil and choosing the best management option for increasing productivity and economic performance and also reduction of nitrate pollution of soil and ground water source with the least limitations and high accuracy is necessary. The Eu-Rotate-N model has been developed for simulation of nitrogen use and specifically for optimization of nitrogen use in variation of vegetables in a wide range of conditions, which without the need to calibration has presented satisfactory results in many areas. So this study was conducted to evaluate the efficiency of Eu-Rate-N model in assessment of moisture and nitrogen distribution and yield under different nitrogen fertigation management for pepper plant. Materials and Methods: Sweet pepper was planted at density of 8.33plant per m2 in a row planting method. 150kg per hectare per year of fertilizer was used during the season. Crop yield, soil water and nitrogen content were measured on a regular basis. The treatments consisted of three fertilizer level: zero (N0), the ratio of ammonium to nitrate 20:80 (N1) and 40:60 (N2), which was conducted in a completely randomized block with three replications in Isfahan. Irrigation based on daily monitoring of humidity was used with drip irrigation system. The irrigation Depth was calculated and applied with aim of replacing the water content deficiency in the root zone up to field capacity (FC) for the no water deficit treatment. Coefficients were modified only for plant coefficients and length of each growth stage according to the area. To compare simulated data with measured data in field, indices of statistical root mean square error (RMSE), normalized root mean square error (NRMSE), coefficient of determination (r2) and index of agreement Wilmot (d) were used. Results and Discussion: The NRMSE index for nitrate and soil water content was 11.45, 12.08, the RMSE was 0.89, 0.022, the r2 was 0.998, 0.996 and the d was 0.667, 0.66 respectively. All calculated indices for soil water and nitrate content were in the acceptable range. NRMSE index was less than 20 percent in all treatments which was indicating good ability of model in simulating soil water and nitrate content and r2 was more than 90 percent which pointed out to well process of simulation of the model. The simulation accuracy was greater at the end of the growing season. Comparing of RMSE statistical index for different depths showed that the simulation accuracy was increased by increasing depth which can be due to changes in surface evaporation and also the effect of environmental factors on surficial layers more than other layers. Generally the best simulation was related to the layer of 80 to 100 cm. And the average RMSE was 0.019 cm3 per cm3 for soil moisture content and 0.22 mg per kg for soil nitrate.In the layer of 80-100 cm the best simulation of soil moisture and nitrate content between treatments was related to N0 by the RMSE equal to 0.024 cm3 per cm3 and 0.21 mg per kg respectively and the weakest simulation was related to N3.The simulated yield in all treatments was less than its actual value. Comparison of simulations between three treatments demonstrated the usefulness of EU-Rotate N to examine the effects of management on, nitrate leaching. Conclusions: The Eu-rotate-n model without calibration for site location was well capable of estimating soil water and nitrate content under different fertilizer management for Isfahan climatic conditions nevertheless it is suggested to use to calibrate yield functions to improve the yield simulation. Generally we can use Eu-rotate-n model for simulation of water and nitrogen content and eventually approach to integrated and optimal management in the farm in the hot, dry conditions of Isfahan.

The article introduced an upgraded approach to assessing the groundwater vulnerability to nitrate pollution. By using the results of fild measurements and process-based models outputs, author takes into account effects of nitrogen biogeochemical processes, that were hitherto underestimated in the evaluation schemes. The upgraded methodological self-validated approach to vulnerability assessment in Lower Savinja Valley case study increases reliability and thus effectiveness of decision-making in the water management. This was achieved by using the process-based models outputs in the new pattern classifiation schemes with the predictions of pollution phenomena. Spatial prediction of groundwater nitrate pollution probability and vulnerability classifiation of the study area in Lower Savinja Valley was assessed by weights-of-evidence model (WofE). The increased degree of probability for the groundwater contamination with nitrates was determined for 62.5 percent of the aquifer area of the Lower Savinja Valley. About 27 percent of the most nitrate vulnerable areas in Lower Savinja Valley need groundwater nitrate mitigation through land-use measures and public sewage system construction.

Water pollution by excessive amounts of nitrate (NO3−) has become a global issue. Technologies to clean up nitrate-contaminated water bodies include phytoremediation. In this context, this research aimed to evaluate four tree species (Salix alba L., Populus alba L., Corylus avellana L. and Sambucus nigra L.) to remediate nitrate-contaminated waters (100 and 300 mg L−1). Some physiological parameters showed that S. alba L. and P. alba L. increased particularly photosynthetic activity, chlorophyll content, dry weight, and transpired water, following the treatments with the above NO3− concentrations. Furthermore, these species were more efficient than the others studied in the phytodepuration of water contaminated by the two NO3− levels. In particular, within 15 days of treatment, S. alba L. and P. alba L. removed nitrate quantities ranging from 39 to 78%. Differently, C. avellana L. and S. nigra L. did not show particular responses regarding the physiological traits studied. Nonetheless, these species removed up to 30% of nitrate from water. In conclusion, these data provide exciting indications on the chance of using S. alba L. and P. alba L. to populate buffer strips to avoid NO3− environmental dispersion in agricultural areas.

Although representing a paramount mechanism against nitrogen excess in agricultural landscapes, soil denitrification is still a largely unknown term in nitrogen balances at the watershed scale. In the present work, a comprehensive investigation of nitrogen sources and sinks in agricultural soils and waters was performed with the aim of gaining insights into the relevance of soil denitrification in a highly farmed sub-basin of the Po River delta (Northern Italy). Agricultural statistics, water quality datasets, and results of laboratory experiments targeting nitrogen fluxes in soils were combined to set up a detailed nitrogen budget along the terrestrial−freshwater continuum. The soil nitrogen budget was not closed, with inputs exceeding outputs by 72 kg N·ha−1·year−1, highlighting a potential high risk of nitrate contamination. However, extensive monitoring showed a general scarcity of mineral nitrogen forms in both shallow aquifers and soils. The present study confirmed the importance of denitrification, representing ~37% of the total nitrogen inputs, as the leading process of nitrate removal in heavily fertilized fine-texture soils prone to waterlogged conditions.

The protection of water resources and development of mitigation strategies require large-scale information on water pollution such as nitrate. Machine learning techniques like random forest (RF) have proven their worth for estimating groundwater quality based on spatial environmental predictors. We investigate the potential of RF and quantile random forest (QRF) to estimate redox conditions and nitrate concentration in groundwater (1 km × 1 km resolution) using the European Water Framework Directive groundwater monitoring network as well as spatial environmental information available throughout Germany. The RF model for nitrate achieves a good predictive performance with an R ^2 of 0.52. Dominant predictors are the redox conditions in the groundwater body, hydrogeological units and the percentage of arable land. An uncertainty assessment using QRF shows rather large uncertainties with a mean prediction interval (MPI) of 53.0 mg l ^−1 . This study represents the first nation-wide data-driven assessment of the spatial distribution of groundwater nitrate concentrations for Germany.

Fertilization management and meteorological conditions can affect leachate composition and the balance of nitrogen (N) added during the cultivation of ornamentals. The main objectives of this study were to estimate the N balance components and to establish relationships between the N concentration in leachates and meteorological variables when different fertilization strategies are used in an outdoor potted crop of Osteospermum ecklonis (DC.) Norl. ‘Purple Red’. Two fertilizations strategies, i.e. continuous fertigation (NS) and incorporated controlled-release fertilizer (CRF), were applied to the crop. The treatments were two NS doses (NO3-N concentration in each NS, NS-A: 154 mg L-1 and NS-B: 112 mg L-1) and two CRF doses (CRF-C: 5.0 g L-1 of substrate and CRF-D: 2.5 g L-1 of substrate). The N loss by leaching was higher in the NS-A treatment than in the other ones (1.1 g pot-1, 11% of total available N). The amount of N accumulated by the plants was higher in the NS treatments than in the CRF treatments (average 2.5 g pot-1, 29.5% of total available N). However the efficiency of use of N was the greatest in the CRF-D treatment (23.9 g dry matter produced g-1 N supplied). About 50% of the total available N was measured in the substrate in all treatments (average 3.8 g pot-1). The concentration of N in the leachates for the two CRF treatments did not correlate with the substrate temperature or precipitation. The N released from the CRF matched the nutritional requirements of the plants better than the N applied by continuous fertigation.

Groundwater contamination is a major problem related strongly to both; protection of environment and the need of water. In the present study groundwater quality was investigated in the central part of the Nile Delta (El-Gharbiya Governorate). El-Gharbiya Governorate is an agricultural land and its densely populated area inhabited, includes small communities which totally not served by public sewers. Hydrochemical analyses were used to assess the quality of water in samples taken from the canals, drains and groundwater. A laboratory study and mathematical modeling works were presented. Two numerical computer models by the applying of finite difference method were adopted. Both models deal with the flow as a three-dimensional and unsteady. Results obtained include determining the levels of water and the values of solute concentration and distribution of it in the region at different times. The groundwater model MODFLOW was used to deal with the hydrodynamics of the flow through porous media. A solute transport model which can be communicated with MODFLOW through data files MT3DMS, was used to solve the problem of contaminants transport and the change of their concentrations with time. A proposed groundwater remediation scheme by using group of extraction wells was suggested at Birma region where the concentration values of ammonium contaminant are the up most according to hydrochemical analyses results. Proposed scenario for cleaning is to use a set of wells to pump contaminated groundwater extraction for treatment and reused to irrigation.

High nitrate concentration in groundwater is a major problem in agricultural areas in Iran. Nitrate pollution in groundwater of the particular regions in Isfahan province of Iran has been investigated. The objective of this study was to evaluate the performance of Adaptive Neural-Based Fuzzy Inference System (ANFIS) for estimating the nitrate concentration. In this research, 175 observation wells were selected and nitrate, potassium, magnesium, sodium, chloride, bicarbonate, sulphate, calcium and hardness were determined in groundwater samples for five consecutive months. Electrical conductivity (EC) and pH were also measured and the sodium absorption ratio (SAR) was calculated. The five-month average of bicarbonate, hardness, EC, calcium and magnesium are taken as the input data and the nitrate concentration as the output data. Based on the obtained structures, four ANFIS models were tested against the measured nitrate concentrations to assess the accuracy of each model. The results showed that ANFIS1 was the most accurate (RMSE = 1.17 and R2 = 0.93) and ANFIS4 was the worst (RMSE = 2.94 and R2 = 0.68) for estimating the nitrate concentration. In ranking the models, ANFIS2 and ANFIS3 ranked the second and third, respectively. The results showed that all ANFIS models underestimated the nitrate concentration. In general, the ANFIS1 model is recommendable for prediction of nitrate level in groundwater of the studied region.

Nitrate pollution in surface water has become an environmental problem of global concern. The effective way for controlling the nitrate pollution of surface water is to identify the pollution source and reduce the input of nitrate. In recent decades, nitrogen (δ15N) and oxygen (δ18O) isotopes of nitrate has been used as an effective approach for identifying the source and fate of nitrate pollution in surface water. However, owing to the complexity of nitrate pollution source and the influence of isotopic fractionation, the application of this method has some limitations. In this work, we systematically discussed the fundamental principle of using nitrogen and oxygen isotopes to trace the nitrate source, the fate identification of nitrate, and the major testing techniques. Subsequently, the applications of nitrogen and oxygen isotopes for source identification of surface water were illustrated. However, there are still significant gaps in the application of the source identification and transformation mechanisms to nitrate and many research questions on these topics need to be addressed.

The alluvial aquifer system of the Florina basin (320 km2) in North Greece is a representative area where irrigated agriculture is applied. Groundwater is the main source of water. The highest and mean nitrate concentrations in groundwater are 67.9 mg/L and 25 mg/L, respectively. High values could be associated with the use of nitrogen fertilizers from agricultural activities. This study deals with the evaluation of the groundwater quality. For this reason, hydrochemical analyses from 29 groundwater samples and water level measurements were performed for the wet and dry periods of 2016. The suitability of groundwater quality for irrigation purposes is examined by using different indices (Chlorinity Index, SAR, Sodium Percentage, Potential Salinity and Kelly’s index). In addition, the DRASTIC method was modified by using statistical methods, land use map and nitrate concentrations and applied in order to assess the groundwater vulnerability to external pollution. Notably, there was no correlation between the standard DRASTIC method and nitrate concentrations. However, the modified version and the obtained risk map showed high correlation with nitrate concentrations (ρ = 0.55) and the Groundwater Quality; hence, it is suggested as the base for a protection plan of the alluvial aquifer.