Nitrate Leaching And Economic Analysis Package Research Articles

Nitrogen Dynamics and Losses in Direct‐Drilled Maize Systems

The knowledge of nitrogen (N) losses in direct‐drilling agrosystems is essential to develop strategies to increase fertilizer efficiency and to minimize environmental damage. The objectives were i) to quantify the magnitude of N volatilization and leaching simultaneously as affected by different urea fertilization rates and ii) to evaluate the capacity of these specific plant–soil systems to act as a buffer to prevent nitrate leaching. Two experiments were conducted during 2001/02 and 2002/03 growing seasons in Alberti, Argentina. The crop was direct‐drilled maize and the soil a Typic Argiudoll. Ammonia losses, N uptake by crop at flowering and harvest, grain yield, N in previous crop residues, and soil nitrate content up to 2‐m depths were determined. Nitrogen availability, soil nitrate (NO3)‐N up to 1 m plus fertilizer N, was linearly and highly associated with crop N uptake at flowering (R2=0.93, P<0.01) and at harvest (R2=0.852, P<0.01). Around 17.5% of fertilizer N was lost by volatilization in 10 days. The obtained values of residual nitrate N up to the 150‐cm depth were associated (R2=0.960, P<0.001) with those predicted by the nitrate leaching and economic analysis package (NLEAP) model. Maize in the direct‐drilling system was able to cycle N from the previous crop residues, N from soil organic matter, and N from fertilizers with few losses.

Characterizing Coral Condition Using Estimates of Three-Dimensional Colony Surface Area

Readily available nitrogen (N) sources such as ammonium nitrate with excessive irrigation present a potential hazard for the environment. The computer program Nitrate Leaching and Economic Analysis Package (NLEAP) is a mechanistic model developed for rapid site-specific estimates of nitrate-nitrogen (NO3-N) moving below the root zone in agricultural crops and potential impacts of NO3-N leaching into groundwater. In this study, the value of NLEAP was tested to simulate N uptake by crops and NO3-N leaching parameters in large lysimeters under the tomato crop. Three seedlings of tomato variety of H-2274 (Lycopersicum esculentum L.) were transplanted into each lysimeter. N fertilizer at the rate of 140 kg N ha(-1) was sidedressed in two split applications, the first half as ammonium sulphate and the second half as ammonium nitrate. The lysimeters were irrigated based on programs of C 0.75, 1.00, 1.25 and 1.50, C referring to class A-Pan evaporation coefficients. Parameters such as leaching index (LI), annual leaching risk potential (ALRP), N available for leaching (NAL), amount of NO3-N leached (NL) and amount of N taken up by the crops (NU) were estimated using the NLEAP computer model. To test the ability of model to simulate N uptake and NL, measured values were compared with simulated values. Significant correlations, R2 = 0.92 and P < 0.03 for the first year and R2 = 0.86 and P < 0.06 for the second year, were found between measured and simulated values for crop N consumption, indicating that the NLEAP model adequately described crop N uptake under the varied irrigation programs using an optimal N fertilization program for the experimental site. Significant correlations, R2 = 0.96 and P < 0.01 for the first year and R2 = 0.97 and P < 0.01 for the second year, were also found between measured and simulated values of NL, indicating that the NLEAP model also adequately predicted NL under the varied irrigation programs. Therefore, this computer model can be useful to estimate the NO3-N moving beyond the root zone under conditions in which the present experiment was carried out. Also, the NLEAP-estimated NAL values and other parameters can also be used to improve N management practices and N fertilizer recommendations that will help to decrease the adverse effect of N fertilizer on groundwater quality and farm profitability.

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

Groundwater pollution caused by leaching of NO 3-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 NO 3-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 NO 3. The model adequately simulated nitrogen leaching for each year ( R 2=0.93 and P<0.03 for 1996, and R 2=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 NO 3 leaching under the experimental conditions. The results also showed that the NO 3 available for leaching (NAL) values were important background information for determining an optimum N rate for groundwater quality and maximum gain, and NO 3 available for leaching (NAL), amount of NO 3 leached (NL), movement risk index (MRI), and annual leaching risk potential (ALRP) parameters should be considered together to estimate the nitrogen pollution risk.

Evaluation of Nitrate‐Nitrogen Transport in a Potato–Barley Rotation

Well water NO−3–N concentrations have been found to exceed 10 mg L−1 of NO−3–N for some areas of the San Luis Valley (SLV) of South‐Central Colorado. The region's predominant soils are sandy soils, with a dominant potato (Solanum tuberosum L.) followed by malting barley (Hordeum vulgare L.) crop rotation. There is limited knowledge about how much NO−3–N is lost by leaching from these systems, and protocols need to be developed to evaluate the NO−3–N transport out of these coarse textured soils from these arid and semiarid irrigated cropping systems. Management information, N content at harvest, initial and final NO−3–N in the soil profile, and other supportive data were collected at 14 commercial fields and used as inputs for the Nitrate Leaching and Economic Analysis Package (NLEAP) model, version 1.20. NLEAP simulated available soil water for the root zone as well as the transport of NO−3–N in the soil profile, and can be used as part of the protocol to evaluate the NO−3–N transport of these systems. Best recommended practices in this region, such as application of N fertilizer rates on the basis of soil test analysis and split applications of N fertilizers, kept the net transport of NO−3–N out of the potato–barley systems to a minimum. Our approach of applying simulation models to assess management scenarios showed that barley served as a scavenger for the NO−3–N that was added with irrigation water and the residual soil nitrate from the potato growing period.

An Internet-based simulation model for nitrogen management in agricultural settings.

Complex chemical, physical, and biological processes mediate nitrogen (N) transformations and movement during agricultural production, making the optimization of fertilizer use and environmental protection exceedingly difficult. Various computer models have been developed to simulate the site-specific fate and transport of N resulting from different crop production scenarios, but these models are very complex and difficult to use for most farmers, consultants, and conservationists. In an effort to facilitate access and simplify the use of sophisticated models, the U.S. Department of Agriculture (USDA) has developed an Internet-based nitrogen analysis tool. Based on the Nitrate Leaching and Economic Analysis Package (NLEAP), the Web site allows a user to conduct multiyear N simulation modeling specific to a crop field. Servers handle much of the required data assembly and formatting, thus sparing the user's resources. Model runs are executed on the servers and the results are transmitted to the user. This new tool is presented along with early implementation results.

Simulation of Nitrate‐Nitrogen Dynamics for Cropping Systems with Different Rooting Depths

Most agricultural systems in the San Luis Valley of south‐central Colorado include rotations that have crops with different rooting depths. The previous version of Nitrate Leaching and Economic Analysis Package (NLEAP), 1.10, was only capable of simulating the effect of management practices on the rooting zone of each crop to the nearest 0.30‐m increment. Therefore, a new version of NLEAP was needed to simulate the effect of best management practices (BMPs) on residual soil NO−3–N (RSN) for the root zone of each crop grown in the region and for a similar soil depth for these systems (e.g., 0–0.91 m). The improved NLEAP version 1.20 simulates maximum rooting depth to the nearest 0.03 m and RSN in multiple soil depths. These new features allowed us to simulate the effect of BMPs on RSN for the root zones of shallower‐rooted crops such as lettuce (Lactuca sativa L.) (0–0.37 m), potato (Solanum tuberosum L.) (0–0.40 m), and deeper‐rooted crops such as small grains (0–0.61 to 0–0.84 m). NLEAP simulated RSN for a soil depth identical for all of these cropping systems (0–0.91 m) (P &lt; 0.001). This new version can be used by extension agents, farmers, consultants, and others to evaluate the effect of BMPs on soil NO−3–N dynamics for different rooting zones and for similar soil depths in the agricultural system, a capability that was not available with the previous version of NLEAP.

Simulating the Impact of Management Practices on Nitrous Oxide Emissions

AbstractEffective evaluation of alternative management strategies to control global warming requires tools for simulating emissions of N2O from soils across a range of soil properties, weather, and management inputs. We hypothesized that with modification to the nitrification and denitrification submodels of the Nitrate Leaching and Economic Analysis Package (NLEAP) model, we could simulate daily N2O emissions as a function of soil moisture, temperature, N content, and other factors. Field parameterization was conducted on an Ulm clay loam soil (a fine, montmorillonitic, mesic Ustollic Haplargid) and validation experiments for N2O gas emissions were performed on an on‐farm swine effluent study site on a Valent sandy soil (a mixed, mesic Ustic Torripsamment). The unitless model parameters reflecting the maximum fraction of selected N transformations emitted as N2O for nitrification (αN), wet‐period denitrification (αw), and dry‐period denitrifiation (αd) were calibrated as 0.065, 0.050, and 0.520 separately and then used in the validation study. The trends and magnitudes of simulated N2O emissions were statistically consistent with the results obtained from the field experiments (r = 0.78). Experimental results showed that the decline of N2O emission rates from 70 to 2 g N ha−1 d−1 during the growing season was related to soil N content decline from 33 to 4 mg kg−1. Simulated effects of field management on annual N2O emissions indicated that plowing decreased N2O relative to notillage corn (Zea mays L.), irrigation increased N2O 14% relative to dry‐land corn, and doubling fertilization N rates from 100 to 200 kg ha−1 increased N2O emissions 60%.

NLEAP model simulation of climate and management effects on N leaching for corn grown on sandy soil

The Nitrate Leaching and Economic Analysis Package (NLEAP) model was used to evaluate effects of climate and N fertility on nitrate leaching from a 3-yr field experiment of continuous corn ( Zea mays L.). Half of the plots were randomly chosen to be either nonirrigated or irrigated (based upon calculated potential evapotranspiration). Three replications of nitrogen (N) fertility (56, 112 and 224 kg ha −1) were used. Soil was a Hecla sandy loam to loamy sand (Pachic Udic Haploboroll). Soil and climate data were from the upper Midwest U.S.A. database for NLEAP. On-site data were used in the model when available. This study shows that NLEAP is capable of integrating data collected for nonirrigated and irrigated conditions on sandy soil for a wide range of N treatments and predicting the nitrate available for leaching (NAL). Precipitation distribution and amount were different in each year. Calculated NAL provided an excellent indicator of potential nitrate leaching hazard. NLEAP output showed that leaching of residual N on this sandy soil is very sensitive to early-spring precipitation. The NLEAP model provided valuable insights concerning effects of climate and N and irrigation management on N leaching. To obtain optimum yields while minimizing nitrate leaching, this study indicates the need to use soil and plant-tissue testing, post-emergence N-fertilizer application, and modem irrigation-scheduling technology. Also, use of the NLEAP model along with field-plot experiments provide additional important information concerning timing of N-leaching events relative to climate and an additional assessment of the effectiveness of fertilizer-N management decisions.

Identification and mitigation of nitrate leaching hot spots using NLEAP-GIS technology

Leaching of NO 3N from agricultural lands often occurs in well-defined hot spot areas when viewed across geographical regions of hundreds or thousands of kM 2 and often appears as areas of high NO 3N concentrations in shallow underlying aquifers. Delineation of high-NO 3N zones can be achieved by combining models such the Nitrate Leaching and Economic Analysis Package (NLEAP) with Geographical Information System (GIS) technology to calculate the long-term potential mass of NO 3N leached from the crop root zone. Once identified, the hot spots can be further analyzed with the model to evaluate and rank appropriate alternative management techniques. A simulation analysis using the NLEAP model showed that long-term NO 3N leaching from corn ( Zea mays L.) grown under furrow irrigation on a coarse-textured soil could be reduced by 53% with N management alone, while an 84% reduction in leached NO 3N was achieved for combined N and water management (sprinkler irrigation). This type of modeling analysis can be completed after a few weeks of effort, while comparable field studies would take several years to finish.

REGIONAL ASSESSMENT OF NLEAP NO3‐N LEACHING INDICES1

ABSTRACT: Nonpoint source ground water contamination by nitrate nitrogen (NO3‐N) leached from agricultural lands can be substantial and increase health risks to humans and animals. Accurate and rapid methods are needed to identify and map localities that have a high potential for contamination of shallow aquifers with NO3‐N leached from agriculture. Evaluation of Nitrate Leaching and Economic Analysis Package (NLEAP) indices and input variables across an irrigated agricultural area on an alluvial aquifer in Colorado indicated that all leaching indices tested were more strongly correlated with aquifer NO3‐N concentration than with aquifer N mass. Of the indices and variables tested, the NO3‐N Leached (NL) index was the NLEAP index most strongly associated with groundwater NO3‐N concentration (r2 values from 0.37 to 0.39). NO3‐N concentration of the leachate was less well correlated with ground water NO3‐N concentration (r2 values from 0.21 to 0.22). Stepwise regression analysis indicated that, although inorganic and organic/inorganic fertilizer scenarios had similar r2 values, the Feedlot Indicator (proximity) variable was significant over and above the NO3‐N Leached index for the inorganic scenario. The analysis also showed that combination of either Movement Risk Index (MIRI) or NO3‐N concentration of the leachate with the NO3‐N Leached index leads to an improved regression, which provides insight into area‐wide associations between agricultural activities and ground water NO3‐N concentration.

Using climate/weather data with the NLEAP model to manage soil nitrogen

Local climate/weather conditions can have profound effects on soil fertility management and leaching of nitrates. The application of simulation models together with appropriate climate and soil databases provides a mechanism to evaluate current and alternative management options and identify techniques that will minimize nitrate leaching. The Nitrate Leaching and Economic Analysis Package (NLEAP) model and databases were applied in the form of sensitivity analyses to rainfed climate conditions found in the midwest and to irrigated agriculture in the semiarid Great Plains. Model results supported with field validation data illustrate the importance of local climate/weather patterns on nitrogen management and nitrate leaching amounts and distributions. Site-specific management strategies appear to be necessary for optimal fertility management and control of nitrate leaching. Results obtained from short term transient and long term steady state runs with the NLEAP model illustrate how the model can be used in conjunction with appropriate climate databases as an aid to management decisions regarding control of nitrate nitrogen leaching.

Soil Nitrate Leaching Potential Indices: Using a Simulation Model as a Screening System

AbstractSimulation models LEACHM‐N (Leaching Estimation and Chemistry Model) and NLEAP (Nitrate Leaching and Economic Analysis Package) were first tested using NO3 leaching data obtained from lysimeter and tile drainage studies conducted at three University of Minnesota experiment stations. Both simulation models did well in simulating total (seasonally accumulated) leaching loss of NO3‐N from the soil profile. LEACHM‐N was selected as a screening tool to develop soil NO3 leaching potential (NLP) ratings using soil survey information and representative county weather station data. Simulated growing season total NO3‐N leached from the soil profile (below 1.5 m) were used as NLP index. Crop management practices and initial N were kept constant. Soil NO3 leaching potential ratings for three Minnesota counties, Redwood, Stearns, and Sherburne were developed using this method. This soil NLP rating information was included in the Soil Survey Information System (SSIS) to create leaching potential rating maps, which can be used to plan best N management schemes.