Groundwater Nitrate Research Articles

Human health risk assessment of nitrate and heavy metals in urban groundwater in Southeast Nigeria

Groundwater contamination by nitrate and heavy metals is a growing global concern due to its detrimental effects on human health through ingestion and dermal exposure. This study aimed to assess the concentrations of nitrate and heavy metals (Pb, Cu, Cd, and Fe) in groundwater and evaluate the associated health risks among different age groups (females, males, and children) in the Nnewi and Awka regions of southeast Nigeria. Standard methods were followed. Ten groundwater samples were collected from each study locality, and their physicochemical parameters were analyzed. The evaluation of heavy metal levels in groundwater was conducted using the risks of cancer and health hazard index as indicators of public health impact. The results showed that while nitrate levels were within acceptable limits, heavy metal concentrations exceeded permissible levels in all samples. Carcinogenic risk (CR) analysis revealed that approximately 40% of Nnewi samples and 80% of Awka samples exceeded the permitted range of ≤1 × 10 −6–1 × 10 −4. In the Nnewi region, the order of heavy metal toxicity was Cd > Pb > Cu > Fe, while in Awka, it was Pb > Cd > Cu > Fe, resulting in severe non-carcinogenic health hazards for users. Cd and Pb were identified as the most significant contaminants impacting water quality in both regions. Children exhibited greater vulnerability to health risks compared to adults in both areas. These findings contribute to our understanding of localized nitrate and heavy metal contamination, highlight the vulnerability of children, and emphasize the importance of regular monitoring and management practices.

Potential health risk assessment of nitrate in groundwater of Tonk district in Rajasthan, north western India

ABSTRACT Anthropogenic activities like adding synthetic nitrogenous fertilisers in agriculture fields, animal and human waste are the main factors responsible for the increase in nitrate concentration in groundwater of any area. Groundwater is the main source of not only irrigation but also dependency for drinking which has increased on it with decreasing surface sources. Today, increase in such anthropogenic activities has resulted in upsurge of the natural nitrate concentration to the extent of crossing its acceptable limit in drinking water. The Bureau of Indian Standard (BIS, 2012) 1 has prescribed the limit of 45 mg/L, whereas for WHO (2011) 2 the limit of nitrate is 50 mg/L. The goal of this present study is to assess the natural and anthropogenic NO3 concentrations in groundwater in a semi arid area of Rajasthan in Tonk District and its related risks to human health in the different groups of ages, such as children, males, and females. Being immune adults has little less effect on its continuous exposure than children. Even though these risks are non-carcinogenic, incessant exposure can create several health issues. In juveniles, it is known to cause methemoglobinemia, in adults it causes gastric and other stomach issues on prolonged consumption as well as dermal contact. The results show that the oral exposure of nitrate was very high compared to dermal contact. On the basis of non-carcinogenic health risk, the total Hazard Index (HITotal) values of groundwater nitrate were an average of 1.16 for males, 1.37 for females, and 1.58 for children. The nitrate health risk assessment shows that about 39%, 44%, and 51% of the samples constitute the non-carcinogenic health risk to males, females, and children, respectively.

An Integrated Framework to Assess the Environmental and Economic Impact of Fertilizer Restrictions in a Nitrate-Contaminated Aquifer

Groundwater nitrate contamination caused by the excessive use of nitrogen-based fertilizers has been widely recognized as an issue of significant concern in numerous rural areas worldwide. To mitigate nitrate contamination, corrective management practices, such as regulations on fertilizer usage, should be implemented. However, these measures often entail economic consequences that impact farmers’ income, and thus should be properly assessed. Within this context, an integrated framework combining the environmental and economic assessment of fertilization restrictions through multi-criteria decision analysis is presented in an effort to efficiently manage groundwater nitrate contamination in rural areas. For this task, various scenarios involving reductions (10%, 20%, 30%, 40% and 50%) in fertilizer application were investigated, evaluated and ranked in order to determine the most suitable option. The environmental assessment considered occurrences of nitrates in groundwater, with a specific emphasis on nitrate concentrations in water-supply wells, as obtained by a nitrate fate and transport model, while the economic analysis focused on the losses experienced by farmers due to the reduced fertilizer usage. Our case-study implementation showed that a 30% reduction in fertilization is the most appropriate option for the area being studied, highlighting the importance of adopting such an approach when confronted with conflicting outcomes among alternatives.

Tracing the fate of seabird‐derived nitrogen in a coral reef using nitrate and coral skeleton nitrogen isotopes

AbstractSeabirds transfer nutrients from the ocean to their nesting island, potentially altering nitrogen (N) cycling within adjacent terrestrial and marine ecosystems. Yet, the processes involved in seabird‐N transfer along the land–sea continuum remain elusive. Using δ15N and δ18O measurements of groundwater nitrate, we demonstrate the role of brackish groundwater located within a coral island's landmass as a major reservoir of nitrate (at millimolar levels). Nearly all of the total dissolved seabird‐derived N leaching into the groundwater (mostly ammonium and uric acid) is converted to nitrate by nitrification, as supported by the relatively low δ18O of the groundwater nitrate (3.97‰ ± 0.30‰). Comparison of nitrate δ15N and δ18O suggests that little denitrification takes place within the groundwater lens, implying that the high δ15N of groundwater nitrate (13.73‰ ± 0.05‰) derives from the high trophic position of seabirds and postdepositional processes that increase the δ15N of seabird excreta. Seawater and coral skeleton samples from a reef flat exposed to groundwater had higher δ15N values than at sites devoid of groundwater influence, indicating that the main source of N at the latter site was the Subtropical Upper Water, while the groundwater nitrate dominated the exposed reef flat N pool up to 200 m from shore. In addition, these results indicate that coral‐bound δ15N can detect seabird‐derived nitrate δ15N, raising opportunities to reconstruct historical seabird‐N inputs to coral reefs in relation to climatic and other changes, such as the introduction of invasive species.

Hydrochemical Evolution and Nitrate Source Identification of River Water and Groundwater in Huashan Watershed, China

The combined hydrochemical analysis, factor analysis, and isotopic signals of water and nitrate were applied to explore the hydrochemical origin and identify the sources and transformation of nitrate in river water and groundwater in the Huashan watershed. Additionally, a Bayesian isotope mixing model (SIAR) was employed for quantitative assessment of the nitrate sources. The results indicated that both river water and groundwater were dominated by HCO3-Ca and HCO3-Ca·Mg types; both originated from precipitation and were influenced by evaporation. The main constituent ions in the river water and groundwater primarily originated from carbonate and silicate dissolution, with the presence of cation exchange in the groundwater. The water chemistry of river water was greatly influenced by physicochemical factors, while that of groundwater was mainly controlled by water–rock interaction. NO3− in river water was mainly influenced by soil nitrogen (SN) and manure and septic wastes (MSWs), while NO3− in groundwater was jointly affected by ammonium fertilizers (AF), SN, and MSWs. With the exception of denitrification observed in the groundwater at the watershed outlet, denitrification was absent in both groundwater in the piedmont area and in river water. The SIAR model results demonstrated that the contribution rates of atmospheric precipitation (AP), AF, SN, and MSWs to river water were 12%, 21%, 25%, and 42%, respectively, while to groundwater, they were 16%, 27%, 10%, and 47%, respectively. Overall, MSWs were the main sources of nitrate in the river water and groundwater. It is necessary to prevent the leakage of MSWs when managing water resources.

Dynamics of soil water and nitrate within the vadose zone simulated by the WHCNS model calibrated based on deep learning

Excessive application of water and nitrogen fertilizer during farmland management practices leads to serious groundwater nitrate pollution. A field experiment was conducted during the spring maize growth period in Alxa, Inner Mongolia, China. The soil Water Heat Carbon Nitrogen Simulator (WHCNS) model was calibrated by the ensemble smoother method (ES(DL)) based on the field experiment. Then dynamics of soil water content, soil water percolation flux, soil nitrate concentration and soil nitrate leaching flux were simulated with the calibrated WHCNS model under different water and nitrogen fertilization treatments within the vadose zone. The main conclusions are as follows: ES(DL) is feasible for the calibration of the WHCNS model. RMSE_Maximum a posteriori (RMSE_MAP) of soil water content are 0.0301 cm3 cm−3 and 0.0302 cm3 cm−3 for model calibration and model validation, respectively. RMSE_MAP of soil nitrate concentration are 5.49 mg N kg−1 and 3.86 mg N kg−1 for model calibration and model validation, respectively. Both average soil nitrate concentration and average nitrate leaching flux increase with increasing irrigation amount under the same nitrogen fertilization level for the depths of 1.2 m and 1.8 m. However, average soil nitrate concentration decreased and leaching flux increased with increasing irrigation amount under the same nitrogen fertilization level for the depths of 10 m and 20 m. The study of nitrate dynamics in the deep vadose zone contributes to better understand the procedure of nitrate pollution in groundwater caused by excessive water and nitrogen application.

Origin and health risks of nitrate in groundwater from a riverine reservoir basin in an agricultural region of Sichuan Basin

Origin and health risks of nitrate in groundwater from a riverine reservoir basin in an agricultural region of Sichuan Basin

Structure properties and industrial applications of anion exchange resins for the removal of electroactive nitrate ions from contaminated water.

The presence of nitrates in lakes, rivers, and groundwater is common. Anion exchange resins (AER) are polymeric structures that contain functional groups as well as a variety of particle sizes that are used for removing nitrate ions from solutions. This article provides a concise review of the types and properties of AER, synthesis methods, characterization, and environmental applications of AER. It discusses how different factors affect the adsorption process, isotherm and kinetic parameters, the adsorption mechanism, and the maximum adsorption capacities. Additionally, the present review addresses AER's regeneration and practical stability. It emphasizes the progress and proposes future strategies for addressing nitrate pollution using AER to overcome the challenges. This review aims to act as a reference for researchers working in the advancement of ion exchange resins and presents a clear and concise scientific analysis of the use of AER in nitrate adsorption. It is evident from the literature survey that AER is highly effective at removing nitrate ions from wastewater effluents.

Impact of Nitrogen Fertilization on Soil Nitrate Concentrations in an Onion Field in the Saiss Basin

High nitrogen (N) fertilizer rates can result in excessive nitrate (NO3-N) in soils and groundwater. The Saiss basin is an agricultural area in Morocco, where substantial increases in nonpoint source pollution from excessive N fertilization is commonly observed. The purpose of this study was to determine the short-term effect of N fertilizer application rates on soil NO3-N and soil water contents (SWC) in an onion (Allium cepa L.) field over two consecutive years (2021 and 2022). The field experiment was conducted in a randomized complete block design. Six N rates, namely 0, 90, 135, 180, 225, and 270 Kg N/ha were considered in drip-irrigated onion crops. Soil samples were collected from five consecutive soil layers, namely 0-20, 20-40, 40-60, 60-80, and 80-100 cm, and analyzed for NO3-N contents and SWC. SWC were lower before irrigation and increased significantly after irrigation for both seasons. There was no significant effect of N rates on SWC. Soil NO3-N decreased significantly with time. In the first season, lowest NO3-N levels was observed after harvest for all N rates. Visually, a marked accumulation of nitrate in soil was observed in the three highest N rates after harvest. Statistically, N rates did not show significant effect on soil NO3-N (p>0,05) in 2021 and 2022. This finding may be explained by the predominance of the denitrification process at Douyet station.

Nitrate Source and Transformation in Groundwater under Urban and Agricultural Arid Environment in the Southeastern Nile Delta, Egypt

With the intensification of human activities, nitrate pollutants in groundwater are receiving increasing attention worldwide. Especially in the arid Nile Delta of Egypt, groundwater is one of the most valuable water resources in the region. Identifying the source of nitrate in groundwater with strong human disturbances is important to effective water resource management. This paper examined the stable isotopes (δ15N/δ18O-NO3 and δ2H/δ18O-H2O) and the hydrogeochemical parameters of the shallow groundwaters in the arid southeast of the Nile Delta to assess the potential sources and transformation processes of nitrate under severe urban and agricultural activities. The results revealed that the groundwaters were recharged by the Nile River. Meanwhile, the infiltration of irrigation water occurred in the west, while the mixing with the deep groundwater occurred in the east regions of the study area. The TDS, SO42−, NO3−, and Mn2+ concentrations of groundwaters (n = 55) exceeded the WHO permissible limit with 34.6%, 23.6%, 23.6%, and 65.5%, respectively. The NO3− concentrations in the shallow groundwaters ranged from 0.42 mg/L to 652 mg/L, and the higher levels were observed in the middle region of the study area where the unconfined condition prevailed. It extended to the deep groundwater and eastward of the study area in the groundwater flow direction. The δ15N-NO3 and δ18O-NO3 values suggested that the groundwater NO3− in the west and east regions of semi-confined condition were largely from the nitrification of soil organic nitrogen (SON) and chemical fertilizer (CF). In contrast, wastewater input (e.g., domestic sewage and unlined drains) and prevalent denitrification were identified in the middle region. The denitrification might be tightly coupled with the biogeochemical cycling of manganese. This study provides the first report on the groundwater NO3− dynamics in the Nile Delta, which generated valuable clues for effective water resource management in the arid region.

Mechanism of denitrification in subsurface-dammed Ryukyu limestone aquifer, southern Okinawa Island, Japan

Denitrification crucially regulates the attenuation of groundwater nitrate and is unlikely to occur in a fast-flowing aquifer such as the Ryukyu limestone aquifer in southern Okinawa Island, Japan. However, evidences of denitrification have been observed in several wells within this region. This study analyzed environmental isotopes (δ15NNO3 and ẟ18ONO3) to derive the rationale for denitrification at this site. Additionally, the presence of two subsurface dams in the study area may influence the processes involved in nitrate attenuation. Herein, we analyzed 150 groundwater samples collected spatially and seasonally to characterize the variations in the groundwater chemistry and stable isotopes during denitrification. The values of δ15NNO3 and δ18ONO3 displayed a progressive trend up to +59.7 ‰ and + 21 ‰, respectively, whereas the concentrations of NO3−–N decreased to 0.1 mg L−1. In several wells, the enrichment factors of δ15NNO3 ranged from −6.6 to −2.1, indicating rapid denitrification, and the δ15NNO3 to δ18ONO3 ratios varied from 1.3:1 to 2:1, confirming the occurrence of denitrification. Denitrification intensively proceeds under conditions of depleted dissolved oxygen concentrations (<2 mg L−1), sluggish groundwater flow with longer residence times, high concentrations of dissolved organic carbon (>1.2 mg L−1), and low groundwater levels during the dry season with precipitation rates of <100 mm per month (Jun–Sep). SF6 analysis indicated the exclusive occurrence of denitrification in specific wells with groundwater residence times exceeding 30 years. These wells are located in close proximity to the major NE–SW fault system in the Komesu area, where the hydraulic gradient was below 0.005. Detailed geological and lithological investigations based on borehole data revealed that subsurface dams did not cause denitrification while the major NE–SW fault system uplifted the impermeable basement rock of the Shimajiri Group, creating a lithological gap at an equivalent depth that ultimately formed a sluggish groundwater area, promoting denitrification.

Sampling methods may drive short-term groundwater nitrate variability in an irrigated watershed connected to a coastal lagoon (Campo de Cartagena-Mar Menor, SE Spain)

This study highlights concerns regarding the reliability of groundwater nitrate data used in official surveys, such as within the EU-mandated Water Framework Directive (WFD). The focus is on the Campo de Cartagena - Mar Menor hydrosystem in Spain, a region known for its intensively irrigated watershed and eutrophicated lagoon, where monitoring the evolution of nitrate contamination in surface and groundwater is crucial but challenging due to the risk of inconsistent characterization leading to erratic remediation measures. The study employed an experimental approach in private wells that belong to a longstanding official nitrate survey network marked by irregular sampling practices. Importantly, these wells lacked comprehensive design documentation and were frequently used by farmers. The study aimed to evaluate the representativity of dissolved nitrate measurements in such an emblematic case, while investigating the source of the water using geochemical and isotope tracers. This assessment considered the effects of different sampling techniques (bailer or pumping) and sampling parameters (depth and time), acknowledging actual practices. The research highlights several key findings. Firstly, the bailer sampling method proved to account for a substantial portion of the observed variation in nitrate content. Secondly, in some cases, pumping introduced contributions from different water horizons, complicating the interpretation of nitrate data. Thirdly, alterations in the sampling protocol had a notable impact on the resulting nitrate measurements. Furthermore, the study emphasized a critical issue: the lack of analytical uncertainty estimation in official surveys introduces significant bias in result interpretation, with discrepancies exceeding 100 mg/L in four of the six wells analyzed. This underscores the pressing need for improved sampling protocols, dedicated borehole infrastructure and precise data interpretation. Given the potential unreliability of some official groundwater nitrate data shared under EU or other regulations, with corresponding economic and environmental impacts, the study recommends meticulous verification before transmitting data.

Development of machine-learning-based models for identifying the sources of nitrate and fluoride in groundwater and predicting their human health risks

AbstractThis research aimed to identify the main sources of groundwater pollution and assess the non-carcinogenic human health risk resulting from nitrate and fluoride contamination. These goals were achieved by employing unsupervised and supervised machine algorithms, including principal component analysis (PCA) and multilayer perceptron artificial neural networks (MLP-ANN). Thirty-seven groundwater samples were analyzed for twelve physical and chemical parameters, including pH, EC, TDS, TH, Cl, F, SO4, NO3, Ca, Mg, Na, and HCO3, and the initial investigation indicated that except for Cl, F, Ca, and Mg, all the parameters are above the guidelines of the World Health Organization (WHO). PCA indicated that mineral dissolution is the main source of F, while high NO3 concentration primarily resulted from agricultural operation due to extensive use of nitrogen and calcium-based fertilizers. Consequently, the non-carcinogenic human health risk (HHR) for children and adults is evaluated based on NO3 and F. The conventional approach for assessing HHR is time-consuming and often associated with errors in calculating hazard quotients (HQ) and hazard indices (HI). In this research, MLP-ANN is suggested to overcome these limitations. In the MLP-ANN modeling, the data were divided into two parts training (80%) and validation (20%), with NO3 and F concentration as inputs and HQ and HI as outputs. The performance of the resulting models was tested using root mean square error (RMSE) and coefficient of determination (R2). The model provided a satisfactory result with a maximum RMSE of 4% and R2 higher than 97% for training and validation. As a result, obtained HIs suggested that 97.3% of the groundwater samples in the study area are suitable for human consumption. The non-carcinogenic HHR is successfully assessed using machine learning algorithms, and the results have led to the conclusion that this approach is highly recommended for effectively managing groundwater resources.

Pengukuran Anion Anorganik Secara Simultan dalam Sampel Air Tanah dan Air Ledeng Menggunakan Kromatografi Ion

Ion chromatography is an advanced and highly sensitive form of ion exchange chromatography that can effectively detect ion species, whether organic or inorganic ions. This research study utilized ion chromatography with a suppressed conductivity detection system to separate and measure the concentration of fluoride, chloride, nitrite, bromide, nitrate, phosphate, and sulfate ions in groundwater and tap water samples. The eluent solution used in this separation contained 6.0 mmol/L Na2CO3 and 0.25 mmol/L NaHCO3, which was crucial in ensuring the accuracy and selectivity of the detections. The samples were collected in 3 sub-districts in Ternate City, and the study's findings shed light on the water quality in the area.

Spatial variability of nitrate leaching and risk assessment of nitrate contamination in the Ghiss-Nekor alluvial aquifer system (Northeastern Morocco) through Disjunctive Kriging

In this study, groundwater nitrate monitoring data from water supply and water management organizations were processed in a GIS environment to evaluate spatial patterns of nitrate occurrence and explore its correlation with the corresponding land uses in Ghiss-Nekor alluvial groundwater (northeastern Morocco). Land-use/Land Cover within the Ghiss-Nekor plain incorporated rangeland, built area, crop fields, water bodies, dense vegetation, and bare ground categories, encompassing respectively about 39.06 %, 36.69 %, 17.57 %, 4.63 %, 1.24 %, and 0.81 % of the total area. According to the World Health Organization (WHO), the selected thresholds are an acceptable concentration of nitrate for potable water (50 mg/L) and a human affected value (13 mg/L). Simple Kriging and Disjunctive Kriging (D.K.) geostatistical methods were compared with a deterministic interpolation method (GPI) to identify the convenient approach to predict nitrate concentrations at unsampled sites. D.K. provided more accurate predictive performance and highlighted that nitrate contamination is higher in wells in the southern half of the study area, where nitrate concentrations exceeded 50 mg/L in 29.2 % (33,3 km²) of the study area. Areas occupying 21.28 % of the total surface, with nitrate contents exceeding the human-affected value, are located near small industrial sites, residential septic tanks, and agricultural areas. No significant correlation was found between the nitrate concentrations and the depth of the wells. The probability of nitrate content exceeding the thresholds of 13 and 50 mg/L is respectively less than 0.5 in 61.35 % (69.94 km²) and 77.63 % (88.4 km²) of the total study area, whereas the maximum likelihood of nitrate contamination is found along uncontrolled urban discharges located within highly permeable deposits. The assessment also demonstrated that areas showing high predicted probabilities of nitrate contamination diminish with increasing threshold value. The present study shed light on the necessity of depicting the extent of polluted areas, particularly in vulnerable alluvial aquifers, where exposure to higher levels of drinking water contaminants threatens human health.

Assessing Groundwater Quality and Diagnosing Nitrate Pollution in the Sidi Allal Region: A GIS-Based Approach Utilizing the Groundwater Pollution Index

Groundwater is a critical resource for various human activities, yet it faces contamination risks from agricultural, industrial, and domestic sources. This study aimed to evaluate groundwater in Morocco’s Sidi Allal region using the groundwater pollution index (GPI) and diagnose nitrate pollution. The study included 45 groundwater wells from the study area, and physicochemical parameters such as pH, electrical conductivity, cations, and anions were examined in the laboratory. The geographic information system (GIS) was used to determine the spatial distribution of groundwater quality parameters. The groundwater pollution index and nitrate pollution index (NPI) were determined. The inverse distance weighting method (IDW) was used to create a spatial distribution map. The results indicated that the calculated GPI values ranged from 0.856 to 7.416, with an average of 2.06. About 40% of groundwater samples were highly polluted and unsuitable for drinking. The NPI values ranged between −0.74 and 10.5, with an average of 5.1. About 64% of the total groundwater samples were considered highly polluted according to the NPI classification, suggesting that the groundwater was unsuitable for drinking purposes. The spatial distribution map revealed the availability of appropriate groundwater in the central area of the study area and inappropriate groundwater near the Esbou River and Nassour Canal. The findings of this study revealed high concentrations of nitrates in groundwater samples in the central part of the study area, indicating that this increase in nitrates may be due to intensive use of nitrogen fertilizers in agricultural activities and sewage waste.

Identification of surface water - groundwater nitrate governing factors in Jianghuai hilly area based on coupled SWAT-MODFLOW-RT3D modeling approach

A comprehensive understanding of the key controlling factors on NO3-N spatiotemporal distribution in surface and groundwater is of great significance to nitrogen pollution control and water resources management in watershed. Hence, the coupled SWAT-MODFLOW-RT3D model was employed to simulate nitrate (NO3−) fate and transport in Huashan watershed system. The model was calibrated using a combination of stream discharge, groundwater levels, NO3-N in-stream loading and groundwater NO3-N concentrations. The simulation revealed the significant spatiotemporal variations in surface water-groundwater nitrate interactions. The annual average percolation of NO3− from rivers to groundwater was 171.5 kg/km2 and the annual average discharge NO3− content from groundwater into rivers was 451.9 kg/km2 over the simulation period. The highest percolation of NO3− from rivers to groundwater occurred in April and the highest discharge NO3− content from groundwater into rivers occurred in July. Grassland and agriculture land contributed more nitrate contents in river water and groundwater compared to bare land and forest in the study area and the water exchange was the primary driving force for nitrate interactions in the surface water-groundwater system. Sensitivity analysis indicated that river runoff and groundwater levels were most influenced by the SCS runoff curve number f (CN2) and aquifer hydraulic conductivity (K), which, in turn, significantly affected nitrate transport. Regarding water quality parameters, the denitrification exponential rate coefficient (CDN) had the most pronounced impact on NO3-N in-stream loading and groundwater NO3-N concentrations. This study underscores the central role of surface-groundwater (SW-GW) interactions in watershed-scale nitrate research and suggests that parameters with higher sensitivity should be prioritized in analogous watershed modeling.

Transport of nitrate-containing groundwater to coastal areas through buried tunnel valleys, Denmark

Nitrogen impact on the aquatic environment, including coastal areas, is too high in many countries worldwide, particularly in areas with intensive agriculture. Efficient mitigation initiatives demand that important pathways and the fate of nitrate in the hydrological cycle are known. In this study, we focus on groundwater nitrate contamination in two near-shore catchment areas in north-west Denmark. Groundwater in the area is mainly located in buried tunnel valleys, which are subsurface structures eroded by meltwater during Pleistocene glaciations in former glaciated areas. Groundwater samples from the aquifers inside the buried valleys reveal the presence of up to 120 mg/l nitrate down to 10 m below sea level and about 1 km down from the stream outlet towards the coast. We interpret the complex tunnel-valley infill to be responsible for the spatial heterogeneity of the groundwater geochemistry, where sandy geological windows create localised hydraulic pathways and complex redox structures. Groundwater and stream water chemistry in the study area clearly demonstrate the role of groundwater in nitrate transport within the catchment as well as the direct pathway to the coast bypassing the stream and riverine systems. Our results show that the buried tunnel valleys potentially contribute to submarine groundwater discharge and therefore could be responsible for a hitherto unaccounted input of nitrogen to the marine environment.

A machine learning-based approach to predict groundwater nitrate susceptibility using field measurements and hydrogeological variables in the Nonsan Stream Watershed, South Korea

Identifying and predicting the nitrate inflow and distribution characteristics of groundwater is critical for groundwater contamination control and management in rural mixed-land-use areas. Several groundwater nitrate prediction models have been developed; in particular, a nitrate concentration model that uses dissolved ions in groundwater as an input variable can produce accurate results. However, obtaining sufficient chemical data from a target area remains challenging. We tested whether machine learning models can effectively determine nitrate contamination using field-measured data (pH, electrical conductivity, water temperature, dissolved oxygen, and redox potential) and existing geographic information system (GIS) data (lithology, land cover, and hydrogeological properties) from the Nonsan Stream Watershed in South Korea, an area where nitrate contamination occurs owing to intensive agricultural activities. In total, 183 groundwater samples from different wells, mixed municipal sites, and agricultural activities were used. The results indicated that among the four machine learning models (artificial neural network (ANN), classification and regression tree (CART), random forest (RF), and support vector machine (SVM)), the RF (R2: 0.74; RMSE: 3.5) and SVM (R2: 0.80; RMSE: 2.8) achieved the highest prediction accuracy and smallest error in all groundwater parameter estimates. Land cover, aquifer type, and soil drainage were the primary RF and SVM model input variables, representing agricultural activity-related and hydrogeological infiltration effects. Our research found that in rural areas with limited hydro-chemical data, RF and SVM models could be used to identify areas at high risk of nitrate contamination using spatial variability, GIS-aided visualization, and easily accessible field-measured groundwater quality data.

Groundwater Nitrate Contamination in Arid Areas of Haidong

Groundwater Nitrate Contamination in Arid Areas of Haidong