Nitrate migration and transformations in groundwater quantified by dual nitrate isotopes and hydrochemistry in a karst World Heritage site

Characterizing the impact of reservoir storage and discharge on nitrogen dynamics in an upstream wetland using a δ15N and δ18O dual-isotope approach

The identification of nitrate sources in reservoir water is important for watershed-scale surface pollution management. Significant fluctuations in river water levels arising from reservoir storage and discharge influence nitrate sources and transport processes. The Sanmenxia Reservoir, in the middle reaches of the Yellow River in China, undergoes significant water level changes (290-316 m), altering the composition of the nitrogen sources. This study employed a δ15N and δ18O dual-isotope method and MixSIAR modeling to quantify the contributions of nitrate sources. This reveals the impact of reservoir water impoundment and discharge on nitrogen dynamics in the upstream region of the wetland and the model sensitivity for each nitrate source. The results showed that the average concentrations of nitrate‑nitrogen (NO- 3-N) were elevated during the impoundment period compared to the discharge period. Nitrogen sources exhibited varying proportions in surface water, groundwater, and soil water during both the impoundment and discharge periods. The predominant sources include manure and sewage (MS), with a maximum proportion of 57.4 % in surface water. Soil nitrogen (SN) accounted for 25.8 % of groundwater nitrogen and 32.1 % of soil water nitrogen during the impoundment period, whereas, during the discharge period, soil nitrogen made up 41.4 % of surface water nitrogen, manure and sewage contributed 44.8 % of groundwater nitrogen, and manure and sewage dominated with 56.7 % of soil water nitrogen. Sensitivity analysis of the MixSIAR model revealed that the isotopic composition of the manure and sewage primary source most significantly influenced the apportionment results of the riverine nitrate source. Reservoir discharge facilitates the dissimilatory nitrate reduction to ammonium (DNRA). The migration of NO- 3 from surface water to soil water and groundwater occurred from the impoundment period to the discharge period.

Revealing the drivers and genesis of NO3-N pollution classification in shallow groundwater of the Shaying River Basin by explainable machine learning and pathway analysis method

Nitrate (NO3-N), as one of the ubiquitous contaminants in groundwater worldwide, has posed a serious threat to public health and the ecological environment. Despite extensive research on its genesis, little is known about the differences in the genesis of NO3-N pollution across different concentrations. Herein, a study of NO3-N pollution concentration classification was conducted using the Shaying River Basin as a typical area, followed by examining the genesis differences across different pollution classifications. Results demonstrated that three classifications (0-9.98 mg/L, 10.14-27.44 mg/L, and 28.34-136.30 mg/L) were effectively identified for NO3-N pollution using Jenks natural breaks method. Random forest exhibited superior performance in describing NO3-N pollution and was thereby affirmed as the optimal explanatory method. With this method coupling SEMs, the genesis of different NO3-N pollution classifications was proven to be significantly different. Specifically, strongly reducing conditions represented by Mn2+, Eh, and NO2-N played a dominant role in causing residual NO3-N at low levels. Manure and sewage (represented by Cl-) leaching into groundwater through precipitation is mainly responsible for NO3-N in the 10-30 mg/L classification, with a cumulative contribution rate exceeding 80 %. NO3-N concentrations >30 mg/L are primarily caused by the anthropogenic loads stemming from manure, sewage, and agricultural fertilization (represented by Cl- and K+) infiltrating under precipitation in vulnerable hydrogeological conditions. Pathway analysis based on standardized effect and significance further confirmed the rationality and reliability of the above results. The findings will provide more accurate information for policymakers in groundwater resource management to implement effective strategies to mitigate NO3-N pollution.

Basin-wide tracking of nitrate cycling in Yangtze River through dual isotope and machine learning

The nitrate (NO3-) input has adversely affected the water quality and ecological function in the whole basin of the Yangtze River. The protection of water sources and implementation of "great protection of Yangtze River" policy require large-scale information on water contamination. In this study, dual isotope and Bayesian mixing model were used to research the transformation and sources of nitrate. Chemical fertilizers contribute 76 % of the nitrate sources in the upstream, while chemical fertilizers were also dominant in the midstream (39 %) and downstream (39 %) of Yangtze River. In addition, nitrification process occurred in the whole basin. Four machine learning models were used to relate nitrate concentrations to explanatory variables describing influence factors to predict nitrate concentrations in the whole basin of Yangtze River. The anthropogenic and natural factors, such as rainfall, GDP and population were chosen to take as predictor variables. The eXtreme Gradient Boosting (XGBoost) model for nitrate has a better predictive performance with an R2 of 0.74. The predictive models of nitrate concentrations will help identify the nitrate distribution and transport in the whole Yangtze River basin. Overall, this study represents the first basin-wide data-driven assessment of the nitrate cycling in the Yangtze River basin.

Unveiling the dynamic of nitrogen through migration and transformation patterns in the groundwater level fluctuation zone of a different hyporheic zone sediment

This study investigates the impact of water levels and soil texture on the migration and transformation of nitrate (NO3--N) and ammonium (NH4+-N) within a soil column. The concentrations of NO3--N gradually decreased from an initial concentration of 34.19 ± 0.86 mg/L to 14.33 ± 0.77 mg/L on day 70, exhibiting fluctuations and migration influenced by water levels and soil texture. Higher water levels were associated with decreased NO3--N concentrations, while lower water levels resulted in increased concentrations. The retention and absorption capacity for NO3--N were highest in fine sand soil, followed by medium sand and coarse sand, highlighting the significance of soil texture in nitrate movement and retention. The analysis of variance (ANOVA) confirmed statistically significant variations in pH, dissolve oxygen and oxidation-reduction potential across the soil columns (p < 0.05). Fluctuating water levels influenced the migration and transformation of NO3--N, with distinct patterns observed in different soil textures. Water level fluctuations also impacted the migration and transformation of NH4+-N, with higher water levels associated with increased concentrations and lower water levels resulting in decreased concentrations. Among the soil types considered, medium sand exhibited the highest absorption capacity for NH4+-N. These findings underscore the significant roles of water levels, soil texture, and soil type in the migration, transformation, and absorption of nitrogen compounds within soil columns. The results contribute to a better understanding of nitrogen dynamics under varying water levels and environmental conditions, providing valuable insights into the patterns of nitrogen migration and transformation in small-scale soil column experiments.

Dissolved inorganic carbon budget of two alpine catchments in the central Tibetan Plateau: Glaciation matters

Dissolved inorganic carbon (DIC) fluxes account for over one-third of the total carbon transported in most rivers. The DIC budget for glacial meltwater of the Tibetan Plateau (TP), however, is still poorly understood, despite the fact, the TP has the largest glacier distribution outside of the Poles. In this study, the Niyaqu and Qugaqie catchments in the central TP were selected to examine the influence of glaciation on the DIC budget in vertical evasion (CO2 exchange rate at the water-air interface) and lateral transport (sources and fluxes) from 2016 to 2018. Significant seasonal variation in DIC concentration was found in the glaciated Qugaqie catchment, but was absent in the not glaciated Niyaqu catchment. δ13CDIC showed seasonal changes for both catchments, with more depleted signatures during the monsoon season. The average CO2 exchange rates in river water of Qugaqie were ~8 times lower compared to Niyaqu with values of -1294.6 ± 438.58 mg/m2/h and -163.4 ± 581.2 mg/m2/h, respectively, indicating that proglacial rivers can act as a substantial CO2 sink due to CO2 consumption by chemical weathering. DIC sources were quantified via the MixSIAR model using δ13CDIC and ionic ratios. During the monsoon season, the contribution from carbonate/silicate weathering driven by atmospheric CO2 was 13-15 % lower, while biogenic CO2 involved in chemical weathering was 9-15 % higher, indicating a seasonal control on weathering agents. Carbonate dissolution driven by H2SO4/HNO3 was the most important contributor to DIC in both catchments (40.7 ± 2.2 % in Niyaqu and 48.5 ± 3.1 % in Qugaqie). The net CO2 consumption rate in the not glaciated Niyaqu catchment was close to 0 (-0.07 ± 0.04 × 105 mol/km2/y), indicating the carbon sink effect caused by chemical weathering in this area was weak. The net CO2 consumption rate in the glaciated Qugaqie catchment, however, was much lower than that in the not glaciated catchment with a value of -0.28 ± 0.05 × 105 mol/km2/y. This study highlights that chemical weathering in small glaciated catchments of the central TP plays an active role in releasing CO2 to the atmosphere.

EMMTE: An Excel VBA tool for source apportionment of nitrate based on the stable isotope mixing model

Dual nitrate stable isotopes combined with end-member mixing models are typically used to identify nitrate sources in fields of geochemistry and environmental science, which helps to quantitively depict the geochemical behaviors of nitrate and accurately control the sources of nitrate pollution in waters. Recently, various models with different computation principles, working efficiency, and operation difficulty have been developed and applied in the source apportionment of nitrate. In this paper, an end-member mixing model tool on Excel™, namely EMMTE, has been written with Visual Basic for Application (VBA) and built into a macro-enabled Excel™ spreadsheet. Monte Carlo simulation and constraint relative deviation between the observed and the predicted values were included in the working algorithm to solve the mass balance equation. After comparison with the internationally recognized Bayesian framework (mixing stable isotope analysis in R, MixSIAR) in different cases (three practical cases and one virtual case), the preliminary results showed that the contribution of various sources to groundwater nitrate calculated by EMMTE was highly consistent with that by MixSIAR and the performance of EMMTE seemed to be as good as that of MixSIAR as indicated by the higher goodness-of-prediction, lower root-mean-square error, and lower relative deviation. Therefore, EMMTE is applicable in the source apportionment of groundwater nitrate, and might also be extended to other water bodies and mixtures. It provides a simple, feasible, and user-friendly for front-line workers without experience with MixSIAR to quantitively source apportionment of nitrate in waters.

Novel insights into source apportionment of dissolved organic matter in aquifer affected by anthropogenic groundwater recharge: Applicability of end-member mixing analysis based optical indices

The composition and main sources of dissolved organic matter (DOM) in groundwater may change significantly under long-term anthropogenic groundwater recharge (AGR); however, the impact of AGR on quantitative sources of groundwater DOM has seldom been reported. This study evaluated the applicability of optical indices combined with mixing stable isotope analysis in R (MixSIAR) in end-member mixing analysis (EMMA) of groundwater DOM. Fluorescent indices, including C1%, C2%, and C3%, were more sensitive to AGR than other absorbance indices, as indicated by the significant difference between the dominant area of artificial groundwater recharged by surface water and the dominant area of natural groundwater recharged by atmospheric precipitation (NGRP). BIX-C1% was selected as the optimal dual index after the screening protocol of groundwater DOM for EMMA. Our results showed that DOM in the aquifer was mainly subject to autochthonous DOM and the contribution of background groundwater to AGRSW and NGRP groundwater accounted for 36.15% ± 32.41% and 55.46% ± 37.17% (p < 0.05), respectively. Therefore, AGR significantly changed the native DOM in the groundwater. In allochthonous sources of DOM, sewage and surface water contributed 29.54% ± 24.87% and 21.32% ± 28.08%, and 24.79% ± 15.56% and 15.21% ± 14.20% to AGRSW and NGRP groundwater, respectively. The contribution of surface water to AGRSW groundwater was significantly higher than that to NGRP groundwater (p < 0.05), indicating that AGR introduced significantly more DOM from surface water to groundwater. This study provides novel insights into the quantitative source apportionment of DOM in groundwater under long-term AGR, which will facilitate the environmental risk assessment of present AGR measures and the sustainable management of clean water.

Source availability and hydrological connectivity determined nitrate-discharge relationships during rainfall events in karst catchment as revealed by high-frequency nitrate sensing

Karst terrain seasonal monsoonal rainfall is often associated with high concentrations of nitrate-N in streams draining agricultural land. Such high concentrations can pose problems for environmental and human health. However, the relationship between rainfall events that mobilize nitrate and resulting nitrate export remains poorly understood in karst terrain. To better understand the processes that drive nitrate dynamics during rainfall events, the characteristics of individual rainfall events were analyzed using sensor technology. Thirty-eight rainfall events were separated from the high-frequency dataset spanning 19 months at a karst spring site. The results revealed that nitrate-discharge (N-Q) hysteresis in 79% of rainfall events showed anticlockwise hysteresis loop patterns, indicating nitrate export from long distances within short event periods. Karstic hydrological connectivity and source availability were considered two major determining factors of N-Q hysteresis. Gradual increase in hydrological connectivity during intensive rainfall period accelerated nitrate transportation by karst aquifer systems. Four principal components (PCs, including antecedent conditions PC1&3 and rainfall characteristics PC2&4 explained 82% of the cumulative variance contribution to the rainfall events. Multiple linear regression of four PCs explained more than 50% of the variation of nitrate loading and amplitude during rainfall events, but poorly described nitrate concentrations and hydro-chemistry parameters, which may be influenced by other factors, e.g., nitrate transformation, fertilization time and water-rock interaction. Although variation of N concentration during event flow is evident, accounting for antecedent conditions and rainfall factors can help to predict rainfall event N loading during rainfall events. Pollution of the karstic catchment occurred by a flush of nitrate input following rainfall events; antecedent and rainfall conditions are therefore important factors to consider for the water quality management. Reducing source availability during the wet season may facilitate to reduction of nitrogen loading in similar karst areas.

Seasonal variations of microbial community structure, assembly processes, and influencing factors in karst river

The physicochemical properties and microbial communities have significant annual and seasonal changes in karst aquifers. To explore the changes of microbial community and their relationships with environmental factors, water samples were collected from a typical karst river. Microbial communities in winter (Jan-2017 and Jan-2019) were stable with high similarity in spite of the 2 years sampling interval, but the microbial communities in Aug-2017 was different from that in Aug-2018. In four sampling times, there were 275 shared genera, whose average relative abundance ranging from 89.04 to 96.27%. The winter and summer specific genera were mainly from the recharge of tributary site K6 and discharge of waste water treatment plant (K2 and K3), respectively. The deterministic processes had a more significant effect on the microbial community assembly in winter than that in summer, which was affected by environmental pressure from pollution. Furthermore, antibiotics and inorganic nitrogen pollution affected element cycles of nitrogen and sulfur indirectly through microbial ecological modules in karst river, and the denitrification and desulfurization processes were potentially inhibited. These findings contributed to understand the changes and its assembly mechanism of microbial community, as well as the feedback to environment in polluted karst river.

Impacts of anthropogenic groundwater recharge (AGR) on nitrate dynamics in a phreatic aquifer revealed by hydrochemical and isotopic technologies

Although anthropogenic groundwater recharge (AGR) can either elevate or decline the concentration of nitrate in the phreatic aquifer with high hydraulic conductivity, the long-term impact of AGR on nitrate dynamics in the phreatic aquifer and its reason is seldom disclosed. In this study, the hydrogen and oxygen stable isotopes (δ²H-H₂O and δ¹⁸O-H₂O) combined with mixing stable isotope analysis in R (MixSIAR) were used to group the study area into the dominant area of AGR by surface water (AGRSW) and the dominant area of natural groundwater recharged by precipitation (NGRP). Hydrochemical parameters and multiple stable isotopes, including δ²H-H₂O, δ¹⁸O-H₂O, δ¹⁵N-NO₃^-, δ¹⁸O-NO₃^-, and δ¹³C-DIC, were applied to explore the impacts of AGR on the concentration, biogeochemical processes, and main sources of nitrate. The results showed that AGR by surface water with low nitrate content can reduce nitrate pollution in groundwater. The characteristic of δ¹⁸O-NO₃^- value revealed that nitrification was the primary biogeochemical process of nitrogen in groundwater. AGR may enhance nitrification as indicated by the δ¹⁸O-NO₃^- value closer to the nitrification theoretical line. Dual nitrate stable isotopes and MixSIAR revealed that chemical fertilizer (CF), soil nitrogen (SN), and surface water (SW) contributed 10.88%, 49.92%, and 27.64% to nitrate in AGRSW groundwater, respectively, which was significantly different from their contributions to NGRP groundwater (p < 0.05). Notably, AGR significantly increased the contribution of SW but decreased the contribution of CF and SN in groundwater. This study provided a basis and guidance for groundwater quality assessment and pollution control in the phreatic aquifer with high hydraulic conductivity.

Effect of rainfall-runoff process on sources and transformations of nitrate using a combined approach of dual isotopes, hydrochemical and Bayesian model in the Dagang River basin

The control of agricultural nitrogen through inflow rivers is crucial for lake aquatic environment conservation, while nitrate is the main form of non-point source pollution of agricultural nitrogen in watersheds. Therefore, understanding the nitrate sources and transformation in the intensive-agricultural region was particularly concerned. Nitrate sources and transformation varied largely during some crucial periods or events. However, low-resolution sampling campaigns increased some uncertainties due to without considering the effect of key driving factors for identifying nitrate transformations and sources. In our study, high-frequency sampling and analysis of nitrogen and oxygen isotope, hydrochemical and Bayesian model was conducted at the Dagang River to capture nitrate sources and transformations and identify its response to rainfall-runoff process at the event scale. In addition, the N cycle process was refined by comparing the variation and relationship of water quality factors and isotopes before, during, and after rainfall. We found that nitrate and major ions derived from similar agricultural activities caused by anthropogenic factors, such as domestic sewage from rural residents and livestock waste, through field survey and principal component analysis. The δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- in Dagang River ranged from +0.05‰ to +9.94‰ and + 1.49‰ to +11.64‰, respectively. The spatio-temporal variations of nitrate isotopes and hydrochemical compositions of river water suggested that nitrification was the dominant nitrate transformation process although the mixing effect occurred in some periods, especially during, and after the rainfall. The relationship between NO₃^-/Cl^- and Cl^- ratios suggested the occurrence of denitrification in downstream of the river basin after the rainfall. The results of Bayesian model showed that livestock manure and groundwater contributed to the most (66.4 ± 31.9%) nitrate, which indicated the necessity to establish its regulatory policy to avoid the overuse of livestock manure and groundwater in Dagang River. This study benefit for developing concrete and legible management and conservation strategies for decreasing the effect of anthropogenic nitrogen loading on lake eutrophication.

Recent advances in the source identification and remediation techniques of nitrate contaminated groundwater: A review

Researchers have long been committed to identify nitrate sources in groundwater and to develop an advanced technique for its remediation because better apply remediation solution and management of water quality is highly dependent on the identification of the NO₃^- sources contamination in water. In this review, we systematically introduce nitrate source tracking tools used over the past ten years including dual isotope and multi isotope techniques, water chemistry profile, Bayesian mixing model, microbial tracers and land use/cover data. These techniques can be combined and exploited to track the source of NO₃^- as mineral or organic fertilizer, sewage, or atmospheric deposition. These available data have significant implications for making an appropriate measures and decisions by water managers. A continuous remediation strategy of groundwater was among the main management strategies that need to be applied in the contaminated area. Nitrate removal from groundwater can be accomplished using either separation or reduction based process. The application of these processes to nitrate removal is discussed in this review and some novel methods were presented for the first time. Moreover, the advantages and limitations of each approach are critically summarized and based on our own understanding of the subject some solutions to overcomes their drawbacks are recommended. Advanced techniques are capable to attain significantly higher nitrate and other co-contaminants removal from groundwater. However, the challenges of by-products generation and high energy consumption need to be addressed in implementing these technologies for groundwater remediation for potable use.

Source identification and apportionment of the nitrogen in groundwater based on isotope methods in the Beilin region of Suihua basin, northeastern China

Multi-isotope method was used to analyze the migration and transformation characteristics of nitrogen in groundwater in the center of a typical confined water basin, and a simplified isotope mixing model was established to quantify the contribution of potential nitrate sources in the center of the basin. Based on the water quality monitoring results, the contour map of nitrate concentration in groundwater in the center of the basin was drawn. The results showed that the nitrate concentration in groundwater in the center of the basin increased gradually from upstream to downstream. The high value area of nitrate concentration in phreatic water is mainly affected by agricultural activities and infiltration of sewage discharge from upstream urban areas. The high value area of nitrate concentration in confined water is mainly due to the water level depression funnel caused by large exploitation of confined water. The quantitative results of N-O isotope mixing model for potential nitrate sources show that the main recharge sources of groundwater in the center of the basin are atmospheric precipitation, agricultural irrigation water, and the lateral inflow of upstream groundwater. Agricultural irrigation water has the highest contribution rate of 67.01%. The main recharge sources of confined aquifer in the center of the basin are phreatic water leakage and lateral inflow of upstream confined water. The contribution rate of upstream confined water is between 45.55% and 56.35%, which is basically maintained at about 50%. Compared with the calculation results of D-O isotope mixing model, the accuracy of the established N-O isotope mixing model meets the basic requirements. The results of this study can provide technical reference and theoretical support for the identification and quantitative research of potential nitrate sources in groundwater under the same type of hydrogeological conditions. PRACTITIONER POINTS: Multiple isotope fingerprint comparison to identify nitrate source contribution ratio. Migration and transformation of nitrogen in the center of a typical confined water basin Simplified the traditional isotope mixing model to quickly quantify the source of contamination.

Nitrate concentration analysis and prediction in a shallow aquifer in central-eastern Tunisia using artificial neural network and time series modelling

Agricultural activities have become a major source of groundwater nitrate contamination. In this context, this study aims to analyse nitrate concentrations in a shallow aquifer of Mahdia-Kssour Essef in central-eastern Tunisia, identify the assignable sources, and predict the future levels using artificial neural network (ANN) and autoregressive integrated moving average (ARIMA) models. The results showed that nitrate concentrations measured in 21 pumping wells across the plain ranged from 17 to 521 mg L^-1. A total of 67% of the monitoring points greatly exceed the standard guideline value of 50 mg L^-1. The main relevant anthropogenic and natural factors, such as soil texture, land use, fertilizers application rates, livestock waste disposal, and groundwater table, are positively correlated with groundwater nitrate concentration. The ANN model showed good fitting between measured and simulated results with coefficient of determination (R²), root-mean-square error (RMSE), and mean absolute error (MAE) values of 0.88, 53.95, and 39.64, respectively. The ARIMA applied on annual average nitrate concentrations from 1998 to 2017 revealed that the best fitted model (p, d, q) is (1, 2, 1). The R² value is approximately 0.36, and the Theil inequality coefficient and bias proportion values are small and close to zero. These results proved the ARIMA model's adequacy in forecasting annual average nitrate concentrations of 116 mg L^-1 in 2025. These findings may be useful in making groundwater management decisions, particularly in rural and semi-arid areas, and the proposed ARIMA model could be used as a managed tool to monitor and reduce the nitrate intrusion into groundwater.

New insight into the response and transport of nitrate in karst groundwater to rainfall events

Although numerous studies focused on nitrate source, transformation and transport of river water in karst area have been reported, it's still unclear in understanding nitrate main source and transformation in karst groundwater system and how nitrate transport from soil to water during rainfall events in karst critical zone. In order to explore the response and transport of nitrate in karst groundwater to rainfall events, different depths of well water before, during and after rainfall event were sampled, and hillslope runoff, surface runoff of different land-use types during rainfall event were sampled synchronously at a typical karst agricultural catchment in Southwest China. Results showed that fluctuations of EC, pH and DO in deep borehole well (W1) and artesian well (W2) were small, on the contrary, variations of EC and DO in shallow well (W3) were large during sampling period. The nitrate concentrations and isotopic values indicated that nitrate in karst groundwater mainly originated from chemical fertilizer (CF), and influenced by denitrification process. High intensity of denitrification was observed in deep groundwater (87%) and artesian well water (almost 100%). Extremely high dual nitrate isotope values up to 46.8 ± 1.5‰ and 24.7 ± 0.5‰ were found in the deep artesian well. The small variation of water chemistry (EC, DO and pH), nitrate concentration and dual nitrate isotope values in deep wells during sampling period suggested that newly supplied nitrogen in deep groundwater during rainfall events also comes from deep groundwater. Low nitrogen concentrations in hillslope subsurface flow and surface runoff suggests that nitrogen transport process leading to increase of water nitrogen content mainly occur in depression. Nitrogen in depression soil is mainly transported to groundwater through fissures, fractures and conduits, rather than through vertical migration processes in the soil during rainfall events.

Nitrate fate and decadal shift impacted by land use change in a rural karst basin as revealed by dual nitrate isotopes

Nitrate pollution in oxygenated karst aquifers is common due to nitrification and anthropogenic inputs. However, the shift of nitrogen sources influenced by enhanced rural tourism activities and land use changes are not well understood. In this study, hydrochemistry and dual nitrate isotopes of water samples from a rural karst basin in Chongqing, southwestern China were employed to investigate the nitrate fate and its decadal change during the periods from 2007-2008 and 2017-2019. The results showed that δ¹⁵N-NO₃ and δ¹⁸O-NO₃ values at the groundwater basin resurgence averaged 9 ± 3.4‰ and 2.5 ± 3.4‰, respectively, with a mean NO₃^- concentration of 19.7 ± 5.4 mg/L in 2017-2019, clearly exceeding natural background levels. The dual isotope results suggested that nitrification occurred at the sampled sites. From 2007-2008 to 2017-2019, the mean δ¹⁵N-NO₃ values from the primary sink point and the resurgence of the underground river water samples increased from -0.2 ± 2.1 to 11.2 ± 4.8‰, 4.2 ± 0.9 to 9.0 ± 3.4‰, respectively. A Bayesian mixing model in R (MixSIAR) based on the isotopes revealed that soil organic nitrogen, and manure and sewage proportions for the groundwater increased by 34% and 23%, respectively, while chemical fertilizer and atmospheric precipitation proportions decreased by 32% and 25%, respectively. These decadal changes resulted from reforestation practices and enhanced rural tourism activities in the basin, which were evidenced by the change of land use patterns. The elevated nitrogen load from the rapid development of rural tourism is likely to increase this contamination in the near future if the infrastructure cannot meet the demands. The results from this study could contribute to minimizing environmental health risks in drinking water when rural tourism activities are increasing.

Identification and apportionment of shallow groundwater nitrate pollution in Weining Plain, northwest China, using hydrochemical indices, nitrate stable isotopes, and the new Bayesian stable isotope mixing model (MixSIAR)

Groundwater nitrate (NO₃^-) pollution is a worldwide environmental problem. Therefore, identification and partitioning of its potential sources are of great importance for effective control of groundwater quality. The current study was carried out to identify the potential sources of groundwater NO₃^- pollution and determine their apportionment in different land use/land cover (LULC) types in a traditional agricultural area, Weining Plain, in Northwest China. Multiple hydrochemical indices, as well as dual NO₃^- isotopes (δ¹⁵N-NO₃ and δ¹⁸O-NO₃), were used to investigate the groundwater quality and its influencing factors. LULC patterns of the study area were first determined by interpreting remote sensing image data collected from the Sentinel-2 satellite, then the Bayesian stable isotope mixing model (MixSIAR) was used to estimate proportional contributions of the potential sources to groundwater NO₃^- concentrations. Groundwater quality in the study area was influenced by both natural and anthropogenic factors, with anthropological impact being more important. The results of LULC revealed that the irrigated land is the dominant LULC type in the plain, covering an area of 576.6 km² (57.18% of the total surface study area of the plain). On the other hand, the results of the NO₃^- isotopes suggested that manure and sewage (M&S), as well as soil nitrogen (SN), were the major contributors to groundwater NO₃^-. Moreover, the results obtained from the MixSIAR model showed that the mean proportional contributions of M&S to groundwater NO₃^- were 55.5, 43.4, 21.4, and 78.7% in the forest, irrigated, paddy, and urban lands, respectively. While SN showed mean proportional contributions of 29.9, 43.4, 61.5, and 12.7% in the forest, irrigated, paddy, and urban lands, respectively. The current study provides valuable information for local authorities to support sustainable groundwater management in the study region.

Research Advances in the Analysis of Nitrate Pollution Sources in a Freshwater Environment Using δ15N-NO3- and δ18O-NO3. Int J Environ Res Public Health 2021;18:ijerph182211805. [PMID: 34831560 PMCID: PMC8623930 DOI: 10.3390/ijerph182211805]

Nitrate is usually the main pollution factor in the river water and groundwater environment because it has the characteristics of stable properties, high solubility and easy migration. In order to ensure the safety of water supply and effectively control nitrate pollution, it is very important to accurately identify the pollution sources of nitrate in freshwater environment. At present, as the most accurate source analysis method, isotope technology is widely used to identify the pollution sources of nitrate in water environment. However, the complexity of nitrate pollution sources and nitrogen migration and transformation in the water environment, coupled with the isotopic fractionation, has changed the nitrogen and oxygen isotopic values of nitrate in the initial water body, resulting in certain limitations in the application of this technology. This review systematically summarized the typical δ¹⁵N and δ¹⁸O-NO₃^- ranges of NO₃^- sources, described the progress in the application of isotope technique to identify nitrate pollution sources in water environment, analyzed the application of isotope technique in identifying the migration and transformation of nitrogen in water environment, and introduced the method of quantitative source apportionment. Lastly, we discussed the deficiency of isotope technique in nitrate pollution source identification and described the future development direction of the pollution source apportionment of nitrate in water environment.

Identification of Natural and Anthropogenic Geochemical Processes Determining the Groundwater Quality in Port del Comte High Mountain Karst Aquifer (SE, Pyrenees)

The Port del Comte Massif (SE, Pyrenees) contains one of the most important vulnerable and strategic karst aquifers for supplying freshwater to the city of Barcelona (Spain). It is a fragile system, whose possible environmental impact is highly conditioned by land use. To improve the hydrogeological knowledge of the system, between September 2013 and October 2015, a detailed fieldwork was carried out for the revision of the geological model, the inventory of water points, and the in situ physico-chemical characterization on major elements and isotopes of up to a total of 43 springs, as well as precipitation water. This paper focuses on the characterization of the geochemical processes that allow explanation of the observed chemical variability of groundwater drained by the pristine aquifer system to determine the origin of salinity. The results show that the main process is the dissolution of calcite and dolomite, followed by gypsum and halite, and a minor cation exchange-like process. Sulfur and oxygen isotopes from dissolved sulfate in the studied springs point out a geogenic origin related to the dissolution of gypsum from Triassic and Tertiary materials, and that the contribution from anthropogenic sources, like fertilizers, is lower. Nitrate in groundwater is not an important issue, with a few localized cases related with agricultural activities. The multidisciplinary approach has allowed the development of a consistent hydrogeological conceptual model of the functioning of the aquifer system, which can be replicated in other places to understand the geogenic character of the hydrogeochemistry.

The evolution of hydrochemical and isotopic signatures from precipitation, surface water to groundwater in a typical karst watershed, Central Texas, USA

The Upper Cibolo Creek (UCC) karst watershed in Central Texas, USA, represents a portion of the drainage area that supplies water to the recharge zone for the Edwards Aquifer. However, the surface water-groundwater interactions along the UCC are not well quantified, and the hydraulic interactions are important for water budget and water quality of the aquifer. In this study, we investigated the evolution of hydrochemical and isotopic signatures (δ¹⁸O, δ²H and d-excess) from precipitation, surface water to groundwater in the UCC watershed from 2017 to 2019, and investigated surface water-groundwater interactions using samples from 14 creeks/spring sites. Factor analysis for the observed parameters demonstrates that changes in water hydrochemistry are primarily controlled by human activity, precipitation input, and water-rock interaction. Hierarchical clustering analysis of temporal isotope variations confirms that significant surface water-groundwater interactions occur in the UCC watershed. We identified relationships between nitrate concentrations at creek/spring sites and land-use conditions, and nitrate input sources were determined utilizing the dual-isotope analyses (δ¹⁵N and δ¹⁸O) of nitrate. This study provides capacity for a more precise assessment of water resources and water quality in Central Texas.

Groundwater contamination assessment in Ulaanbaatar City, Mongolia with combined use of hydrochemical, environmental isotopic, and statistical approaches

Ulaanbaatar City, Mongolia is rapidly becoming urbanized and attracts great attention because of environmental issues. This study was performed to assess the status of groundwater quality in Ulaanbaatar at an early but growing stage of urbanization, focusing on nitrate contamination in relation to land use. Along with high total dissolved solids and NO₃^- concentrations, significant contamination of groundwater is indicated by positive loadings of NO₃^-, Cl^- and δ¹⁵N-NO₃^- along the first principal component of the principal component analysis (PCA). Based on the concentrations and δ¹⁵N values of nitrate, groundwater is classified into two groups: Group I (baseline quality) and II (contaminated). Nitrate in Group II water in urbanized (esp. peri-urban) areas is higher in concentration (> 10 mg/l NO₃^-) and N-isotopic values (> 10‰ δ¹⁵N-NO₃^-), while pristine hydrochemistry is observed restrictedly in grassland and forest areas. Other ions (e.g., Cl^- and SO₄^2-) are also higher in Group II water. The δ¹⁵N-NO₃^- values in Group II water in combination with the spatial distribution on the land use map indicate that nitrate originates from untreated sewage effluents including pit-latrine leakage in peri-urban areas, while nitrate in Group I water originates from soil organic matter. The relationship between nitrate concentrations and δ²H (and δ¹⁸O) values of water suggests that nitrate enrichment is also influenced by evaporation during groundwater recharge. With the help of PCA for compositional data, we suggest a hydrochemical index for groundwater contamination assessment; i.e., the Groundwater Quality Index (GQI) that consists of three variables (concentrations of dissolved silica, nitrate and chloride) and can be used to delineate zones vulnerable to nitrate contamination as a crucial step for the efficient monitoring and management of groundwater quality. The study results suggest an urgent need for the management of unsealed pit latrines that are common in peri-urban areas with high population density.

Identification of nitrate sources and transformations in basin using dual isotopes and hydrochemistry combined with a Bayesian mixing model: Application in a typical mining city

The external nitrogen load input caused by human activities exacerbates the eutrophication process of aquatic ecosystems in mining areas, causing water quality problems. However, knowledge of the sources and environmental behavior of nitrate in the surface water of mining areas is still very limited. This study investigated the nitrate content and spatiotemporal variation characteristics of surface water in the Linhuan mining area, identified the sources and transformation processes of nitrate using isotopes and hydrochemistry, and evaluated the contribution rates of different potential nitrate sources based on a Bayesian mixing model. The nitrogen pollution in the surface water in the mining area seriously exceeded class Ⅴ of the Environmental Quality Standard of Surface Water of China (GB3838-2002). The NO₃^- content ranged from 0.87 to 3.41 mg/L, showing obvious seasonal and spatial differences. Isotope and NO₃^-/Cl^- analysis indicated that nitrate in the subsidence area water (SAW) was mainly derived from chemical fertilizer (NF) and soil organic nitrogen (NS), while nitrate in the mainstream of the Huihe River water (HRW) was mainly derived from manure/sewage (MS). The nitrate in the tributary of the Baohe River water (BRW) was mainly derived from soil NS, and nitrification was a nitrogen conversion pathway in the soil. The results of the Bayesian mixing model showed that the main sources of nitrate in the BRW, HRW and SAW were NF (34.5%), MS (68.8%) and NF (40.8%) in the wet season, and NS (33.4%), MS (70.9%) and NF (58.1%) in the dry season, respectively. The results of this study provide a new integrated method for the identification of nitrate pollution sources in mining areas, and this method can be used to improve the biogeochemical information of nitrogen in the aquatic ecosystems of mining areas and help formulate relevant measures to reduce water nitrogen pollution.

Hydrogeological controls on ammonium enrichment in shallow groundwater in the central Yangtze River Basin

The controlling processes of excessive ammonium in surface water and groundwater in the central Yangtze River Basin remain unclear. In this study, monitoring of water levels and temporal-spatial distributions of major N compounds were implemented at the large Jiangshan plain and at the local site scale in the central Yangtze River Basin. The results indicate that the recharge, movement and transformation of ammonium were controlled by hydrogeological conditions. Manure and sewage from anthropogenic activities were identified as the main source of nitrogen compounds. The nitrogen loading into aquifers were governed by water table and groundwater flow. After entering subsurface soils, nitrification and dissimilatory nitrate reduction to ammonium (DNRA) were proposed as the ammonium consumption and production mechanisms, respectively, by combining the concentrations of ammonium‑nitrogen and nitrate‑nitrogen with the corresponding isotopic compositions. These microbially mediated processes controlling transport and transformation of nitrogen compounds were influenced by the seasonally varying groundwater flow regime that changed the redox conditions in the aquifers. In the subsurface environments, ammonium was converted to nitrate when sufficient oxygen supply was available, and this process was reversed under anoxic conditions along the groundwater flow path. A conceptual model for the reactive transport of nitrogen compounds jointly controlled by the vertical groundwater flows and biogeochemical processes was proposed, which provides new insights into the genesis of high ammonium groundwater.

Nitrate sources and biogeochemical processes in karst underground rivers impacted by different anthropogenic input characteristics

Nitrate is one of the most common pollution sources in groundwater, particularly in highly vulnerable karst aquifers. The potential for nitrification and denitrification within karst aquifers varies in different settings depending on the extent of anthropogenic inputs, so that accurate identification of nitrate sources can be difficult. Geochemical data and dual nitrate isotopes were measured in this study, incorporating a Bayesian isotopic mixing model, and used to identify nitrate sources, nitrification and denitrification, and quantitatively determine nitrate sources under different extents of anthropogenic inputs in three karst catchments within Chongqing Municipality, SW China: Laolongdong (an urbanized area), Qingmuguan (a suburban village), and Shuifang Spring (a protected natural area). At the Laolongdong catchment, the groundwater was in a reducing condition and enriched in δ¹⁵N_NO3 (averaging 18.9 ± 6.9‰) and δ¹⁸O_NO3 (averaging 8.5 ± 4.6‰). Manure and sewage waste were the main contributing nitrate sources. A slope of 1.8: 1 of the dual isotopes suggested a denitrification process occurring in anaerobic conduit flow. Within the Qingmuguan catchment, groundwater had average δ¹⁵N_NO3 and δ¹⁸O_NO3 values of 9.7 ± 3.5‰, and 1.9 ± 3.4‰, respectively. The data showed evidence for nitrification, and the contribution of soil organic nitrogen was 52.1%, followed by a contribution of 44.8% from manure and wastewater. At the Shuifang Spring catchment, the mean δ¹⁵N_NO3 and δ¹⁸O_NO3 values in groundwater were 8.8 ± 2.9‰, 2.3 ± 4.6‰, respectively. Nitrification was the dominant process and most of the nitrate was derived from soil organic nitrogen. This study suggests that karst underground rivers overlain by urban land use undergo denitrification, while the suburban and relatively pristine karst aquifers are dominated by nitrification, allowing development of a conceptual model for nitrate sources and transformations in karst aquifers from the categories of land use (i.e., urban, suburban, and pristine areas). MAIN FINDING: Anthropogenic activities can change biogeochemical nitrogen dynamics of vulnerable karst aquifers, such that the groundwater overlain by an urban settlement has undergone denitrification, while suburban and pristine areas have been dominated by nitrification.