Risk Of Nitrate Contamination Research Articles

The Evaluation of a Novel Denitrifying Woodchip Bioreactor: Fairmont, MN, USA

The risk of nitrate contamination became a reality for Fairmont in Minnesota, when water rich in NO3-N exceeded the drinking water standard of 10 mg/L. This was unexpected because this city draws its municipal water from a chain of lakes that are fed primarily by shallow groundwater under row-crop land use. Spring soil thaw drives cold water into a subsurface pipe where almost no NO3-N reduction occurs. This paper focuses on NO3-N reduction before the water enters the lakes and no other nitrogen management practices in the watershed. A novel denitrifying bioreactor was constructed behind a sediment forebay, which then flowed into a chamber covered by a greenhouse before entering a woodchip bioreactor. In 2022 and 2023, water depth, dissolved oxygen, and temperature were measured at several locations in the bioreactor, and continuous NO3-N was measured at the entry and exit of the bioreactor. The results showed better performance at a low water depth with lower dissolved oxygen and higher water temperature. The greenhouse raised the inlet temperature in 2022 but did not in 2023. The forebay and the greenhouse may have impeded the denitrification process due to the high dissolved oxygen concentrations in the influent and the stratification of dissolved oxygen caused by algae in the bioreactor.

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

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

RISK ASSESSMENT OF NITRAT CONTAMINATED IN GROUNDWATER IN GIAO THUY DISTRICT, NAMDINH PROVINCE, VIETNAM

Environmental pollution due to agricultural production activities, and the use of fertilizers and pesticides is a matter of great concern due to its harmful effects on the soil environment, water environment, and ecosystems. In this study, the risk of nitrate contamination in shallow groundwater related to agricultural land was evaluated using DRATIC and IPNOA models with 66 soil samples and 132 groundwater samples. The results showed that hazard was found at very low with HI values ranging from 3.5-6.06. The RI of nitrate-contaminated groundwater from agricultural activities is in the range of 539 - 1058. The assessment results show that the vulnerability index has a significant impact on the RI index, and areas with a high vulnerability index have a higher risk of groundwater pollution. The NO3- concentration seems to be stable, ranging from 0.02 to 0.11 mg/l, and all meet with the QCVN 09:2018/BNTMT for groundwater quality. No clear correlation between vulnerability factor and risk factor with NO3- concentration in groundwater.

Predicting Regional-Scale Elevated Groundwater Nitrate Contamination Risk Using Machine Learning on Natural and Human-Induced Factors

Predicting Regional-Scale Elevated Groundwater Nitrate Contamination Risk Using Machine Learning on Natural and Human-Induced Factors

Assessing Nitrate Contamination Risks in Groundwater: A Machine Learning Approach

Groundwater is one of the primary sources for the daily water requirements of the masses, but it is subjected to contamination due to the pollutants, such as nitrate, percolating through the soil with water. Especially in built-up areas, groundwater vulnerability and contamination are of major concern, and require appropriate consideration. The present study develops a novel framework for assessing groundwater nitrate contamination risk for the area along the Karakoram Highway, which is a part of the China Pakistan Economic Corridor (CPEC) route in northern Pakistan. A groundwater vulnerability map was prepared using the DRASTIC model. The nitrate concentration data from a previous study were used to formulate the nitrate contamination map. Three machine learning (ML) models, i.e., Support Vector Machine (SVM), Multivariate Discriminant Analysis (MDA), and Boosted Regression Trees (BRT), were used to analyze the probability of groundwater contamination incidence. Furthermore, groundwater contamination probability maps were obtained utilizing the ensemble modeling approach. The models were calibrated and validated through calibration trials, using the area under the receiver operating characteristic curve method (AUC), where a minimum AUC threshold value of 80% was achieved. Results indicated the accuracy of the models to be in the range of 0.82–0.87. The final groundwater contamination risk map highlights that 34% of the area is moderately vulnerable to groundwater contamination, and 13% of the area is exposed to high groundwater contamination risk. The findings of this study can facilitate decision-making regarding the location of future built-up areas properly in order to mitigate the nitrate contamination that can further reduce the associated health risks.

Development of a groundwater contamination index based on the agricultural hazard and aquifer vulnerability: Application to Portugal

Reducing nitrate leaching may not result in a significant improvement of groundwater quality. The amount of nitrate reaching groundwater depends not only on the hazard related to agricultural activities but also on-site specific groundwater vulnerability. Using national databases and other compiled datasets, the agricultural hazard was calculated as the ratio of (i) the nitrate leached estimated from the N surplus, and (ii) the water surplus, a proxy of the percolating water below the root zone. By combining the hazard with a multi-parameter groundwater vulnerability, a spatially explicit groundwater contamination risk, developed for mainland Portugal, was computed for 1999 and 2009. Results show an increase from 8,800 to 82,679 ha of the territory rated with a very high contamination risk. The priority areas were successfully screened by the Index, coinciding with the current Vulnerable Zones, although additional hotspots were detected in southern Portugal. Percolation, including both irrigation activity and precipitation, was found to be a key driver for the groundwater contamination risk due to its opposite effects in the hazard and in the vulnerability. Reducing nitrogen leaching may be insufficient to reduce the risk of nitrate contamination if there is a relatively larger reduction in precipitation. This index is particularly useful when applied to contrasting situations of vulnerability and hazard, which require distinct mitigation measures to mitigate groundwater contamination.

In Search for the Missing Nitrogen: Closing the Budget to Assess the Role of Denitrification in Agricultural Watersheds

Although representing a paramount mechanism against nitrogen excess in agricultural landscapes, soil denitrification is still a largely unknown term in nitrogen balances at the watershed scale. In the present work, a comprehensive investigation of nitrogen sources and sinks in agricultural soils and waters was performed with the aim of gaining insights into the relevance of soil denitrification in a highly farmed sub-basin of the Po River delta (Northern Italy). Agricultural statistics, water quality datasets, and results of laboratory experiments targeting nitrogen fluxes in soils were combined to set up a detailed nitrogen budget along the terrestrial–freshwater continuum. The soil nitrogen budget was not closed, with inputs exceeding outputs by 72 kg N·ha−1·year−1, highlighting a potential high risk of nitrate contamination. However, extensive monitoring showed a general scarcity of mineral nitrogen forms in both shallow aquifers and soils. The present study confirmed the importance of denitrification, representing ~37% of the total nitrogen inputs, as the leading process of nitrate removal in heavily fertilized fine-texture soils prone to waterlogged conditions.

Regional simulation of nitrate leaching potential from winter wheat-summer maize rotation croplands on the North China Plain using the NLEAP-GIS model

Identifying the regional characteristics of nitrate leaching from croplands is of great importance when attempting to assess the groundwater contamination risk due to nitrate leaching from croplands. The regional scale model in the Nitrogen Loss and Environmental Assessment Package with GIS Capabilities (NLEAP-GIS), which takes spatial variations in soil profile properties, meteorological data, and farm practices into account, was adopted in this study to simulate the occurrence dynamics and spatial pattern of nitrate leaching downwards through the crop root zone (0–100 cm) in winter wheat (Triticum aestivum L.)-summer maize (Zea mays L.) rotation croplands during 2011 and 2012 across the Jing-Jin-Ji region on the North China Plain (NCP). The results showed that the monthly nitrate leaching occurrences were driven by rainfall, irrigation, and fertilizer application. The simulated large spatial variation in cumulative nitrate leaching was positively correlated with both rainfall and fertilizer N application rates, whereas it was negatively correlated with N use efficiency. The cumulative nitrate leaching was mostly lower than 10 kg N ha–1 during the winter wheat growing season, whereas nitrate leaching during the summer maize growing season was much higher and mostly ranged from 20 to 100 kg N ha–1. The average cumulative nitrate leaching in the winter wheat-summer maize rotation system was 55.7 ± 33.5 kg N ha–1, accounting for 17.2 ± 10.2 % of the fertilizer N applied (average 176.3 ± 86.2 kg N ha–1 during each crop season). Fertilizer N application rates of 100–200 kg N ha–1 are recommended during each winter wheat and summer maize season to simultaneously achieve higher grain yields, greater N use efficiency, and a lower groundwater nitrate pollution risk on the NCP. The simulated spatial variation in nitrate leaching implied that there was a potential nitrate groundwater contaminant source and the results contributed to the spatial distribution assessment of groundwater nitrate contamination risk caused by fertilizer N inputs.

Nitrate contamination risk of the Zagreb aquifer

ABSTRACT Nitrates present one of the main groundwater contaminants in the world and in the Zagreb aquifer. In order to reduce nitrate concentrations in groundwater, it is necessary to spatially define main nitrogen sources and areas which have the highest risk of nitrate contamination. This paper presents a map of nitrate contamination risk in the area of the Zagreb aquifer. It was constructed based on nine different layers that include natural characteristics and anthropogenic pressures. For the construction of the Main map, which has been defined as the most representative one, 15 different variations have been tested. The Main map has shown that the urban part of the City of Zagreb, especially central and eastern parts, together with the area of Jakuševec landfill and marshalling station, present areas with the highest risk of nitrate contamination, which is consistent with the results of previous research.

Ion exchange resin samplers to estimate nitrate leaching from a furrow irrigated wheat-maize cropping system under different tillage-straw systems

Nitrate (NO3-N) leaching from agricultural soils can lead to substantial losses of fertilizer nitrogen (N) and cause considerable contamination of aquatic ecosystems and groundwater. This study aimed at estimating NO3-N leaching losses for three tillage-straw management systems in the intensely cropped Yaqui Valley, Northern Mexico using ion exchange resin samplers. To this end data were collected in 2013/2014 from a tillage experiment established in 2005 as a randomized complete block design with two replications and three subplots on a Hyposodic Vertisol. Tillage-straw treatments were conventionally tilled beds with incorporated crop residue (CTB-straw incorporated), permanent beds with crop residue retained at the surface (PB-straw retained) and permanent beds with residue burning (PB-straw burned). Ion exchange resin samplers were installed at 90cm depth in a consecutive crop rotation of wheat (Triticum durum L.) and maize (Zea mays L.) for 6 and 5 months, respectively (from first pre-plant fertilization to harvest). Leaching losses were higher with maize than with wheat cultivation (68.2 and 53.5kgha−1 season−1 NO3-N; P=0.25). Tillage-straw treatment did not significantly affect NO3-N leaching in wheat, but it did in maize. NO3-N leaching for wheat was 51.1kgha−1 season−1 NO3-N in CTB-straw incorporated, 60.8kgha−1 season−1 NO3-N in PB-straw retained and only 46kgha−1 season−1 NO3-N in PB-straw burned. For maize, overall leaching losses were highest for PB-straw retained (81.9kgha−1 season−1 NO3-N), followed by 75.6kgha−1 season−1 NO3-N for CTB-straw incorporated and 47.7kgha−1 season−1 NO3-N for PB-straw burned. Soil NO3-N concentrations were significantly affected by sampling date and depth. PB-straw burned had highest residual soil NO3-N after crop harvest. Ion exchange resins-based NO3-fluxes displayed high spatial variability, therefore a large number of repetitions was necessary. As 19% of N applied to wheat and 34% of N applied to maize was lost through leaching, farming practices that could lower the risk of nitrate contamination during cropping should be promoted. Additional multi-annual studies are necessary to assess the effects of reduced irrigation, climatic variation and different fertilizer application on nutrient leaching in different tillage-straw systems of northwestern Mexico.

Methodological approach to assessment of groundwater contamination risk in an agricultural area

Water contamination by nitrates of agricultural origin is a major problem in Sardinia (Italy) where Nitrate Vulnerable Zones (NVZs) has been identified in the Arborea reclamation area (W. Sardinia), where intensive agriculture and farming are the mainstays of the local economy. Agricultural practices have seen an increase in the use of animal and chemical fertilizers for enhancing soil productivity. This, accompanied by the intensive use of groundwater resources for irrigation has led to the deterioration of groundwater quality, in areas particularly vulnerable to nitrate contamination. In the test area, the intrinsic nitrate contamination risk from agricultural sources has been evaluated through the combined application of the parametric methods, SINTACS, SI and IPNOA. Risk assessment, using vulnerability and hazard mapping, is considered a fundamental aspect of sustainable groundwater management. All parameters used in this risk assessment were prepared, classified, weighted and integrated in a GIS environment. Results show that nitrate concentrations are located in those areas where agricultural and livestock farming are concentrated. These results could, consequently, be interesting for future development and long term planning of groundwater protection management. The risk methods adopted, verified by comparing the distribution of nitrates in the groundwater with the different vulnerability classes, proved to be a valid tool. In fact the areas with nitrate concentration of more than 100mg/l coincide well with those at high risk identified by the model and the areas with nitrate concentration of less than 25mg/l closely match those areas with low and moderate risk.

Land-use change and costs to rural households: a case study in groundwater nitrate contamination

Loss of grassland from conversion to agriculture threatens water quality and other valuable ecosystem services. Here we estimate how land-use change affects the probability of groundwater contamination by nitrate in private drinking water wells. We find that conversion of grassland to agriculture from 2007 to 2012 in Southeastern Minnesota is expected to increase the future number of wells exceeding 10 ppm nitrate-nitrogen by 45% (from 888 to 1292 wells). We link outputs of the groundwater well contamination model to cost estimates for well remediation, well replacement, and avoidance behaviors to estimate the potential economic value lost due to nitrate contamination from observed land-use change. We estimate $0.7–12 million in costs (present values over a 20 year horizon) to address the increased risk of nitrate contamination of private wells. Our study demonstrates how biophysical models and economic valuation can be integrated to estimate the welfare consequences of land-use change.

Assessment of groundwater contamination in an agricultural peri-urban area (NW Portugal): an integrated approach

The excessive use of pesticides and fertilisers in agriculture has generated a decrease in groundwater and surface water quality in many regions of the EU, constituting a hazard for human health and the environment. Besides, on-site sewage disposal is an important source of groundwater contamination in urban and peri-urban areas. The assessment of groundwater vulnerability to contamination is an important tool to fulfil the demands of EU Directives. The purpose of this study is to assess the groundwater vulnerability to contamination related mainly to agricultural activities in a peri-urban area (Vila do Conde, NW Portugal). The hydrogeological framework is characterised mainly by fissured granitic basement and sedimentary cover. Water samples were collected and analysed for temperature, pH, electrical conductivity, chloride, phosphate, nitrate and nitrite. An evaluation of groundwater vulnerability to contamination was applied (GOD-S, Pesticide DRASTIC-Fm, SINTACS and SI) and the potential nitrate contamination risk was assessed, both on a hydrogeological GIS-based mapping. A principal component analysis was performed to characterised patterns of relationship among groundwater contamination, vulnerability, and the hydrogeological setting assessed. Levels of nitrate above legislation limits were detected in 75 % of the samples analysed. Alluvia units showed the highest nitrate concentrations and also the highest vulnerability and risk. Nitrate contamination is a serious problem affecting groundwater, particularly shallow aquifers, especially due to agriculture activities, livestock and cesspools. GIS-based cartography provided an accurate way to improve knowledge on water circulation models and global functioning of local aquifer systems. Finally, this study highlights the adequacy of an integrated approach, combining hydrogeochemical data, vulnerability assessments and multivariate analysis, to understand groundwater processes in peri-urban areas.

Nitrogen fertigation: An integrated agronomic and environmental study

Proper management of the N applied to crops is necessary in order to increase yield, improve water use efficiency (WUE) and reduce the pollutions risks with the least economic, environmental and health costs. A field study with melon crops was conducted during 2005, 2006 and 2007 in central Spain, using 11 different amounts of N. Some environmental indexes have been proposed, to provide an essential tool for determining the groundwater pollution risks associated with common agricultural practices. These indexes are related to variation in the nitrate concentration of drinking water (Impact Index (II)) and groundwater (Environmental Impact Index (EII)). Also, the Management Efficiency (ME) was calculated, which is related to the amount of fruit produced per gram of N leached (Nl). To determine the optimum dose of N, it was also necessary to know the N mineralisation (NM). Our results show that 160kgha−1 of available N (Nav) produced the maximum fruit yield (FY), enhanced WUE and gave an NM of 85kgha−1, while the impact indexes did not exceed the fixed maximum allowable limits and ME was adequate. The proposed indexes proved to be an effective tool for determining the risk of nitrate contamination and confirmed that the optimum dose of N corresponded to the maximum FY with minimal loss of Nl.

Broiler Litter vs. Ammonium Nitrate as Nitrogen Source for Bermudagrass Hay Production: Yield, Nutritive Value, and Nitrate Leaching

ABSTRACTThe Lower Suwannee River Basin (LSRB) in northern Florida is environmentally sensitive. This study evaluated two surface‐applied N sources for ‘Tifton 85’ bermudagrass (Cynodon spp.) hay production and associated risk of nitrate contamination of groundwater. The study was conducted at two locations in the LSRB where soils are deep, sandy Entisols. During a 2.5‐yr period, bermudagrass received sole N source ammonium nitrate (AN), applied at 42, 84, 126, and 168 kg N ha−1 per growth interval, or sole N source broiler (chicken, Gallus gallus domesticus) litter (BL), applied at 84 and 126 kg N ha−1 Plots were arranged using a randomized block design with three or four replications depending on the location. Suction‐cup lysimeters were installed at a 1.4‐m soil depth to monitor nitrate movement from the primary rooting zone. For AN, dry matter yield and crude protein (CP) concentration increased with an increase in N level, while forage P declined and in vitro digestible organic matter increased. Forage yield with BL was 64, 48, and 67% of yield with AN applied at common levels in 1998, 1999, and 2000, respectively. Forage CP was mostly less for BL than for AN, but forage P was greater for BL. A potential risk to groundwater quality due to nitrate leaching below the primary rooting zone was observed only with AN applied at 168 kg N ha−1 Probable ammonia emissions from surface‐applied BL, however, likely resulted in poorer bermudagrass production and could impact nearby surface waters.

Assessment of nitrate contamination risk: The Italian experience

The purpose of this study is to show the results of the Italian research project of national interest (PRIN) launched in 2006 and finished in 2008, concerning the “assessment of groundwater contamination risk by nitrates assessment”. The project verified the IPNOA method for nitrate groundwater contamination risk assessment in four test-sites of Italy. The IPNOA is a parametric index which assesses the potential hazard of nitrate contamination originating from agriculture on a regional scale. The method integrates two categories of parameters: the hazard factors (HF), which represent all farming activities that cause, or might cause, an impact on soil quality in terms of nitrate (use of fertilisers, application of livestock and poultry manure, food industry wastewater and urban sludge), and the control factors (CF) which adapt the hazard factors to the characteristics of the site (geographical location, climatic conditions and agronomic practices). Finally, the Potential Risk Map is obtained by coupling the potential hazard of nitrate pollution (IPNOA) and the aquifer Contamination Vulnerability Map. The project was carried out by five Research Units (RU) from the Politecnico di Torino, Universities of Piacenza, Florence, Naples and Palermo. The geochemistry of groundwaters from the four test-sites was studied to determine the distribution of nitrate, and to evaluate groundwater chemical facies. All the study areas are affected by groundwater nitrate contamination and often by hydrogeochemical peculiarities. In some cases isotopic study, δ 18O–NO 3 δ 15N–NO 3, allowed to differentiate nitrates of chemical fertilisers from those of biological origin, as well as denitrification processes.

Groundwater Nitrate Contamination Risk Induced by Irrigation from Polluted River Water

Groundwater contamination experiments using irrigation water from the polluted Kuihe River were conducted at the Hanwang hydrological field station, near Xuzhou City. As part of this study, a numerical model was developed on the basis of a mathematical equation with a finite-difference approximation. The model is capable of simulating nitrogen transformation processes during subsurface transport. Numerical simulations were conducted to estimate nitrogen species concentrations along a flowpath during irrigation. Because of the complex field irrigation conditions, uncertainties of the model input parameters were analyzed and probability density functions (PDFs) of the model input parameters were constructed using the available field data or professional judgement. The PDFs and a Monte Carlo simulation technique were used in this study for the evaluation of risk of groundwater contamination. The results of this study demonstrated that the nitrate mass leaching into groundwater with a 25 and 75% probability w...

Groundwater Nitrate Contamination Risk Assessment: A Comparison of Parametric Systems and Simulation Modelling

Groundwater nitrate contamination is a source of rising concern that has been faced through the introduction of several regulations in different countries. However the methodologies used in the definition of Nitrate Vulnerable Zones are not included in the regulations. The aim of this work was to compare different methodologies, used to asses groundwater nitrate contamination risks, based on parametric systems or simulation modelling. The work was carried out in Piedmont, Italy, in an area characterised by intensive animal husbandry, high N load, a shallow water table and a coarse type of sub-soil sediments. Only N loads from agricultural non-point sources were considered. Different methodologies with different level of information have been compared to determine the groundwater nitrate contamination risk assessment: N load, IPNOA index, the intrinsic contamination risk from nitrates, leached N and N concentration of the soil solution estimated by the simulation model. The good correlation between the IPNOA index and the intrinsic nitrate contamination risk revealed that the parameters that describe the soil in this area did not lead to a different classification of the parcels. The intrinsic nitrate contamination risk was greatly influenced by N fertilisation, however the effect of the soils increased the variability in comparison to the IPNOA index. The leached N and N concentration in the leaching were closely correlated. The dilution effect of percolated water was almost negligible. Both methodologies were slightly correlated to the N fertilisation and the two indexes. The correlations related to the intrinsic nitrate contamination risk was higher than those related to IPNOA, and this means that the effect of taking into account soil parameters increases the correlation to the prediction of the simulation model.

Residual soil nitrogen in soil landscapes of Canada as affected by land use practices and agricultural policy scenarios

Agri-environmental indicators are being developed in Canada to assess and report on the environmental sustainability of agricultural production activities. Concerns about water quality have led to the development of an indicator called residual soil nitrogen ( RSN), which reflects annual nitrogen left in the soil profile after crops are harvested. The Canadian agricultural nitrogen budget (CANB) is used to integrate this indicator with the economic Canadian regional agriculture model (CRAM) to assess the implications of national and regional agricultural policy scenarios. CANB has built-in scaling-up and scenario-analysis capabilities, so that its outputs can be generated and mapped at the soil landscapes of Canada (scale 1:1 million) level, as well at provincial and national scales. Using census of agriculture data for 1981 and 1996, the CANB model predicted RSN levels across Canada for 2008. The impacts of CRAM policy scenarios in the year 2008, which include changes in crop areas, animal numbers, fertilization and animal feeding practices, each with a low, medium and high level of adoption, are evaluated in terms of changes in RSN compared to a 2008 ‘business as usual’ scenario. National average RSN values are projected to increase from 21.8 kg N/ha in 1981 to 36.5 kg N/ha in the 2008 ‘business as usual’ scenario. Between 1996 and 2008, the proportion of farmland containing greater than 40 kg of excess N/ha increased from 18% to 34% in response to increased fertilizer use, increased manure application and increases in the area of legume crops. Changes in land use practices, such as decreasing the summerfallow area or switching some annual cropland to perennial forages and forestry, appear to have a minimal effect on RSN levels as compared to the ‘business as usual’ scenario. However, policy scenarios that improve nitrogen fertilization and animal feeding practices were found to significantly decrease RSN levels and thereby reduce the risk of nitrate contamination of the environment.

In Situ Measurements of Nitrate Leaching Implicate Poor Nitrogen and Irrigation Management on Sandy Soils

Minimizing the risk of nitrate contamination along the waterways of the U.S. Great Plains is essential to continued irrigated corn production and quality water supplies. The objectives of this study were to quantify nitrate (NO(3)) leaching for irrigated sandy soils (Pratt loamy fine sand [sandy, mixed, mesic Lamellic Haplustalfs]) and to evaluate the effects of N fertilizer and irrigation management strategies on NO(3) leaching in irrigated corn. Two irrigation schedules (1.0x and 1.25x optimum) were combined with six N fertilizer treatments broadcast as NH(4)NO(3) (kg N ha(-1)): 300 and 250 applied pre-plant; 250 applied pre-plant and sidedress; 185 applied pre-plant and sidedress; 125 applied pre-plant and sidedress; and 0. Porous-cup tensiometers and solution samplers were installed in each of the four highest N treatments. Soil solution samples were collected during the 2001 and 2002 growing seasons. Maximum corn grain yield was achieved with 125 or 185 kg N ha(-1), regardless of the irrigation schedule (IS). The 1.25x IS exacerbated the amount of NO(3) leached below the 152-cm depth in the preplant N treatments, with a mean of 146 kg N ha(-1) for the 250 and 300 kg N preplant applications compared with 12 kg N ha(-1) for the same N treatments and 1.0x IS. With 185 kg N ha(-1), the 1.25x IS treatment resulted in 74 kg N ha(-1) leached compared with 10 kg N ha(-1) for the 1.0x IS. Appropriate irrigation scheduling and N fertilizer rates are essential to improving N management practices on these sandy soils.