Gaseous losses of nitrogen by ammonia volatilization and nitrous oxide emissions from rice paddies with different irrigation management

To reveal the influence of non-flooding controlled irrigation (NFI) on gaseous nitrogen (N) losses in forms of ammonia volatilization (AV) and nitrous oxide (N₂O) emissions from high N inputs rice paddies, lysimeter experiments were conducted with flooding irrigation (FI) as check. Compared with FI paddies, AV losses in NFI paddies decreased by 18.5–20.5 % and N₂O emissions increased by 1.43–1.9 kg N ha^?1. Weekly AV losses immediately after fertilization accounted for over 83 % of seasonal losses in both treatments. High N₂O emissions from NFI paddies always occurred in drying process after N application, with peaks observed when water-filled pore space (WFPS) fell in 75–85 %. Water management immediately after N fertilization is crucial for mitigating gaseous N losses from rice paddies. Bringing N into shallow rhizosphere by irrigation and covering it with deep water will be helpful in preventing AV. Maintaining a flooding period and keeping WFPS higher than 85 % in the first drying process after fertilization might be effective to reduce N₂O emissions peaks for NFI paddies.     

Soil N and salinity leaching after the autumn irrigation and its impact on groundwater in Hetao Irrigation District,China

Soil water and salinity are crucial factors influencing crop production in arid regions. An autumn irrigation system employing the application of a large volume of water (2200–2600 m³ ha⁻¹) is being developed in the Hetao Irrigation District of China, since the 1980s with the goal to reduce salinity levels in the root zone and increase the water availability for the following spring crops. However, the autumn irrigation can cause significant quantities of NO₃⁻ to leach from the plant root zone into the groundwater. In this study, we investigated the changes in soil water content, NO₃–N and salinity within a 150 cm deep soil profile in four different types of farmlands: spring wheat (F_W), maize (F_M), spring wheat–maize inter-planting (F_W–M) and sunflower (F_S). Our results showed that (1) salt losses mainly occurred in the upper 60 cm of the soil and in the upper 40 cm for NO₃–N; (2) the highest losses of salt and NO₃–N could be observed in F_W, whereas the lowest losses were found in F_W–M.NO₃–N concentration, pH and electrical conductivity (EC) in the groundwater were also monitored before and after the autumn irrigation. We found that the autumn irrigation caused the groundwater concentration of NO₃–N to increase from 1.73 to 21.6 mg L⁻¹, thereby, exceeding the standards of the World Health Organization (WHO). Our results suggest that extensive development of inter-planting tillage might be a viable measure to reduce groundwater pollution, and that the application of optimized minimum amounts of water and nitrogen to meet realistic yield goals, as well as the timely application of N fertilizers and the use of slow release fertilizers can be viable measures to minimize nitrate leaching.     

The contribution of maize cropping in the Midwest USA to global warming: A regional estimate

Agricultural soils emit about 50% of the global flux of N₂O attributable to human influence, mostly in response to nitrogen fertilizer use. Recent evidence that the relationship between N₂O fluxes and N-fertilizer additions to cereal maize are non-linear provides an opportunity to estimate regional N₂O fluxes based on estimates of N application rates rather than as a simple percentage of N inputs as used by the Intergovernmental Panel on Climate Change (IPCC). We combined a simple empirical model of N₂O production with the SOCRATES soil carbon dynamics model to estimate N₂O and other sources of Global Warming Potential (GWP) from cereal maize across 19,000 cropland polygons in the North Central Region (NCR) of the US over the period 1964-2005. Results indicate that the loading of greenhouse gases to the atmosphere from cereal maize production in the NCR was 1.7 Gt CO₂e, with an average 268 t CO₂e produced per tonne of grain. From 1970 until 2005, GHG emissions per unit product declined on average by 2.8 t CO₂e ha⁻¹ annum⁻¹, coinciding with a stabilisation in N application rate and consistent increases in grain yield from the mid-1970’s. Nitrous oxide production from N fertilizer inputs represented 59% of these emissions, soil C decline (0-30 cm) represented 11% of total emissions, with the remaining 30% (517 Mt) from the combustion of fuel associated with farm operations. Of the 126 Mt of N fertilizer applied to cereal maize from 1964 to 2005, we estimate that 2.2 Mt N was emitted as N₂O when using a non-linear response model, equivalent to 1.75% of the applied N.     

Estimating potential nitrate leaching in nitrogen fertilized and irrigated tomato using the computer model NLEAP

Groundwater pollution caused by leaching of NO₃-N from agricultural systems has caused public concern for decades. To preserve the groundwater and reduce economic losses for the farmers, a rapid and accurate estimation of NO₃-N moving below the root zone is crucial. In this study, the value of the computer program NLEAP (Nitrate Leaching and Economic Analysis Package) to simulate nitrate leaching was evaluated using data from an experiment conducted with 12 lysimeters (1.25 m i.d. and 2 m deep) in 1996 and 1997. Three tomato (H2274 variety) seedlings were planted in each lysimeter and nitrogen rates of 0, 80, 160, and 240 kg N ha⁻¹, as ammonium nitrate and ammonium sulphate, were applied to the lysimeters under a fixed irrigation program. Effluent was collected from the outlets of the lysimeters and analyzed for NO₃. The model adequately simulated nitrogen leaching for each year (R²=0.93 and P<0.03 for 1996, and R²=0.87 and P<0.06 for 1997). The high coefficients of determination, between observed and simulated values, revealed that the model can be successfully used to estimate the amount of the NO₃ leaching under the experimental conditions. The results also showed that the NO₃ available for leaching (NAL) values were important background information for determining an optimum N rate for groundwater quality and maximum gain, and NO₃ available for leaching (NAL), amount of NO₃ leached (NL), movement risk index (MRI), and annual leaching risk potential (ALRP) parameters should be considered together to estimate the nitrogen pollution risk.     

Simulation of drainage water quality with DRAINMOD

The design and management of drainage systems should consider impacts on drainage water quality and receiving streams, as well as on agricultural productivity. Two simulation models that are being developed to predict these impacts are briefly described. DRAINMOD-N uses hydrologic predictions by DRAINMOD, including daily soil water fluxes, in numerical solutions to the advective-dispersive-reactive (ADR) equation to describe movement and fate of NO₃-N in shallow water table soils. DRAINMOD- CREAMS links DRAINMOD hydrology with submodels in CREAMS to predict effects of drainage treatment and controlled drainage losses of sediment and agricultural chemicals via surface runoff. The models were applied to analyze effects of drainage intensity on a Portsmouth sandy loam in eastern North Carolina. Depending on surface depressional storage, agricultural production objectives could be satisfied with drain spacings of 40 m or less. Predicted effects of drainage design and management on NO₃-N losses were substantial. Increasing drain spacing from 20 m to 40 m reduced predicted NO₃-N losses by over 45% for both good and poor surface drainage. Controlled drainage further decreases NO₃-N losses. For example, predicted average annual NO₃-N losses for a 30 m spacing were reduced 50% by controlled drainage. Splitting the application of nitrogen fertilizer, so that 100 kg/ha is applied at planting and 50 kg/ha is applied 37 days later, reduced average predicted NO₃-N losses but by only 5 to 6%. This practice was more effective in years when heavy rainfall occurred directly after planting. In contrast to effects on NO₃-N losses, reducing drainage intensity by increasing drain spacing or use of controlled drainage increased predicted losses of sediment and phosphorus (P). These losses were small for relatively flat conditions (0.2% slope), but may be large for even moderate slopes. For example, predicted sediment losses for a 2% slope exceeded 8000 kg/ha for a poorly drained condition (drain spacing of 100 m), but were reduced to 2100 kg/ha for a 20 m spacing. Agricultural production and water quality goals are sometimes in conflict. Our results indicate that simulation modeling can be used to examine the benefits of alternative designs and management strategies, from both production and environmental points-of-view. The utility of this methodology places additional emphasis on the need for field experiments to test the validity of the models over a range of soil, site and climatological conditions.     

A comparative study of some environmental impacts of conventional and organic farming in Australia

The provision of food causes environmental impacts that range from local through to global in scale. Organic farming, used in general here to mean farming practices with a greater emphasis on long-term sustainability, is one general approach to reduce these impacts. Whilst organic farming may be argued to be superior to conventional farming on the basis of local impacts, it is not often clear how organic farming performs relative to conventional farming in terms of wider, global impacts. In this paper we present a comparative assessment of on-farm and indirect energy consumption, land disturbance, water use, employment, and emissions of greenhouse gases, NO_x, and SO₂ of organic and conventional farming in Australia. A hybrid input-output-based life-cycle technique is employed in order to ensure a complete coverage of indirect requirements originating from all upstream production stages. Using data from a detailed survey of organic farms, the results show that direct energy use, energy related emissions, and greenhouse gas emissions are higher for the organic farming sample than for a comparable conventional farm sample. Direct water use and employment are significantly lower for the organic farms than for the conventional farms. However, the indirect contributions for all factors are much higher for the conventional farms, leading to their total impacts being substantially higher. This shows that indirect effects must be taken into account in the consideration of the environmental consequences of farming, in particular for energy use and greenhouse gas emissions, where the majority of impacts usually occur off-farm. Subject to yield uncertainties for organic versus conventional farming, from the sample here we can conclude that in addition to their local benefits, organic farming approaches can reduce the total water, energy and greenhouse gases involved in food production.     

Greenhouse gas emissions from the Canadian dairy industry in 2001

In order to demonstrate the impact of an increase in production efficiency on greenhouse gas (GHG) emissions, it is important to estimate the combined methane (CH₄), nitrous oxide (N₂O) and carbon dioxide (CO₂) emissions per unit of production. In this study, we calculated the GHG emissions from the Canadian dairy industry in 2001 as a fraction of the milk production and per dairy animal. Five regions were defined according to the importance of the dairy industry. N₂O and CO₂ emissions are directly linked with areas allocated to the dairy crop complex which includes only the crop areas used to feed dairy cattle. The dairy crop complex was scaled down from sector-wide crop areas using the ratios of dairy diet to national crop production of each crop type. Both fertilizer application and on-farm energy consumption were similarly scaled down from sector-wide estimates to the dairy crop complex in each region. The Intergovernmental Panel on Climate Change (IPCC) methodology, adapted for Canadian conditions, was used to calculate CH₄ and N₂O emissions. Most of the CO₂ emission estimates were derived from a Fossil Fuel for Farm Fieldwork Energy and Emissions model except for the energy used to manufacture fertilizers. Methane was estimated to be the main source of GHG, totalling 5.75 Tg CO₂ eq with around 80% coming from enteric fermentation and 20% coming from manure management. Nitrous oxide emissions were equal to 3.17 Tg CO₂ eq and carbon dioxide emissions were equal to 1.45 Tg. The GHG emissions per animal were 4.55 Mg CO₂ eq. On an intensity basis, average GHG emissions were 1.0 kg CO₂ eq/kg milk. Methane emissions per kg of milk were estimated at 19.3 l CH₄/kg milk which is in agreement with Canadian field measurements.     

Evaluation of the DRAINMOD-N II model for predicting nitrogen losses in a loamy sand under cultivation in south-east Sweden

The DRAINMOD-N II model (version 6.0) was evaluated for a cold region in south-east Sweden. The model was field-tested using four periods between 2002 and 2004 of climate, soil, hydrology and water quality data from three experimental plots, planted to a winter wheat-sugarbeet-barley-barley crop rotation and managed using conventional and controlled drainage. DRAINMOD-N II was calibrated using data from a conventional drainage plot, while data sets from two controlled drainage plots were used for model validation. The model was statistically evaluated by comparing simulated and measured drain flows and nitrate-nitrogen (NO₃-N) losses in subsurface drains. Soil mineral nitrogen (N) content was used to evaluate simulated N dynamics. Observed and predicted NO₃-N losses in subsurface drains were in satisfactory agreement. The mean absolute error (MAE) in predicting NO₃-N drainage losses was 0.16 kg N ha⁻¹ for the calibration plot and 0.21 and 0.30 kg N ha⁻¹ for the two validation plots. For the simulation period, the modelling efficiency (E) was 0.89 for the calibration plot and 0.49 and 0.55 for the validation plots. The overall index of agreement (d) was 0.98 for the calibration plot and 0.79 and 0.80 for the validation plots. These results show that DRAINMOD-N II is applicable for predicting NO₃-N losses from drained soil under cold conditions in south-east Sweden.     

Water quality implications of raising crop water productivity

Because of a growing and more affluent population, demand for agricultural products will increase rapidly over the coming decades, with serious implications for agricultural water demand. Symptoms of water scarcity are increasingly apparent, threatening ecosystem services and the sustainability of food production. Improved water productivity will reduce the additional water requirements in agriculture. However, there is a tradeoff between the quantity of water used in agriculture and the quality of return flow. Where yields are low due to limited nitrogen (N) and water supply, water productivity can be enhanced through higher fertilizer applications and improved water management. This limits the amount of additional water needed for increased food demand, thus leaving more water for environmental requirements. But it also increases the amount of nitrate (NO₃–N) leaching, thus adversely affecting the water quality of return flows.This paper quantifies the tradeoff between enhanced water productivity and NO₃–N leaching and shows the importance of the right management of water and N applications. Using the Decision Support System for Agro-technology Transfer (DSSAT) crop model, several scenarios combining different water and N application regimes are examined for maize (Zea mays L.) in Gainesville, FL, USA. Without adequate water, nitrogen use efficiency (NUE) remains low, resulting in substantial NO₃–N leaching. Too much water leads to excessive NO₃–N leaching and lower water productivity. The lack of N is a cause of low water productivity but too much of it leads to lower NUE and higher losses. The paper concludes that increased NO₃–N leaching is an inevitable by-product of increased water productivity, but its adverse impacts can greatly be reduced by better management of water and N application. The paper briefly shows that leaching can be reduced and water productivity increased by split application of N-fertilizer. This implies that improved water and nutrient management at field- and scheme-level is a prerequisite to limit adverse impacts of agriculture on ecosystems, now and especially in the future.     

Using the DRAINMOD-N model to study effects of drainage system design and management on crop productivity,profitability and NO3–N losses in drainage water

The environmental impacts of agricultural drainage have become a critical issue. There is a need to design and manage drainage and related water table control systems to satisfy both crop production and water quality objectives. The model DRAINMOD-N was used to study long-term effects of drainage system design and management on crop production, profitability, and nitrogen losses in two poorly drained soils typical of eastern North Carolina (NC), USA. Simulations were conducted for a 20-yr period (1971–1990) of continuous corn production at Plymouth, NC. The design scenarios evaluated consisted of three drain depths (0.75, 1.0, and 1.25 m), ten drain spacings (10, 15, 20, 25, 30, 40, 50, 60, 80, and 100 m), and two surface conditions (0.5 and 2.5 cm depressional storage). The management treatments included conventional drainage, controlled drainage during the summer season and controlled drainage during both the summer and winter seasons. Maximum profits for both soils were predicted for a 1.25 m drain depth and poor surface drainage (2.5 cm depressional storage). The optimum spacings were 40 and 20 m for the Portsmouth and Tomotley soils, respectively. These systems however would not be optimum from the water quality perspective. If the water quality objective is of equal importance to the productivity objective, the drainage systems need to be designed and managed to reduce NO₃–N losses while still providing an acceptable profit from the crop. Simulated results showed NO₃–N losses can be substantially reduced by decreasing drain depth, improving surface drainage, and using controlled drainage. Within this context, NO₃–N losses can be reduced by providing only the minimum subsurface drainage intensity required for production, by designing drainage systems to fit soil properties, and by using controlled drainage during periods when maximum drainage is not needed for production. The simulation results have demonstrated the applicability of DRAINMOD-N for quantifying effects of drainage design and management combinations on profits from agricultural crops and on losses of NO₃–N to the environment for specific crop, soil and climatic conditions. Thus, the model can be used to guide design and management decisions for satisfying both productivity and environmental objectives and assessing the costs and benefits of alternative choices to each set of objectives.     

Ammonia abatement strategies in livestock production: A case study of a poultry installation

This study uses a linear programming approach to compare the potential effectiveness of uniform rules (under the Integrated Pollution Prevention and Control Directive) and a landscape-scale (a scale that includes different land-uses) based policy for reducing ammonia (NH₃) emissions and their related impacts from an operating case-study poultry installation. The model incorporates a variety of potential NH₃ abatement techniques. It also incorporates the first application of a spatial model of the diffusion of environmental impacts from NH₃ emissions. This models N deposition at a nearby nature reserve.     

Sensitivity analysis and field testing of the RISK-N model in the Central Valley of Chile

We present the results from a sensitivity analysis and a preliminary short-term, site-scale performance assessment of the analytical soil and groundwater nitrate transport RISK-N. The study was carried out in the Central Valley of Chile, on a 2.6 ha corn (Zea mays L.) field underlain by a shallow unconfined aquifer during the cropping season 2000–2001. Nitrogen levels in soils as well as NO₃⁻–N irrigation water and groundwater concentrations were monitored through the crop-growing period, the latter by a network of 16 monitoring wells. A sensitivity analysis shows that both the nitrate flux from the vadose zone and NO₃⁻–N groundwater concentration are mainly influenced by the initial soil nitrogen levels, water input, and soil porosity. Also, simulated groundwater NO₃⁻–N levels are sensitive to changes on the saturated zone denitrification constant. An additional analysis further reveals the significance of the latter parameter, in conjunction with the amount of applied nitrogen fertilizer. We obtained a good agreement between observed average and simulated values. While the model performs well when spatially averaged values are used (root mean square error, RMSE = 1.4 mg l⁻¹ of NO₃⁻–N), the prediction error increases (RMSE = 1.9 mg l⁻¹ of NO₃⁻–N) when the concentration in each well is considered. This fact could be explained by the time and space scale of the experiment and the characteristics of the RISK-N model. The model is easy to use and seems appropriate for mid- and long-term studies of nitrogen contamination in groundwater for agricultural conditions in the Central Valley of Chile and under limited field data availability conditions. However, it needs to be tested for longer periods and under different climatic conditions, soil types, and aquifer characteristics, before its range of applicability can be fully established and recognized.     

Monitoring and modelling draining and resident soil water nitrate concentrations to estimate leaching losses

Quantifying nitrogen (N) losses below the root zone is highly challenging due to uncertainties associated with estimating drainage fluxes and solute concentrations in the leachate. Active and passive soil water samplers provide solute concentrations but give limited information on water fluxes. Mechanistic models are used to estimate leaching, but require calibration with measured data to ensure their reliability. Data from a drainage lysimeter trial under irrigation in which soil profile nitrate (NO₃⁻) concentrations were monitored using wetting front detectors (passive sampler) and ceramic suction cups (active sampler) were compared to NO₃⁻ concentrations in draining and resident soil water as simulated by the research version of the Soil Water Balance model (SWB-Sci). SWB-Sci is a daily time-step, cascading soil water and solute balance model that provides draining NO₃⁻ concentrations by accounting for incomplete solute mixing. As hypothesized, suction cup concentrations aligned closely with resident soil water concentrations, while wetting front detector concentrations aligned closely with draining soil water NO₃⁻ concentrations. These results demonstrate the power of combining monitoring and modelling to estimate NO₃⁻ leaching losses. Access to measured draining and resident NO₃⁻ concentrations, especially when complemented with modelled fluxes, can contribute greatly to achieving improved production and environmental objectives.     

Life cycle assessment of greenhouse gas emissions from beef production in western Canada: A case study

A life cycle assessment (LCA) was conducted to estimate whole-farm greenhouse gas (GHG) emissions from beef production in western Canada. The aim was to determine the relative contributions of the cow-calf and feedlot components to these emissions, and to examine the proportion of whole-farm emissions attributable to enteric methane (CH₄). The simulated farm consisted of a beef production operation comprised of 120 cows, four bulls, and their progeny, with the progeny fattened in a feedlot. The farm also included cropland and native prairie pasture for grazing to supply the feed for the animals. The LCA was conducted over 8 years to fully account for the lifetime GHG emissions from the cows, bulls and progeny, as well as the beef marketed from cull cows, cull bulls, and progeny raised for market. The emissions were estimated using Holos, a whole-farm model developed by Agriculture and Agri-Food Canada. Holos is an empirical model, with a yearly time-step, based on the Intergovernmental Panel on Climate Change methodology, modified for Canadian conditions and farm scale. The model considers all significant CH₄, N₂O, and CO₂ emissions and removals on the farm, as well as emissions from manufacture of inputs (fertilizer, herbicides) and off-farm emissions of N₂O derived from nitrogen applied on the farm. The LCA estimated the GHG intensity of beef production in this system at 22 kg CO₂ equivalent (kg carcass)⁻¹. Enteric CH₄ was the largest contributing source of GHG accounting for 63% of total emissions. Nitrous oxide from soil and manure accounted for a further 27% of the total emissions, while CH₄ emissions from manure and CO₂ energy emissions were minor contributors. Within the beef production cycle, the cow-calf system accounted for about 80% of total GHG emissions and the feedlot system for only 20%. About 84% of enteric CH₄ was from the cow-calf herd, mostly from mature cows. It follows that mitigation practices to reduce GHG emissions from beef production should focus on reducing enteric CH₄ production from mature beef cows. However, mitigation approaches must also recognize that the cow-calf production system also has many ancillary environmental benefits, allowing use of grazing and forage lands that can preserve soil carbon reserves and provide other ecosystems services.     

Simulating field-scale nitrogen management scenarios involving fertiliser and slurry applications

The long-term effects of nitrogen (N) fertiliser and slurry management practices in agricultural systems has been simulated using event driven physically based models. The Swedish soil water model SOIL and its associated nitrogen cycle model SOILN has been used to simulate the long-term impacts (over 12 years) of 360 management scenarios; three slurry applications with 10 spreading dates (involving single and split applications) for surface spreading and injection of slurry, and three fertiliser applications with two spreading dates. The effects of the N management scenarios on NO₃–N drainage flows, total gaseous N losses and crop yields for grass, winter and spring cereals is investigated. Furthermore, seven soils with varying degrees of drainage efficiency and three climatic conditions (East and West coast Scotland and Southern Ireland) are studied.The aim of this work is to produce N-budget tables for an expert agricultural decision system (ADS) which deals specifically with N best management practises for fertiliser and slurry applications. Simulations conducted in this study were based on input parameters calibrated for specific sites in previous studies on hydrology and NO₃–N transport to subsurface drains with associated crop growth.The results of this study show that increasing rates of N applications (in the form of slurry and fertiliser) resulted in a non-linear increase in both the N leached through subsurface drains and the N harvest yield. Surface spreading and injection of slurry gave similar trends. The most important decision about slurry spreading concerns the selection of spreading date and the selection of fields which are likely to produce only moderate leaching effects. Application of slurry in autumn (as a single or split loading), invariably leads to large losses through N leaching, with a single application always resulting in the highest loss. Significant differences are evident for N leaching from the seven soil types. Climatic variation as exemplified in the three meteorological data sets, produces noticeable and significant differences in both N leached and harvest crop totals. This study also aims to identify that a field environmental risk assessment (ERA) using a physically based model such as SOILN can be determined such that strategic agronomic decisions involving N management can be made. In practice this is so provided that a farm manager can recognise and match the actual soil type and drainage condition of the fields on which spreading is to occur with the simulated field types within a similar climate region.     

Identification of irrigation and N management practices that contribute to nitrate leaching loss from an intensive vegetable production system by use of a comprehensive survey

Considerable NO₃⁻ contamination of underlying aquifers is associated with greenhouse-based vegetable production in south-eastern Spain, where 80% of cropping occurs in soil. To identify management factors likely to contribute to NO₃⁻ leaching from soil-based cropping, a survey of irrigation and N management practices was conducted in 53 commercial greenhouses. For each greenhouse: (i) a questionnaire of general irrigation and N management practices was completed, (ii) amounts of N applied in manure were estimated; and for one crop in each greenhouse: (a) irrigation volume was compared with ETc calculated using a mathematical model and (b) total amount of applied fertiliser N was compared with crop N uptake. Total irrigation during the first 6 weeks after transplanting/sowing was generally excessive, being >150 and >200% of modelled ETc in, respectively, 68 and 60% of greenhouses. During the subsequent period, applied irrigation was generally similar to modelled ETc, with only 12% of greenhouses applying >150% of modelled ETc. Large irrigations prior to transplanting/sowing were applied in 92% of greenhouses to leach salts and moisten soil. Volumes applied were >20 and >40 mm in, respectively, 69 and 42% of greenhouses. Chemical soil disinfectants had been recently applied in 43% of greenhouses; associated irrigation volumes were >20 and >40 mm in, respectively, 78 and 48% of greenhouses conducting disinfection. Nitrogen and irrigation management were generally based on experience, with very little use of soil or plant analysis. Large manure applications were made at greenhouse construction in 98% of greenhouse, average manure and N application rates were, respectively, 432 m³ ha⁻¹ and 3046 kg N ha⁻¹. Periodic manure applications were made in 68% of greenhouses, average application rates for farmyard and pelleted manures were, respectively, 157 and 13 m³ ha⁻¹ (in 55 and 13% of greenhouses); the average N rate was 947 kg N ha⁻¹. Manure N was not considered in N fertiliser programs in 74% of greenhouses. On average, 75% of fertiliser N was applied as NO₃⁻. Applied fertiliser N was >1.5 and >2 times crop N uptake in, respectively, 42 and 21% of crops surveyed. The survey identified various management practices likely to contribute to NO₃⁻ leaching loss. Large manure applications and experiential mineral N management practices, based on NO₃⁻ application, are likely to cause accumulation of soil NO₃⁻. Drainage associated with: (i) the combined effect of large irrigations immediately prior to and excessive irrigations for several weeks following transplanting/sowing and (ii) large irrigations for salt leaching and soil disinfection, is likely to leach accumulated NO₃⁻ from the root zone. This study demonstrated that surveys can be very useful diagnostic tools for identifying crop management practices, on commercial farms, that are likely to contribute to appreciable NO₃⁻ leaching.     

Simulation of bromide and nitrate leaching under heavy rainfall and high-intensity irrigation rates in North China Plain

Heavy rainfall and irrigations during the summer months in the North China Plain may cause losses of nitrogen because of nitrate leaching. The objectives of this study were to characterize the leaching of accumulated N in soil profiles, and to determine the usefulness of Br⁻ as a tracer of surface-applied N fertilizer under heavy rainfall and high irrigation rates. A field experiment with bare plots was conducted near Beijing from 5 July to 6 September 2006. The experiment included three treatments: no irrigation (rainfall only, I0), farmers’ practice irrigation (rainfall plus 100 mm irrigation, I100) and high-intensity irrigation (rainfall plus 500 mm irrigation, I500), with three replicates. Transport of surface-applied Br⁻ and NO₃⁻ (assuming no initial NO₃⁻ in the soil profile) and accumulated NO₃⁻ in soil profiles were all simulated with the HYDRUS-1D model. The model simulation results showed that Br⁻ leached through the soil profile faster than NO₃⁻. When Br⁻ was used as a tracer for surface-applied N fertilizer to estimate nitrate leaching losses, the amount of N leaching may be overestimated by about 10%. Water drainage and nitrate leaching were dramatically increased as the irrigation rate was increased. The amounts of N leaching out of the 2.1-m soil profile under I0, I100 and I500 treatments were 195 ± 84, 392 ± 136 and 612 ± 211 kg N ha⁻¹, equivalent to about 20 ± 5%, 40 ± 6% and 62 ± 7% of the accumulative N in the soil profile, respectively. N was leached more deeply as the irrigation rate increased. The larger amount of initial accumulated N was in soil profile, the higher percentage of N leaching was. N leaching was also simulated in summer under different weather conditions from 1986 to 2006. The results indicated that nitrate leaching in rainy years were significantly higher than those in dry and normal years. Increasing the irrigation times and decreasing the single irrigation rate after fertilizer application should be recommended.     

Nitrate leaching assessment in a long-term experiment under supplementary irrigation in humid Argentina

Applying high rates of nitrogen (N) fertilizer to crops has two major disadvantages: (1) the low N fertilizer use efficiency and (2) the loss of N by leaching, which may cause groundwater nitrate (NO₃⁻) pollution, especially in humid areas.The objectives of this study were to adjust and validate the LEACH-W model simulations with data observed in the field; to quantify nitrate concentrations in the soil solution; to estimate N loss by leaching; and to determine the moments during the year when greatest nitrate transport events occur beyond the rooting profile.A randomized complete block design with four replications was established on a typic Argiudoll. Crop fertilization treatments consisted of three N rates (0, 100, and 200 kg N ha⁻¹) using urea and ammonium nitrate solution (UAN) as the N source. Corn (Zea mays L.) was planted and ceramic soil-water suction samplers were installed to depths of 1, 1.5 and 2 m. Drainage was estimated by the LEACH-W model, which adjusted very well the actual volume of water in the soil profile. Nitrogen losses were statistically analyzed as repeated measure data, using the PROC MIXED procedure.Losses of nitrate-nitrogen (NO₃⁻-N) during the study increased as the rate of N applied increased. At all depths studied, statistically significant higher values were found for 200 N compared to 100 N and 0 N, and for 100 N compared to 0 N (p < 0.001).The greatest NO₃⁻-N losses through leaching occurred during crop growth. Significant differences (p < 0.05) were found between cropping and fallow in the three treatments and depths studied for seasons 4 and 5; these two seasons produced the highest drainage volumes at all depths.     

Spatial and temporal variability of nitrate in irrigated salad crops

The objective of this study was to analyze the spatial and seasonal variations in NO₃ ^–-N concentration in soil samples and solution samplers and the N leaching of an irrigated crop cultivated intensively in the Mediterranean zone. Although much information is available from controlled field experiments concerning N concentration and its spatial variability, quantitative estimates of nitrate fluxes under normal farming conditions and when the field is directly managed by farmers are rare. This is particularly true for gardening crops in the Mediterranean zone, where high evapotranspiration rates lead to intensive irrigation and may be responsible for N leaching. A field experiment was conducted in the Departement du Gard under agricultural conditions. Salads (Cichorium endivia, Lactuca sativa) were planted in three consecutive periods. The field was irrigated with sprinklers. Local measurements with a neutron probe were made at two sites (row, interrow), and an experimental plot (95 m×25 m) was surveyed at 36 points located on a 10 m×10 m equilateral grid to analyze the spatial variability of water and NO₃ ^–-N balances. To analyze the basic statistical properties of our sampling scheme, random fields of soil concentration were simulated with the turning-bands method. Sampling strategy simulations indicated that when a spatial structure exists, sampling according to a regular grid was more efficient than a purely random sampling strategy. Global trends indicated high spatial variability for nitrate leaching with differences between periods of different irrigation intensity (97 kg ha^–1 NO₃ ^–-N leaching during the spring and summer, and 199 kg ha^–1 NO₃ ^–-N leaching during autumn and winter). Leaching caused temporal variations in the spatial distributions of NO₃ ^–-N. The origin of the spatial variability of N leaching was explained by first, the variability in NO₃ ^–-N concentration in the soil profile, and second, by spatial variability in irrigation. Furthermore, the spatial distribution of the NO₃ ^–-N concentration was time dependent, and NO₃ ^–-N spatial distributions became independent after approximately 2 or 3 months under our conditions. Our results show that better management of irrigation and fertilizer in spring and summer may reduce N leaching and, thus, improve ground water quality. Received: 15 March 1996     

Simulation of transpiration, drainage, N uptake, nitrate leaching, and N uptake concentration in tomato grown in open substrate

Free-drainage or “open” substrate system used for vegetable production in greenhouses is associated with appreciable NO₃⁻ leaching losses and drainage volumes. Simulation models of crop N uptake, N leaching, water use and drainage of crops in these systems will be useful for crop and water resource management, and environmental assessment. This work (i) modified the TOMGRO model to simulate N uptake for tomato grown in greenhouses in SE Spain, (ii) modified the PrHo model to simulate transpiration of tomato grown in substrate and (iii) developed an aggregated model combining TOMGRO and PrHo to calculate N uptake concentrations and drainage NO₃⁻ concentration. The component models simulate NO₃⁻-N leached by subtracting simulated N uptake from measured applied N, and drainage by subtracting simulated transpiration from measured irrigation. Three tomato crops grown sequentially in free-draining rock wool in a plastic greenhouse were used for calibration and validation. Measured daily transpiration was determined by the water balance method from daily measurements of irrigation and drainage. Measured N uptake was determined by N balance, using data of volumes and of concentrations of NO₃⁻ and NH₄⁺ in applied nutrient solution and drainage. Accuracy of the two modified component models and aggregated model was assessed by comparing simulated to measured values using linear regression analysis, comparison of slope and intercept values of regression equations, and root mean squared error (RMSE) values. For the three crops, the modified TOMGRO provided accurate simulations of cumulative crop N uptake, (RMSE = 6.4, 1.9 and 2.6% of total N uptake) and NO₃⁻-N leached (RMSE = 11.0, 10.3, and 6.1% of total NO₃⁻-N leached). The modified PrHo provided accurate simulation of cumulative transpiration (RMSE = 4.3, 1.7 and 2.4% of total transpiration) and cumulative drainage (RMSE = 13.8, 6.9, 7.4% of total drainage). For the four cumulative parameters, slopes and intercepts of the linear regressions were mostly not statistically significant (P < 0.05) from one and zero, respectively, and coefficient of determination (r²) values were 0.96-0.98. Simulated values of total drainage volumes for the three crops were +21, +1 and −13% of measured total drainage volumes. The aggregated TOMGRO-PrHo model generally provided accurate simulation of crop N uptake concentration after 30-40 days of transplanting, with an average RMSE of approximately 2 mmol L⁻¹. Simulated values of average NO₃⁻ concentration in drainage, obtained with the aggregated model, were −7, +18 and +31% of measured values.