Occurrence Of Nitrate Research Articles

Impact of leaky wells on nitrate cross-contamination in a layered aquifer system: Methodology for and demonstration of quantitative assessment and prediction

Poorly constructed wells can cause deterioration of groundwater quality by carrying surface contaminants into a deep subsurface aquifer system. In this study, the impact of leaky wells on groundwater contamination was quantitatively evaluated in a layered aquifer system of the Gosan agricultural fields, Jeju Island, Korea, where degradation in groundwater quality by nitrate has been reported. We introduce a leaky-well module and a double-domain integration method to compute nitrate cross-contamination through a layered aquifer system. The simulation results clearly revealed that the leaky wells rapidly degraded the water quality of the underlying aquifer by acting as a direct pathway for nitrate-rich shallow groundwater. The model results predicted that in order to decrease the NO3-N concentration at the regional groundwater wells below the maximum contamination level (MCL), the maximum allowable fertilizer amount of Gosan would be 45–65% of the currently applied fertilizer level, whereas sealing of the regional groundwater wells would rapidly decrease the NO3-N concentration below the MCL without reducing fertilizer usage. Our study demonstrated that the well conditions and hydrogeological system play major roles in the occurrence of nitrate in the underlying aquifer in Gosan; therefore, a proper groundwater management plan against nitrate contamination should be established on the basis of a comprehensive understanding of the hydrogeologic system of the area.

Dietary Nitrate and the Epidemiology of Cardiovascular Disease: Report From a National Heart, Lung, and Blood Institute Workshop.

In view of continuing unanswered questions regarding the geographical and demographic distribution of cardiovascular disease, and recent discoveries about the effects of dietary nitrate on cardiovascular physiology, the National Heart, Lung, and Blood Institute (NHLBI) convened a workshop to

Redox conditions and groundwater quality issues of selected alluvial aquifers in Serbia

Redox conditions are an important regulator of aqueous biogeochemistry and knowledge about them is crucial for an understanding of the fate and occurrence of nitrates, emerging substances, and organic compounds in shallow groundwater. The aim of this paper is to determine redox categories, along with prevailing redox processes, and the differences in groundwater quality between shallow alluvial aquifers of Serbia's major rivers. The research was conducted on public water-supply wells in the alluvial plain of the Velika Morava River, the Danube River, the Tisa River and the alluvial aquifer of the Sava River. The study period is 2010–2014 and the number of collected and analysed samples 243. The redox categories and processes are characterised by concentrations of aqueous redox species (dissolved oxygen, nitrate, dissolved iron, manganese, and sulphate and sulphide concentrations). Parameters such as Eh, total organic carbon, HCO3−, pH, total iron concentrations, temperature and specific conductivity were also analysed. Different geological and hydrogeological settings, groundwater abstraction, distances between the wells and the river, well depths, and anthropogenic impacts result in diverse redox conditions. Groundwater in selected alluvial aquifers is mostly defined as anoxic, with one predominant process, or mixed anoxic, with various redox processes occurring simultaneously.

Hydrogeochemical Characterization of Groundwater in and Around a Wastewater Irrigated Forest in the Southeastern Edge of the Tengger Desert, Northwest China

Groundwater is an essential part of water resources for human survival and economic development in arid regions over the world. Human activities and environmental change have imposed significant impacts on groundwater environment. To investigate the hydrogeochemical characteristics and evolution of groundwater in and around a desert region impacted by wastewater irrigation, 84 groundwater samples were collected and analyzed for 18 indices. Statistical and graphical approaches were applied to delineate the general hydrochemical characteristics of groundwater and the major factors influencing its evolution. Stable isotopes of 2H and 18O were applied to identify groundwater evaporation process. Hydrogeochemical modeling was also adopted to quantify the major reactions occurring in the groundwater system. The results reveal that the abundance of cations is Na+ > Ca2+ > Mg2+ > K+ for groundwater in the entire study area, while the abundance of anions for groundwater in the desert region is HCO3 − > Cl− > SO4 2−, and that for groundwater in the alluvial plain is HCO3 − > SO4 2− > Cl−. Groundwater chemistry in the study area is mainly of rock dominance, and dissolution/precipitation of minerals and cation exchange are major natural factors governing the formation of groundwater chemistry. However, stable isotopes and the occurrence of nitrate show that shallow groundwater evaporation and human activities also have some impacts on groundwater quality. Hydrochemical type transits from Ca–Cl to HCO3·SO4–Ca type, and then to HCO3·SO4–Ca·Mg type along the flow path. The transition is influenced by multiple factors with water–rock interactions the predominant one. The water–rock interactions for the upper and lower sections of the flow path, indicated by hydrogeochemcial modeling, are different due to different geologic and hydrogeologic conditions.

The potential of major ion chemistry to assess groundwater vulnerability of a regional aquifer in southern Quebec (Canada)

Groundwater vulnerability mapping provides useful but limited information for developing protection plans of the resource. Classical vulnerability ranking methods often do not take into account complex hydrostratigraphy and never consider groundwater flow dynamics. The objective of this work was to test the potential of major ion chemistry to assess regional-scale intrinsic groundwater vulnerability. Because it reflects water–sediment and water–rock interactions, the new vulnerability index reflects both infiltration processes and groundwater hydrodynamics. The method was applied on a regional fractured bedrock aquifer located in the Becancour region of southern Quebec (Canada). In this region, hydrogeochemistry shows that freshly recharged groundwater evolves from (Ca, Mg)–HCO3 and Ca–SO4 to Na–HCO3 type with gradually increasing confinement conditions in the fractured aquifer and tends to Na–Cl type locally by mixing with trapped marine pore-water. The new method identified recharge areas as those of the highest vulnerability and gradually decreasing vulnerability as confinement of the aquifer increased. It also highlights local discontinuities in confinement that differ from the regional pattern. Results showed a good correlation between groundwater vulnerability estimated with the new method and nitrate occurrence in groundwater. Eighty-two per cent of all samples presenting detectable nitrate concentrations were characterized by a Hydrogeochemical Vulnerability Index greater than 9 (maximum is 10). The ability of the new vulnerability method to identify areas vulnerable to detectable nitrate concentrations was much higher than that deriving from the DRASTIC method. This work confirms that major ions chemistry contains significant information about groundwater vulnerability and could be used to improve groundwater resource management.

Modelling nitrate pollution pressure using a multivariate statistical approach: the case of Kinshasa groundwater body, Democratic Republic of Congo

A multivariate statistical modelling approach was applied to explain the anthropogenic pressure of nitrate pollution on the Kinshasa groundwater body (Democratic Republic of Congo). Multiple regression and regression tree models were compared and used to identify major environmental factors that control the groundwater nitrate concentration in this region. The analyses were made in terms of physical attributes related to the topography, land use, geology and hydrogeology in the capture zone of different groundwater sampling stations. For the nitrate data, groundwater datasets from two different surveys were used. The statistical models identified the topography, the residential area, the service land (cemetery), and the surface-water land-use classes as major factors explaining nitrate occurrence in the groundwater. Also, groundwater nitrate pollution depends not on one single factor but on the combined influence of factors representing nitrogen loading sources and aquifer susceptibility characteristics. The groundwater nitrate pressure was better predicted with the regression tree model than with the multiple regression model. Furthermore, the results elucidated the sensitivity of the model performance towards the method of delineation of the capture zones. For pollution modelling at the monitoring points, therefore, it is better to identify capture-zone shapes based on a conceptual hydrogeological model rather than to adopt arbitrary circular capture zones.

A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA

Summary We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN). Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R2 and a version with R2 within one standard error of the maximum (the 1SE model). The former yielded CV training R2 values of 0.94–1.0. Cross-validation testing R2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.

Risk assessment of groundwater pollution with a new methodological framework: application of Dempster–Shafer theory and GIS

Managing natural groundwater resources is challenged by nitrate pollution resulting from agricultural activities. This issue is emerging as an important environmental concern that needs to be addressed through effective groundwater management. Groundwater assessment is an important aspect of groundwater management, particularly in arid and semi-arid regions. This study focused on the Kerman Plain, which is exposed to intensive agricultural activities and land exploitation that result in intense land pollution. The effects of nitrate pollution may be controlled by applying specific measures. Dempster–Shafer theory (DST) was applied in this study to develop a new methodology for assessing pollution risk. Applying this theory as a pioneering approach to assessing groundwater pollution risk is the novel component of this research. This approach provides a major advantage by dealing with varying levels of precision related to information. The spatial association between DRASTIC parameters including D (depth of water), R (net recharge), A (aquifer media), S (soil media), T (topography), I (impact of vadose zone) and C (hydraulic conductivity) and underground nitrate occurrence was evaluated by applying bivariate DST to assign mass functions. Dempster’s rule of combination using GIS was then applied to determine a series of combined mass functions for multiple hydrogeological data layers. The uncertainty of system responses was directly addressed by the proposed methodology. Finally, the modified DRASTIC map with the highest validity and accuracy was selected and combined with the damage map. The comparison between nitrate distribution and vulnerability and the risk maps exhibit high similarity between different vulnerability degrees and nitrate concentrations. Long-term planning of preventive measures and associated developments can be aided by the regions with low and very low risks located in the northeast, northwest, and central regions.

On-site Sanitation Influence on Nitrate Occurrence in the Shallow Groundwater of Mahitsy City, Analamanga Region, Madagascar

Nitrate contamination of groundwater has inclined to be a critical issue in areas where groundwater is the only available resource for water supply for drinking use purpose. In developing countries such as Madagascar, on-site sanitation can be a significant source of nitrate contamination of shallow groundwater, depending on the type of sub-surface layer and hydrogeological environment, the arrangements and behavior of sanitation, and the design of sanitation used for defecation. This study was carried out to investigate the nitrate occurrence in shallow groundwater of Mahitsy city, Analamanga Region of Madagascar, and to assess the on-site sanitation influence on nitrate concentration in drinking water well. Water samples were collected from dug wells in rainy and dry seasons. The analytical results showed that the measured nitrate concentration was in the range of 1.5 mg/L and 580 mg/L with an average of 348 mg/L for all water samples. Thirteen out of fifteen samples had nitrate concentration exceeding the WHO guideline value (50mg/L). Data analysis indicated that nitrate concentration in dry season (average 409 mg/L) was greater as compared to rainy season (371 mg/L). However, the difference was not significant at the 0.05 level. Significant positive correlation (0.849, p < 0.01) was found between nitrate and chloride concentration with chloride/nitrogen ratio of about 1:2.23, suggesting the same source for nitrate and chloride. Nitrate concentrations of well waters were strongly correlated to distance between water wells and sanitation facilities (-0.466, p = 0.08), to water table level (-0.558, p < 0.05) and to age of water wells (0.655, p < 0.01).

Identifying sources of groundwater nitrate contamination in a large alluvial groundwater basin with highly diversified intensive agricultural production

Groundwater quality is a concern in alluvial aquifers underlying agricultural areas worldwide. Nitrate from land applied fertilizers or from animal waste can leach to groundwater and contaminate drinking water resources. The San Joaquin Valley, California, is an example of an agricultural landscape with a large diversity of field, vegetable, tree, nut, and citrus crops, but also confined animal feeding operations (CAFOs, here mostly dairies) that generate, store, and land apply large amounts of liquid manure. As in other such regions around the world, the rural population in the San Joaquin Valley relies almost exclusively on shallow domestic wells (≤150 m deep), of which many have been affected by nitrate. Variability in crops, soil type, and depth to groundwater contribute to large variability in nitrate occurrence across the underlying aquifer system. The role of these factors in controlling groundwater nitrate contamination levels is examined. Two hundred domestic wells were sampled in two sub-regions of the San Joaquin Valley, Stanislaus and Merced (Stan/Mer) and Tulare and Kings (Tul/Kings) Counties. Forty six percent of well water samples in Tul/Kings and 42% of well water samples in Stan/Mer exceeded the MCL for nitrate (10mg/L NO3-N). For statistical analysis of nitrate contamination, 78 crop and landuse types were considered by grouping them into ten categories (CAFO, citrus, deciduous fruits and nuts, field crops, forage, native, pasture, truck crops, urban, and vineyards). Vadose zone thickness, soil type, well construction information, well proximity to dairies, and dominant landuse near the well were considered. In the Stan/Mer area, elevated nitrate levels in domestic wells most strongly correlate with the combination of very shallow (≤21 m) water table and the presence of either CAFO derived animal waste applications or deciduous fruit and nut crops (synthetic fertilizer applications). In Tulare County, statistical data indicate that elevated nitrate levels in domestic well water are most strongly associated with citrus orchards when located in areas with a very shallow (≤21 m) water table. Kings County had relatively few nitrate MCL exceedances in domestic wells, probably due to the deeper water table in Kings County.

Analysis of Nitrate occurrence and distribution in Groundwater in the Gaza Strip using major ion chemistry by Baalousha H.

Nitrate in groundwater in the Gaza Strip, Palestine has become a serious problem in the last decade. As a result of extensive use of fertilizers, discharging of wastewater from treatment plants, and leakage of wastewater form cesspools, increased levels of nitrate up to 400 mg/l have been detected in groundwater. Nitrate concentrations more than 50 mg l-1 are very harmful to infant, foetuses, and people with health problems. The most efficient way to prevent nitrate impacts is to identify the sources of nitrate and to reduce them at the source. In this study, samples of groundwater from 63 wells were collected and chemically analyzed. Analysis of these samples revealed they have nitrate concentrations more than the maximum permissible limit recommended by World Health Organization (WHO). The major ion chemistry analysis was used to identify nitrate sources. Based on the relation between land use and nitrate concentration in groundwater, sources of nitrate were identified. These sources are: (1) leakage from wastewater treatment plants, (2) leakage from cesspits, and (3) intensive agricultural activities. It was found that the leakage of wastewater from cesspits and over-loaded treatment plants has greater influence on groundwater nitrate contamination more than agricultural activities. This study shows the important role of the type of infiltrated water into the sub-soil, combined land use, in determining the source of nitrate in groundwater.

Adsorption of fluoride from aqueous solution using low cost adsorbent

High fluoride levels beyond the recommended value of 1.5 mg/L have been detected in several groundwater wells in Northern Ghana. This occurrence has led to the capping of many high yielding wells that hitherto have been major sources of drinking water for the populace in these arid areas. Most of the fluoride removal technologies applied in the area has not been versatile in effectively removing fluoride because of the varying water qualities. This study focused on screening adsorbents including high aluminium or iron containing bauxite ores, fabricated zeolite and activated Neem seeds for removal of fluoride from drinking water. The model water used was prepared by simulating the prevailing groundwater quality in Northern Ghana. The high aluminium bauxite ore (HABO) had the highest fluoride removal capacity. Within the pH range tested (5–7), the fluoride removal decreased with increasing pH. Occurrence of sulfate, chloride and nitrate in the model water reduced the fluoride removal capacity by 57, 24 and 38% respectively. The combined effect of these anions showed a 60% reduction in the fluoride removal capacity. The Freundlich and Langmuir isotherms gave an adsorption capacity (K) of 0.90 mg/g for the HABO. The adsorption kinetics fitted well the pseudo second-order kinetic model. The HABO is thermally stable and has kaolinite [Al2Si2O5(OH)5] and gibbsite [Al(OH)3] as its major components. X-ray fluorescence (XRF) and energy dispersive X-ray (EDX) results showed Al, Fe, Ti, O, C and Si as the predominant elements in the HABO.

Spatial variability of nitrous oxide and methane emissions from an MBT landfill in operation: Strong N2O hotspots at the working face

Mechanical biological treatment (MBT) is an effective technique, which removes organic carbon from municipal solid waste (MSW) prior to deposition. Thereby, methane (CH4) production in the landfill is strongly mitigated. However, direct measurements of greenhouse gas emissions from full-scale MBT landfills have not been conducted so far. Thus, CH4 and nitrous oxide (N2O) emissions from a German MBT landfill in operation as well as their concentrations in the landfill gas (LFG) were measured. High N2O emissions of 20–200gCO2eq.m−2h−1 magnitude (up to 428mgNm−2h−1) were observed within 20m of the working face. CH4 emissions were highest at the landfill zone located at a distance of 30–40m from the working face, where they reached about 10gCO2eq.m−2h−1. The MBT material in this area has been deposited several weeks earlier. Maximum LFG concentration for N2O was 24.000ppmv in material below the emission hotspot. At a depth of 50cm from the landfill surface a strong negative correlation between N2O and CH4 concentrations was observed. From this and from the distribution pattern of extractable ammonium, nitrite, and nitrate it has been concluded that strong N2O production is associated with nitrification activity and the occurrence of nitrite and nitrate, which is initiated by oxygen input during waste deposition. Therefore, CH4 mitigation measures, which often employ aeration, could result in a net increase of GHG emissions due to increased N2O emissions, especially at MBT landfills.

Impacts of human activities on the occurrence of groundwater nitrate in an alluvial plain: A multiple isotopic tracers approach

Nitrate pollution is a severe problem in areas with intensive agricultural activities. This study focuses on nitrate occurrence and its constraints in a selected alluvial fan using chemical data combined with environmental isotopic tracers (18O, 3H, and 15N). Results show that groundwater nitrate in the study area is as high as 258.0 mg/L (hereafter NO3 −) with an average of 86.8 mg/L against national drinking water limit of 45 mg/L and a regional baseline value of 14.4 mg/L. Outside of the riparian zone, nitrate occurrence is closely related to groundwater circulation and application of chemical fertilizer. High groundwater nitrate is found in the recharge area, where nitrate enters into groundwater through vertical infiltration, corresponding to high 3H and enriched 18O in the water. In the riparian zone, on the contrary, the fate of groundwater nitrate is strongly affected by groundwater level. Based on two sampling transects perpendicular to the riverbank, we found that the high level of nitrate corresponds to the deeper water table (25 m) near the urban center, where groundwater is heavily extracted. Groundwater nitrate is much lower (<12.4 mg/L) at localities with a shallow water table (5 m), which is likely caused by denitrification in the aquifer.

A Comparison of Data‐Driven Groundwater Vulnerability Assessment Methods

Increasing availability of geo-environmental data has promoted the use of statistical methods to assess groundwater vulnerability. Nitrate is a widespread anthropogenic contaminant in groundwater and its occurrence can be used to identify aquifer settings vulnerable to contamination. In this study, multivariate Weights of Evidence (WofE) and Logistic Regression (LR) methods, where the response variable is binary, were used to evaluate the role and importance of a number of explanatory variables associated with nitrate sources and occurrence in groundwater in the Milan District (central part of the Po Plain, Italy). The results of these models have been used to map the spatial variation of groundwater vulnerability to nitrate in the region, and we compare the similarities and differences of their spatial patterns and associated explanatory variables. We modify the standard WofE method used in previous groundwater vulnerability studies to a form analogous to that used in LR; this provides a framework to compare the results of both models and reduces the effect of sampling bias on the results of the standard WofE model. In addition, a nonlinear Generalized Additive Model has been used to extend the LR analysis. Both approaches improved discrimination of the standard WofE and LR models, as measured by the c-statistic. Groundwater vulnerability probability outputs, based on rank-order classification of the respective model results, were similar in spatial patterns and identified similar strong explanatory variables associated with nitrate source (population density as a proxy for sewage systems and septic sources) and nitrate occurrence (groundwater depth).

Modeling simultaneous exceedance of drinking-water standards of arsenic and nitrate in the Southern Ogallala aquifer using multinomial logistic regression

The occurrence of elevated levels of arsenic and nitrate in aquifers impacted by agricultural activities is common and can result in adverse health effects in rural areas. Numerous wells located in the Ogallala aquifer in the Southern High Plains of Texas have tested positive for both arsenic and nitrate MCL exceedance. To model the simultaneous exceedance of both chemicals, two types of Logistic Regression (LR) models were developed by (a) treating arsenic and nitrate independently and combining the marginal probabilities of their exceedance, and (b) treating the two exceedances together by using a multinomial model. Influencing variables representative of both soil and aquifer properties and data for which was readily available were identified. The predictive capacities of the two models were evaluated using Received Operating Characteristics (ROCs) and spatial trends in predictions were studied. The LR model constructed from the marginal probabilities had lower overall accuracy (59% correct classifications) and was extremely conservative by over-predicting outcomes. In contrast, the multinomial model showed good overall accuracy (79% correct classifications), made the correct predictions 90% of the time when both arsenic and nitrate MCL exceedances were observed, and was a good fit for wells located in agricultural areas. The results of the multinomial model also confirm previous studies that attributed shallow subsurface arsenic to anthropogenic activities. Based on the insights provided by the model it is recommended that where agricultural areas are concerned, the occurrence of arsenic and nitrate are better evaluated together.

Spatial and Temporal Distribution of Nitrate Pollution in Groundwater of Abuja, Nigeria

Groundwater has been recognized as playing a very important role in the development of Abuja, Nigeria’s Capital as many households, private and government establishments depends solely on hand-dug wells and boreholes for their daily water needs. Exploitation of groundwater is rather delicate because of its potency to contamination and difficulty to remediate when compared to surface water. The purpose of this paper is to present the occurrence of nitrate in groundwater of Abuja and discuss the implication and sources of the nitrate. High nitrate level in drinking water leads to infant methaemoglobinaemia (blue-baby syndrome), gastric cancer, metabolic disorder and livestock poisoning. A simplified map of nitrate occurrences in Abuja indicates that some areas have nitrate concentration above the WHO and NSDWQ guide limit of 50 mg/l and it is dominant in the rainy season than dry season. The number of people drinking water with nitrate concentration above the permissible level cannot be quantified presently. The sources of nitrate in the groundwater were attributed to bedrock dissolution in the course of groundwater migration and more importantly anthropogenic activities such as on-site sanitation, waste dumpsites and agricultural chemicals. Water treatment by bio-denitrification and nitrate pollution control programs should be introduced at local, state and federal levels in order to educate people on the need to protect groundwater from nitrate pollution caused by agricultural activity and indiscriminate disposal of wastes.

Vulnerability of Recently Recharged Groundwater in Principle Aquifers of the United States To Nitrate Contamination

Recently recharged water (defined here as <60 years old) is generally the most vulnerable part of a groundwater resource to nonpoint-source nitrate contamination. Understanding at the appropriate scale the interactions of natural and anthropogenic controlling factors that influence nitrate occurrence in recently recharged groundwater is critical to support best management and policy decisions that are often made at the aquifer to subaquifer scale. New logistic regression models were developed using data from the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program and National Water Information System for 17 principal aquifers of the U.S. to identify important source, transport, and attenuation factors that control nonpoint source nitrate concentrations greater than relative background levels in recently recharged groundwater and were used to predict the probability of detecting elevated nitrate in areas beyond the sampling network. Results indicate that dissolved oxygen, crops and irrigated cropland, fertilizer application, seasonally high water table, and soil properties that affect infiltration and denitrification are among the most important factors in predicting elevated nitrate concentrations. Important differences in controlling factors and spatial predictions were identified in the principal aquifer and national-scale models and support the conclusion that similar spatial scales are needed between informed groundwater management and model development.

Linking hydrogeochemistry to nitrate abundance in groundwater in agricultural settings in Ireland

Nitrate (NO3-–N) contamination of groundwater and associated surface waters is an increasingly important global issue with multiple impacts on terrestrial, aquatic and atmospheric environments. Investigation of the distribution of hydrogeochemical variables and their connection with the occurrence of NO3-–N provides better insights into the prediction of the environmental risk associated with nitrogen use within agricultural systems. The research objective was to evaluate the effect of hydrogeological setting on agriculturally derived groundwater NO3-–N occurrence. Piezometers (n = 36) were installed at three depths across four contrasting agricultural research sites. Groundwater was sampled monthly for chemistry and dissolved gases, between February 2009 and January 2011. Mean groundwater NO3-–N ranged 0.7–14.6 mg L−1, with site and groundwater depth being statistically significant (p < 0.001). Unsaturated zone thickness and saturated hydraulic conductivity (Ksat) were significantly correlated with dissolved oxygen (DO) and redox potential (Eh) across sites. Groundwater NO3-–N occurrence was significantly negatively related to DOC and methane and positively related with Eh and Ksat. Reduction of NO3-–N started at Eh potentials <150 mV while significant nitrate reduction occurred <100 mV. Indications of heterotrophic and autotrophic denitrification were observed through elevated dissolved organic carbon (DOC) and oxidation of metal bound sulphur, as indicated by sulphate (SO42-). Land application of waste water created denitrification hot spots due to high DOC losses. Hydrogeological settings significantly influenced groundwater nitrate occurrence and suggested denitrification as the main control.

Changes in Shallow Groundwater Quality Beneath Recently Urbanized Areas in the Memphis, Tennessee Area1

Barlow, Jeannie R.B., James A. Kingsbury, and Richard H. Coupe, 2012. Changes in Shallow Groundwater Quality Beneath Recently Urbanized Areas in the Memphis, Tennessee Area. Journal of the American Water Resources Association (JAWRA) 48(2): 336‐354. DOI: 10.1111/j.1752‐1688.2011.00616.xAbstract: Memphis, the largest city in the state of Tennessee, and its surrounding suburbs depend on a confined aquifer, the Memphis aquifer, for drinking water. Concern over the potential for downward movement of water from an overlying shallow aquifer to the underlying Memphis aquifer provided impetus for monitoring groundwater quality within the shallow aquifer. The occurrence of volatile organic compounds (VOCs), nitrate, and pesticides in samples from the shallow well network indicate a widespread affect on water quality from the overlying urban land use. Total pesticide concentration was generally higher in more recently recharged groundwater indicating that as the proportion of recent water increases, the occurrence of pesticides related to the current urban land use also increases. Groundwater samples with nitrate concentrations greater than 1.5 mg/l and detectable concentrations of the pesticides atrazine and simazine also had higher concentrations of chloroform, a VOC primarily associated with urban land use, than in other samples. The age of the water from these wells indicates that these concentrations are most likely not representative of past agricultural use, but of more recent urban use of these chemicals. Given that the median age of water represented by the shallow well network was 21 years, a lag time likely exists between changes in land use and the occurrence of constituents related to urbanization in shallow groundwater.