Variations In Nitrate Concentrations Research Articles

Optimized fertilization using online soil nitrate data

Abstract. A new soil nitrate monitoring system that was installed in a cultivated field enabled us, for the first time, to control the nitrate concentration across the soil profile. The monitoring system was installed in a full-scale agricultural greenhouse setup that was used for growing a bell pepper crop. Continuous measurements of soil nitrate concentrations were performed across the soil profile of two plots: (a) an adjusted fertigation plot, in which the fertigation regime was frequently adjusted according to the dynamic variations in soil nitrate concentration, and (b) a control plot, in which the fertigation was managed according to a predetermined fertigation schedule that is standard practice for the area. The results enabled an hourly resolution in tracking the dynamic soil nitrate concentration variations in response to daily fertigation and crop demand. Nitrate–nitrogen (N–NO3) concentrations in and below the root zone, under the control plot, reached very high levels of ∼ 180 ppm throughout the entire season. Obviously, this concentration reflects excessive fertigation, which is far beyond the plant demand, entailing severe groundwater pollution potential. On the other hand, frequent adjustments of the fertigation regime, which were carried out under the adjusted fertigation plot, enabled control of the soil nitrate concentration around the desired concentration threshold. This enabled a substantial reduction of 38 % in fertilizer application while maintaining maximum crop yield and quality. Throughout this experiment, decision-making on the fertigation adjustments was done manually based on visual inspections of the soil's reactions to changes in the fertigation regime. Nevertheless, it is obvious that an algorithm that continuously processes the soil nitrate concentration across the soil profile and provides direct fertigation commands could act as a “fertistat” that sets the soil nutrients at a desired optimal level. Consequently, it is concluded that fertigation that is based on continuous monitoring of the soil nitrate concentration may ensure nutrient application that accounts for plant demand, improves agricultural profitability, minimizes nitrate down-leaching and significantly reduces water resource pollution.

Where the past meets the present: connecting nitrogen from watersheds to streams through groundwater flowpaths

Groundwater discharge to streams is a nonpoint source of nitrogen (N) that confounds N mitigation efforts and represents a significant portion of the annual N loading to watersheds. However, we lack an understanding of where and how much groundwater N enters streams and watersheds. Nitrogen concentrations at the end of groundwater flowpaths are the culmination of biogeochemical and physical processes from the contributing land area where groundwater recharges, within the aquifer system, and in the near-stream riparian area where groundwater discharges to streams. Our research objectives were to quantify the spatial distribution of N concentrations at groundwater discharges throughout a mixed land-use watershed and to evaluate how relationships among contributing and riparian land cover, modeled aquifer characteristics, and groundwater discharge biogeochemistry explain the spatial variation in groundwater discharge N concentrations. We accomplished this by integrating high-resolution thermal infrared surveys to locate groundwater discharge, biogeochemical sampling of groundwater, and a particle tracking model that links groundwater discharge locations to their contributing area land cover. Groundwater N loading from groundwater discharges within the watershed varied substantially between and within streambank groundwater discharge features. Groundwater nitrate concentrations were spatially heterogeneous ranging from below 0.03–11.45 mg-N/L, varying up to 20-fold within meters. When combined with the particle tracking model results and land cover metrics, we found that groundwater discharge nitrate concentrations were best predicted by a linear mixed-effect model that explained over 60% of the variation in nitrate concentrations, including aquifer chemistry (dissolved oxygen, Cl−, SO4 2−), riparian area forested land cover, and modeled physical aquifer characteristics (discharge, Euclidean distance). Our work highlights the significant spatial variability in groundwater discharge nitrate concentrations within mixed land-use watersheds and the need to understand groundwater N processing across the many spatiotemporal scales within groundwater cycling.

Impact of Lockdown on the Surface Water Quality in Kelani River, Sri Lanka

The COVID-19 lockdown has been regarded as a catalyst for the restoration of natural water bodies worldwide. Therefore, this study aims to investigate the impacts of the lockdown on the water quality of the Kelani River, Sri Lanka. The water quality downstream of the Kelani River Basin was greatly improved during the lockdown season, The concentration of biological oxygen demand (BOD) decreased downstream by ~46% during the lockdown, while that in the middle and upstream reduced by 7.1% and 5.0%, respectively. The concentration of chemical oxygen demand (COD) was diminished by around 65%, 52%, and 43% in downstream, middle stream, and upstream, respectively, in the lockdown season. However, in post-lockdown season, upstream showed the highest spatial variation in nitrate concentration, which may be due to excessive use of fertilizers in that region. Many industries temporarily shut down or scaled back operations during the lockdown, which allowed for a large reduction in the discharge of pollutants, particularly in the river’s downstream region. The river’s water quality showed a significant improvement as a result of temporarily suspending human activities.

In situ temperature-compensated ultraviolet spectrophotometry to estimate nitrate and chloride concentrations in estuarine seawater with different salinity and composition

Various methods have been proposed for in situ measurement of nitrate concentrations from the ultraviolet (UV) absorbance spectrum of seawater with stable salinity and constituents. However, salinity and temperature affect the UV absorption spectrum of seawater. In sea areas with large variability in salinity and water temperature, accurate nitrate ion concentration measurements remain challenging. We performed in situ measurements of nitrate, chloride, and bromide in estuarine seawater with different salinity compositions and applied water temperature compensation. First, the impact of water temperature on the UV absorbance of chloride, bromide, and nitrate was experimentally investigated and represented in a mathematical model. Next, chloride, bromide, and nitrate concentrations were estimated by suppressing the impact of residual components from the UV absorbance spectra of seawater using principal component regression (PCR). Hence, the chloride, bromide, and nitrate concentrations were determined by measuring the UV absorbance spectrum of seawater alone, without measuring water temperature and electrical conductivity. The proposed method was more accurate (±1.39 μM below 100 μM and ±0.90 μM below 20 μM) than the conventional method (±2.35 μM below 100 μM and ±1.88 μM below 20 μM) and PCR without water temperature compensation (±3.67 μM). In a field study, an in situ UV spectrophotometer with water temperature compensation was used to measure depth profiles of nitrate concentrations in estuarine seawater. We successfully measured the depth profiles of low chloride and high nitrate concentrations in the surface layer as well as high chloride and low nitrate concentrations in the lower layer. The proposed method enables in situ measurements of nitrate concentrations in waters with either stable or highly variable salinity and composition. Unlike conventional chemical analysis, our method can describe detailed spatiotemporal variations in nitrate concentrations.

A deep learning-based novel approach to generate continuous daily stream nitrate concentration for nitrate data-sparse watersheds

High-frequency stream nitrate concentration provides critical insights into nutrient dynamics and can help to improve the effectiveness of management decisions to maintain a sustainable ecosystem. However, nitrate monitoring is conventionally conducted through lab analysis using in situ water samples and is typically at coarse temporal resolution. In the last decade, many agencies started collecting high-frequency (5–60 min intervals) nitrate data using optical sensors. The hypothesis of the study is that the data-driven models can learn the trend and temporal variability in nitrate concentration from high-frequency sensor-based nitrate data in the region and generate continuous nitrate data for unavailable data periods and data-limited locations. A Long Short-Term Memory (LSTM) model-based framework was developed to estimate continuous daily stream nitrate for dozens of gauge locations in Iowa, USA. The promising results supported the hypothesis; the LSTM model demonstrated median test-period Nash-Sutcliffe efficiency (NSE) = 0.75 and RMSE = 1.53 mg/L for estimating continuous daily nitrate concentration in 42 sites, which are unprecedented performance levels. Twenty-one sites (50 % of all sites) and thirty-four sites (76 % of all sites) demonstrated NSE > 0.75 and 0.50, respectively. The average nitrate concentration of neighboring sites was identified as a crucial determinant of continuous daily nitrate concentration. Seasonal model performance evaluation showed that the model performed effectively in the summer and fall seasons. About 26 sites showed correlations >0.60 between estimated nitrate concentration and discharge. The concentration-discharge (c-Q) relationship analysis showed that the study watersheds had four dominant nitrate transport patterns from landscapes to streams with increasing discharge, including the flushing pattern being the most dominant one. Stream nitrate estimation impedes due to data inadequacy. The modeling framework can be used to generate temporally continuous nitrate at nitrate data-limited regions with a nearby sensor-based nitrate gauge. Watershed planners and policymakers could utilize the continuous nitrate data to gain more information on the regional nitrate status and design conservation practices accordingly.

Evaluation of nitrate concentrations in groundwater of Llío and San Pablo, Guano – EC

This paper analyzes the groundwater of the Chambo aquifer in the Llío and San Pablo sector, with emphasis on the temporary alternation of nitrate concentration, identifying the anthropogenic activities that may influence this area. This from the cartographic definition of the areas of begging influence the crossing of geological, hydraulic and anthropic activities. The temporality of the geochemical data is 5 years (2016-2020), these results show that water quality meets the requirements of the Ecuadorian national standard, and that the main composition of water is bicarbonated type of calcium-magnesium. Even if the groundwater in this sector meets the standard, variation in nitrate concentration is evident. This type of concentration is presented by the effect of agricultural activities on the surface of the soil, where nitrates occur naturally due to the nitrogen cycle, and that are dragged into the water table by infiltration when the rainy season occurs. In addition, it was found that the type of rock found underground cannot naturally generate nitrates.

Assessment of land use and monsoon impact on high nitrate groundwater and health risk in the hard rock aquifer, South India.

Groundwater sustainability in hard rock aquifers is compromised largely due to nitrate contamination from anthropogenic sources resulting in diminishing potable resources and attendant health issues. A purpose-driven study through an integrated approach was undertaken in the area of interest (hard rock aquifer) to assess the variations in nitrate concentration and resultant health impacts in response to variations in monsoon and land use patterns. Groundwater samples (n = 284) were collected for a period of three years (2017-2019) and analysed. From the analytical data, it is inferred that 27% and 9% of groundwater samples in the study area have high NO3- values of > 45mg/l and > 100mg/l, respectively. NO3- contamination zones mapping illustrates that NO3-contaminated area (> 45mg/l) varied seasonally 1164 km2 (2017), 1086 km2 (2018) and 1640 km2 (2019)) and high-risk area (NO3- > 100mg/l) has reduced drastically during 2018 due to dilution by monsoon (277 km2 (2017), 41 km2 (2018), 634 km2 (2019)). The lowest NO3- and Cl-concentrations are recorded during 2018 which coincides with high rainfall (2061mm). NO3- concentrations in response to land use pattern indicate that the hot spots (NO3- > 45mg/l and > 100mg/l) are observed in groundwater samples of residential areas which are vulnerable to contamination from domestic wastewater, septic tanks and other pollutants. Further, wastewater infiltration facilitated the dissolution of certain minerals in the unsaturated zone which enhanced the accumulation of NO3- and other ions in this aquifer. Mineral weathering, denitrification and evaporation processes also affected the groundwater chemistry. The health risk model (HQoral) indicates that groundwater in 1261 km2 (2017), 1232 km2 (2018) and 1669 km2 (2019) is unsuitable for drinking (HQ > 1) and causes adverse health risks to the local inhabitants. The study has identified areas from the central and southeastern regions significantly affected by nitrate pollution underpinning the necessity of using treated groundwater for drinking purposes.

Spatio-temporal variation of nitrate based on Landsat 8 in Playa Colorada bay, Sinaloa, Mexico.

Characterizing water quality in coastal waters through spatial observations is challenging, due to spatial and temporal variations in water composition. Nitrate, an important compound for water quality assessment, has received little attention in estimates made from satellite measurements, even though it can be estimated using models generated from multispectral images. Since nitrate is a non-optically active parameter that can be correlated with optically active parameters, it was related to bands of the visible and infrared spectrum, captured in Landsat-8 images, and used to generate empirical models to estimate the spatio-temporal variation of nitrate concentration in the Playa Colorada Bay, in the state of Sinaloa Northwest Mexico. Four sampling campaigns were performed, two in spring and two in fall. Nitrate nitrogen (NO3-N) concentration ranged between 0.69 and 1.80mg/L, values higher than those recommended in the Mexican ecological criteria of water quality for the protection of marine aquatic life in coastal areas. Generated models showed a significant relationship (P < 0.05) between NO3-N and band reflectance in the infrared (band 5) and short-wave infrared (band 6 and band 7) spectra of Landsat-8 imagery. The B6 band appeared in all models selected to estimate NO3-N in the bay. These results evidence the potential of Landsat-8 images for the estimation of nitrate in the coastal waters of Sinaloa, México.

Patterns of long-term variations of nitrate concentration – Stream discharge relationships for a drained agricultural watershed in Mid-western USA

Nitrate Concentration–discharge (C-Q) relationshipshave been used to infer nitrate sources, storage, reactions, and transport in watersheds, and to reveal key processes that control runoff chemistry. Yet, studies on long-term nitrate C-Q relationships are limited due to scarce high frequency (e.g., daily) concentration data. In this paper, using a long-term high-frequency dataset (1976–2019) comprising stream flow and nitrate concentrations, we quantitatively analyzed the long-term variations of event-scale hysteresis patterns (quantified by hysteresis index, HI, and flushing index, FI) to infer the leaching mechanisms of nitrate in an artificially drained agricultural watershed in Mid-western U.S. Our results revealed that most events exhibited anti-clockwise behaviors (HI < 0), regardless of whether nitrate was flushed or diluted during events. This means that water with high levels of nitrate-N reaches the stream network slower than water with lower nitrate concentrations. Long-term mean FI was close to zero but had strong seasonal patterns with dilution patterns observed during Winter and Summer, and flushing patterns during late Spring and Fall. The consistently negative HI values regardless of the FI value gave a strong indication of the preponderant role of the near-drain zone that usually exhibits accelerated leaching and less accumulation of nitrate in the soil profile in these drained agricultural watersheds. Both HI and FI depicted strong but opposite seasonality because of weather patterns and agricultural activities, particularly N fertilization. Overall, our findings suggest a little evidence of the role of deep groundwater and instead a strong evidence of the role of subsurface drainage as the primary pathway for nitrate transport in drained agricultural watersheds. Therefore, artificial drainage could dampen N legacy caused by the historically intensive N fertilization in drained agricultural landscapes.

Variation of nitrate concentration and light level on growth rate of diatom Chaetoceros muelleri

Microalgae are cultured as natural feed for the cultivation of mollusks, crustaceans (early larval stages), and zooplankton. Diatoms are phytoplankton groups commonly used as feed, one of which is Chaetoceros muelleri. This study aims to identify the optimal nitrate concentrations and light level (irradiance) for the growth rate of C. muelleri. Culture was placed in nitrate 1,330; 5,305; and 27,030 mg/L (N1, N2, N3, respectively); and light 50, 100, and 150 µmol/m2/s, with three replications for each treatment. The response variable observed was the growth rate of C. muelleri and nitrate uptake. Each nitrate treatment resulted in a significant difference in the growth rate of C. muelleri (LSD, p &lt; 0.01). The N3 treatment produced the highest growth rate (average 0,188-0,193 cells/day), while N1 produced the lowest specific growth rate (average 0,149-0,157 /day). In light treatment, a significant difference was only seen in the light levelof 150 µmol/m2/s (LSD, p &lt; 0.05) which produced the highest growth rate (average 0.157-0.193 cells/day), especially in the nitrate N1 and N2. Meanwhile based on the significance test, the interaction between nitrate and light treatment was not significant.Keywords: Chaetoceros muelleri; Growth rate; Irradiance; Nitrate

NIT-DRAIN model to simulate nitrate concentrations and leaching in a tile-drained agricultural field

Agricultural pollution, due to excessive land fertilization, affects the quality of both surface and ground water. This paper presents a conceptual and reservoir-based model that simulates the time variation of nitrate concentrations [NO3-] at the outlet of a subsurface drainage network, referred to herein as “NIT-DRAIN.” The model is based on a simplified scheme of water and nitrate transfer processes by decomposing the soil profile located between the drain and the mid-drain into three interconnected and conceptual compartments. Hence, the fast transfer throughout the macroporosity located above the pipe is described by the first compartment while the low and residual nitrate transfers are managed by the two other compartments. The model assumes that all seasonal nitrogen transformations at the field scale lead to the remaining pool of nitrate available for leaching at the beginning of the winter season (RNBW). This variable is updated by the model at the beginning of each hydrological year. The NIT-DRAIN model requires two input data: the measured or simulated drainage discharge and the RNBW. Seven parameters were introduced to manage nitrate leaching and water flow through the three soil compartments using two different transfer functions. The calibration and validation step (C/V) was performed to assess the performance of the model in reproducing the nitrate concentration observations acquired at Rampillon (355 ha, data for 6 years), located east of Paris, France. The results showed performance criteria of KGE greater than 0.5 and of RMSE less than 5 mgNO3-/l, which confirm the ability of the model to simulate the observed nitrate concentrations with a good agreement. The annual model calibration framework, implemented to assess the parameter variability, confirms the model stability and consistency. However, the use of simulated drainage discharges as input underlines the need to reproduce with accuracy the earlier low discharge values by the drainage model. The innovative management of nitrate transfer through the conceptual compartments based on the annual update of the RNBW variable enables the simulation of the nitrate concentrations with a high performance using a limited number of input data. In addition, the periods of flushing and dilution are clearly identified by the NIT-DRAIN model thanks to the accurate estimation of the nitrate storage variation inside each model compartment.

Rice transcription factors OsLBD37/38/39 regulate nitrate uptake by repressing OsNRT2.1/2.2/2.3 under high-nitrogen conditions

Nitrate (NO3−) uptake involves a finely regulated and complex multilevel response system. Elucidating the molecular mechanism of nitrate uptake may lead to improving the growth and productivity of plants in the presence of dynamic variation in nitrate concentration. In this study, we identified three lateral organ boundaries domain (LBD) transcription factors, OsLBD37, OsLBD38, and OsLBD39, as regulators of nitrate uptake in response to nitrogen (N) availability. OsLBD37, OsLBD38, and OsLBD39 were induced by ammonium and glutamine in rice roots. Individual or collective knockout of OsLBD37, OsLBD38, and OsLBD39 led to increased concentrations of nitrate and increased expression of OsNRT2.1, OsNRT2.2, and OsNRT2.3 respectively under high-N conditions, whereas overexpression of each of these three LBD genes produced opposite effects where N accumulation was reduced. Dual-luciferase reporter assay further confirmed that OsLBD37, OsLBD38, and OsLBD39 possessed transcription inhibitory activities in rice protoplast cells, downregulating the expression of OsNRT2.1/OsNRT2.2/OsNRT2.3. Yeast two-hybrid and bimolecular fluorescence complementation assays showed that OsLBD37 interacted with OsLBD37, OsLBD38, and OsLBD39 in the nucleus. Together, these results show that OsLBD37, OsLBD38, and OsLBD39 collaborate to inhibit the expression of OsNRT2.1/OsNRT2.2/OsNRT2.3 transporters under N-sufficient conditions, thereby helping rice plants avoid excessive nitrate accumulation that may affect their growth.

A Mathematical Model Development for Simulating Nitrate Pollutant Transport along a River

Contamination of surface water bodies by a wide range of organic and inorganic pollutants has been a serious problem in the recent time, these have an effect on human and aquatic animals. The water quality deterioration calls for regular monitoring of the water quality in order to maintain the health and sustainability of the aquatic ecosystems. Accurate monitoring of discharged pollutants into the rivers may be time taking and labour intensive. Water quality models are significant tools for simulating water quality and controlling the surface water pollution. The purpose of this study is to develop a simplified mathematical model which is hybrid cells in series model (HCIS) to simulate the spatial and temporal variation of nitrate concentration in natural rivers. The HCIS model was formulated to serve as an alternative method to the Fickian based models. Analytical solutions for the first order reaction kinetics of nitrate with the advection and dispersion process were derived using Laplace transformation technique. The model considered the effect of nitrate concentration at several points along the river downstream by considering the transformation of nitrite to nitrate through nitrification process. In addition, the uptake of nitrate by algae for its growth and conversion of nitrate to nitrogen gas due to denitrification process were considered. The HCIS-NO3 model was applied to uMgeni River, South Africa to investigate the nitrate concentration along the river. Furthermore, the quantitative measures based on the coefficient of determination (R2) and standard errors (SE) were used to evaluate the performance of the model. The result shows that the simulated values agreed with the measured values of nitrate concentration in the river which resulted in a R2 value of 0.72 and a low standard error. Analytical solutions of HCIS - NO3 model were compared with the numerical solutions of the Fickian based ADE model for hypothetical problems. Comparison of the responses indicates that the HCIS - NO3 and ADE- NO3 models were in good agreement. The study shows that the hybrid model is a simple and effective tool for simulating pollutant transport in natural rivers.

Evaluation of the groundwater resources vulnerability index using nitrate concentration prediction approach

This study evaluates the vulnerability of aquifers to the nitrate concentration variations. Prediction of nitrate concentration using MT3DMs modeling for a period of 10 years. The results showed that most of the wells have faced concentration increment, where it is exacerbated in the lower areas of agricultural and urban lands. The prediction of nitrate concentration zoning map obtained from the model was used to calibrate the DRASTIC vulnerability index in the aquifer. The AHP and Wilcoxon method was applied to calibrate the parameters of the DRASTIC index. The final results of the vulnerability index showed that the central aquifer parts located downstream of the agricultural lands and urban areas along the main drainage had the highest vulnerability degree. Correlation analysis showed that the correlation coefficient improved from 0.47 to 0.72, and the accuracy of the index was increased to identify the areas susceptible to development where have the least vulnerability.

Health Risk Assessment for Exposure to Nitrate in Drinking Water in Central Java, Indonesia.

Since 2005, over 30 epidemiological studies have evaluated the association between nitrate in drinking water and adverse health outcomes. Conditions that lead to nitrate pollution in water, such as open defecation, the proximity of septic tanks to water sources, and the use of inorganic fertilizer, are rampant in Indonesia, which has experienced little research evaluating nitrate in drinking water. We conducted a health risk assessment for exposure to nitrate in drinking water and evaluated the nitrate concentration in key water sources in two villages of rural Central Java, Indonesia. The nitrate concentrations in the drinking water ranged from 3.55 mg/L to 26.75 mg/L as NO3−. Daily nitrate intake estimates, calculated at 50% and 95% exposure to the maximum nitrate concentration of the drinking water in both villages, were above the levels associated with birth defects, colorectal cancer, and thyroid conditions observed in other studies. There was a large variation in nitrate concentrations between and within the villages at different water sources. Further research into whether these health outcomes exist in rural Central Java, Indonesia will be required to better understand this risk.

Spatiotemporal variation of nitrate concentrations in soil and groundwater of an intensely polluted agricultural area

Nitrate pollution in groundwater is a serious problem in many parts of the world. However, due to the diffuse and common spatially over-lapping character of potential several non-point pollution sources, it is often difficult to distinguish main nitrate sources responsible for the pollution. For this purpose, we present a novel methodology applied to groundwater for an intensely polluted area. Groundwater samples were collected monthly from April 2017 to March 2018 in Shimabara City, Nagasaki, Japan. Soil samples were collected seasonally at soil surface and 50 cm depth at 10 locations during the same period. Sequential extraction by water and extract agents was performed using calcium phosphate for anions and strontium chloride for cations. Mean nitrate concentration in groundwater close to a livestock waste disposal site (hereinafter called “LWDS”) was 14.2 mg L−1, which is exceeding Japanese drinking water standards (10 mg L−1). We used coprostanol concentration, which is a fecal pollution indicator, to identify pollution sources related to livestock waste. For this purpose, we measured coprostanol (5β) and cholestanol (5α) and then calculated the sterol ratio (5β/(5β + 5α)). The ratios for three groundwater sampling sites were 0.28, 0.26, and 0.10, respectively. The sterol ratios indicated no pollution (< 0.3). However, the detection of coprostanol originating from animal and human waste showed that groundwater was clearly affected by this pollution source. Nitrate levels in the soil were relatively high in samples collected close to the LWDS and coprostanol contents were affected by livestock waste. Soil and groundwater nitrate concentrations displayed a complex but strong relationship. Nitrate contents were shown to be transported downstream from source areas in both soil and groundwater.

Exposure and health risk assessment of nitrate contamination in groundwater in Coimbatore and Tirupur districts in Tamil Nadu, South India

Anthropogenic factors are contaminating crystalline aquifers more rapidly than natural sources and affecting human health in many states in India. Since a large population depends on untreated groundwater, identifying the sources of this contamination and assessing the related human health risk are essential to ensure a good-quality water supply. Nitrate is one of the most widespread means of groundwater contamination in many parts of India. Coimbatore and Tirupur districts are the most rapidly growing industrial urban areas in southern India. This paper deals with nitrate contamination and possible health risks for children and adults in the Coimbatore and Tirupur districts based on 93 groundwater samples. To achieve this goal, classical hydrochemical and deterministic hazard identification methods coupled with spatial mapping technologies were applied. A wide variation in nitrate concentration, between 1 and 415 mg/L, was observed, with 37% of the samples exceeding the WHO permissible limit of 50 mg/L. The distinct concentrations of nitrate and other ions observed spatially can be attributed to the diverse geochemical and land use settings in the study area. The bivariate plots of NO3 with other ions suggested that the principal origin of nitrate in this study is related to the excess application of fertilizers and sewages. The spatial variation of NO3, in comparison with the land use map, confirmed these results. The values of hazard quotient (HQ) via ingestion exceeded the critical value, one in 40% in males, 42% in females, and 45% in children. However, HQ values via oral pathways are within one and pose no exposure risk. Thus, the hazard index corresponds to HQingestion only. The health risk was in the increasing order of male>female>children, and shows that body weight is the most critical factor that is influencing the health impact to children as compared to adults. The spatial variation of hazard index values showed that groundwater quality is highly polluted with NO3 in the north and northeastern parts of the study area, mainly due to intensive agricultural practices, and poses critical health concerns. Considering the increasing population and higher dependencies on groundwater, immediate and sufficient measures are proposed.

Linking nitrate dynamics to water age in underground conduit flows in a karst catchment

Although numerous studies on nitrate transport and transformation in karst catchments have been reported, many challenges in understanding nitrate fluxes remain due to the unique architecture of karst critical zones and complex hydrological processes. Water age is an important descriptor of hydrological function providing insight to into flow paths and water sources at the catchment scale. This offers a potential opportunity to better understand the spatio-temporal variations in nitrate dynamics in karst catchments. We linked the nitrate dynamics of underground conduit flow to water age extracted from a robust tracer-aided model for a karst catchment in southwestern China. The results show that nitrate dynamics in underground conduit flow are controlled by the coupling of nitrate supply and of flow paths in the karst catchment. High contributions of drainage from small fractures water leads to low nitrate concentrations in underground conduit flow during the dry season. This reveals that the small fractures may be another important “hot spot” for denitrification leading to nitrate removal in the karst critical zone. The switching between transport limited and supply limited conditions cause the marked variations in nitrate concentration of underground conduit flow during wet season. Although rapid infiltration via large fractures and sinkholes have strong dilution effects on nitrate in underground conduit flow at beginning of rainfall, more nitrate was transported out of the catchment with drainage during rainfall events due to the mobilization of soil nitrate by rainfall. Meanwhile, the capacity to transport nitrate out of catchment can be potentially activated when the ‘old’ water is displaced by rainfall under high wetness condition.

Deep Nitrate Accumulation in a Highly Weathered Subtropical Critical Zone Depends on the Regolith Structure and Planting Year

Nitrate accumulated deep (>100 cm) in the regolith (soil and saprolite) threatens groundwater quality, but most studies focus only on nitrate nearer the surface (<100 cm). Surface soil management versus regolith interactions affect deep nitrate leaching, but their combined impact remains unclear. This study measured how deep nitrate accumulation was affected by crop practices including orchard/cropland planting years, regolith structure, and soil properties in highly weathered subtropical red soils. Deep nitrate storage varied from 43.6 to 1116.3 kg ha-1. Regolith thickness was positively correlated with nitrate storage (R2 = 0.43, p < 0.05). Reticulated red clay (110-838 cm) had 81% of the accumulated nitrate and overlapped with 79% of the nitrate accumulation layer. All of the nitrate accumulation parameters (except for peak depth (PD)) generally increased with the planting years. The difference in peak nitrate concentration (9.0-20.0 mg kg-1) with planting year gradient (3-58 years) varied by 2.2 times, and the difference in nitrate storage (43.6-425.7 kg ha-1) varied by 9.8 times. Texture and pH explain 41.6% of the variation in nitrate concentration. As soil management practices interact with deeper regolith to control the spatial pattern of nitrate accumulation, vulnerable regions could be identified to avoid high accumulation.

Spatial and temporal variability in discharge and nitrate in Iowa subsurface drains.

Agricultural subsurface drainage can be an important conduit of nitrate from agricultural fields to streams. This study focused on understanding the variability in nitrate concentrations and loads, exported by subsurface drains, into a small, north-central Iowa stream. Ninety-three subsurface drains in this watershed were sampled up to 5 times between 2006 and 2008. Additionally, 2 subsurface drains and the stream draining the study area (South Fork Iowa River near Blairsburg, IA, USA) were sampled frequently during the growing seasons in 2007 and 2008. Spatial variability analysis revealed no distinct spatial pattern in nitrate concentrations. The median nitrate concentrations were not significantly different when the drain outlets were characterized by diameter (17-23 cm, 27-48 cm, 60-108 cm). The eight large subsurface drains (part of the public drainage network) had less variability in nitrate concentration than the smaller drain sizes and generally contributed 70-87% of the total water and nitrate loads exported by subsurface drains to the stream. During high-discharge events, the medium-sized (27-48 cm) subsurface drains discharging to the stream became more important by contributing a higher discharge and nitrate load. The temporal variability examined in this study found that discharge and nitrate loads were influenced by the amount of precipitation that had occurred over the previous months. This paper demonstrates the spatial and within-season homogeneity of nitrate delivery to a stream from an intensely agricultural landscape that has subsurface drainage.