Reducing Nutrient Losses While Increasing Farm Profit Through Precision Conservation

Date: 
Dec 2015

Issue

Efforts to reduce nutrient losses may be hampered by perceived economic costs and privacy concerns. In some cases, farmers have not seen a clear economic incentive to change land management in ways proven to reduce nutrient losses, and don’t want to share detailed information about their farm operation with public entities.

Objective

This project is designed to show farmers where incorporating adaptive management practices would save them money and how it would improve water quality, without asking them for data.

Approach

A combination of high-precision, site-specific data, publicly available data and cropping system models will be used to identify the least profitable areas of fields that also have the greatest potential for nitrogen loss. Results will provide clear, spatially explicit estimates of nitrogen loss and be delivered to farmers through a commercially supported web-based tool.

Project Updates

September 2017

FINAL REPORT

Evidence from our research and others suggests that the poorest economic performing areas of crop fields may also be some of the poorest performers environmentally. Our research developed a method that takes either yield monitor data or publicly available data and combines it with field and modeling research on alternative management strategies. We feel this work could potentially alter the way we manage crops. By targeting specific areas of fields in a data intensive and spatially explicit way, we can manage for higher yields or alternative low input land covers. This could potentially increase farmer profit and minimize nutrient runoff.

Objective 1. Evaluate the impact of incorporating adaptive management practices identified in NRS Scientific Assessment on profitability and water quality at the sub-field and regional scale.

After finalizing the analysis of state wide simulations, we completed an analysis to separate management vs soil factors underlying spatial patterns in nitrogen loss and profitability.  We have also completed the aggregation of the state wide numbers to estimate the total state N budget.  These analyses are discussed in the publication, "Targeted subfield switchgrass integration could improve the farm economy, water quality, and bioenergy feedstock production,"  which has now been accepted by Global Change Biology Bioenergy (see Brandes et al, 2018, in Research Publications, under N&P Management).

Objective 2. “ Develop a tool to assist farmer decision for precision placement of nutrients and/or perennials”.   

The site specific, yield monitor-driven version of the analysis is nearly complete.  We have completed the evaluation against the Gilmore City observations and are moving to a case study to demonstrate application.  We have now completed the sensitivity analysis to determine the dependence of model assumptions on model outputs.  This sensitivity analysis will help improve the framework for the decision support tool.  The next step will be for AgSolver to begin testing the tool with their Profit Zone Manager customers.  The research and development for this step is complete, however the release of the tool will depend on the outcome of actions at AgSolver.

March 2017

After finalizing the analysis of statewide simulations, researchers began an analysis to separate management versus soil factors underlying spatial patterns in nitrogen loss and profitability. Aggregation of the statewide numbers to estimate the total state N-budget is underway. The site-specific, yield-monitor-driven version of the analysis is nearly complete. A sensitivity analysis has been added to determine the dependence of model assumptions on model outputs. This sensitivity analysis will help improve the framework for the decision support tool.

December 2016

Analysis of statewide simulations is being finalized.  Current results quantify the impact of switchgrass integration at varying thresholds of replacement that depend on simulated profitability and N loss for a respective land unit. The team conducted two additional analyses. One represents a conservative scenario where less than 10% of current land is converted, which limits conversion to the least profitable and highest leaching areas in Iowa. The other is an aggressive scenario where about 41% reduction in nutrient loss occurs. The site-specific, yield-monitor driven version of the analysis is nearly complete, and the team is developing a case study to demonstrate application. The framework is in place for this decision support tool. 

September 2016

Statistical analysis of the evaluation of model simulations against data collected for 1989 to 2015 at the Gilmore City site has indicated a model overestimation of nitrate leaching in dry years. The team continues to adjust for tile drainage, plus is correcting errors in weather inputs to improve model calibration before moving to large-scale simulation for the test sites. The simulations have been run at the common land unit scale for the entire state of Iowa. The team has added in varying price and yield assumptions as well as fertility management options. Outputs have been analyzed at the county and state scale. Preliminary results indicate perennial placement on unprofitable acres can reduce nitrate leaching. 

June 2016

The team is in the statistical analysis phase of evaluating model simulations against data collected and maintained from 1989-2015 at the Gilmore City site. Initial results indicate there are some model biases that lead to underestimation of nitrate leaching in years where the observed values are large.  The team is working to adjust for tile drainage and improve model calibration before moving to large-scale simulation at the test sites. Simulations have been run at the common land unit scale for the entire state of Iowa. These outputs are being analyzed at the county and state scale. Preliminary results indicate perennial placement on unprofitable acres can reduce nitrate leaching.  

March 2016

The team is progressing through the evaluation of model simulations against data collected and maintained from 1989-2015 at the Gilmore City site. Management, soil and weather data sets are complete and simulations have been conducted. Those data now are being evaluated against the leaching data observed for each plot over the lifespan of the experiment. The field experiment was planted and the nitrogen treatments were applied. In an effort to develop a tool to assist farmer decision for precision placement of nutrients and/or perennials, simulations are being run at the common land unit scale for the entire state of Iowa. These outputs will be the basis for the tool once performance evaluations are complete.

December 2015

Carbon and nitrogen samples taken at a subfield-scale from an ongoing precision nitrogen management field project are being processed. Model development is in the implementation phase, and simulations have been conducted for each of the fields in the database. To work towards a tool to assist farmer decision on precision placement of nutrients and/or perennials, the team developed a visualization of profitability distribution, as well as explanatory input variables in maps and diagrams. This provided a better understanding of the cost and revenue dynamics that led to the drastic decrease in profitability in 2015 compared to previous years. A manuscript was written and submitted to Environmental Research Letters on the profitability results, and the implications these have on economic incentives for management change.