economics – Livestock and Poultry Environmental Learning Community

April 21, 2022June 22, 2022

Evaluating Costs and Benefits of Manure Management Systems for a Decision-Support Tool

Purpose

The purpose of the decision-support tool is to help livestock producers understand the costs of implementing new technology and the potential benefits associated with nutrient and water recovery, and how these compare across systems. Livestock agriculture is under increased scrutiny to better manage manure and mitigate negative impacts on the environment. At the same time, the nutrients and water present in manure management systems hold potential economic value as crop fertilizer and irrigation water. While technologies are available that allow for recovery and/or recycling of solids, nutrients and water, appropriate decision-support tools are needed to help farmers evaluate the practicality, costs, and benefits of implementing these systems on their unique farms.

What Did We Do?

In designing and refining the tool, we consider which economic components are important in driving the decision algorithm, as well as what is the most valuable economic output information for the user. We developed several “scenarios” defined by the unit processes used in the capture, treatment, storage, and usage of dairy manure. The costs and benefits related to each unit process were evaluated and aggregated for each scenario. Unit processes included flush/scrape activities, reception pit, sand recovery, solids separation, anaerobic digestion, composting, pond/lagoon storage, and tanker/drag hose land application.

Economic information was gathered from published literature, government documents, extension tools, and communication with academic, industry, and extension experts. We evaluated capital costs as an annual capital recovery value; operational costs including labor, energy, and repair and maintenance; cost savings resulting from sand/organic bedding and water reuse; fertilizer value of manure for use on-farm; revenue potential including the sale of treated manure nutrients and energy from anaerobic digestion; and the combined net costs or net benefits. Economic results are integrated into the multi-criteria decision algorithm. Results also elucidate economic tradeoffs across manure management systems (MMS), which can be used by farmers to assist in their decision-making.

What Have We Learned?

Economics is often about evaluating trade-offs between different choices or decisions. When evaluating results from the tool, we see that an increase in capital spending may lead to decreases in operational costs relative to capital costs, depending on farm size. This is due to a general reduction in labor and fuel costs associated with automated or additional manure treatment (e.g. increased spending on an MMS). For example, additional manure treatment can reduce land application expenses and increase cost savings from recovered sand or organic bedding. However, this larger capital outlay may or may not be possible based on the farm’s financial circumstances.

Future Plans

The next steps are to complete the economic analyses of a total of 60 MMS and integrate these into the decision-support tool. We plan to demonstrate this tool to extension specialists and producers to refine the user interface, key assumptions, functioning of the decision algorithm, and the usability of the results.

Authors

Erin E. Scott, PhD Graduate Assistant, University of Arkansas

Corresponding author email address

erins@uark.edu

Additional authors

Sudharsan Varma Vempalli, Postdoctoral Research Associate, University of Arkansas

Jacob Hickman, Program Coordinator, University of Arkansas

Jennie Popp, Professor, University of Arkansas

Richard Stowell, Professor, University of Nebraska-Lincoln

Teng Lim, Extension Professor, University of Missouri

Greg Thoma, Professor, University of Arkansas

Lauren Greenlee, Associate Professor, Penn State University

Additional Information

Related presentation during this session by Varma et al., titled “A Decision-Support Tool for The Design and Evaluation of Manure Management and Nutrient Reuse in Dairy and Swine Farm Facilities”.

Acknowledgements

We acknowledge funding support from the United States Department of Agriculture (USDA) National Institute of Food and Agriculture (NIFA) grant award (# 2018-68011-28691). We would also like to thank our full project team and outside experts for their guidance on this project.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2022. Title of presentation. Waste to Worth. Oregon, OH. April 18-22, 2022. URL of this page. Accessed on: today’s date.

March 5, 2019March 20, 2019

Inclusion of the Environment Bottom Line in Waste to Worth: The Interaction Between Economics, Environmental effects, and Farm Productivity in Assessment of Manure Management Technology and Policy

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Purpose

In a global context, the pork industry constitutes a huge economic sector but many producers operate on very thin margins. In addition, pork is one of the largest and most important agricultural industries in North Carolina and the United States but faces a number of challenges in regards to waste management and environmental impacts.On more local scales, swine producers face a number of additional constraints including land availability, waste management options (technical and regulatory), nutrient management costs, profits, risk, and return on investment. In the face of increasingly stringent environmental regulations, decreasing land availability, and higher costs for fertilizer, it is necessary to consider alternative technologies with the potential for improving environmental conditions and creating value added products. Technology assessments generally focus on technical performance as the measure of “utility” or usefulness. Primary physical performance measures such as efficiency, production rate, and capacity, while necessary may not be sufficient for capturing the overall value of a technology. A significant amount of research has evaluated the feasibility of technology adoption based on traditional economic measures but far less research has attempted to “value” environmental performance either at farm-scale or in the larger context (e.g. supply chain response to changes in technology or policy and regulation). Considering response over time, the extent to which environmental and economic policies and regulations positively or negatively affect technology innovation, emission and nutrient management, competitiveness, and productivity, remains largely unknown.

The purpose of this study is to evaluate the environmental and economic tradeoffs between current swine waste management practices in North Carolina and alternative scenarios for future on-farm decision making that include new technologies for waste removal, treatment, and nitrogen recovery. In addition, we begin to understand these economic and environmental tradeoffs in the context of various environmental policy and regulation scenarios for markets of carbon, electricity, and mineral fertilizer.

What did we do?

Using waste samples from swine finishing farms in southeastern NC, laboratory and bench scale experiments were conducted to determine the quantity and quality of biogas generation from anaerobic digestion and nitrogen recovery from an ammonia air stripping column. Based on these data as well as information from literature, six trial life cycle assessment scenarios were created to simulate alternatives for annual manure waste management for one finishing barn (3080 head) on the farm. Materials, energy, and emissions were included as available for all system components and processes including but not limited to waste removal from barns (flushing or scraping), treatment (open air lagoon or covered lagoon digester), nitrogen recovery (ammonia air stripping column), and land application (irrigation). A description of the scenarios as well as processes that are included/excluded for each can be found in Table 1. All scenarios were modeled over a one year operational period using a “gate to gate” approach where the mass and energy balance begins and ends on the farm (i.e. production of feed is not included and manure is fully utilized on the farm). It was assumed that each scenario included an existing anaerobic treatment lagoon with manure flushing system (baseline, representative of NC swine farms). In the remaining scenarios, the farm had an option of covering the lagoon and using it as a digester to produce biogas (offsetting natural gas); covering the digester and ammonia air stripping column for nitrogen recovery (offsetting mineral ammonium sulfate); installing a mechanical scraper system in the barn (replaces flushing); and/or different combinations of these. Open LCA, an open source life cycle and sustainability assessment software, was used for inventory analysis and the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI 2.0) was used to characterize environmental impacts to air, water, and land. From Table 2 preliminary results indicate that all scenarios had a similar pattern in terms of impact for the assessed categories. The open air lagoon had the highest overall environmental impact followed by scraping manure with digestion and recovery and scraped slurry digestion with no nutrient recovery. Flushed manure to the digester with nutrient recovery had the lowest overall environmental impact, followed closely by scraped whole slurry to the digester with nutrient recovery.

Using energy and emissions data from the initial life cycle assessment on alternative scenarios for swine waste management systems we have started to characterize the environmental and economic outcomes arising from selected on farm technologies. More specifically we began to examine the regulatory, institutional, and market barriers associated with technology adoption within the swine industry. We provide a theoretical model to support quantification of the change in revenues and expenses that result from changes in three major markets connected to swine production – carbon, electricity, and fertilizer. We examine some of the economic characteristics of environmental benefits associated with changes to farm practices. Finally, we discuss implications for innovation in technology and policy.

What have we learned?

Preliminary results are somewhat mixed and further research is needed to see how sensitive the life cycle assessment inputs and outputs are to system components. While there is a clear indication that covering lagoons, with or without additional nutrient recovery, reduces environmental impact – farm scale systems can be quite expensive and no further determination can be made until a full economic analysis has been conducted. Modeling secondary effects, such as increased ammonia emissions in barns from flush water recirculated from digesters, remains to be included. Besides farm level cost and returns, review of literature has pointed to additional barriers to adoption of reduced environmental impact technologies. Examples of barriers include deficient or non-existent markets for environmental benefits, and various state and federal regulations and policies related to renewable energy, carbon offsets, new farm waste management technology, etc. Solutions such as better cooperation between energy firms, regulatory agencies, and farmers as well as increased financial incentives such as carbon credits, renewable energy credits, net metering options, and enabling delivery of biogas to natural gas pipelines can greatly increase the profitability and implementation of this technology on NC hog farms.

Future Plans

As this is an ongoing multi-disciplinary project, future plans include the expansion of existing data to form a more comprehensive life cycle inventory with options for both new and existing swine farms, which include additional options for waste treatment, nutrient recovery, and land application/fertilizer methods, etc. Energy and emissions data from the life cycle model will continue to be utilized as inputs into a more fully integrated model capable of reflecting the true “cost” and “values” associated with waste management treatment systems. In addition, it is expected that the integrated model will include the flexibility to simulate overall costs and returns for various sizes of operations within the county, region, and if possible state-wide.

Corresponding author, title, and affiliation

Shannon Banner, Graduate Student, North Carolina State University

Corresponding author email

sbcreaso@ncsu.edu

Other authors

Dr. John Classen, Dr. Prince Dugba, Mr. Mark Rice, Dr. Kelly Zering

Acknowledgements

Funding for this project was provided by a grant from Smithfield Swine Production Group

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2017. Title of presentation. Waste to Worth: Spreading Science and Solutions. Cary, NC. April 18-21, 2017. URL of this page. Accessed on: today’s date.

March 5, 2019March 6, 2019

Anaerobic Digestion – Highlights of Successful Project Feasibility Studies

Purpose

Feasibility studies are a form of decision-making tool that require research, data collection and analysis to evaluate investments in new technology or projects. They answer key questions about a project’s technical and financial viability, including project structure and organization and the costs, benefits, and risks involved. The analyses completed are so important that many grant programs require feasibility studies before making project grant awards. Financial investors and banks commonly may require the most rigorous form of feasibility study prior to making any investment.

What did we do?

To develop a catalog of steps needed to perform a successful feasibility study, we reviewed the literature on feasibility studies, as well as dozens of studies done on the subject of anaerobic digestion. We also talked with a range of experts in project development.

What have we learned?

General Assessment Study or Screening—Most basic feasibility studies assess the viability of different opportunities within a defined industry or geographic area. On a project level, a general assessment determines if a potential project meets basic criteria thresholds to support more in-depth analysis?

Project-Based, Techno-Economic Study—A higher level of research and analysis is used to establish project viability. These studies consider the costs, benefits, and risks of building a specific type of project, with specific technology, on a specific site. For this purpose the study might incorporate readily available data about technology choices and make assumed adjustments about how it would perform under site-specific conditions. This level of analysis forces project advocates to put their ideas and assumptions on paper and test whether the conclusion is sound and realistic.

Investment-Grade Study—The most rigorous feasibility study is used to validate the marketability of a specific project from an investment perspective. It would look beyond basic techno-economic viability to establish the actual planned inputs and outputs of a project. It can include detailed equipment specifications and estimates, as well as detailed mass, energy, and water balance calculations. It may also identify key providers of feedstocks as well as potential end users. Detailed scheduling may be required to complete financial analyses accurately. With a detailed proforma showing financial analyses of cash flow and return on investment, this high level of feasibility study is sometimes termed “investment-grade.” These types of studies often include sensitivity analyses to explore the impact on a project’s viability from changes to one or more key assumptions. Sensitivity analyses can clarify which of the many assumptions made are most critical to project success.

Getting the best, most reliable and accurate data is perhaps the most critical element of a successful feasibility study. Typical steps observed in many feasibility studies:

Define project goals and scope
Establish the project criteria necessary for success
Inputs: potential feedstocks from measured results, existing data, or surveys of sources
Outputs, calculated from inputs: biogas, liquid and solid effluents and nutrients, and environmental attributes
Financial costs: capital expenses, including cost of money, and ongoing operation and maintenance expenses
Revenues (10 or more): methane energy power or fuel, surplus thermal energy, tip fees, value of solids, liquids-water, liquids-nutrients, environmental attributes, ecosystem services (e.g., GHG offsets, water quality/quantity benefits), carbon dioxide, and/or bioplastics.
Cost offsets as revenues: e.g., rainwater diversion, reduction in manure handling/spreading, odor reduction, avoided disposal, etc.
Financial analyses: cash flow, simple payback, EBITA (earnings before interest, taxes and amortization), net present value, return on investment, sensitivity analyses, life-cycle analyses
Project finance: grants and loan guarantees, debt, and equity
Project ownership and liabilities: including design, build, own, operate, maintain

Future Plans

We will continue to evaluate methods to add value and publish the full results in a Anaerobic Digestion technology brief on this topic.

Authors

Jim Jensen, Sr Bioenergy & Alt Fuel Specialist, Washington State University Energy Program jensenj@energy.wsu.edu

Craig Frear, Chad Kruger, and Georgine Yorgey, Center for Sustaining Agriculture and Natural Resources, Washington State University

Additional information

http://www.energy.wsu.edu/

http://csanr.wsu.edu/

Acknowledgements

This research was supported by Biomass Research Funds from the WSU Agricultural Research Center; and by the Washington State Department of Commerce.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2015. Title of presentation. Waste to Worth: Spreading Science and Solutions. Seattle, WA. March 31-April 3, 2015. URL of this page. Accessed on: today’s date.

March 5, 2019March 21, 2019

Global Supply of Phosphate

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Why Are We Concerned About Global Phosphorus Supply?

There has been a great deal of press coverage in the past few years about the supplies and reserves of rock phosphate across the globe with some predicting exhaustion of these supplies within a few decades. This presentation examines the supplies, reserves and trends in the world phosphorus supply.

Authors

Mike Stewart, International Plant Nutrition Institute mstewart@ipni.net

Additional Information

International Plant Nutrition Institute http://www.ipni.net

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2013. Title of presentation. Waste to Worth: Spreading Science and Solutions. Denver, CO. April 1-5, 2013. URL of this page. Accessed on: today’s date

March 5, 2019August 5, 2020

Software For Evaluating the Environmental Impact of Dairy and Beef Production Systems

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Why Model Environmental Impacts of Livestock?

Quantifying the long term environmental impacts of dairy and beef production is complex due to the many interactions among the physical and biological components of farms that affect the amount and type of emissions that occur. Emissions are influenced by climate and soil characteristics as well as internal management practices. Software models are needed to perform an integrated and comprehensive assessment of all important environmental and economic effects of farm management and mitigation strategies. Related: Manure value & economics

What Did We Do?

Figure 1. The Integrated Farm System Model simulates the performance, determines the economics, and predicts the air and water emissions of farm production systems.

Software tools were created that perform whole-farm analyses of the performance, economics and environmental impact of dairy and beef production systems. The Integrated Farm System Model (IFSM) is a comprehensive research tool that simulates production systems over many years of weather to quantify losses to the environment and the economics of production. From the simulated performance and losses, environmental footprints are determined for carbon, energy use, water use and reactive nitrogen loss. Crop, dairy and beef producing farms can be simulated under different management scenarios to evaluate and compare potential environmental and economic benefits. The Dairy Gas Emissions Model (DairyGEM) provides a simpler educational tool for studying management effects on greenhouse gas, ammonia and hydrogen sulfide emissions and the carbon, energy and water footprints of dairy production systems.

What Have We Learned?

Analyses with either the IFSM or DairyGEM tools illustrate the complexity of farming systems and the resultant effect of management choices. Although IFSM was primarily developed and used as a research tool, it is also used in classroom teaching and other education applications. DairyGEM provides an easier and more graphical tool that is best suited to educational use.

Future Plans

Figure 2. DairyGEM is an educational tool for evaluating management effects on air emissions and environmental footprints of dairy production systems.

Development of these software tools continues. Work is currently underway to add the simulation of VOC emissions to both models. Routines are also being implemented to better represent the performance and emissions of beef feed yards.

Authors

C. Alan Rotz, Agricultural Engineer, USDA/ARS; al.rotz@ars.usda.gov

Additional Information

The IFSM and DairyGEM software tools are available through Internet download [https://www.ars.usda.gov/research/software/?modeCode=80-70-05-00] for use in individual, workshop and classroom education. Reference manuals and other detailed information on the models is also available at this website.

Acknowledgements

Many people have contributed to the development of these models and software tools. Although they can not all be listed here, they are acknowledged in each software program.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2013. Title of presentation. Waste to Worth: Spreading Science and Solutions. Denver, CO. April 1-5, 2013. URL of this page. Accessed on: today’s date.

March 5, 2019July 8, 2020

Integrating Manure into Feed Ration Optimization

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* Presentation slides are available at the bottom of the page.

Abstract

Ration optimization models currently minimize the purchase price of feeds used to meet nutrient requirements. Not included in optimization models is the value of manure nutrients resulting from ration alternatives. This project extends the linear program that is used to minimize ration cost to include the value of manure excreted and stored. Microsoft EXCEL’s Solver GRG Nonlinear Add-in is used to optimize the integrated decision because of the non-linear aspects of manure excretion as a function of feed fed.

Several economic and production changes over the last 10 years warrant an investigation of the impact of optimizing both feed and manure decisions simultaneously. Distillers Dried Grains with Solubles (DDGS) have become a common feed high in phosphorus, lessening the need for inorganic phosphorus sources. Including DDGS in the diet also increases the manure concentration of phosphorus. If phosphorus is needed on nearby crop fields, there is potential to increase manure value while simultaneously reducing feed cost. In contrast, feeding phytase may reduce feed cost, while reducing manure value if phosphorus in manure is valued. Feeding synthetic amino acids can also reduce feed cost while reducing the amount of nitrogen excreted and available as a fertilizer in the manure. Adding to the importance of considering manure value is the increased costs of fertilizers. Manure is increasingly seen as a viable alternative to commercial fertilizers and might affect the whole farm profitability if included in the ration cost decision.

This project considers swine rations and examines how they might have changed during the past 10 years if manure value had been incorporated into the ration optimization decision. We will attempt to determine when manure fertilizer value relative to feed costs justifies integrating feed and manure optimization. Results indicate that incorporating manure value into the optimization routine would change some diet formulations.

Why Consider Manure Nutrients When Balancing Rations?

The value of manure supplied nutrients (N, P and K) has increased significantly over the past decade. Feedstuffs, such as DDGS, have been incorporated into the diets in ways that reduce the need for P supplementation. These developments have moved manure from a waste product to a co-product in livestock production. By integrating feed and manure management decisions it was hypothesized that profit could be improved.

What Did We Do?

The 2012 version of the National Swine Nutrition Guide (NSNG) ration software contains an optimization model for least cost ration formulation that calculates the potential manure value associated with different optimized diets. This recognition of the value of manure is an important contribution.

We incorporated the value of manure (as estimated by the NSNG) into the least cost ration optimization routine so that the objective function changed from minimizing the cost of feed to minimizing the net cost of feed. Net diet cost was defined as the cost of feed less the value of manure. Optimization of this equation required the use of the GRG non-linear optimization routine of Microsoft EXCEL.

This project evaluated least cost swine rations and how they might have changed during the past 10 years if manure value had been incorporated into the ration optimization decision. We specifically examined rations for 50-100 lb. and 200-250 lb. pigs. Rations were optimized with the following limitations: 1) manure was/was not included in the objective function; 2) DDGS were/were not allowed as a feedstuff in the rations.

What Have We Learned?

Assuming that the full value of the manure could be obtained, incorporating manure into the least cost ration optimization reduced net diet cost seven of the last 10 years for 50-100 lb. and 200-250 lb. pigs when DDGS were allowed in the diets. The ten-year mean improvement in net diet cost was $0.61/ton with a range from $0 to $8.41/ton of feed. More typically differences were small, exceeding $1.00/ton only in 2005 and 2006. Increasing manure value required increasing feed cost by an a 10-year average of $1.14/ton. The uncertainty in extracting manure value may make farmers hesitant to increase feed cost in hopes of capturing additional manure value. Two years may provide insight into the opportunity to incorporate manure value into the least cost feed decision. In 2006, a savings of $8.41/ton of feed fed was obtained by including 40% DDGS in the 50-100 lb. pig diet; this savings required increasing the feed cost by $1.76/ton resulting in a $10.18/ton increase in manure value in associated excreted nutrients. In 2009, a net ration savings of $.61/ton was obtained by eliminating phytase which was in the original least cost ration formulation. Phytase reduced the need for expensive phosphorus feedstuffs but not sufficiently when the value of manure was considered.

Future Plans

Non-linear optimization routines may find local optima rather than a global optimum. A procedure needs to be developed that insures that the global optimum is found before incorporating manure into the least cost ration decision will become widespread.

Authors

Dr. Ray Massey, Extension Professor, Agricultural and Applied Economics, University of Missouri, masseyr@missouri.edu

John Lory, Extension Associate Professor of Extension, Division of Plant Science, University of Missouri

Marcia Shannon, Associate Professor, Swine Nutrition, University of Missouri

Additional Information

The 2012 version of the National Swine Nutrition Guide can be found at the U.S. Pork Center of Excellence (https://www.usporkcenter.org/product/national-swine-nutrition-guide/)

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2013. Title of presentation. Waste to Worth: Spreading Science and Solutions. Denver, CO. April 1-5, 2013. URL of this page. Accessed on: today’s date.

Integrating Manure Into Feed Ration Optimization from LPE Learning Center

April 5, 2013March 3, 2020

Minnesota Watershed Nitrogen Reduction Planning Tool

Abstract

Using the nitrogen reduction planning model involves three steps. The first step is to select a watershed, enter hypothetical adoption rates for each BMP, and compare the effectiveness and cost of the individual BMPs. The second step is to compare suites of the BMPs that would attain any given reduction in the N load at minimum cost. The third step is to “drill down” to the details and assumptions behind the models of effectiveness and costs of any particular BMP and make any adjustments to reflect your particular situation.

Why Develop a Nitrogen Reduction Planning Tool?

A watershed-level nitrogen reduction planning tool (Excel spreadsheet) compares the effectiveness and cost of nine different “best management practices” (BMPs), alone and in combination, for reducing N loads leaving a Minnesota watershed. The Minnesota Pollution Control Agency is developing a new set of standards for nitrate nitrogen in surface waters based on aquatic life toxicity. The tool was developed to assist the agency and local resource managers to better understand the feasibility and cost of various “best management practices” to reduce N loading from Minnesota cropland.

What Did We Do?

The BMPs are: reducing corn N fertilizer rates to extension recommended rates, changing fertilizer application timing, seeding cover crops, installing tile line bioreactors or controlled drainage, planting riparian buffers, or converting some corn and soybean acres to a perennial crop. The spreadsheet does its analysis for a watershed that the user selects. However, the N loadings and crop economic calculations are done first by agroecoregion before aggregating the results into the watershed of interest. Agroecoregions are units having relatively homogeneous climate, soil and landscapes, and land use/land cover. The spreadsheet includes area data for the fifteen high-N HUC8 watersheds that make up roughly the southern half of the state, along with the state as a whole. When the user selects a watershed for analysis, formulas retrieve results as an area-weighted average of the agroecoregions making up that watershed. Each of the fifteen HUC8 watersheds includes between four and nine agroecoregions.

The N loadings from each agroecoregion are calculated in three categories: drainage tile discharges, leaching from cropland, and runoff. Nitrogen loading amounts modeled are “edge-of-field” measures that do not account for denitrification losses that occur beyond the edge of field as groundwater travels towards and is discharged to streams. The BMPs consider only loading from cropland, but loading from forests and impervious urban and suburban land is also included in the totals.

What Have We Learned?

The EPA’s Science Advisory Board has said that a 45% reduction in both N and P is needed in the Mississippi River to reduce the size of the Gulf of Mexico hypoxic zone. This tool suggests that the BMPs considered are not likely to achieve much more than half that reduction even at high adoption rates. Reducing N fertilizer rates on corn down to extension-recommended levels and shifting from fall to spring or sidedressed applications tend to be among the cheaper BMPs to adopt, but the results vary across watersheds and weather scenarios. Various other factors such as crop and fertilizer prices also affect the results, hence the need for a computer tool.

Future Plans

The tool and results of a larger project will be reviewed during the first half of 2013. The tool may then play a role in implementation of the new N state standards in the state.

Authors

William F. Lazarus, Professor and Extension Economist, University of Minnesota wlazarus@umn.edu

Geoff Kramer, Research Fellow, Department of Biosystems and Bioproducts Engineering, University of Minnesota

David J. Mulla, Professor, Department of Soil, Water, and Climate, University of Minnesota

David Wall, Senior Hydrologist, Watershed Division, Minnesota Pollution Control Agency

Additional Information

The latest version of the tool and an overview paper are available at the author’s project page.

Davenport, M. A., and B. Olson. “Nitrogen Use and Determinants of Best Management Practices: A Study of Rush River and Elm Creek Agricultural Producers Final Report, submitted to the Minnesota Pollution Control Agency as part of a comprehensive report on nitrogen in Minnesota Surface Waters.” Department of Forest Resources, University of Minnesota, St. Paul, Minnesota, September 2012.

Fabrizzi, K., and D. Mulla. “Effectiveness of Best Management Practices for Reductions in Nitrate Losses to Surface Waters In Midwestern U.S. Agriculture. Report submitted to the Minnesota Pollution Control Agency as part of a comprehensive report on nitrogen in Minnesota Surface Waters.” September 2012.

Lazarus, W. F., et al. “Watershed Nitrogen Reduction Planning Tool (NBMP.xlsm) for Comparing the Economics of Practices to Reduce Watershed Nitrogen Loads.” December 11, 2012, http://wlazarus.cfans.umn.edu/.

Mulla, D. J., et al. “Nonpoint Source Nitrogen Loading, Sources and Pathways for Minnesota Surface Waters. Report submitted to the Minnesota Pollution Control Agency as part of a comprehensive report on nitrogen in Minnesota Surface Waters.” Department of Soil, Water & Climate, University of Minnesota, September 2012.

Acknowledgements

Partial support for this project was provided by the Minnesota Legislature.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2013. Title of presentation. Waste to Worth: Spreading Science and Solutions. Denver, CO. April 1-5, 2013. URL of this page. Accessed on: today’s date.