Assessment of Delta Nitrogen Losses (∆ NL) at the Field Level Jorge A. Delgado 1*, Marvin J. Shaffer 2, Harbans Lal 3 and Shaun Mckinney 3 1 USDA-ARS-Soil.

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Assessment of Delta Nitrogen Losses (∆ NL) at the Field Level Jorge A. Delgado 1*, Marvin J. Shaffer 2, Harbans Lal 3 and Shaun Mckinney 3 1 USDA-ARS-Soil Plant Nutrient Research Unit, Fort Collins Colorado, 80526; * Corresponding Author ; 2 USDA-ARS(retired), Loveland CO 80538; 3 USDA-NRCS, WNTSC, Portland, OR Corresponding Author * Note: If you are interested in the NTT website, please leave your name and address in sheet. We defined a new concept of field-level delta nitrogen (N) losses (∆ NL) as a comparison between management scenarios. We defined delta nitrogen losses (∆ NL) as a function of improved N use efficiencies of field management scenarios that reduce the average N inputs and/or modify other management practices thus lowering N losses from a farm field. The ∆ NL refer to potential downstream reductions in nonpoint source nitrogen loading of streams or other water bodies and/or in reduced loading of the atmosphere with N-associated greenhouse gases from agriculture. Nitrogen credits as traded on the Communities Market commonly refer to discounted reductions in agricultural nitrogen losses that apply to a project downstream from an agricultural area. We used a newly released Windows XP version of the Nitrogen Loss and Environmental Assessment Package (NLEAP) with a Geographic Information System (GIS) capability (NLEAP-GIS) to assess no-till systems from a humid North Atlantic US site, manure management from a Midwestern US site, and irrigated cropland from an arid Western US site. The new NLEAP-GIS can be used to quickly identify the best scenario that shows the greatest potential to maximize field-level ∆ NL for environmental conservation. Abstract Summary and Conclusions The new concept of field-level ∆ NL was defined as a function of improved N use efficiencies of field management scenarios that reduce the average N inputs and/or modify other management practices thus lowering N losses from a field. A spatial/temporal N loss tool such as NLEAP-GIS can be used to quickly identify the best scenario that shows the greatest potential to maximize ∆ NL at the field level and minimize N losses to the environment. The assessment of ∆ NL at the field level was also incorporated into the new version of the NLEAP-GIS (Fig. 6). A prototype Nitrogen Trading Tool (NTT) using this concept was developed by USDA-NRCS-ARS to assess N losses to the environment using internet capabilities (Fig. 7). The ∆ NL approach can be used to conduct quick assessment of management practices on N losses and help nutrient managers make decisions that contribute to positive reductions in farm N inputs and that improve nitrogen use efficiencies. In our approach, we interpret these ∆ NL as positive reductions in farm N inputs and other management changes that improve nitrogen use efficiencies, as shown by a positive reduction in N losses and potential positive reduction in N transport to the environment that could be used to help assess Nitrogen Trading Tool opportunities. References Delgado, J.A Quantifying the loss mechanisms of nitrogen. J. Soil Water Conserv. 57: Delgado, J. A., M. J. Shaffer, H. LAL and S. McKinney Assessment of Delta Nitrogen Losses at the Field Level (In review) Hall, M.D., M.J. Shaffer, R.M. Waskom and J.A. Delgado Regional nitrate leaching variability: What makes a difference in northeastern Colorado. J. Am. Water Resource Assoc. 37: Shaffer, M.J., and J.A. Delgado Field techniques for modeling nitrogen management. p In R.F. Follett and J.L. Hatfield (ed.) Nitrogen in the environment. CRC Press, New York, NY. Shaffer, M.J., J.A. Delgado, C. Gross and R.F. Follett Nitrogen Loss and Environmental Assessement Package. In Advances in Nutrient management for Water Quality (Accepted) Introduction Figure 3. Twenty-four year simulation for a continuous potato (PP) and barley (BB) rotation in relation to NO 3 -N leached (medium nitrogen input for a rotation grown in Gunbarrel soil in Colorado). Figure 4. Twenty-four year simulation of fall and spring applied (double rate, MSDR) and manure reduced rate (spring applied, MSRR) applications in relation to dentrification losses (forage corn grown in Haskin soil in Ohio). Figure 5. Twenty-four year simulated N 2 O-N emissions from the continuous, no- till corn on Tetotum loam and Bojac sandy loam soils from Virginia. Delta N Method Figure 6. Nitrogen Trading Tool in NLEAP-GIS new XP windows version Figure 7. Nitrogen Trading Tool Internet version (USDA-NRCS and ARS cooperation) *. We propose a new approach to assess ∆ NL that integrates inputs changes, other management changes, local soil factors and climate for each farm, then applies simulation modeling to compare changes in N losses that can be translated into N credits. This reduces uncertainty and allows the introduction of the all-important spatial and time factors into the process. Depending on local regional conditions, proposed management changes may or may not have immediate effects on N loading downstream, and the magnitude of these effects is likely to change over time. The final assessment for N credits should result from a prediction of effect at the target project over the lifetime of the project. There is a need to evaluate the effect of management scenarios on atmospheric, leaching, and surface transport N losses at the field level with a new ∆ NL system approach. Our ∆ NL concept is based on improving N management practices that reduce N inputs, increase N use efficiency, and reduce N losses within a watershed starting at the field level. To avoid accounting for N inputs twice (while we are quantifying N losses in the environment), we need to understand and assess the N inputs, processes, and N losses with an N balance approach within the N cycle (Delgado, 2002). We cannot simultaneously include reductions in N inputs and N losses, since this would be double accounting. We recommend a modeling approach based on long-term simulations and GIS to evaluate effects of the management scenarios accounting for N inputs (e.g., high, medium and low N inputs), crop rotations, soil factors and other management options on long term N losses from the field. There is potential to apply environmental credits to account for reductions in nonpoint sources of N. To assist with these efforts, prototype Nitrogen Trading Tools (NTT) are being developed. We defined the new concept of field-level delta nitrogen (N) losses (∆ NL) as a comparison between management scenarios that include the major N loss components (Fig. 1). We defined a positive delta N (+∆ NL) as a scenario that positively impacts the environment by reducing N losses with a new management scenario. We defined a negative delta N (-∆ NL) as a scenario that negatively impacts the environment by increasing N losses. A negative delta represents the increase of N losses to the environment. Sites and best management scenarios: To demonstrate the N simulation model’s mass balance approach to assess the new nitrogen ∆ NL concept, we selected three general management scenarios from diverse regions of the US. We evaluated typical no-till systems from the humid North Atlantic region (Virginia), manure operations from the Midwestern US region (Ohio), and irrigated systems from the dry Western US region (Colorado). We collected information from these regions and developed average scenarios that were representative of local practices following a simulated approach as described by Shaffer and Delgado (2001). Details of the management scenarios tested at each site are described in Delgado et al. (2007, in review). Time frame (24 years): For a modeling approach to evaluate the effect of management scenarios and crop rotations on reduced N losses, we suggest a time period that consists of 12 years of sequential model initialization and 12 years of sequential model evaluation. Soil and weather databases and assessments of long-term effects on delta nitrogen losses: We used the USDA-NRCS SURRGO soil and weather databases that were assessed and downloaded from NRCS Internet web sites. We selected the new NLEAP model to assess ∆ NL for the Nitrogen Trading Tool (NTT) (Shaffer et al. 2008). This simulation model has been widely tested across several sites in the USA (Fig. 2) (Hall et al. 2001) and internationally. NLEAP was able to simulate losses of NO 3 -N leaching (Fig. 3), denitrification (Fig. 4) and N 2 O emissions (Fig. 5) across the U.S. regions. An example of the Delta N losses in NLEAP-GIS is shown in Figure 6. An example of assessment of Delta N losses for a USDA-NRCS/ARS internet prototype Nitrogen Trading Tool is shown in Figure 7. FIELD SOIL PROFILE (Basic Management Scenario – New Management Scenario) = Inputs Manure/Compost N Fertilizer, N Fixation Legumes Figure 1. Flows of nitrogen for an assessment of delta nitrogen losses for nitrate leaching (  NO 3 -N), nitrogen surface transport (  N st -N), ammonia volatilization (  NH 3 -N), nitrous oxide emissions (  N 2 O-N) and denitrification (  N 2 -N). N 2 O-N NO 3 -N NH 3 -NN 2 -N N st -N Where:  N L -N =  NO 3 -N +  N 2 -N +  N 2 O-N +  NH 3 -N +  N st -N Observed (kg-N/ha) Predicted kg N / ha 1:1 Correspondence R 2 = 0.89 NLEAP Residual Soil Nitrate-N Figure 2. As an example, the combined results for 150+ site-years of validation testing of NLEAP under irrigated agriculture in northeastern and south-central Colorado (from Hall et al. 2001). Accounted above Optional