Simulated Nitrate Concentrations Research Articles

Assessment of Nitrate in Groundwater from Diffuse Sources Considering Spatiotemporal Patterns of Hydrological Systems Using a Coupled SWAT/MODFLOW/MT3DMS Model

In recent years, due to various anthropogenic activities, such as agriculture and livestock, the presence of nitrogen-associated contaminants has been increasing in surface- and groundwater resources. Among these, the main compounds present in groundwater are ammonia, nitrite, and nitrate. However, it is sometimes difficult to assess such effects given the scarcity or lack of information and the complexity of the system. In the current study, a methodology is proposed to assess nitrate in groundwater from diffuse sources considering spatiotemporal patterns of hydrological systems using a coupled SWAT/MODFLOW/MT3DMS model. The application of the model is carried out using a simplified simulation scheme of hydrological and agricultural systems because of the limited spatial and temporal data. The study area includes the Cuitzeo Lake basin in superficial flow form and the Morelia–Querendaro aquifer in groundwater flow form. The results within the methodology are surface runoff, groundwater levels, and nitrate concentrations present in surface- and groundwater systems. The results indicate that the historical and simulated nitrate concentrations were obtained within acceptable values of the statistical parameters and, therefore, are considered adequate.

Land-Water Transport and Sources of Nitrogen Pollution Affecting the Structure and Function of Riverine Microbial Communities.

The characterization of variations in riverine microbiota that stem from contaminant sources and transport modes is important for understanding biogeochemical processes. However, the association between complex anthropogenic nitrogen pollution and bacteria has not been extensively investigated owing to the difficulties faced while determining the distribution of nitrogen contaminants in watersheds. Here, we employed the Soil and Water Assessment Tool alongside microbiological analysis to explore microbial characteristics and their responses to complex nitrogen pollution patterns. Significant variations in microbial communities were observed in sub-basins with distinct land-water pollution transport modes. Point source-dominated areas (PSDAs) exhibited reduced microbial diversity, high number of denitrification groups, and increased nitrogen cycling compared with others. The negative relative deviations (-3.38) between the measured and simulated nitrate concentrations in PSDAs indicated that nitrate removal was more effective in PSDAs. Pollution sources were also closely associated with microbiota. Effluents from concentrated animal feeding operations were the primary factors relating to the microbiota compositions in PSDAs and balanced areas. In nonpoint source-dominated areas, contaminants from septic tanks become the most relevant sources to microbial community structures. Overall, this study expands our knowledge regarding microbial biogeochemistry in catchments and beyond by linking specific nitrogen pollution scenarios to microorganisms.

Machine learning models to predict nitrate concentration in a river basin

Aquifer-stream interactions affect the water quality in Mediterranean areas; therefore, the coupling of surface water and groundwater models is generally used to solve water-planning and pollution problems in river basins. However, their use is limited because model inputs and outputs are not spatially and temporally linked, and the data update and fitting are laborious tasks. Machine learning models have shown great potential in water quality simulation, as they can identify the statistical relationship between input and output data without the explicit requirement of knowing the physical processes. This allows the ecological, hydrological, and environmental variables that influence water quality to be analysed with a holistic approach. In this research, feature selection (FS) methods and algorithms of artificial intelligence—random forest (RF) and eXtreme Gradient Boosting (XGBoost) trees—are used to simulate nitrate concentration and determine the main drivers related to nitrate pollution in Mediterranean streams. The developed models included 19 inputs and sampling of nitrate concentration in 159 surface water quality-gauging stations as explanatory variables. The models were trained on 70 percent data, with 30 percent used to validate the predictions. Results showed that the combination of FS method with local knowledge about the dataset is the best option to improve the model’s performance, while RF and XGBoost simulate the nitrate concentration with high performance (r = 0.93 and r = 0.92, respectively). The final ranking, based on the relative importance of the variables in the RF and XGBoost models, showed that, regarding nitrogen and phosphorus concentration, the location explained 87 percent of the nitrate variability. RF and XGBoost predicted nitrate concentration in surface water with high accuracy without using conditions or parameters of entry and enabled the observation of different relationships between drivers. Thus, it is possible to identify and delimit zones with a spatial risk of pollution and approaches to implementing solutions.

Modeling Monthly Nitrate Concentration in a Karst Spring with and without Discrete Conduit Flow

Understanding the coupled continuum pipe-flow framework for modeling contaminant transport in karst systems is critical for protecting water resources therein. This study simulated point and non-point source nitrate concentration in a karst spring and investigated the results generated from the flow and transport model with and without discrete conduit flow. CFPv2 and CMT3D models were integrated to address the changes in nitrate concentration at a monthly scale in a karst spring, and the results were compared with that from an equivalent porous media (EPM) model with high-hydraulic conductivity (K) zones set in the main karstified area to represent conduits. The results show that the CFPv2+CMT3D model is able to describe well the recession of nitrate concentration in spring discharge, and the relatively larger deviation (slower nitrate recession) from the observed trend for the EPM model is probably a result of the limitation of utilizing high hydraulic conductivity cells to represent conduit. Moreover, simulated hydraulic heads in poorly karstified areas from the two models both show slight differences from the observations (the head RMSE values of calibration/validation for CFPv2 and MODFLOW models are 0.16 m/0.25 m and 0.26 m/0.17 m, respectively), indicating the inclusion of conduits may not affect the simulation considerably, and the lower the proportion of karstic area, the slight effects brought from the inclusion of conduits in the model. For highly karstified areas, the CFPv2+CMT3D model could provide more accurate results (head RMSE of calibration/validation for CFPv2 and MODFLOW are 0.22 m/0.06 and 0.52 m/0.47 m, respectively), showing the coupled continuum pipe-flow framework may be more appropriate for applying to highly and maturely karstified areas where the variations in the behavior of flow and contaminant transport are more affected by turbulent flow regime.

Vulnerability assessment, transport modeling and simulation of nitrate in groundwater using SI method and modflow-MT3DMS software: case of Sminja aquifer, Tunisia

Like most North African countries, Tunisia is characterized by a harsh arid and semi-arid climate with scarce water resources and poor water quality on most of its territory. The quality of groundwater is not immune to pollution. Sminja aquifer, located in Zaghouan district in Northeastern Tunisia, has been used to meet Zaghouan agglomeration needs for drinking purposes and irrigation uses. On the other hand, the region has suffered from inefficient usage and mismanagement of water resource due to appropriate legal, political, and economic frameworks to take into consideration the regional vulnerability to climate change and population growth. The application of the Susceptibility Index (SI) makes it possible to evaluate the impact of agricultural activities on the water quality in Sminja aquifer, using five parameters [depth of water (D), net recharge (R), aquifer media (A), topography (T) and Land use (LU)]. Modular three-dimensional multispecies transport model was used to assess, simulate and predict pollution transport of nitrate. The vulnerability index's spatial distribution shows that the most vulnerable area was found in the extreme north of the Sminja aquifer. It shows that a high vulnerability characterizes 21% of the study area (70 < SI < 60). The moderate to high vulnerability areas to pollution occupied 12% of the aquifer and the moderate to low vulnerability zones occupied 67% of the total area. The outputs of the SI reflect a good correlation with the measured nitrate concentrations. After calibration completion, the MT3DMS transport model results showed a good correlation between measured and simulated nitrate concentrations. The predict scenarios show that the nitrate propagates in all the aquifer, from the irrigated area to the non-irrigated area.

Checking the Plausibility of Modelled Nitrate Concentrations in the Leachate on Federal State Scale in Germany

In Germany, modelled nitrate concentrations in the leachate are of great importance for the development of scenarios for the long-term achievement of the groundwater quality target according to the specific requirements of the EU Water Framework Directive as well as within the context of the recently adopted general administrative regulation for the designation of nitrate-polluted areas in Germany. For the German federal states of North Rhine-Westphalia (NRW) and Rhineland-Palatinate (RLP), an area-covering modelling of mean long-term nitrate concentrations in leachate with high spatial resolution was carried out using the model system RAUMIS-mGROWA-DENUZ. Hotspot regions with nitrate concentrations in the leachate of 50 mg NO3/L and more were identified for intensively farmed areas in the Münsterland, Lower Rhine, and Vorderpfalz. The validity of modelled values was checked using measured values from 1119 preselected monitoring stations from shallow springs and aquifers filtered near to the surface with oxidizing properties. For the land use categories of urban areas, arable land, grassland, and forest, an at least good agreement of modelled nitrate concentrations in the leachate and measured nitrate concentrations in groundwater was obtained at numerous sites. An equally good agreement was obtained for 1461 measuring stations from the area of responsibility of the Erftverband, which is a major water supplier in the Lower Rhine region. Here, discrepancies have been analyzed in detail due to profound regional knowledge on observation sites. It turned out that in most cases, accuracy limitations of input data (e.g., N balance surpluses of agriculture at the municipal level, 1:50,000 soil map) have been the reason for larger deviations between observed and modelled values. In a broader sense, the case study has shown on the one hand that the model system RAUMIS-mGROWA-DENUZ is able to reliably represent interrelationships and influencing factors that determine simulated nitrate concentrations in the leachate. On the other hand, it has been proven that observed nitrate concentrations in groundwater may provide a solid data source for checking the plausibility of modelled nitrate concentrations in leachate in cases where certain preselection criteria are applied.

A lumped model to simulate nitrate concentration evolution in groundwater at catchment scale

Groundwater nitrate contamination requires implementation of measures to reduce the impact of agricultural sources. Models appear as a way to understand the nitrate transfer and its temporal trend as well as a forecasting tool useful for decision making. Given their ease of implementation compared to discretized models, lumped models seem appropriate tool for stakeholder purposes but remain rarely used in transport modelling. The lumped model BICHE, simulating both hydrologic and nitrate transport in a coupled way, was applied on three sites having contrasted hydrogeological characteristics and under various agricultural pressures. The model has an automatic calibration procedure which is used under constraints fixed by the operator. It was executed on three catchments on a long duration simulation (about 30 years) and performed again 5 years later. This extension of the dataset allowed to evaluate the robustness of the calibration. Whether for the water level or the nitrate concentrations modelling, the performance of the model was almost not altered, confirming the validity of the calibration. Results highlighted model performance for long-term trend of nitrate concentration whereas very short-term variations were less well reproduced, especially for the studied site showing large weekly fluctuations. Certain data, in particular agricultural data, are particularly difficult to obtain for the whole catchment at a detailed time step and the use of rough estimation for these data generate uncertainties. This aspect is however not prohibitive since the purpose of such modelling is to forecast global trends in nitrate concentrations under various types of scenarios. This modelling for the three sites allowed an analysis of the effect of agricultural changes in term of nitrate concentration but also on time lag between the implementation of these changes and their impact on groundwater quality. Considering the ease of implementation, the robustness of model and the quality of the simulations obtained, we confirm that this tool is particularly relevant for stakeholders to address groundwater nitrate contamination.

Modeling shallow groundwater nitrate concentrations by direct coupling of the vadose and the saturated zone

In many aquifers in plains and valley basins, water movement and solute fate in the vadose zone is described without considering the actual depth of the groundwater table. However, for shallow groundwater conditions (i.e., when the water table is few meters below the ground surface), there is a feedback from the groundwater table on the soil moisture content which influences plant growth and evapotranspiration. Thus, an interactive coupling between vadose zone and groundwater processes is needed. In this research the implementation of a time step-based (direct) coupling between the soil water movement and nitrogen fate model SIMWASER/STOTRASIM and the groundwater flow and solute transport model FEFLOW is shown and applied to a part of an aquifer in southeast Austria. At the aquifer scale, areas with time step-based coupling are combined with areas of sequential coupling to account for shallow groundwater levels. To speed up the computation of vadose zone processes, a clustering approach is developed by grouping elements of similar groundwater level and nitrate concentrations time series together. Through the comparison between direct and sequential coupling results, it is demonstrated that including the feedback in the coupling reduces simulated nitrate concentrations by about 10%. Thus, if shallow groundwater conditions exist, the time step-based approach allows considering the interaction between vadose and saturated processes, which may lead to improved compromises between agricultural land use and groundwater protection.

Hydrologic and water quality responses to biomass production in the Tennessee river basin

AbstractReducing dependence on fossil‐based energy has raised interest in biofuels as a potential energy source, but concerns have been raised about potential implications for water quality. These effects may vary regionally depending on the biomass feedstocks and changes in land management. Here, we focused on the Tennessee River Basin (TRB), USA. According to the recent 2016 Billion‐Ton Report (BT16) by the US Department of Energy, under two future scenarios (base‐case and high‐yield), three perennial feedstocks show high potential for growing profitably in the TRB: switchgrass (Panicum virgatum), miscanthus (Miscanthus × giganteus), and willow (Salix spp.). We used the Soil &amp; Water Assessment Tool (SWAT) to compare hydrology and water quality for a current landscape with those simulated for two future BT16 landscapes. We combined publicly available temporal and geospatial datasets with local land and water management information to realistically represent physical characteristics of the watershed. We developed a new autocalibration tool (SWATopt) to calibrate and evaluate SWAT in the TRB with reservoir operations, including comparison against synthetic and intermediate response variables derived from gage measurements. Our spatiotemporal evaluation enables to more realistically simulate the current situation, which gives us more confidence to project the effects of land‐use changes on water quality. Under both future BT16 scenarios, simulated nitrate and total nitrogen loadings and concentrations were greatly reduced relative to the current landscape, whereas runoff, sediment, and phosphorus showed only small changes. Difference between simulated water results for the two future scenarios was small. The influence of biomass production on water quantity and quality depended on the crop, area planted, and management practices, as well as on site‐specific characteristics. These results offer hope that bioenergy production in the TRB could help to protect the region's rivers from nitrogen pollution by providing a market for perennial crops with low nutrient input requirements.

Simplified Lumped Groundwater Model to Simulate Nitrate Concentration Dynamics

AbstractModeling of the nitrate concentration in groundwater can help ensure proper groundwater management and utilization, especially as a drinking water supply. Here, a groundwater nitrate tank m...

Modelling of nitrates in River Nzoia using MIKE 11

Eutrophication is a serious problem in Lake Victoria as a result of enrichment by nutrients transported by the rivers draining into it. River Nzoia is one of the main rivers draining into the lake. The main aim of this study was to simulate the level of nitrates using MIKE 11 and to establish relationship between nitrogen and phosphorus. The model was calibrated using water quality data for 2009 and validated with March 2013 data and then it was used to simulate nitrate concentration for the wet month of April 2013. The model performance was good with R2 values of between 0.87 and 0.98 and EF values of between 0.73 and 0.96. From the simulations, the effluent discharge from municipal and industrial wastewater ponds elevated the concentration of the nitrates in the river. Analysis of the concentrations of nitrates for wet and dry periods showed significant variations indicating significant contributions from the catchment through run-off. The relationship between total nitrogen and total phosphorus was analysed and found to have a strong positive correlation (r = 0.714, p &amp;lt; 0.05) indicating that both originate from similar sources or are influenced by the same factors such as agriculture.

Data assimilation of physical and chlorophyll a observations in the California Current System using two biogeochemical models

Biogeochemical numerical models coupled to physical ocean circulation models are commonly combined with data assimilation in order to improve the models’ state or parameter estimates. Yet much still needs to be learned about important aspects of biogeochemical data assimilation, such as the effect of model complexity and the importance of more realistic model formulations on assimilation results. In this study, 4D-Var-based state estimation is applied to two biogeochemical ocean models: a simple NPZD model with 4 biogeochemical variables (including 1 phytoplankton, 1 zooplankton) and the more complex NEMURO model, containing 11 biogeochemical variables (including 2 phytoplankton, 3 zooplankton). Both models are coupled to a 3-dimensional physical ocean circulation model of the U.S. west coast based on the Regional Ocean Modelling System (ROMS). Chlorophyll satellite observations and physical observations are assimilated into the model, yielding substantial improvements in state estimates for the observed physical and biogeochemical variables in both model formulations. In comparison to the simpler NPZD model, NEMURO shows a better overall fit to the observations. The assimilation also results in small improvements for simulated nitrate concentrations in both models and no apparent degradation of the output for other unobserved variables. The forecasting skill of the biogeochemical models is strongly linked to model performance without data assimilation: for both models, the improved fit obtained through assimilation degrades at similar relative rates, but drops to different absolute levels. Despite the better performance of NEMURO in our experiments, the choice of model and desired level of complexity should depend on the model application and the data available for assimilation.

Evaluation of HYDRUS-2D model to simulate the loss of nitrate in subsurface controlled drainage in a physical model scale of paddy fields

Agriculture is a major source of nitrogen usage and release to environment. Due to the effect of water movement on solute transport, investigating the effect of different management scenarios of irrigation and drainage could be useful for reducing nitrate loss and environmental pollution. This study is a scientific attempt to assess the ability of HYDRUS-2D model to simulate the effect of subsurface controlled drainage on nitrate loss of paddy fields. So, two physical models with difference in depth of subsurface controlled drainage (40 and 60 cm) were constructed. The tanks were filled with loam silty soil texture and then transplanted rice. 90 kg/ha potassium nitrate fertilizer was added in two stages of rice growth. Mid-season drainage was applied 26 days after transplantation. After 17 days, drains were closed again and applied flooded irrigation with 5-cm water stagnant layer above soil surface. During experiment, nitrate concentration of drain water was measured. HYDRUS-2D was calibrated with measured data in 60 cm drain depth and validated with 40 cm drain depth. HYDRUS-2D could simulate nitrate concentration with the coefficient of determination 0.95 and 0.89 in calibration and validation stages, respectively. The comparison between the volume of drain water and nitrate concentration from the drains in the depths of 40 and 60 cm indicated lower nitrate load in depth of 40 cm. The results obtained proved that the presence of hardpan layer in depth of 25 cm rather than the absence of it causes increase in 3 % of average nitrate concentration and reduce in 17 % of water discharge.

Estimation of nitrate load from septic systems to surface water bodies using an ArcGIS-based software

Nitrate, as a commonly identified groundwater and surface water pollutant, poses serious threats to human health and the environment. One important source of nitrate in the environment is due to wastewater treatment using Onsite Sewage Treatment and Disposal Systems (OSTDS) (a.k.a., septic systems). To facilitate water resources and environmental management, an ArcGIS-Based Nitrate Load Estimation Toolkit (ArcNLET) is developed to simulate nitrate transport and estimate nitrate load from septic systems and collocated fertilizer applications in groundwater to surface water bodies. It is a screening tool based on a simplified conceptual model of groundwater flow and nitrate transport. It is used in this study to estimate nitrate load from thousands of septic systems to surface water bodies in two neighborhoods located in Jacksonville, FL, USA, where nitrate due to septic systems is believed to be one of the reasons of nutrient enrichment and an isotope study indicates that denitrification is significant. A global sensitivity analysis is performed to identify critical parameters for model calibration, and the most critical parameter is the first-order decay coefficient used to simulate the denitrification process. Hydraulic conductivities at different soil zones have different levels of influence on simulated nitrate concentrations at different locations. By manually adjusting model parameters, simulated shapes of water table and nitrate concentration agree reasonably with average field observations, suggesting that ArcNLET is able to simulate spatial variability of field observations. Estimated nitrate loads exhibit spatial variability, which is useful to facilitate decisions on the conversion of OSTDS into sewers in certain areas for reducing nitrate load from septic systems to surface water bodies.

Assessment of nitrate contamination of groundwater using lumped-parameter models

In this paper, lumped-parameter models (LPMs) were developed and utilized to simulate nitrate concentration in the groundwater of Gaza City and Jabalia Camp (GCJC) in the Gaza Coastal Aquifer (GCA) in Palestine. In the GCJC area, nitrate levels exceed the maximum contaminant level (MCL) of 10 mg/L NO 3-N (45 mg/L NO 3) in many wells. Elevated nitrate concentrations in the groundwater of GCJC area are due to the disposal of untreated wastewater, the existence of heavy agriculture in the surrounding areas, and the use of cesspits for wastewater disposal. The developed LPMs utilize monthly time steps and take into consideration all the sources and sinks of water and nitrate in the study area. The main outcomes of the LPMs are the average temporal water table elevation and nitrate concentration. In order to demonstrate LPMs usability, a set of management options to reduce nitrate concentration in the groundwater of the study area were proposed and evaluated using the developed LPMs. Four broad management options were considered where these options tackle the reduction of nitrate concentration in the lateral inflow, rehabilitation of the wastewater collection system, reduction in cesspit usage, and the restriction on the use of nitrogen-based fertilizers. In addition, management options that encompass different combinations of the single management options were taken into account. Different scenarios that correspond to the different management options were investigated. It was found based on the LPMs that individual management options were not effective in meeting the MCL of nitrate. However, the combination of the four single management options with full rehabilitation and coverage of the wastewater collection network along with at least 60% reduction in both nitrate concentration in the lateral inflow and the use of nitrogen-based fertilizers would meet the MCL constraint by the end of the management period.

Modeling wintertime particulate matter formation in central California

A wintertime episode during the 2000 California Regional PM Air Quality Study (CRPAQS) was simulated with the air quality model CMAQ–MADRID. Model performance was evaluated with 24-h average measurements available from CRPAQS. Modeled organic matter (OM) was dominated by emissions, which were probably significantly under-represented, especially in urban areas. In one urban area, modeled daytime nitrate concentrations were low and evening concentrations were high. This diurnal profile was not explained by the partition of nitrate between the gas and particle phases, because gaseous nitric acid concentrations were low compared to PM nitrate. Both measured and simulated nitrate concentrations aloft were lower than at the surface at two tower locations during this episode. Heterogeneous reactions involving NO 3 and N 2O 5 accounted for significant nitrate production in the model, resulting in a nighttime peak. The sensitivity of PM nitrate to precursor emissions varied with time and space. Nitrate formation was on average sensitive to NO x emissions. However, for some periods at urban locations, reductions in NO x caused the contrary response of nitrate increases. Nitrate was only weakly sensitive to reductions in anthropogenic VOC emissions. Nitrate formation tended to be insensitive to the availability of ammonia at locations with high nitrate, although the spatial extent of the nitrate plume was reduced when ammonia was reduced. Reductions in PM emissions caused OM to decrease, but had no effect on nitrate despite the role of heterogeneous reactions. A control strategy that focuses on NO x and PM emissions would be effective on average, but reductions in VOC and NH 3 emissions would also be beneficial for certain times and locations.

Assessment of the Impact of Nutrient Management Practices on Nitrate Contamination in the Abbotsford-Sumas Aquifer

The impact of recent changes to nutrient management practices in raspberry fields on the loading and subsequent transport of nitrate through the vadose zone of the Abbotsford-Sumas aquifer is investigated numerically. Previous studies have shown that nitrate concentrations in the aquifer have remained relatively stable despite a shift in nutrient management practices. Using an estimate of net annual available nitrogen in fields that are fertilized using synthetic fertilizer, nitrate concentrations as a function of time and depth through the vadose zone are simulated from spring to late fall. Results indicate rapid leaching of nitrate owing to the permeable nature of the aquifer and suggest that nitrate loading to the water table may occur earlier than previously thought, possibly due to spring rains. For an average fertilizer application rate of 90 kg of N/ha, the simulated nitrate concentration on Oct 1 within the top 1 m of soil is 33 mg of N/kg, while the residual soil nitrate measured in late September was 37 mg of N/kg. Taking into account the effects of dilution within the saturated zone, the simulated peak nitrate concentration is similar to average observed peak concentrations in a shallow monitoring well. A solution is offered for estimating nitrate concentration at the water table as a function of the rate of synthetic fertilizer applied to raspberry fields.

A model simulation analysis of soil nitrate concentrations—Does soil organic matter pool structure or catch crop growth parameters matter most?

Three different soil organic matter (SOM) submodels were tested within the framework of the soil–plant–atmosphere model Daisy. The three submodels were: the original Daisy SOM module (OLD) with relatively non-dynamic humus pools, a recalibrated Daisy SOM module (STD) with the same pool structure as the original, but with a more rapid turnover of the active humus pool, and a newly developed SOM model structure (CNSIM), with inclusion of a soil microbial residuals pool of relatively rapid turnover, and a relatively recalcitrant added organic matter pool, producing a larger and more sustained residual N mineralisation. Furthermore, two different parameterisations of the catch crop submodules, differing in grass growth and N assimilation dynamics, were tested and the relative influence of SOM module or catch crop growth module on the simulated variables assessed. The simulations were carried out with data from a field experiment with four mixed cropping systems and compared to measured results of crop production, N uptake and soil nitrate concentration. The cropping sequence was 3 years of grassland (cut or grazed) followed by 3 years of spring cereals with ryegrass as a catch crop and two levels of fertiliser application. Independently of the SOM module, plant production and nitrogen uptake for cereals were simulated well. The dynamics of the added organic matter (AOM) and SOM of the two Daisy submodules were nearly identical, whereas the CNSIM submodule built much more nitrogen into the AOM pools, especially during the pasture years. During the period with spring barley, the CNSIM module simulated similar amounts of AOM as the other modules. In general, the simulated nitrate concentrations at 100 cm depth were higher than the measured values, but the changed dynamics in the CNSIM simulations resulted in even higher overestimation of the nitrate concentration than the two other modules. The choice of catch crop submodule had a considerable effect on nitrate concentration and therefore the potential for nitrate leaching, possibly overshading more futile differences produced by the different SOM submodules. The simulations show the importance of applying appropriate intercrop submodels when the model is used for simulating rotations with intercropping of grass-clover or undersown catch crops.

Modeling nitrate fluxes at the catchment scale using the integrated tool CAWAQS

Nitrates fluxes in the Grand Morin basin (1200 km(2)), that is subjected to intense agricultural pressure, are considered using in-stream observations (around 250 sampling days over 5 years) and physically based simulations using the CAWAQS model (CAtchment WAter Quality Simulator). In-stream nitrate concentration averaged 6 mg N L(-1), increasing by approximately 0.2 mg N L(-1) yr(-1) around this value (period 1991-1996). Our results show that, over the period of 1991-1996, the differences between in-stream observed nitrate concentrations and simulated nitrate concentrations result from nitrate losses at the basin scale. These losses are due to denitrification by transfer through wetlands, alluvial plains, the hyporheic zone, and by benthic processes in rivers. A mean annual mass balance at the basin scale indicates that 40% of the infiltration flux (3360 kg N km(-2) yr(-1)) is removed from the system via the river network, 40% is stored in aquifers and 20% is lost by denitrification (period 1991-1996).

Nitrate contamination of groundwater: A conceptual management framework

In many countries, public concern over the deterioration of groundwater quality from nitrate contamination has grown significantly in recent years. This concern has focused increasingly on anthropogenic sources as the potential cause of the problem. Evidence indicates that the nitrate (NO 3) levels routinely exceed the maximum contaminant level (MCL) of 10 mg/l NO 3-N in many aquifer systems that underlie agriculture-dominated watersheds. Degradation of groundwater quality due to nitrate pollution along with the increasing demand for potable water has motivated the adoption of restoration actions of the contaminated aquifers. Restoration efforts have intensified the dire need for developing protection alternatives and management options such that the ultimate nitrate concentrations at the critical receptors are below the MCL. This paper presents a general conceptual framework for the management of groundwater contamination from nitrate. The management framework utilizes models of nitrate fate and transport in the unsaturated and saturated zones to simulate nitrate concentration at the critical receptors. To study the impact of different management options considering both environmental and economic aspects, the proposed framework incorporates a component of a multi-criteria decision analysis. To enhance spatiality in model development along with the management options, the utilization of a land use map is depicted for the allocation and computation of on-ground nitrogen loadings from the different sources.