Groundwater Nitrate Research Articles

Elevated arsenic concentrations in groundwater of the Upper Indus Plain of Pakistan across a range of redox conditions

Groundwater of the Ravi River floodplain is particularly elevated in arsenic (As) on both sides of the Pakistan-India border. To understand this pattern, 14 sites were drilled to 12–30 m depth across floodplains and doabs of Pakistan after testing over 20,000 wells. Drill cuttings were collected at 1.5 m intervals, 132 of which were sand overlain by 77 intervals of clay and/or silt. Radiocarbon dating of clay indicates deposition of the aquifer sands tapped by wells 20–30 kyr ago. Most (85 %) of the sand samples were gray in color, indicating partial reduction to Fe(II) oxides, whereas most (92 %) of the clay and/or silt samples were orange. Associations between groundwater electrical conductivity, dissolved Fe, sulfate, and nitrate suggest that wells can be elevated (>10 μg/L) in As in the region due to either reductive dissolution of Fe oxides, evaporative concentration, or alkali desorption. In the Ravi floodplain, 47 % of 6445 wells tested contain >10 μg/L As compared to only 9 % of 14,165 tested wells in other floodplains and doabs. The As content of aquifer sands in the Ravi floodplain of Pakistan averages 4 ± 4 mg/kg (n = 66) and is higher than the average of 2 ± 2 mg/kg (n = 51) for aquifer sands outside the Ravi. Synchrotron spectroscopy and column-based speciation indicate predominance of As(V) over As(III) in both aquifer sands and groundwater. Whereas multiple processes may be responsible for elevated levels of As in groundwater across the region, spatial heterogeneity in groundwater As concentrations in the Ravi floodplain seems linked to variations in As concentrations in aquifer sands. Regulation by the solid phase may limit variations in groundwater As over time in response to natural and human-induced changes in hydrology. This means spatial heterogeneity could be taken advantage of to lower the exposure across the region with more testing and targeted drilling.

Groundwater nitrate pollution risk assessment based on the potential impact of land use, nitrogen balance, and vulnerability

The predicting groundwater nitrate pollution risk, especially in terms of changes in fertilizing, has not been fully investigated so far. In particular, there is no comprehensive method to assess this risk in areas of different land use type, and not only in agricultural areas. The aim of this study was to develop a novel multicriteria methodology for groundwater nitrate pollution risk assessment, which meets these issues. A further aim was to determine how much this risk would change if the amount of organic and synthetic fertilization was reduced. An assumption was that groundwater pollution risk is a combination of the potential adverse impacts of land use, fertilization, and intrinsic groundwater vulnerability to pollution. The impact of fertilization was holistically evaluated by balancing nitrogen from spatially differentiated the size of the breeding, species of livestock, manure and synthetic fertilizers input, and spatially differentiated topsoil, with nitrogen uptake by different crops. The nitrate concentration in the leachate was used as a measure of the impact of fertilization. This concentration was compared to the natural baseline nitrate concentration in groundwater. Three fertilization scenarios for groundwater pollution risk assessment in two study areas were discussed. Under typical agricultural, climatic, soil, and geological conditions in Europe for the current total fertilization level of 95-120 kg N ha−1 groundwater nitrate pollution risk is low and moderate, but for fertilization of 150-180 kg N ha−1, a reduction in the total fertilization (synthetic and manure) by 40 to 50% may be required to achieve low risk of degradation of natural groundwater quality. Predictive simulations of groundwater nitrate pollution risk confirmed that reducing synthetic and organic fertilization has an effect, especially in areas with intensive fertilization. This method may allow for a holistic and scenario-based assessment of groundwater pollution risk and may help decision-makers introduce solutions to manage this risk under conditions of climate change, preservation of groundwater quality, and food security.

Assessment of Nitrate in Groundwater from Diffuse Sources Considering Spatiotemporal Patterns of Hydrological Systems Using a Coupled SWAT/MODFLOW/MT3DMS Model

In recent years, due to various anthropogenic activities, such as agriculture and livestock, the presence of nitrogen-associated contaminants has been increasing in surface- and groundwater resources. Among these, the main compounds present in groundwater are ammonia, nitrite, and nitrate. However, it is sometimes difficult to assess such effects given the scarcity or lack of information and the complexity of the system. In the current study, a methodology is proposed to assess nitrate in groundwater from diffuse sources considering spatiotemporal patterns of hydrological systems using a coupled SWAT/MODFLOW/MT3DMS model. The application of the model is carried out using a simplified simulation scheme of hydrological and agricultural systems because of the limited spatial and temporal data. The study area includes the Cuitzeo Lake basin in superficial flow form and the Morelia–Querendaro aquifer in groundwater flow form. The results within the methodology are surface runoff, groundwater levels, and nitrate concentrations present in surface- and groundwater systems. The results indicate that the historical and simulated nitrate concentrations were obtained within acceptable values of the statistical parameters and, therefore, are considered adequate.

Risk assessment for the distribution and levels of fluoride and nitrate in groundwater in a semi-arid area of northern Mexico

This study assessed groundwater quality and associated risks in a semi-arid region located in a city in the Northern zone of Mexico. To conduct this study, we collected 92 groundwater samples and analyzed 14 physicochemical parameters across 18 sectors. Only fluoride (F−) and nitrate (NO3–N) exceeded Mexican regulations and WHO guidelines for drinking water. Approximately 65 % of samples surpassed the 1.5 mg/L permissible limit for F−, with the highest recorded concentration reaching 3.60 mg/L in two sectors among the 18 studied, 34 % of samples exhibited NO3−-N concentrations in the 10.64–17.27 mg/L range across three sectors, surpassing permissible levels. Pearson Correlation Analysis revealed strong positive correlations with HCO3−, EC, Mg2+, Ca2+, NO3−, Cl−, SO42−, and Na+. Moderate correlations existed for the total hardness, alkalinity, Cl−, NO3−, SO42−, Na+, Mg2+, and EC. K+ showed weak correlations. PIG values indicated significant pollution of F− in all of 18 sectors (PIG <1). HQ for F− exceeded tolerable levels in 14 adult and 16 child sectors, posing an intolerable risk. Nitrate's HQ was below <1 for all age groups, suggesting non-carcinogenic effects. THI indicated high F− and NO3−-N exposure risks for children in the study area. It is recommended to implement effective water treatment technologies, such as reverse osmosis or adsorptive materials, in those sectors reported as a potential risk to human health to ensure access to safe drinking water.

Predicting areal extent of groundwater contamination through geostatistical methods exploration in a data-limited rural basin

The areal extent of regulatory standard exceedance for groundwater arsenic, fluoride, and nitrate was estimated and compared for multiple methods to evaluate groundwater contamination in a rural basin of New Mexico, USA. First, three geostatistical kriging techniques – Ordinary Kriging (OK), Universal Kriging (UK), and Empirical Bayesian Kriging (EBK) – were explored. Next, the exploration was extended to multivariate analysis (Co-OK, Co-UK, and EBK-regression) using groundwater pH as the other variable, compared to interpolation only considering the contaminant as a primary variable. Finally, non-parametric Indicator Kriging (IK) was utilized for probability mapping and assessing the likelihood of surpassing critical thresholds for contaminant concentrations. The contamination area changes with different kriging methods deployed, and the performances of kriging variants vary for the three chemical components. The models that best fit the empirical data were determined. The study examined the influence of the explanatory variable on the multivariate kriging prediction accuracy. The multivariate kriging approaches enhanced surface prediction accuracy and tended to cover the data limitation of the primary variable interpolations. The multivariate kriging improved spatial prediction of arsenic and fluoride by increasing the Empirical Coverage Probability (ECP) up to 0.05–0.25 from case to case; however, no improvement was observed in ECP for nitrate contamination distribution, as the explanatory variable pH was only weakly correlated with nitrate, suggesting that a stronger correlation between the primary and secondary variables can increase the probability of obtaining prediction improvements through multivariate kriging. This study developed a methodology for characterizing and identifying locations where groundwater had elevated concentrations of contaminants, threatening human health through drinking water exposure. By improving the spatial characterization of groundwater contaminants within the data-limited rural basin, policymakers planning improvements will support mitigation strategies to manage contamination sources of groundwater resources.

Dissolved organic matter and nutrient processing in organic-rich subterranean estuaries: Implications for future land use and climate scenarios

The subterranean estuary (STE) is a recognized reactive biogeochemical zone at the groundwater–seawater interface in coastal regions. However, few studies have explored dissolved organic matter (DOM) and nutrient processes in buried organic-rich STEs (with up to 20 % of organic matter content), despite their potential contributions to coastal water hypoxia and greenhouse gas emissions. This study conducted controlled laboratory experiments to investigate the physicochemical controls on DOM and nutrient processing in organic-rich STEs, considering variations in groundwater nitrate (NO3–) concentrations, salt concentration, seawater ions, and incubation times. Results showed elevated levels of dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) in pore water, primarily from particulate organic matter (POM) degradation that originated from decayed vascular plants. POM-to-DOM degradations further resulted in the accumulation of ammonium (NH4+) and highly unsaturated compounds in all treatments. The addition of high-ionic-strength treatments (e.g., seawater and sodium chloride [NaCl] solution) reduced DOC solubility and selectively removed dissolved aromatic compounds in porewater. The cation-rich seawater shifted the porewater NH4+ generation pathway from predominantly biological (re)mineralization in freshwater to abiotic (desorption via ion exchange) pathways in the saline water setup. Orthophosphate (PO43−) dynamics were likely to be influenced by the iron-rich sediment surface in both freshwater and saline water scenarios. Our experiments further indicated that the long-term incubation enriched DOM concentration with a high degradation state. This work demonstrated that organic-rich STEs are significant sources of less labile DOM and NH4+ to coastal waters. In the context of global climate change, our results illustrate the sensitivity of DOM and nutrient biogeochemical cycling in STEs to salinization and altered residence time, consequently affecting the quantity and quality of DOM and nutrients transported to coastal waters.

Hybrid analytic network process (ANP)-Entropy model, time series analysis for predicting nitrate and fluoride in groundwater and cumulative health risk assessment

The study focused on groundwater evaluation of the trans-Himalayan region using a novel concept of Hybrid Analytic Network Process (ANP) - entropy and Holt's exponential smoothing model for short-term prediction of groundwater quality. Hierarchy cluster analysis of groundwater was performed to identify the sources and spatial distribution of water quality. The PCA coupled with multivariate analysis dictated a high correlation of various ions i.e., NO3−, K+, F−, Cl−, SO42−, PO42−, and Na+ with the lithology of the area and helped in identification of various polluting sources i.e., excessive use of fertilizers, wastewater discharges and agrochemicals. The hybrid ANP-entropy technique offered a holistic approach to provide a more accurate and complete understanding of groundwater quality and revealed that groundwater quality in 21.43% (in winter) and 42.86% (in summer) of the locations fall into the poor category. The non-carcinogenic health risk analysis revealed that fluoride poses a major potential health risk followed by nitrate, primarily via the oral pathway while it was negligible through the dermal pathway. The total hazard index was observed highest in children (1.99) followed by infants (1.64). 95th percentile of the probable risk obtained through Monte Carlo simulation also dictated highest risk to infants than child. The predicted values of the Holt's exponential smoothing model for the year 2021 and 2022 was varied within ±5 % of the observed values. The proposed model effectively treats uncertainties in groundwater quality assessment and considers average and incremental increase both hence, can be used for short-term prediction and trend analysis of groundwater quality.

A Review of the Status, Effects, Prevention, and Remediation of Groundwater Contamination for Sustainable Environment

Most water systems that support ecosystems and feed humans are depleted or stressed. Aquifer characteristics, topography, subsurface activities, climate, and geochemical processes regulate groundwater availability, a reliable source of fresh water. Globally, agriculture, industries, and the domestic sector are the three major sectors that consume vast quantities of freshwater resources. Further anthropogenic activities, such as soil leaching, acid rain, fertilizer, pesticides, mining, and other industrial activities, resulted in the release of organic and inorganic pollutants that affected global water resources. In India, groundwater is used in huge quantities, resulting in groundwater depletion of 1 to 2 m a year. Low-income countries face many issues related to water pollution, and the availability of safe water is minimal. In 2019, deaths due to unsafe sanitation accounted for 2.2% of the total global deaths, amounting to 1.2 million people’s deaths. India recorded 6.6% of deaths due to unsafe sanitation in 2019. India and China accounted for around 90.41% and 60.4% of the groundwater utilization for agricultural purposes, respectively. In 2020, China and India utilized vast quantities of nutrients (nitrate and phosphate) for crop growth to enhance crop yield, resulting in the highest nitrate and phosphate concentrations in groundwater. Remediating contaminants from different sources requires knowledge of their concentration, behavior, cycling, and degradation pathways. According to safety guidelines, limiting and optimizing crop organic and inorganic fertilizer, pesticide waste disposal, and empty container disposal can reduce groundwater contamination. The present study summarized groundwater utilization in various sectors, potential sources of groundwater contamination impacts on human health and the environment, preventive measures, and mitigation methods to overcome groundwater pollution.

Analysis of the Distance between the Measured and Assumed Location of a Point Source of Pollution in Groundwater as a Function of the Variance of the Estimation Error

The localization of pollution sources is one of the main tasks in environmental engineering. For this paper, models of spatial distribution of nitrate concentration in groundwater were created, and the point of highest concentration was determined. This point represents the assumed location of the pollution source and differs from the actual location, so there is a certain distance between the measured and assumed location. This paper puts forward a new hypothesis that the distance between the measured and the assumed location is a function of the variance of the estimation error. The scientific contribution of this paper is based on the fact that the interaction of statistical and geostatistical methods can locate the dominant point source of pollution or narrow down the search area. The above hypothesis is confirmed by the example of the Varaždin wellfield, which was closed due to an excessively high groundwater nitrate concentration. Seven different interpolation methods were used to create spatial distribution models. Each method provides a different model, a different variance of the estimation error, and estimates of the location of the pollution source. The smallest value of variance of the estimation error of 1.65 was obtained for the minimum curvature interpolation method and the largest value of variance (24.49) was obtained for the kriging with logarithmic variogram. Our results show a nonlinear and monotonic relationship between the distance and the variance of the estimation error, so logarithmic and rational quadratic models were fitted to the scatter point data. The models were linearized, a t-test was performed, and the results show that the models can be considered reliable, which is confirmed by the values of the coefficients of determination of the linearized models, which are around 0.50. The obtained results can be used in planning additional research work to determine the measured location of the pollution source. The research methodology we used is universal and can be applied to other locations where high concentrations of certain contaminants have been detected in groundwater in alluvial aquifers.

Regional nitrogen budgets of agricultural production systems in Austria constrained by natural boundary conditions

Nitrogen (N) budgets are valuable tools to increase the understanding of causalities between agricultural production and N emissions to support agri-environmental policy instruments. However, regional agricultural N budgets for an entire country covering all major N flows across sectors and environmental compartments, which also distinguish between different N forms, are largely lacking. This study comprehensively analyses regional differences in N budgets pertainting to agricultural production and consumption in the largely alpine and spatially heterogeneous country of Austria. A special focus is on the interconnections between regional agricultural production systems, N emissions, nitrogen use efficiencies (NUE), and natural boundary conditions. Seven regional and one national balance are undertaken via material flow analysis and are analysed with regards to losses into soils, water bodies and atmosphere. Further, NUE is calculated for two conceptual systems of plant and plant-livestock production. The results reveal major differences among regions, with significant implications for agri-environmental management. The high-alpine region, characterized by alpine pastures with a low livestock density, shows consequent low N inputs, the lowest area-specific N outputs and the most inefficient NUE. In contrast, the highest NUE is achieved in a lowland region specialized in arable farming with a low livestock density and a predominance of mineral fertilizer over manure application. In this region, the N surplus is almost as low as in the high-alpine region due to both significantly higher N inputs and outputs compared to the high-alpine region. Nevertheless, due to low precipitation levels, widespread exceedances of the nitrate target level concentration take place in the groundwater. The same issue arises in another non-alpine region characterized by arable farming and high livestock densities. Here, the highest N inputs, primarily via manure, result in the highest N surplus and related nitrate groundwater exceedances despite an acceptable NUE. These examples show that NUE alone is an insufficient target and that adapted criteria are needed for different regions to consider natural constraints and specific framework conditions. In a geographically heterogeneous country like Austria, the regional circumstances strongly define and limit the scope and the potential effectiveness of agricultural N management strategies. These aspects should be integrated into the design, assessment and implementation of agri-environmental programmes.

Numerical modeling of groundwater flow and nitrate transport in karst and wastewater irrigated agricultural and forest landscapes, PA, USA

AbstractUnderstanding the influence of treated wastewater reuse for irrigation on nitrate groundwater contamination in karstic landscape is critical for developing long‐term management plans and assessing the sustainability of these practices. The Pennsylvania State University has been operating a secondary treated wastewater effluent irrigation site—the “Living Filter”—since the 1960s. The objective of this study is to develop a regional groundwater flow and nitrate transport model to assess the impact of treated wastewater and disposal of large volumes of wastewater for irrigation of agricultural and forested lands on nitrate groundwater contamination in a karst landscape in the Spring Creek Watershed in central Pennsylvania. The modular three‐dimensional finite‐difference ground‐water flow model (MODFLOW) was used to construct the groundwater flow model of the local aquifer and simulate three‐dimensional regional changes in the water table over time. The simulation of nitrate fate and transport in the aquifer was conducted by developing a groundwater mass transport model using MODFLOW and a modular three‐dimensional transport multi‐species model (MT3DMS). The calibrated groundwater model yielded a root mean square error of 5.41 ft for the area of irrigation and 24.67 ft for the entire modeled area. Results of the calibrated model show the extension of a nitrate plume over most of the study area with concentrations below 10 mg·L−1 under the current 2015 setting and the long‐term 2035 scenario of increased irrigation rates. The nitrate migration was dominated by the presence of two high conductivity groundwater troughs adjacent to the study area resulting in a near steady‐state total mass since the 1990s.

Hydrochemical characteristics and the impact of human activities on groundwater in a semi-arid plain: a case study of western Jilin Province, Northeast China.

Groundwater is important for human survival and development, particularly in arid and semi-arid regions. This study aimed to analyze the hydrochemical characteristics, influencing factors, and the impact of human activities on groundwater in the semi-arid plains of western Jilin Province, northwest China. The study collected 88 and 151 phreatic and confined water samples, respectively, which were analyzed for 13 water quality indicators using statistical and graphical methods. In order to investigate the impact of anthropogenic activities on water quality and health risks, the improved combined weighted water quality index (ICWQI) based on the entropy weight, criteria importance though inter-criteria correlation (CRITIC), the coefficient of difference method, subjective weight based on quality grading criteria, and the water quality index (WQI) were proposed to evaluate the water quality of the study area. Meanwhile, the human health risk assessment (HHRA) model was used to assess the risks of nitrate to the health of humans in different ages and sex categories. The results indicated that the groundwater in the study area was weakly alkaline and the main hydrochemical types in the phreatic and confined water were HCO3-·Ca-Mg and HCO3--Na. Rock weathering was the dominant process responsible for the generation of groundwater ions, the ions in groundwater primarily originate from the dissolution of halite, gypsum, and feldspar, while dolomitization promotes an increase in Mg2+. Human activities lead to an increase in NO3- in groundwater and have an impact on water quality and human health risks. The ICWQI method was found to yield more precise and rational assessments of water quality. Groundwater quality is primarily affected by nitrate ions. The areas in which groundwater nitrate posed a higher risk to human health were found to be mainly in the saline-alkali lands of Qian'an, Tongyu, and Zhenlai. Fertilizers, pesticides, and livestock farming activities contribute to the pollution of surface water. This surface contamination then infiltrates abandoned confined wells, leading to contamination of the confined aquifers. This study can improve the understanding of groundwater hydrochemical characteristics and the impact of human activities on groundwater in the study area. This study can also contribute to the study of groundwater in semi-arid regions.

Intensification options in cereal-legume production systems generate trade-offs between sustainability pillars for farm households in northern Morocco

CONTEXTFarmers in the MENA (Middle East and North Africa) region face several interrelated challenges including natural resource depletion, low crop productivity, and food and nutrition insecurity. To address some of these challenges, governments are considering different incentives to increase crop production. However, incentives often entail trade-offs and may have diverging effects on economic, social, and environmental sustainability. OBJECTIVESThis study assessed the ex-ante effects of incentives targeted towards increasing crop production on the production and consumption decisions of farm households on the Saïss plain of northern Morocco. METHODSThe assessment was conducted with a dynamic, intertemporal farm household model that simulates farm production and food consumption decisions. The model was calibrated using survey data from 85 farm households for 2014. Four scenarios were codesigned with local stakeholders and then simulated over a continuous 15-year period to capture rainfall variability: (1) increased availability of annual groundwater for irrigated cropping from 31 m3 ha−1 to 215 m3 ha−1, (2) a 15% increase in grain prices for cereals and legumes, (3) introduced drought tolerant crop varieties, and (4) a fourth scenario that combines all factors in the above three scenarios. RESULTS AND DISCUSSIONOur results showed that regardless of the scenario, the area of cereals and legumes cultivated only slightly changed compared to the Baseline scenario. However, according to the scenarios tested, the total production of cereals increased by 10% to 21% and of legumes increased by 2% to 9%. This production increase is the direct consequence of increased crop yields due to an intensification of crop production methods. The incentives increased the consumption of cereals and legumes by up to 43%. This increase was mainly due to a shift from grain to vegetable production that increases cash income, resulting in more food purchases from the market while consumption from own production dropped by up to 53%. The average increase in crop income was 14% in scenarios 1–3 and 28% in scenario 4. However, increased income had ramifications for nature resource stocks, with irrigation water use from groundwater increasing by 593% in the Water scenario and 320% in the combined scenario, relative to the Baseline scenario. In the Water scenario, incomes increased by 15% and nitrogen leached increased by 36%, highlighting the trade-off between economic and environmental sustainability. SIGNIFICANCEThese results show the challenges in obtaining acceptable compromises between the three sustainability pillars as the scenarios increased income but also led to increased groundwater extraction and nitrate leaching.

A century of nitrogen dynamics in agricultural watersheds of Denmark

Intensive agriculture has been linked to increased nitrogen loads and adverse effects on downstream aquatic ecosystems. Sustained large net nitrogen surpluses have been shown in several contexts to form legacies in soil or waters, which delay the effects of reduction measures. In this study, detailed land use and agricultural statistics were used to reconstruct the annual nitrogen surpluses in three agriculture-dominated watersheds of Denmark (600–2700 km2) with well-drained loamy soils. These surpluses and long-term hydrological records were used as inputs to the process model ELEMeNT to quantify the nitrogen stores and fluxes for 1920–2020. A multi-objective calibration using timeseries of river nitrate loads, as well as other non-conventional data sources, allowed to explore the potential of these different data to constrain the nitrogen cycling model. We found the flux-weighted nitrate concentrations in the root zone percolate below croplands, a dataset not commonly used in calibrating watershed models, to be critical in reducing parameter uncertainty. Groundwater nitrate legacies built up in all three studied watersheds during 1950–1990 corresponding to ∼2% of the surplus (or ∼1 kg N ha yr−1) before they went down at a similar rate during 1990–2015. Over the same periods active soil nitrogen legacies first accumulated by approximately 10% of the surplus (∼5 kg N ha yr−1), before undergoing a commensurate reduction. Both legacies appear to have been the drivers of hysteresis in the diffuse load at the catchments’ outlet and hindrances to reaching water quality goals. Results indicate that the low cropland surpluses enforced during 2008–2015 had a larger impact on the diffuse river loads than the European Union’s untargeted grass set-aside policy of 1993–2008. Collectively, the measures of 1990–2015 are estimated to have reset the diffuse load regimes of the watersheds back to the situation prevailing in the 1960s.

A Review on In-Situ Denitrification Technology for Consideration in Jaffna Peninsula Aquifer Remediation

A Review on In-Situ Denitrification Technology for Consideration in Jaffna Peninsula Aquifer Remediation

Source identification and potential health risks of fluoride and nitrate in groundwater of a typical alluvial plain

A comprehensive understanding of the role of natural and anthropogenic factors in groundwater pollution is essential for sustainable groundwater resource management, especially in alluvial plains with intensive anthropogenic activities. Numerous studies have focused on the contribution of individual factors on groundwater pollution in alluvial aquifers, but distinguishing the effects of natural and anthropogenic factors is limited. In this study, 64 wells were sampled in different seasons from the Yellow River alluvial plain in China for hydrochemical and isotopic analysis to investigate the spatiotemporal distribution, sources and health risks of fluoride and nitrate in alluvial aquifers. Results showed that fluoride contamination was widely distributed without significant seasonal variation, and 78.1 % of the dry season samples and 65.6 % of the wet season samples showed fluoride concentrations above the permissible limit (1.5 mg/L). High-F− groundwater was generally accompanied by Na-HCO3 and Na-HCO3·SO4 water types. Fluoride was from a natural origin mainly associated with mineral dissolution, competitive adsorption, cation exchange, and evaporation. Groundwater nitrate contamination was spatially sporadic and showed significant seasonal differences. Only 13.6 % of the dry season samples and 3.2 % of the wet season samples had NO3− concentrations exceeded the permissible limit of 50 mg/L. The hydrochemical phase evolved from bicarbonate or sulfate type to chloride type with increasing nitrate concentration. Manure and sewage attributed to agricultural activities contributed the most nitrogen to groundwater, followed by soil organic nitrogen and chemical fertilizers, revealing the anthropogenic origin of nitrate. Nitrification was the dominant nitrogen transformation process in the wet season, and denitrification was prevalent in the dry season. Oral ingestion of high fluoride groundwater was a major threat to human health, especially for infants. This study provided a significant reference for water resources management in alluvial aquifers.

Non-carcinogenic Health Risk Assessment of Fluoride and Nitrate of Groundwater – A Case Study of the Central Dry Zone of Chikkanayakanahalli Taluk, Tumkur District, Karnataka

Abstract Forty-two groundwater samples were randomly collected from Chikkanayakanahalli taluk during the pre-monsoon season of 2022 and were analysed for Fluoride and Nitrate levels using APHA standard methods. USEPA method was employed to assess the non-carcinogenic health hazards associated with exposure to NO3– and F– from drinking water consumption by computing estimated daily intake (EDI), hazard quotient (HQ) and total hazard index (THI). HQnitrate &amp;gt; 1 through the ingestion pathway was observed in 14.28 and 4.76 % of the groundwater samples, respectively, for children and Teenagers, while HQfluoride &amp;gt; 1 for children was reported in 16.66% of the groundwater samples. Higher mean values of HQFluoride over HQNitrate supported added contribution of fluoride in groundwater of the study area in the non-carcinogenic human health risk over nitrate among different age groups of the local population. Overall, the average THI values were 0.205, 1.452, 1.025 and 0.821, respectively, for Infants, children, Teenagers, and Adults, and their trend was in the order: children &amp;gt; Teenagers &amp;gt; Adults &amp;gt; Infants. It was found that 90.5%, 54.8%, and 14.3% of the samples progressed beyond the standard limit (THI = 1) for children, Teenagers, and adults, respectively, illustrating that children are more prone to non-carcinogenic risks than other age groups. Further, NHHR of F- and NO3- in groundwater was higher for children, attributed to their lower body weight over teenagers and adults, besides average water consumption rates.

An integrated approach combining LISA, BI-LISA, and the modified COPK method to improve groundwater management in large-scale karst areas

Groundwater protection and sustainable utilization of wells in large-scale karst areas face many challenges due to the complexity of numerous groundwater basins and aquifers. Therefore, scientific evidence is needed for groundwater management in these areas. A method combining source vulnerability, spatial autocorrelation, and bivariate spatial autocorrelation is proposed for groundwater management research. Based on the COP method (composed of flow Concentration, Overlying layers, and Precipitation regime), the COPK method is modified by replacing the sinkhole distance with sinkhole density, and incorporating land use and karst network development. The modified COPK method is used to evaluate the vulnerability of nitrate in groundwater in large-scale karst areas. Guizhou Province in China, which is a typical karst region, was evaluated as a study area. Comparatively to the classical COP method, the revised vulnerability map shows more areas of high vulnerability, mainly in the middle of the study area. According to the receiver operating characteristic curve (ROC) analysis, the modified method had a higher accuracy than the classical COP algorithm. Based on the accurate vulnerability index, vulnerability was classified using the natural break method, and the spatial autocorrelation of vulnerability clustering characteristics was studied. The source vulnerability was divided into High-High (HH), High-Low (HL), Low-High (LH), Low-Low (LL), and Not Significant (NS) clusters. This result can clarify the vulnerability clustering of groundwater in specific areas, thereby helping to improve groundwater management accuracy and efficiency. In addition, bivariate spatial autocorrelation was used to study the nitrate content of wells and source vulnerability. The bivariate local Moran's index showed a spatial negative correlation between the two. Similarly, the BI-LISA map can be used to characterize the spatial aggregation of nitrate content and well vulnerability. This result can help groundwater managers develop reasonable measures to protect water wells.

A new probabilistic assessment process for human health risk (HHR) in groundwater with extensive fluoride and nitrate optimized by non parametric estimation method.

Excessive amounts of fluoride (F-) and nitrate (NO3-) in groundwater pose a significant threat to human health. However, a quantitative approach to assessing the human health risks caused by these harmful substances is lacking. To optimize the probabilistic assessment process for human health risk (HHR), this study introduced kernel density estimation (KDE) into the stochastic simulation of F- and NO3- content in groundwater samples. The potential HHRs caused by F- and NO3- in Songyuan City were summarized by combining the probabilistic and deterministic assessments. This study found that the concentrations of F- and NO3- did not follow common probability density functions (PDFs), but the KDE method passed the Kolmogorov-Smirnov test with the critical value of 0.067 and 0.062, showing high fitting accuracy. Monte Carlo simulation indicated that the probability of NO3- for children and adult exceeding the standard is 21.95% and 15.14%, respectively, which is comparable with the results of the deterministic assessment, but the probabilistic assessment emphasized lower probability of HHRs in children caused by excess F-(4.14%). Global sensitivity analysis revealed that excessive NO3- in groundwater has the highest sensitivity of the HHR (>0.1), followed by other factors representing water use habits (>0.01). This study presents a refined probabilistic assessment method for HHR and provides a scientific reference for understanding the state of groundwater environments.

Estimation of Water Quality Index and Factors Affecting Their Changes in Groundwater Resource and Nitrate and Fluoride Risk Assessment

Estimation of Water Quality Index and Factors Affecting Their Changes in Groundwater Resource and Nitrate and Fluoride Risk Assessment