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Wabash River Watershed Water Quality Trading Feasibility Study Final Report September 2011 Prepared for U.S. Environmental Protection Agency Targeted Watershed Grant WS-00E71501-0 Prepared by Conservation Technology Information Center With support from Tetra Tech, Inc. Kieser & Associates, LLC

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Page 1: Wabash River Basin Water Quality Trading Feasibility Study WQT Feasibility Study_091411_final... · Wabash River Watershed Water Quality Trading Feasibility Study Final ... 1.1 What

Wabash River Watershed Water Quality Trading

Feasibility Study

Final Report

September 2011

Prepared for

U.S. Environmental Protection Agency Targeted Watershed Grant WS-00E71501-0

Prepared by

Conservation Technology Information Center

With support from

Tetra Tech, Inc. Kieser & Associates, LLC

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CTIC would like to thank our project partners for their support: Agri Drain Corporation Duke Energy Indiana Association of Soil and Water Conservation Districts Indiana Farm Bureau Indiana Soybean Alliance Purdue University Extension

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Final Report – September 2011 Page i

Contents

1. Introduction ................................................................................................................................ 1 1.1 What is a WQT Market Feasibility Analysis? .................................................................................... 1 1.2 What is the Purpose of the Wabash River Watershed WQT Market Feasibility Analysis? ............. 2 1.3 What Does This Report Contain? ..................................................................................................... 3

2. Understanding the Wabash River Watershed ................................................................................ 3 2.1 Relationship of the Wabash River Watershed to the Gulf of Mexico .............................................. 3 2.2 Overview of Nutrient Sources and Loadings in the Wabash River Watershed ............................... 4

3. Feasibility Analysis Summary........................................................................................................ 5 3.1 Drivers and Incentives for Trading ................................................................................................... 5 3.2 Suitable Pollutants for Trading ........................................................................................................ 8 3.3 Watershed Considerations ............................................................................................................ 10 3.4 Timing ............................................................................................................................................ 10 3.5 Geographic Scope for Trading Analysis .......................................................................................... 11 3.6 Potential Credit Buyers and Sellers ................................................................................................ 15 3.7 Potential Credit Demand ............................................................................................................... 20 3.8 Potential Credit Supply .................................................................................................................. 43 3.9 Potential stakeholder participation ............................................................................................... 58

4. Putting It All Together – Market Analysis and Trading Considerations ......................................... 60 4.1 Pollutant Loads .............................................................................................................................. 60 4.2 Regulatory Drivers ......................................................................................................................... 60 4.3 Trade Ratios ................................................................................................................................... 60 4.4 Baselines ........................................................................................................................................ 71 4.5 Supply Side Credit Generation ....................................................................................................... 73 4.6 Differences in Control Costs .......................................................................................................... 78 4.7 Other Trading Considerations ........................................................................................................ 85

5. Next Steps for Water Quality Trading in the Wabash River Watershed ........................................ 91 5.1 Outreach and Education ................................................................................................................ 91 5.2 Prioritized Subwatershed for Future Analysis ............................................................................... 92 5.3 Trading Program Frameworks ....................................................................................................... 93 5.4 Conclusion ...................................................................................................................................... 94

Appendix A: Letter to Illinois EPA from USEPA .................................................................................. 95

Appendix B: Wabash River Watershed TMDL Reduction Summaries and Wasteload Allocations (WLAs) ....................................................................................................................................... 95

Appendix C: Characterization of Wabash River Nutrient Loads .......................................................... 95

Appendix D: Compilation of Nonpoint Source Analysis Technical Memos .......................................... 95

Appendix E: Point Source Survey Results .......................................................................................... 95

Cited References .............................................................................................................................. 95

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Tables Table 1. Nutrient Breakpoints by Ecoregion Under Consideration by IDEM (from Selvaratnam, S.

and J. Frey 2011) .............................................................................................................................. 6 Table 2. Summary of Nutrient Criteria Development Progress for U.S. EPA, Ohio, Minnesota, and

Wisconsin ......................................................................................................................................... 7 Table 3. Eight-digit HUCs in the Wabash River Watershed across Indiana and Illinois. ............................. 14 Table 4. Number of facilities with NPDES permits in each 8 digit HUC of the Wabash River

watershed ...................................................................................................................................... 15 Table 5. Tippecanoe County’s 2007 Conservation Tillage Data1................................................................. 19 Table 6. Estimated existing nutrient loads from permitted NPDES facilities in the Wabash River

watershed. ..................................................................................................................................... 20 Table 7. Changes in pollutant loads and resulting credit demand under different TN permit

effluent scenarios .......................................................................................................................... 23 Table 8. Changes in pollutant loads and resulting credit demand under different TP permit

effluent scenarios .......................................................................................................................... 26 Table 9. Summary of CWNS information for all facilities in the Wabash River watershed. ....................... 29 Table 10. Indicators associated with advanced treatment facilities in the Wabash River

watershed. ..................................................................................................................................... 29 Table 11. Summary of treatment type by HUC. .......................................................................................... 30 Table 12. Summary of 2008 CWNS permit information for facilities in the Tippecanoe and

Driftwood watersheds. .................................................................................................................. 31 Table 13. Permit limit summaries for facilities in the Driftwood and Tippecanoe watersheds. ................ 32 Table 14. Summary of facility type and flows for WWTPs included in Driftwood and Tippecanoe

nutrient removal analysis .............................................................................................................. 33 Table 15. Summary of ENR treatment levels and assumptions for WWTP upgrade simulations .............. 34 Table 16. Color coding of ENR treatment levels for Tables 17-23 .............................................................. 35 Table 17. 0.05 MGD activated sludge ENR upgrade options and costs ...................................................... 36 Table 18. 0.05 MGD lagoon ENR upgrade options and costs ..................................................................... 36 Table 19. 0.3 MGD activated sludge ENR upgrade options and costs ........................................................ 37 Table 20. 0.3 MGD lagoon ENR upgrade options and costs ....................................................................... 38 Table 21. 0.75 MGD activated sludge ENR upgrade options and costs ...................................................... 39 Table 22. 2.5 MGD trickling filter ENR upgrade options and costs ............................................................. 40 Table 23. 5 MGD activated sludge ENR upgrade options and costs ........................................................... 42 Table 24. Total Nitrogen Exported at the Mouth of 8-Digit HUC Watersheds, Independent of

Upstream Watershed Loading (USGS, 1997). ................................................................................ 44 Table 25. Total Phosphorus Exported at the Mouth of 8-Digit HUC Watersheds, Independent of

Upstream Watershed Loading (USGS, 1997). ................................................................................ 45 Table 26. SPARROW model estimates of agricultural NPS loading ............................................................ 46 Table 27. General Guidelines for Interpreting NO3-N Concentrations in Tile Drainage Water1.

(Purdue University, 2005) .............................................................................................................. 50 Table 28. Filterstrip Treatment Efficiency Results at the Subwatershed Scale, in Percent,

Driftwood Watershed. ................................................................................................................... 51 Table 29. Filterstrip Treatment Efficiency Results at the Subwatershed Scale, in Percent,

Tippecanoe Watershed. ................................................................................................................. 51 Table 30. Filterstrip Treatment Efficiency Results in Percent, Field Scale Results, Driftwood

Watershed. .................................................................................................................................... 52

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Table 31. Cover Crop Treatment Efficiency Results in Percent at the Subwatershed level, Driftwood Watershed. ................................................................................................................... 53

Table 32. Cover Crop Treatment Efficiency Results in Percent at the Subwatershed level, Tippecanoe Watershed. ................................................................................................................. 53

Table 33. Cover Crop Treatment Efficiency Results in Percent, Driftwood Subwatersheds. ..................... 54 Table 34. Cover Crop Treatment Efficiency Results in Percent, Tippecanoe Subwatersheds. ................... 54 Table 35. No-till Residue Management Treatment Efficiency Percents at the Subwatershed level,

Driftwood Watershed. ................................................................................................................... 55 Table 36. No-till Residue Management Treatment Efficiency Percents at the Subwatershed level,

Tippecanoe Watershed. ................................................................................................................. 55 Table 37. No-till Residue Management Treatment Efficiency Results in Percent, Driftwood

Watershed. .................................................................................................................................... 56 Table 38. Annual Nutrient Load Reduction Potential, Wabash River Watershed 8-digit HUC

Subwatersheds. (Assuming a 10 and 25 Percent Participation of Agricultural Row Cropped Acres, 20 Percent Reductions, and 40 lbs TN/acre and 3 lbs TP/acre Loading Rates.) ............................................................................................................................................ 57

Table 39. Estimates of phosphorus bioavialability fractions for specific source categories. ..................... 65 Table 40. Current and Potential Future Point and Nonpoint Source Baselines in the Wabash River

watershed ...................................................................................................................................... 71 Table 41. 2011 Indiana EQIP General Eligible Practices .............................................................................. 75 Table 42. Summary of Credit Production per Acre of BMP ........................................................................ 75 Table 43. Summary of BMP Credit Production and Annualized Life Cycle Cost per Acre .......................... 76 Table 44. Summary of Annualized Life Cycle Cost per Credit: Filter Strips (Prime Land) ........................... 76 Table 45. Summary of Annualized Life Cycle Cost per Credit: Filter Strips (Marginal Land) ...................... 77 Table 46. Summary of Annualized Life Cycle Cost per Credit: Cover Crops ............................................... 77 Table 47. Summary of Annualized Life Cycle Cost per Credit: Residue Management ................................ 78 Table 48. Comparison of Potential Estimated Upgrade Costs and NPS BMP Costs for Small (<.3

MGD) Facilities by Treatment Level ............................................................................................... 79 Table 49. Comparison of Potential Estimated Upgrade Costs and NPS BMP Costs for Medium (.3

MGD – 5 MGD) Facilities by Treatment Level ................................................................................ 79 Table 50. Comparison of Potential Estimated Upgrade Costs and NPS BMP Costs for Large (>5

MGD) Facilities by Treatment Level ............................................................................................... 80 Table 51. Resulting demand and supply factoring in estimated cost margins for each TP permit

effluent scenario ............................................................................................................................ 81 Table 52. Resulting demand and supply factoring in cost margins for each TN permit effluent

scenario .......................................................................................................................................... 83

Figures

Figure 1. Location of the Wabash River watershed in relation to the MARB and the hypoxic zone in the Gulf of Mexico. ...................................................................................................................... 4

Figure 2. Location and size of major reservoirs located in the Wabash River watershed .......................... 13 Figure 3. Location of karst features in the Wabash River watershed ......................................................... 13 Figure 4. NPDES permitted facilities by size and subwatershed in the Wabash River watershed. ............ 16 Figure 5. 2009 Landuse Map of the Wabash Watershed (MRLC, 2009) ..................................................... 18 Figure 6. Number of Beef Cattle per Subwatershed within the Wabash-Patoka Watershed. ................... 47 Figure 7. Number of Dairy Animals per Subwatershed within the Wabash-Patoka watershed. ............... 48

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1. Introduction In 2008, the U.S. Environmental Protection Agency (EPA) awarded a Targeted Watershed Grant to the Conservation Technology Information Center (CTIC) to conduct a water quality trading (WQT) market feasibility analysis for the Wabash River watershed. The 2008 Targeted Watershed Program funded ten projects focusing on water quality trading or other market-based water quality projects to reduce nitrogen, phosphorus, sediment, or other pollutant loadings that cause hypoxia in the Gulf of Mexico. The projects are located in the three Mississippi River sub-basins with the highest nutrient loads contributing to hypoxia in the Northern Gulf of Mexico: the Ohio River, the Upper Mississippi River, and the Lower Mississippi River. The Wabash River watershed is a major tributary to the Ohio River. CTIC partnered with Kieser & Associates, LLC and Tetra Tech, Inc. (Tt) to conduct a market feasibility analysis to determine if the necessary conditions exist in the Wabash River watershed to support the development and implementation of a viable, sustainable water quality trading program involving agricultural nonpoint sources and permitted point sources. This report summarizes the approach and the findings of the Wabash River Watershed WQT market feasibility analysis.

1.1 What is a WQT Market Feasibility Analysis?

Although there might be an interest to conduct WQT in a particular watershed, certain factors need to be present to make it a viable, sustainable program. A WQT feasibility analysis is a process for collecting and analyzing the data and information needed to determine if the technical and economic factors exist to support trading between potential sources. The very basic factors needed to support WQT are as follows:

Well-defined sources and amounts of pollution. WQT requires an understanding of pollutant sources. In the case of the Wabash River watershed, nitrogen and phosphorus are the pollutants of concern. Sources generating nutrient loads are potential buyers and sellers in a water quality trading approach. Collecting information to characterize the type of sources and the associated nutrient loads from each source help to determine if there will be an adequate supply and demand for tradable credits.

Regulatory drivers and incentives. Without regulatory drivers or some type of incentive, sources wouldn’t feel compelled to consider and, ultimately, participate in WQT. The most compelling drivers for WQT are those related to regulatory requirements. In most cases, this is a more stringent permit effluent limit based on a more stringent water quality standard. In other cases, it could be a watershed pollutant reduction goal that might not have a regulatory component, but provides other type of incentives to meet this goal (e.g., avoidance of a total maximum daily load).

Difference in control costs among sources. Sources with high pollutant control costs will have an economic motivation to seek out tradable credits from other sources that are able to control pollutants to meet requirements at a lower cost. It is this difference in control costs among sources that will determine which sources might participate as buyers and which sources might have the ability to participate as sellers. WQT feasibility is largely driven by economics, both actual and perceived costs (e.g., transaction costs and risk factors).

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A WQT market feasibility analysis has two components: 1) a pollutant suitability analysis and 2) an economic suitability analysis.

The pollutant suitability analysis includes information on pollutant type and form, geographic scope, potential buyers and sellers, potential water quality trading credit supply and demand, potential trade ratios to account for pollutant fate and transport as well as uncertainty, issues related to avoiding localized areas of excessive pollutant loading (i.e., hotspots), and duration of water quality trading credits.

The economic suitability analysis includes information on potential buyers’ willingness-to-pay for water quality credits, potential sellers’ price for generating water quality credits, effect of trade ratios on the cost of water quality trading credits, and the potential costs of involving stakeholders in designing and implementing a water quality trading program.

Information from each of these components provides insight as to where WQT might encounter barriers in a particular watershed and what type of trading framework might be most appropriate based on the sources with the greatest potential for participation.

A WQT market feasibility analysis is not intended to provide definitive answers about how WQT should work in a particular watershed, only if the conditions are ripe to support such an effort. WQT program design and implementation requires coordination and facilitation with watershed stakeholders to ensure the program integrates well with other efforts. What the product of a WQT market feasibility analysis can do, however, is give watershed stakeholders a starting place and a foundation when moving into the design phase. The analysis can also identify where watershed stakeholders will potentially have to do additional research to obtain detailed, watershed-specific information that could affect WQT success. This might mean holding focus groups with point sources and nonpoint sources to better understand attitudes, perceptions, and concerns. It might also mean public meetings with watershed residents and organizations that have perceptions and opinions about how to meet water quality goals.

1.2 What is the Purpose of the Wabash River Watershed WQT Market Feasibility Analysis?

The purpose of the WQT market feasibility analysis for the Wabash River watershed is to conduct a preliminary assessment for the potential of viable, sustainable trading to meet water quality goals. This analysis is an initial assessment focused on using mostly existing data examined through the lens of pollutant suitability and economic suitability. The purpose of this analysis was not to collect new data, but to identify where additional data and information might be needed to support further WQT feasibility assessment activities and future WQT program development. The goal is to create a foundation for future work that, over time, watershed stakeholders contribute to more and more. Ultimately, this WQT market feasibility analysis is intended to characterize the watershed for purposes of trading, identify existing data gaps, and make recommendations about WQT feasibility where the data can support these types of recommendations. Where data are not available, the Project Team has identified next steps and additional data needs to move water quality trading in the Wabash River watershed forward.

Through the Wabash River watershed WQT market feasibility analysis, the Project Team led by CTIC reviewed existing watershed data and information available through ongoing Wabash River watershed and Ohio River basin projects, such as the Wabash River Total Maximum Daily Load (TMDL) and TMDLs for subwatersheds in the Wabash River, such as Limberlost Creek, the Little Wabash River, and the

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South Fork Wildcat Creek. Information and data on point sources in the watershed were also obtained from the Indiana Department of Environmental Management (IDEM) and the Illinois Environmental Protection Agency (IEPA), and information from nonpoint source loading estimates were obtained from the U.S. Geological Survey (USGS).

1.3 What Does This Report Contain?

The Wabash River watershed WQT market feasibility analysis report contains the following:

Section 1: Understanding the Wabash River Watershed. An overview of the Wabash River watershed as it relates to the Gulf of Mexico hypoxia issue.

Section 2: Feasibility Analysis Summary. This section provides a discussion of the information used in the pollutant suitability and economic suitability analysis – the two components of the overall WQT market feasibility analysis.

Section 3: Putting It All Together: Market Analysis and Trading Considerations. This section synthesizes the information provided in Section Two to provide an analysis of the overall market potential for water quality trading in the Wabash River watershed. This section also addresses other trading considerations that will affect the market.

Section 4: Next Steps for Water Quality Trading in the Wabash River Watershed. This section identifies data needs and additional analyses to move the concept of water quality trading forward in the Wabash River watershed.

Appendices. The appendices to the report include the Wabash River TMDL and detailed technical memos generated by the Project Team to inform different components of the WQT market feasibility analysis process.

2. Understanding the Wabash River Watershed Characterizing the physical, chemical, and biological attributes of a watershed is an important first step in assessing the feasibility of WQT. This section provides a brief overview of the Wabash River watershed as it relates to the Gulf of Mexico hypoxia issue.

2.1 Relationship of the Wabash River Watershed to the Gulf of Mexico

The area that drains to the Gulf of Mexico is referred to as the Mississippi-Atchafalaya River Basin (MARB). This basin drains 1,245,000 square miles across 31 states and is the focus of the efforts to manage nutrients causing hypoxia in the Gulf of Mexico. Within the MARB, the Wabash River watershed covers approximately 33,000 square miles, draining portions of Indiana and Illinois. Figure 1 shows the location of the Wabash River watershed in relation to the MARB that drains to the Gulf of Mexico.

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Figure 1. Location of the Wabash River watershed in relation to the MARB and the hypoxic zone in the Gulf of Mexico.

While the Wabash River watershed is only 2 percent of the total area of the MARB, it delivers a relatively significant nutrient load to the Gulf of Mexico via the Ohio River – one of the three sub-basins that deliver the highest nutrient loading to the Gulf. According to USGS SPARROW modeling, the Wabash River watershed contributes approximately 9,994 tons of total phosphorus and 139,278 tons of total nitrogen to the Gulf of Mexico each year. Reducing the nutrient load from the Wabash River watershed will contribute to both local water quality improvements and help reduce the load contributing to the Gulf of Mexico’s hypoxic zone.

2.2 Overview of Nutrient Sources and Loadings in the Wabash River Watershed

In 2006, the IEPA and IDEM developed the 2006 Wabash River Nutrient and Pathogen TMDL report to address water quality impairments in the Wabash River watershed. Information from Indiana and Illinois 2002, 2004, and 2006 Clean Water Act (CWA) Section 303(d) listings demonstrate that several segments in the Wabash River watershed are impaired for nutrients, among other pollutants. Review of the data and comparison to state nutrient targets led to a determination that nutrient TMDLs should be developed for all segments of the Wabash River from the Indiana/Ohio state line to the confluence of the Wabash and Vermilion Rivers.

The TMDL addresses nutrient sources that discharge directly to the mainstem of the Wabash River, including point sources permitted under the National Pollutant Discharge Elimination System (NPDES)

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program, subwatersheds, and significant tributaries. Permitted NPDES point sources identified in the TMDL include industrial facilities, power plants, wastewater treatment facilities, municipal separate storm sewer systems (MS4s), combined sewer overflows, and confined animal feeding operations (CAFOs).

Although a detailed source analysis was not conducted for the subwatersheds, the TMDL does provide an analysis of land use/land cover in the subwatersheds and tributaries that drain directly to the Wabash River. Agriculture is the most significant land use in the area that drains directly to the Wabash River (82 percent), as well as the tributaries (53 – 97 percent). The TMDL concluded that nonpoint sources, including agriculture, contribute the largest loads of TP and nitrate to the Wabash, but that point sources can have an important impact during low flow periods. The WWTP loads therefore need to be reduced to meet the in-stream 0.30 mg/L benchmark.

In summary, the Wabash River watershed contains several segments that are impaired for nutrients due to a variety of point and nonpoint sources. This basic understanding of water quality issues in the Wabash River watershed provides a basic foundation for a more in-depth water quality trading market feasibility analysis, presented in Section Two.

3. Feasibility Analysis Summary This section summarizes the information compiled through the pollutant suitability analysis and the economic suitability analysis. This information provides the basis for the water quality trading market analysis and considerations presented in Section Three.

3.1 Drivers and Incentives for Trading

Sources considering WQT generally do so because of more stringent permit effluent limits resulting from changes to water quality standards or implementation of wasteload allocations (WLAs) in approved TMDLs. These are considered regulatory drivers for WQT. In addition to regulatory drivers, sources might consider WQT as a result of other incentives, such as the desire to avoid more stringent permit limits before the development of a TMDL or to meet a pollutant reduction goal established through a watershed management plan. A brief discussion of regulatory drivers and other incentives in the Wabash River watershed is provided below.

3.1.1 Water Quality Standards

State’s water quality standards drive NPDES permit effluent limits and TMDLs; therefore, water quality standards are the ultimate regulatory driver for WQT. If water quality standards result in NPDES permit effluent limits that pose a technical or financial burden for sources, the standards can serve as a driver for WQT.

To date, Indiana has not adopted numeric water quality criteria for nutrients to protect aquatic life uses. As stated in the 2006 TMDL, Indiana uses draft nutrient benchmarks:

Total phosphorus should not exceed 0.3 mg/L.

Nitrate + nitrite should not exceed 10 mg/L.

Dissolved oxygen should not be below the water quality standard of 4.0 mg/L and should not consistently be close to the standard (i.e., in the range of 4.0 to 5.0 mg/L). Values should also

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not be consistently higher than 12 mg/L and average daily values should be at least 5.0 mg/L per calendar day.

No pH values should be less than 6.0 or greater than 9.0. pH should also not be consistently close to the standard (i.e., 8.7 or higher).

Algae growth should not be “excessive” based on field observations by trained staff.

IDEM considers a segment to be impaired for nutrients when two or more of these benchmarks are exceeded based on a review of all recent data. It is anticipated that IDEM will adopt numeric nutrient criteria in the near future. IDEM is working with USGS to develop numeric nutrient criteria that take into account the relationship between stressors and the biological community. Table 1 presents possible numeric nutrient criteria presented by IDEM at the U.S. EPA Nutrient TMDL Workshop in February 2011. The numeric nutrient criteria development effort is still ongoing and these are preliminary values used during the development of the feasibility study.

Table 1. Nutrient Breakpoints by Ecoregion Under Consideration by IDEM

(from Selvaratnam, S. and J. Frey 2011)

Nutrient Breakpoints

Ecoregion

Glacial North Central/West Plains

Low (oligotrophic) TN < 0.60 mg/L None

TP < 0.035 mg/L None

High (eutrophic) TN > 1.2 mg/L TN > 1.7 mg/L

TP > 0.14 mg/L TP > 0.13 mg/L

Once Indiana adopts numeric nutrient criteria, IDEM will issue NPDES permits with more stringent water quality-based effluent limits to meet the new criteria. In Illinois, the state has adopted the following criteria: 0.05 mg/L TP for lakes and 10 mg/L TN for rivers. In addition, U.S. EPA has strongly encouraged IEPA to develop additional nutrient criteria.

Progress in developing nutrient criteria in other U.S. EPA Region 5 states provides context for the direction of future nutrient criteria. Table 2 presents a summary of nutrient criteria development progress for EPA (EPA, 2000a, EPA 2000b and EPA, 2000c), Ohio (Ohio EPA, 2011), Minnesota (MPCA, 2010a, 2010b) and Wisconsin (WI DNR, 2010).

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Table 2. Summary of Nutrient Criteria Development Progress for U.S. EPA, Ohio, Minnesota, and Wisconsin

Authority Status Phosphorus Criteria Nitrogen Criteria

EPA Aggregated Level IV Nutrient Ecoregions

Guidance VI 76.25 ug/L

VII 33 ug/L

IX 36.56 ug/L

VI Total Nitrogen 2.18 ug/L

VII Total Nitrogen 0.54 ug/L

IX Total Nitrogen 69 ug/L

Ohio EPA Developing TMDL derived Site Specific Water Quality Standards

Minnesota Pollution Control Agency

Developing South River Nutrient Region 150 ug/L

Central River Nutrient Region 100 ug/L

4-day chronic toxicity standard for Nitrite + Nitrate of 4.9 mg/L

Wisconsin Department of Natural Resources

Promulgated NR 102 (Phosphorus Rule)

Large Rivers 100 ug/L

Small Rivers 75 ug/L

3.1.2 NPDES Permit Effluent Limits

As stated under the water quality standards discussion, numeric nutrient criteria directly affects NPDES permit limits for nitrogen and phosphorus. To date, IDEM issues NPDES permits that do not contain water quality-based effluent limits for nutrients. This will change when IDEM adopts numeric nutrient criteria, as discussed above. For now, IDEM requires NPDES permitted facilities to conduct discharge monitoring as a way to generate better data on total phosphorus and total nitrogen concentrations. This information will help IDEM in developing future water quality-based effluent limits for nutrients to meet impending numeric nutrient criteria.

A recent review of Illinois NPDES permits conducted by U.S. EPA Region 5 showed that reviewed NPDES permits did not contain nutrient effluent limitations. As a result of the findings of this review, U.S. EPA Region 5 issued a letter in January 2011 that directs Illinois EPA to establish nutrient effluent limitations when it makes the determination that a nutrient discharge will cause an excursion beyond Illinois’ existing narrative nutrient criteria. Appendix A contains a copy of the January 2011 letter from U.S. EPA Region 5 to Illinois EPA about the matter of developing nutrient effluent limitations for nutrient discharges from permitted point sources.

3.1.3 2006 Wabash River TMDLs

The 2006 Wabash River TMDLs contain WLAs for point sources and load allocations (LAs) for nonpoint sources to address nutrient impairments. The TMDL assigns total phosphorus WLAs to point sources. The TP WLAs have not yet been incorporated into NPDES permits because facilities are first required to conduct monitoring to determine their actual discharge concentrations. For tributaries and subwatersheds draining directly to the Wabash River, the TMDL assigns a 4 percent reduction in phosphorus loads and no reductions in nitrate. The 4 percent phosphorus load reduction under the TMDL might serve as a nonpoint source baseline – the amount a nonpoint source seller has to reduce by before becoming eligible to sell credits to buyers in need of credits. A list of other TMDLs and associated WLAs for Wabash River subwatersheds is found in Appendix B.

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3.1.4 Watershed Management Planning

IDEM’s Watershed Management Planning Checklist provides watershed organizations with a framework to develop a Section 319 approvable watershed management plan. Several watershed management plans for subwatersheds of the Wabash River watershed are available through IDEM’s watershed management planning website. Many of these plans contain nutrient reduction goals. For example, the watershed management plan for the Upper Tippecanoe River contains a 20 percent nutrient load reduction goal to be achieved by 2010 and the watershed management plan for the Lower Eel River contains a 10 percent nutrient load reduction goal. Not every subwatershed in the Wabash River watershed has an IDEM-approved watershed management plan, but for those that do, the nutrient load reduction goals established for nonpoint sources can play a role in promoting participation in WQT. In addition, the nutrient load reduction goals quantified in watershed management plans might also serve as a nonpoint source baseline for nonpoint sources in specific watersheds that want to participate in trading as credit sellers.

3.1.5 Gulf Hypoxia Action Plan

In 2008, the Mississippi River/Gulf of Mexico Watershed Nutrient Task Force released the 2008 Action Plan – a national strategy to control hypoxia in the Gulf of Mexico and improve water quality in the MARB. The 2008 Action Plan calls for a dual 45 percent reduction in the riverine total nitrogen load and in the riverine total phosphorus load. This dual nutrient reduction loading goal is not an enforceable goal, but it does provide an overarching target for sources in the Mississippi River Basin – which includes the Wabash River watershed – to strive for to help reduce the hypoxic zone in the Gulf of Mexico.

3.1.6 Summary: Drivers and Incentives for Trading

In summary, a few point source regulatory drivers for WQT are emerging based on TMDLs. Many waters do not currently have nutrient drivers within the Wabash River watershed and likely will not until IDEM adopts numeric nutrient criteria and IEPA adopts more stringent and encompassing criteria. It is likely that IDEM will adopt numeric nutrient criteria in the near future, which will trigger the need to update existing NPDES permits with water quality-based effluent limits for nutrients. When permitted facilities are required to comply with new, more stringent nutrient permit limits, there will be a more tangible regulatory driver for WQT in the Wabash River watershed. The WQT market feasibility analysis for the Wabash River watershed makes the assumption that new numeric nutrient criteria will become a reality in Indiana and act as a driver for sources to consider WQT as a potential implementation tool to achieve more stringent permit limits. If numeric nutrient criteria are not adopted in Indiana and NPDES permits are not re-issued with more stringent nutrient effluent limits, point sources in the Wabash River watershed would not have a sufficient regulatory driver for WQT.

3.2 Suitable Pollutants for Trading

Nitrogen and phosphorus are considered appropriate pollutants for trading under U.S. EPA’s 2003 Water Quality Trading Policy and the U.S. EPA Water Quality Trading Toolkit for Permit Writers. Nutrients are relatively persistent in river environments and the focus of the Gulf of Mexico hypoxia issue. Local eutrophication issues such as dissolved oxygen impairments and nuisance algal blooms require TMDLs and are fueling the consideration of statewide nutrient criteria. Therefore, phosphorus and nitrogen forms are the focus of the Wabash River watershed WQT market feasibility analysis. At a very basic level, this means a focus on total nitrogen and total phosphorus. Difficulties in determining loading of

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reactive nutrient forms exist because of the sizeable variability in concentrations of soluble reactive forms across very short time periods. This has resulted in water quality monitoring programs relying heavily on TN and TP when estimating loads. However, bioavailability of the nutrients discharged by each source can be an important aspect of offsetting. For example, if a reticent nutrient form is traded for a source’s load which is substantially bioavailable the water quality impacts may not be addressed.

In addition, pollutant parameter suitability considerations for WQT include determining at what concentration a nutrient form has acutely toxic properties or quickly manifests other stresses. Lastly, the consideration of persistence is important. A parameter that is quickly attenuated is not a viable offset for impacts further downstream. Discharges of sizeable concentrations of ammonia can create acute toxicity concentrations. Ammonia can also consume high levels of oxygen as the form is converted into NO2 and the NO3. Because of these interactions WQT to address ammonia effluent limits is not appropriate. However, nitrogen in the form of ammonia is a tradable nutrient form when it is present in concentration levels characteristic of healthy ecosystems and not causing the described impacts. In these settings ammonia is cycling normally through the DIN or TN succession. Persistence, or the fate and transport of nutrients is an important consideration when setting eligible boundaries for trading transactions. For both of the nutrients adequate provisions can be included in the program boundaries and location factor to address quicker attenuation rates in headwater streams and downstream persistence. A brief discussion on the considerations related to the different forms of nitrogen and phosphorus in the context of WQT in the Wabash River watershed is provided below.

3.2.1 Nitrogen Considerations

The 2006 Wabash River TMDL established loading limits for TN, which eliminates the need to consider other forms of nitrogen (e.g., nitrate, organic nitrogen) in the Wabash River watershed. While TN will allow all sources to trade with each other because it represents a stable pollutant that provides an equivalent trading relationship, there are some considerations to keep in mind about the impact from different forms of nitrogen. In general, there is greater environmental benefit to removing the more bioavailable forms of nitrogen, which include dissolved organic nitrogen and dissolved inorganic nitrogen (nitrate, nitrite, and ammonia). For example, the Gulf of Mexico 2008 Hypoxia Action Plan states that nitrogen composition should be emphasized in nutrient reduction strategies. Nitrate is the most important form fueling the primary production that leads to hypoxia development in the spring (April, May, and June). Between 2001 and 2005, total annual nitrogen loads to the Gulf of Mexico declined, but in the critical spring months, the reduction in total nitrogen load is from nitrogen forms other than nitrate. Research conducted by the USGS (1997) suggests that the relationship between nitrate concentration and flow might be due to nitrate leached from soil and the unsaturated zone during high flow conditions. In addition, agricultural tile drainage might also contribute to increased nitrate levels during high flows. As a result, WQT in the Wabash River watershed should place a priority on reducing nonpoint sources of DIN and to a lesser extent on bioavailable forms of DON.

3.2.2 Phosphorus Considerations

Similar to TN, the 2006 Wabash River TMDL uses TP, a form of phosphorus that eliminates the need to consider other forms of phosphorus (e.g., soluble phosphorus) in the Wabash River watershed. Using TP allows for an equivalent trading relationship among sources with a phosphorus contribution. However, there are differences in the type of phosphorus associated with point and nonpoint sources. As a result, the potential effect of phosphorus from these sources on the Wabash River watershed will vary. Agricultural nonpoint sources discharge primarily the non-soluble, sediment-attached form of

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phosphorus. Point sources, wastewater treatment facilities in particular, discharge primarily soluble forms of phosphorus. The bioavailability of the TP from each discharger will be considered in Section 4.3 of this report for both the Wabash River and the Gulf of Mexico.

3.3 Watershed Considerations

Nutrient water quality standards are emerging in states across the nation (e.g., Wisconsin and Florida) that have phosphorus criteria levels for selected regions at or below 0.1 mg/L TP. Nitrogen water quality standards, to a much lesser extent in the Midwest, are being considered that would substantially reduce stream concentrations to single digits as compared to the 10 mg/l nitrate drinking water standard. These new criteria could create a setting where it is common for numerous impaired waters to be listed and waters achieving water quality attainment may have limited available capacity for future waste loads. Federal regulations (i.e., 40 CFR 122.44(d) and 40 CFR 122.4(i)) pertaining to NPDES permit requirements expressly prevent a permit effluent limit from “causing or contributing” to water quality violations. These requirements apply to WQT as well. A trade cannot create a local “hot spot” (area of impairment) in one water body because it is protecting another. However, WQT can allow upstream buyers of credits to purchase downstream generated credits if the stream reaches between the two participants is in compliance with water quality standards. In large streams the buyer’s discharge may not significantly alter the stream’s nutrient concentration. In these setting where the stream is in compliance a new discharger could purchase downstream generated credits to comply with waste load allocation requirements of the system.

If the stream’s concentrations are above water quality standards or a permittee’s discharge is substantial to the point where a local violation would be caused, then the appropriate WQT framework would require generated credits upstream of the buyer’s discharge. This assumes the presence of ample credit supply exists upstream of the buyer and that the credit supply will remain persistent within the stream to the point of the buyer’s discharge. Because of these considerations, an understanding of the fate and transport of nutrients in rivers and streams is emerging as a critical issue for water quality standards, estuary protection and effluent limit setting programs. WQT is no different. Fortunately, WQT goals are set by the effluent limit requirements of the permit application and WQT eligibility requirements can be created to address upstream generated nutrient credit attenuation concerns. Tools like the USGS SPARROW model for the entire Mississippi River watershed are being developed at finer resolutions to allow for an understanding of scale requirements that can be used to set boundary conditions for WQT (e.g. a 10-digit HUC evaluation provided replacing the current 8-digit HUC results).

3.3.1 Summary: Suitable Pollutants for Trading

In summary, both total nitrogen and total phosphorus are suitable pollutants for trading in the Wabash River watershed. However, WQT in the Wabash River watershed should focus on strategies to target sources of nitrate and account for the differences in the soluble and non-soluble forms of phosphorus associated with point sources and nonpoint sources. The fate and transport of nutrients within the Wabash River and downstream to the Gulf of Mexico also need to be taken into account.

3.4 Timing

WQT frameworks are required to be contemporaneous with NPDES permit effluent limit requirements. NPS generated credits are both episodic in nature and can have a seasonal variation with more credits being generated in one temperature regime or vegetative growth cycle than another (e.g., spring versus

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winter or pre-crop canopy versus full canopy). NPDES permit effluent limits are assigned to respond to critical periods. The WQT framework must also respond with contemporaneous credit generation for these effluent limits.

The critical period noted in the 2006 Wabash River TMDLs for nutrients include both high flow periods (such as spring runoff) when nutrient loads are high, as well as low flow summer periods when the assimilative capacity of the river is reduced. The critical period in the Gulf of Mexico for the hypoxia issue is late spring/early summer (e.g., April, May, June). Permit effluent limit setting processes for far-field drivers will have to consider other watershed characteristics in addition to critical time periods. For instance, internal loading or recycling of nutrients and transport time for nutrients become relevant considerations when setting protection limits for water bodies.

Where possible, seasonal or annual critical periods for NPDES permit effluent limits should be accompanied by adequate supporting justification. For example, in the Chesapeake Bay trading framework U.S. EPA accepted an annual credit generation window and in Wisconsin the DNR Water Quality Trading Framework allows “banking” of NPS credits to be used within the year generated. Where the critical period is more constrained (e.g., one month) WQT must be structured to contemporaneously generate credits or not be an eligible option.

3.4.1 Summary: Timing

Spring is a critical time period for both the Wabash River watershed and within the Gulf of Mexico. A Wabash River trading framework will therefore need to focus on reducing the load of nutrients during this period.

3.5 Geographic Scope for Trading Analysis

Understanding how the geographic scope of the watershed could affect the viability and sustainability of trading is a key aspect of a WQT market feasibility analysis. Geographic scope of the watershed influences important factors such as pollutant fate and transport, which in turn affects credit supply and demand through the application of trade ratios.

For purposes of the Wabash River watershed WQT market feasibility analysis, the Project Team focused on the Indiana and Illinois portions of the Wabash River watershed. Beginning in the State of Ohio, the Wabash River watershed covers 32,950 square miles extending across most of the State of Indiana (24,320 square miles) and with significant parts of the State of Illinois. Through the pollutant suitability analysis portion of the WQT market feasibility analysis, the Project Team considered conditions throughout the entire Wabash River watershed that could affect trading and then focused in on subwatersheds for a more detailed analysis. In considering the entire watershed, the Project Team took into consideration factors such as the location of major lakes and reservoirs that could act as a pollutant sink and affect fate and transport. Figure 2 shows the location and size of reservoirs located throughout the Wabash River watershed. If water quality trading were to take place in the Wabash River watershed, the design of the trading program would have to take these reservoirs into account through delivery and location trade ratios (see Section 4.3).

Other physical features to consider are the karst regions of the watershed, which total approximately 263,500 acres as shown in Figure 3. Similar to reservoirs, karst features can affect the fate and transport of pollutants and they can also affect runoff rates. Because karst features are limited to the southeast portion of the Wabash River watershed, restrictions on trading due to karst would likely only affect

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credit suppliers located in this area. A water quality trading program design should include guidance on how to identify karst features and tailor eligibility requirements accordingly.

Other geographic considerations include land use practices that change hydrology, chemistry, and biology of a watershed. In the Wabash River watershed, coal mining is of particular interest. Surface coal mines are found in the southeastern portion of the Wabash River watershed. Subwatersheds with coal mining activities might have lower pH levels due to mine runoff that could affect the bioavailability of nutrients. This could affect potential trading activities in close proximity to these areas because understanding fate and transport of pollutants would be challenging and difficult to account for in program design (e.g., credit estimation and trade ratios).

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Figure 2. Location and size of major reservoirs located in the Wabash River watershed

Figure 3. Location of karst features in the Wabash River watershed

In addition to looking at the characteristics across the entire Wabash River watershed that could affect water quality trading, the Project Team looked at subwatersheds to help in the more detailed analysis necessary to understand the factors affecting potential credit supply and demand. The 8-digit Hydrologic Unit Codes (HUCs) found in the Wabash River watershed are listed in Table 3.

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Table 3. Eight-digit HUCs in the Wabash River Watershed across Indiana and Illinois.

BASIN SUBBASIN HUC_8 SQ. MILES

Wabash Salamonie 05120102 552

Wabash Mississinewa 05120103 842

Wabash Eel 05120104 829

Wabash Middle Wabash-Deer 05120105 652

Wabash Tippecanoe 05120106 1,960

Wabash Wildcat 05120107 813

Wabash Middle Wabash-Little Vermilion 05120108 2,287

Wabash Vermilion 05120109 1,439

Wabash Sugar 05120110 808

Wabash Middle Wabash-Busseron 05120111 2,019

Wabash Embarras 05120112 2,442

Wabash Lower Wabash 05120113 1,321

Wabash Little Wabash 05120114 2,148

Wabash Skillet 05120115 1,049

Patoka-White Upper White 05120201 2,754

Patoka-White Lower White 05120202 1,675

Patoka-White Eel 05120203 1,195

Patoka-White Driftwood 05120204 1,154

Patoka-White Flatrock-Haw 05120205 586

Patoka-White Upper East Fork White 05120206 811

Patoka-White Muscatatuck 05120207 1,143

Patoka-White Lower East Fork White 05120208 2,025

Patoka-White Patoka 05120209 859

Total 32,950

No pre-existing watershed model exists for all of the subwatersheds within the Wabash River watershed. Given the size of the Wabash River watershed, conducting detailed modeling for all subwatersheds was not within the scope of this WQT market feasibility analysis. Instead, the Project Team conducted an analysis using the Soil and Water Assessment Tool (SWAT) of two subwatersheds to facilitate a smaller-scale quantitative assessment. The Project Team evaluated factors related to nonpoint source credit suppliers (e.g., agricultural producers) to identify two subwatersheds that would provide characteristics that could be extrapolated to the rest of the Wabash River watershed. The Project Team examined a variety of information such as land use, location of flow gages, cropland data, animal counts, location within the watershed (i.e., headwater or not), and location of karst features. Based on this analysis, the Project Team selected the Tippecanoe and Driftwood subwatersheds for more targeted assessment in the feasibility analysis (the locations of the Tippecanoe and Driftwood subwatersheds are shown in Figures 2 and 3).

3.5.1 Summary: Geographic Scope for Trading Analysis

In summary, the entire Wabash River watershed appears appropriate for WQT as long as trading program design takes into account notable features. These features include karst areas, major lakes and reservoirs, and other land uses that change the natural hydrology. These features could affect nutrient fate and transport, but could be addressed in WQT program design.

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3.6 Potential Credit Buyers and Sellers

In WQT, potential credit buyers are sources that need to reduce a pollutant load to comply with a regulatory requirement and credit sellers are sources that have the means to supply a unit of pollutant load reduction by over-controlling a pollutant load. Depending on the type of water quality trading program, a potential credit buyer is typically a facility covered by a NPDES permit. Potential credit sellers could be either other NPDES permitted point sources that over-control a pollutant discharge or eligible nonpoint sources that generate pollutant load reductions through best management practice implementation. For the purposes of the Wabash River watershed WQT market feasibility analysis, the primary focus is on NPDES permitted facilities as potential credit buyers and agricultural nonpoint sources as potential credit sellers.

3.6.1 NPDES Permitted Facilities as Potential Credit Buyers

According to information provided by IEPA and IDEM, there are 943 facilities with NPDES permits within the Wabash River watershed. Table 4 provides a list of the number of NPDES permitted facilities by 8-digit HUC.

Table 4. Number of facilities with NPDES permits in each 8 digit HUC of the Wabash River watershed

8 Digit HUC # of All Permits Large Medium Small

5120101 62 8 15 39

5120102 19 1 7 11

5120103 39 2 21 16

5120104 25 2 8 15

5120105 11 7 4

5120106 48 2 18 28

5120107 29 3 10 16

5120108 23 4 11 8

5120109 51 8 13 30

5120110 10 2 8

5120111 54 9 22 23

5120112 61 5 20 36

5120113 28 1 10 17

5120114 43 6 12 25

5120115 16 1 5 10

5120201 157 16 62 79

5120202 42 5 15 22

5120203 30 2 13 15

5120204 54 4 20 30

5120205 14 2 7 5

5120206 23 1 11 11

5120207 35 1 19 15

5120208 52 2 22 28

5120209 17 1 7 9

Total 943 86 357 500

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According to Table 4, the most NPDES permits are located in HUC 5120201, which has a total of 157. This HUC has the most facilities across all size categories. Small facilities are the predominant size category in the Wabash River watershed, with more than 50 percent of facilities falling in this category.

Figure 4. NPDES permitted facilities by size and subwatershed in the Wabash River watershed.

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Section 3.6 provides an analysis of the potential credit demand that these facilities might generate through more stringent permit effluent limits. Once a facility has met the nutrient reduction requirements it is possible for this facility to provide further reduction and generate credits for sale to other facilities.

3.6.2 Agricultural Nonpoint Sources as Potential Credit Sellers

WQT frameworks are created to fit the local setting. This includes working with the watershed characteristics to achieve and protect beneficial uses and water quality standards as well as advance watershed management goals. The nutrients in NPS runoff can be adequately quantified and adjusted for equivalence and location at the field scale and be transferable as credits to offset permitted wastewater discharges. However, WQT must fit within the socio-political structure. WQT has the opportunity to accelerate implementation for TMDLs, provide a mechanism for future growth in capped watersheds, and provide interim compliance leverage in cases of variance request or compliance schedule relief. To realize some of these benefits, the appropriate policies and perspectives must be in place. See the discussion on Baselines in Section 4.4.

Land use in the Wabash River watershed includes subregions dominated by forest, urban and agricultural coverages (Figure 5). Forested land use yields relatively light nutrient loading when compared to urban and agricultural land management (Reckhow and Chapra, 1983 and Dodd et al., 1992). The riverine geomorphology includes stable channels, incising channels and enhanced drainage features like channelized streams and ditches. These factors affect nutrient transport pathways and attenuation rates.

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Figure 5. 2009 Landuse Map of the Wabash Watershed (MRLC, 2009)

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The crop coverage map illustrates how much Indiana and Illinois benefit from abundant agricultural resources. Currently these resources are being managed in economically productive livestock and grain commodity production operations. The prevalence of corn-soybean rotations is typical of Midwest states. In addition, livestock density across the watershed is relatively high, but variable in terms of animal type and concentration. A consequence of this production and the physical features of the watershed is that the Wabash River watershed is the highest nutrient loading watershed in the Ohio River Basin (USGS, 2008). This high level of loading sets the stage for reduction opportunities. Current conservation practice adoption varies across the State of Indiana. For example the 2007 CTIC crop residue transect survey results for counties within the Tippecanoe watershed are provided in Table 5. The county variation ranges from 46 percent in some type of corn conservation tillage practices up to 91 percent.

Table 5. Tippecanoe County’s 2007 Conservation Tillage Data1

County (rank) No-Till Mulch Till Reduced Till Conventional Till

Corn Data

Pulaski (19) 21 48 23 9

Kosciusko (24) 26 18 27 29

Fulton (33) 21 20 39 21

White (67) 5 19 23 54

Average corn 18.25 26.25 28 28.25

Soybean Data

White (26) 52 23 13 11

Kosciusko (29) 66 16 10 8

Pulaski (35) 68 25 7 1

Fulton (38) 67 24 8 1

Average soybean 63.25 22 9.5 5.25 1 Indiana State Department of Agriculture Conservation Tillage Data available at: http://www.in.gov/isda/2354.htm

Based on the variable loading rates and variable adoption of conservation practices, the Wabash River watershed consists of both regions containing more than ample credit supply opportunities and those with reduced opportunity. However, within every subwatershed of the Wabash River there exists a number of individual sites that contain the key characteristics desired to supply credits:

1) implementation of a BMP will substantially reduce current NPS loading

2) the site is located in close proximity to the Wabash River or one of its tributaries

3) a willing land owner.

These prerequisites are necessary to supply an adequate volume of credits at an economical price. In low volume regions WQT may be limited to individual permits needing assistance with difficult or costly compliance attainment issues. In the regions with ample ability to supply credits a larger program could be available where many buyers and sellers participate. Section 3.7 describes the methods to preliminarily assess the entire Wabash. A higher resolution of assessment at the local level is advised as part of the WQT framework development process, should WQT programs in the Watershed be pursued. To evaluate and quantify the regional potential at a higher resolution stakeholder input is required. One objective would be to gather farm data regarding operational practices of nutrient and conservation management. This information can be both distinctly individualized and considered confidential by the producer and Farm Bill public programs. Producers may choose to divulge historic practices once

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funding opportunities are present, but often remain silent when requested for data until they are comfortable with the program and the individuals running it.

Section 3.7 provides an analysis of the potential credit supply from these agricultural nonpoint sources located in the Wabash River watershed.

3.7 Potential Credit Demand

Determining the potential credit demand from NPDES permitted facilities in the Wabash River watershed requires an understanding of the estimated pollutant load reductions necessary to meet more stringent permit limits, as well as the type of existing treatment and control technology upgrade options that are available to facilities to meet more stringent permit limits. This section examines both factors that play a role in generating a demand for credits.

3.7.1 Estimates of Existing Pollutant Loads and Pollutant Load Reductions Under Three Permit Limit Scenarios

The Project Team developed a technical memorandum entitled Characterization of Wabash River Nutrient Loads as part of the WQT market feasibility analysis to help estimate potential credit demand. This memorandum is found in Appendix C. This technical memo estimates the existing TN and TP loads under current permit limits and then examines the necessary pollutant load reductions to achieve more stringent permit limits in the future.

Table 6 summarizes estimated existing nutrient loads from the 943 NPDES permitted facilities in the Wabash River watershed. The estimated existing loads are categorized by size of facility in the categories of small, medium, large. Small facilities are those permitted to discharge no more than 0.3 million gallons per day (MGD). Medium-sized facilities are those with permitted discharges that range between 0.3 to 5 MGD. Large facilities discharge more than 5 MGD.

Table 6. Estimated existing nutrient loads from permitted NPDES facilities in the Wabash River watershed.

HUC_8 Facility Size (#

of facilities)

Estimated Existing Loads1

Total Phosphorus Total Nitrogen

Daily Load (lbs/day)

Annual Load (Tons)

Daily Load (lbs/day)

Annual Load (Tons)

05120101

Large (8) 381 70 2,069 378

Medium (15) 104 19 798 146

Small (39) 14 3 85 16

Total (62) 499 91 2,952 539

05120102

Large (1) 8 2 63 12

Medium (7) 39 7 317 58

Small (11) 3 1 22 4

Total (19) 51 9 402 73

05120103

Large (2) 64 12 1,348 246

Medium (21) 79 14 669 122

Small (16) 6 1 46 8

Total (39) 148 27 2,063 376

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HUC_8 Facility Size (#

of facilities)

Estimated Existing Loads1

Total Phosphorus Total Nitrogen

Daily Load (lbs/day)

Annual Load (Tons)

Daily Load (lbs/day)

Annual Load (Tons)

05120104

Large (2) 42 8 418 76

Medium (8) 58 11 357 65

Small (15) 4 1 30 5

Total (25) 104 19 805 147

05120105

Medium (7) 31 6 236 43

Small (4) 2 0 12 2

Total (11) 33 6 248 45

05120106

Large (2) 7 1 73 13

Medium (18) 99 18 736 134

Small (28) 7 1 71 13

Total (48) 113 21 880 161

05120107

Large (3) 276 50 2,065 377

Medium (10) 40 7 325 59

Small (16) 11 2 53 10

Total (29) 326 60 2,443 446

05120108

Large (4) 3,878 708 27,162 4,957

Medium (11) 114 21 652 119

Small (8) 3 1 24 4

Total (23) 3,995 729 27,837 5,080

05120109

Large (8) 1,029 188 5,245 957

Medium (13) 98 18 463 85

Small (30) 4 1 35 6

Total (51) 1,130 206 5,743 1,048

05120110

Medium (2) 5 1 36 7

Small (8) 3 1 24 4

Total (10) 8 1 60 11

05120111

Large (9) 2,749 502 21,571 3,937

Medium (22) 251 46 1,330 243

Small (23) 5 1 43 8

Total (54) 3,005 548 22,943 4,187

05120112

Large (5) 536 98 2,259 412

Medium (20) 103 19 622 113

Small (36) 8 1 65 12

Total (61) 647 118 2,946 538

05120113

Large (1) 68 12 510 93

Medium (10) 63 12 409 75

Small (17) 5 1 31 6

Total (28) 137 25 950 173

05120114

Large (6) 3,155 576 22,613 4,127

Medium (12) 128 23 581 106

Small (25) 9 2 59 11

Total (43) 3,292 601 23,254 4,244

05120115

Large (1) 30 6 135 25

Medium (5) 19 3 85 15

Small (10) 6 1 28 5

Total (16) 55 10 248 45

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HUC_8 Facility Size (#

of facilities)

Estimated Existing Loads1

Total Phosphorus Total Nitrogen

Daily Load (lbs/day)

Annual Load (Tons)

Daily Load (lbs/day)

Annual Load (Tons)

05120201

Large (16) 3,878 708 28,752 5,247

Medium (62) 315 58 3,065 559

Small (79) 17 3 147 27

Total (157) 4,210 768 31,964 5,834

05120202

Large (5) 1,240 226 9,522 1,738

Medium (15) 139 25 993 181

Small (22) 11 2 61 11

Total (42) 1,390 254 10,576 1,930

05120203

Large (2) 49 9 366 67

Medium (13) 54 10 338 62

Small (15) 3 1 21 4

Total (30) 106 19 725 132

05120204

Large (4) 221 40 1,660 303

Medium (20) 84 15 579 106

Small (30) 5 1 40 7

Total (54) 311 57 2,279 416

05120205

Large (2) 153 28 1,041 190

Medium (7) 36 7 272 50

Small (5) 1 0 7 1

Total (14) 190 35 1,320 241

05120206

Large (1) 37 7 571 104

Medium (11) 16 3 165 30

Small (11) 5 1 37 7

Total (23) 57 10 772 141

05120207

Large (1) 53 10 234 43

Medium (19) 93 17 676 123

Small (15) 9 2 58 11

Total (35) 155 28 968 177

05120208

Large (2) 71 13 1,557 284

Medium (22) 78 14 768 140

Small (28) 5 1 42 8

Total (52) 154 28 2,367 432

05120209

Large (1) 36 7 272 50

Medium (7) 48 9 285 52

Small (9) 3 1 17 3

Total (17) 88 16 574 105 1Existing loads based on flow and TN data reported in the Integrated Compliance Information System (ICIS). TN concentrations

were not reported for the vast majority of facilities and therefore were estimated based on reported BOD values. See Characterization of Wabash River Nutrient Loads in Appendix C for details.

Estimating existing loads for the different facility size categories in each 8-digit HUC helps to determine the potential change in pollutant loads when different permit effluent limits are considered. As discussed in Section 3.1, the Project Team has made assumptions about likely future permit effluent limits that would result from numeric nutrient criteria based on trends in other Midwest states. For purposes of the WQT market feasibility analysis, the Project Team developed scenarios using different assumed permit effluent limit values. For TN, the assumed values are 3 mg/L, 5 mg/L, and 8 mg/L. For TP, the assumed values are 0.3 mg/L and 0.5 mg/L.

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Table 7 summarizes the change in pollutant loads for TN under each permit effluent limit scenario. In addition, this table shows the associated pollutant load reduction that each facility size category is estimated to need to achieve the more stringent permit effluent limits. This is assumed to be the potential credit demand for each facility size category.

Table 7. Changes in pollutant loads and resulting credit demand under different TN permit effluent scenarios

HUC_8

Facility Size (# of

facilities)

Annual Load (Tons) Annual Load Reduction

Existing Loads

Estimated Loads Assuming Discharge Value

(Tons) @ 3 (Tons) @ 5 (Tons) @ 8 of 3

mg/L of 5

mg/L of 8

mg/L

05120101

Large (8) 377.5 102.0 147.4 215.4 275.5 230.1 162.1

Medium (15) 145.6 31.9 50.9 79.3 113.7 94.7 66.3

Small (39) 15.6 6.9 8.3 10.3 8.7 7.3 5.3

Total (62) 538.7 140.8 206.5 305.0 397.9 332.2 233.7

05120102

Large (1) 11.6 2.3 3.9 6.2 9.3 7.7 5.4

Medium (7) 57.9 11.5 19.2 30.7 46.3 38.7 27.2

Small (11) 4.0 2.0 2.2 2.6 2.0 1.7 1.3

Total (19) 73.4 15.8 25.3 39.5 57.6 48.1 33.9

05120103

Large (2) 246.0 49.2 82.0 131.2 196.8 164.0 114.8

Medium (21) 122.1 26.3 42.0 65.6 95.7 80.0 56.5

Small (16) 8.3 2.5 3.5 4.9 5.8 4.9 3.4

Total (39) 376.4 78.0 127.5 201.7 298.4 248.9 174.7

05120104

Large (2) 76.2 76.2 76.2 76.2 0.0 0.0 0.0

Medium (8) 65.1 13.5 21.7 34.0 51.6 43.4 31.1

Small (15) 5.5 1.6 2.3 3.2 3.9 3.2 2.3

Total (25) 146.8 91.3 100.2 113.5 55.5 46.7 33.4

05120105

Medium (7) 43.1 9.2 14.9 23.3 33.9 28.3 19.8

Small (4) 2.2 0.8 1.0 1.4 1.4 1.1 0.8

Total (11) 45.3 10.0 15.9 24.7 35.3 29.4 20.6

05120106 (Tippecanoe)

Large (2) 13.3 13.3 13.3 13.3 0.0 0.0 0.0

Medium (18) 134.3 27.3 44.6 70.6 107.0 89.6 63.7

Small (28) 13.0 4.1 5.6 7.8 8.9 7.4 5.2

Total (48) 160.6 44.8 63.5 91.7 115.8 97.0 68.8

05120107

Large (3) 376.8 76.3 126.4 201.5 300.6 250.5 175.3

Medium (10) 59.4 11.8 19.6 31.3 47.6 39.8 28.0

Small (16) 9.7 2.3 3.5 5.4 7.4 6.2 4.3

Total (29) 445.9 90.3 149.5 238.2 355.6 296.4 207.7

05120108

Large (4) 4957.0 990.4 1650.6 2641.0 3966.6 3306.4 2316.1

Medium (11) 118.9 21.7 35.9 57.2 97.2 83.0 61.7

Small (8) 4.3 2.2 2.6 3.1 2.1 1.8 1.2

Total (23) 5080.2 1014.3 1689.0 2701.2 4066.0 3391.2 2379.0

05120109

Large (8) 957.1 184.9 294.1 458.0 772.2 663.0 499.1

Medium (13) 84.5 20.2 28.2 40.4 64.4 56.3 44.2

Small (30) 6.5 6.0 6.0 6.1 0.5 0.4 0.3

Total (51) 1048.1 211.0 328.4 504.5 837.1 719.7 543.6

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HUC_8

Facility Size (# of

facilities)

Annual Load (Tons) Annual Load Reduction

Existing Loads

Estimated Loads Assuming Discharge Value

(Tons) @ 3 (Tons) @ 5 (Tons) @ 8 of 3

mg/L of 5

mg/L of 8

mg/L

05120110

Medium (2) 6.6 1.3 2.2 3.5 5.3 4.4 3.1

Small (8) 4.3 1.5 2.0 2.7 2.8 2.3 1.6

Total (10) 10.9 2.9 4.2 6.2 8.1 6.7 4.7

05120111

Large (9) 3936.7 1354.7 1785.1 2430.6 2582.0 2151.7 1506.2

Medium (22) 242.6 43.4 71.1 112.6 199.2 171.6 130.0

Small (23) 7.8 5.1 5.5 6.2 2.7 2.3 1.6

Total (54) 4187.1 1403.2 1861.6 2549.3 2784.0 2325.5 1637.8

05120112

Large (5) 412.3 62.9 104.8 167.6 349.4 307.5 244.7

Medium (20) 113.5 34.0 44.7 60.8 79.5 68.8 52.7

Small (36) 11.9 9.9 10.1 10.5 2.0 1.7 1.4

Total (61) 537.7 106.8 159.6 238.9 430.9 378.0 298.8

05120113

Large (1) 93.1 18.6 31.0 49.6 74.5 62.1 43.4

Medium (10) 74.7 15.0 24.2 38.0 59.6 50.5 36.7

Small (17) 5.7 2.7 3.1 3.6 3.0 2.6 2.0

Total (28) 173.4 36.3 58.3 91.2 137.1 115.1 82.1

05120114

Large (6) 4126.9 812.8 1354.6 2167.4 3314.2 2772.3 1959.6

Medium (12) 106.1 16.6 27.4 43.4 89.4 78.7 62.6

Small (25) 10.8 6.7 7.2 8.1 4.1 3.6 2.8

Total (43) 4243.8 836.1 1389.2 2218.8 3407.7 2854.6 2025.0

05120115

Large (1) 24.6 3.7 6.1 9.8 20.9 18.4 14.7

Medium (5) 15.4 2.3 3.9 6.2 13.1 11.6 9.3

Small (10) 5.2 1.5 2.0 2.6 3.7 3.2 2.6

Total (16) 45.2 7.5 12.0 18.6 37.7 33.2 26.6

05120201

Large (16) 5247.2 1179.0 1853.3 2864.8 4068.2 3393.9 2382.4

Medium (62) 559.4 125.7 197.1 304.2 433.7 362.3 255.2

Small (79) 26.8 10.1 12.9 17.0 16.8 14.0 9.8

Total (157) 5833.5 1314.7 2063.3 3186.1 4518.8 3770.2 2647.4

05120202

Large (5) 1737.8 475.9 686.2 1001.6 1261.9 1051.6 736.1

Medium (15) 181.2 29.1 47.8 75.8 152.1 133.5 105.4

Small (22) 11.2 3.1 4.3 6.0 8.1 6.9 5.1

Total (42) 1930.2 508.0 738.2 1083.5 1422.1 1192.0 846.7

05120203

Large (2) 66.8 13.4 22.3 35.6 53.4 44.5 31.2

Medium (13) 61.6 11.6 18.8 29.7 50.1 42.8 31.9

Small (15) 3.9 1.1 1.5 2.2 2.8 2.3 1.6

Total (30) 132.3 26.0 42.6 67.6 106.3 89.7 64.7

05120204 (Driftwood)

Large (4) 303.0 60.6 101.0 161.6 242.4 202.0 141.4

Medium (20) 105.7 22.0 35.5 55.8 83.7 70.2 49.9

Small (30) 7.3 3.1 3.8 4.8 4.2 3.5 2.5

Total (54) 416.0 85.7 140.3 222.2 330.3 275.7 193.8

05120205

Large (2) 189.9 37.4 62.4 99.8 152.5 127.5 90.1

Medium (7) 49.6 11.4 17.7 27.3 38.2 31.8 22.3

Small (5) 1.3 1.0 1.0 1.1 0.4 0.3 0.2

Total (14) 240.8 49.8 81.2 128.3 191.1 159.7 112.6

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HUC_8

Facility Size (# of

facilities)

Annual Load (Tons) Annual Load Reduction

Existing Loads

Estimated Loads Assuming Discharge Value

(Tons) @ 3 (Tons) @ 5 (Tons) @ 8 of 3

mg/L of 5

mg/L of 8

mg/L

05120206

Large (1) 104.2 20.8 34.7 55.6 83.3 69.4 48.6

Medium (11) 30.1 9.6 13.0 18.1 20.5 17.1 12.0

Small (11) 6.7 2.0 2.8 4.0 4.7 3.9 2.7

Total (23) 141.0 32.4 50.5 77.7 108.6 90.5 63.3

05120207

Large (1) 42.8 6.4 10.7 17.1 36.4 32.1 25.7

Medium (19) 123.3 30.8 45.9 68.5 92.6 77.5 54.8

Small (15) 10.6 2.4 3.6 5.4 8.2 6.9 5.1

Total (35) 176.7 39.6 60.2 91.1 137.1 116.5 85.6

05120208

Large (2) 284.1 58.9 96.4 152.7 225.2 187.7 131.4

Medium (22) 140.2 29.5 47.5 74.5 110.7 92.7 65.7

Small (28) 7.7 3.2 4.0 5.1 4.4 3.7 2.6

Total (52) 432.0 91.6 147.9 232.3 340.4 284.1 199.7

05120209

Large (1) 49.6 9.9 16.5 26.5 39.7 33.1 23.1

Medium (7) 52.1 10.1 16.8 26.8 41.9 35.3 25.3

Small (9) 3.1 0.7 1.0 1.5 2.3 2.0 1.6

Total (17) 104.7 20.8 34.4 54.7 83.9 70.4 50.1

As shown by Table 7, large facilities in the Wabash River watershed have the most significant credit demand for TN under more stringent permit effluent limitations. However, there are significantly more small facilities compared to medium and large facilities and cumulatively they will also generate a significant credit demand. A portion of small rural facilities might experience difficulties such as being understaffed or not able to generate financial resources necessary to meet new restrictive nutrient requirements within the first permit period (typical of most compliance schedules requirements).

Table 8 summarizes the change in pollutant loads for TP under each permit effluent limit scenario. This table also shows the associated pollutant load reduction that each facility size category is estimated to need to achieve the more stringent permit effluent limits. This is assumed to be the potential credit demand for each facility size category for TP.

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Table 8. Changes in pollutant loads and resulting credit demand under different TP permit effluent scenarios

HUC_8 Facility Size

Estimated Existing Loads

Loads Assuming Discharge

Value of 0.3 mg/L

Loads Assuming Discharge

Value of 0.5 mg/L Annual Load

Reductions (Tons) @ 0.3

Annual Load Reductions (Tons) @ 0.5

Annual Load (Tons)

Annual Load (Tons)

Annual Load (Tons)

05120101

Large (8) 69.5 10.2 14.4 59.3 55.1

Medium (15) 19.0 3.2 5.1 15.8 13.9

Small (39) 2.5 0.7 0.8 1.8 1.7

Total (62) 91.0 14.1 20.3 77.0 70.7

05120102

Large (1) 1.5 0.2 0.4 1.3 1.2

Medium (7) 7.1 1.2 1.9 5.9 5.2

Small (11) 0.6 0.2 0.2 0.4 0.4

Total (19) 9.3 1.6 2.5 7.7 6.7

05120103

Large (2) 11.7 4.9 8.2 6.7 3.5

Medium (21) 14.3 2.6 4.2 11.7 10.2

Small (16) 1.0 0.2 0.3 0.8 0.7

Total (39) 27.0 7.8 12.7 19.2 14.3

05120104

Large (2) 7.6 7.6 7.6 0.0 0.0

Medium (8) 10.6 1.3 2.2 9.2 8.4

Small (15) 0.7 0.2 0.2 0.6 0.5

Total (25) 18.9 9.1 10.0 9.8 8.9

05120105

Medium (7) 5.7 0.9 1.5 4.8 4.2

Small (4) 0.3 0.1 0.1 0.2 0.2

Total (11) 6.0 1.0 1.6 5.0 4.4

05120106 (Tippecanoe)

Large (2) 1.3 1.3 1.3 0.0 0.0

Medium (18) 18.0 2.7 4.5 15.3 13.5

Small (28) 1.2 0.4 0.5 0.8 0.7

Total (48) 20.6 4.5 6.3 16.1 14.3

05120107

Large (3) 50.4 7.8 12.8 42.6 37.6

Medium (10) 7.2 1.2 1.9 6.1 5.3

Small (16) 2.0 0.2 0.4 1.7 1.6

Total (29) 59.6 9.2 15.1 50.4 44.5

05120108

Large (4) 707.7 99.0 165.1 608.6 542.6

Medium (11) 20.9 2.2 3.6 18.7 17.3

Small (8) 0.5 0.2 0.3 0.3 0.3

Total (23) 729.0 101.4 168.9 627.6 560.1

05120109

Large (8) 187.7 18.5 29.4 169.2 158.3

Medium (13) 17.9 2.0 2.8 15.8 15.0

Small (30) 0.7 0.6 0.6 0.1 0.1

Total (51) 206.3 21.1 32.8 185.2 173.5

05120110

Medium (2) 0.9 0.1 0.2 0.8 0.7

Small (8) 0.5 0.2 0.2 0.4 0.3

Total (10) 1.4 0.3 0.4 1.1 1.0

05120111 Large (9) 501.7 135.9 178.9 365.8 322.8

Medium (22) 45.8 4.3 7.1 41.4 38.7

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HUC_8 Facility Size

Estimated Existing Loads

Loads Assuming Discharge

Value of 0.3 mg/L

Loads Assuming Discharge

Value of 0.5 mg/L Annual Load

Reductions (Tons) @ 0.3

Annual Load Reductions (Tons) @ 0.5

Annual Load (Tons)

Annual Load (Tons)

Annual Load (Tons)

Small (23) 0.9 0.5 0.6 0.4 0.3

Total (54) 548.4 140.8 186.6 407.6 361.8

05120112

Large (5) 97.8 6.3 10.5 91.6 87.4

Medium (20) 18.8 3.4 4.5 15.4 14.3

Small (36) 1.5 1.0 1.0 0.5 0.5

Total (61) 118.1 10.7 16.0 107.5 102.2

05120113

Large (1) 12.4 1.9 3.1 10.5 9.3

Medium (10) 11.6 1.5 2.4 10.1 9.2

Small (17) 0.9 0.3 0.3 0.7 0.6

Total (28) 24.9 3.6 5.8 21.3 19.1

05120114

Large (6) 575.8 81.3 135.5 494.5 440.3

Medium (12) 23.3 1.7 2.7 21.7 20.6

Small (25) 1.6 0.7 0.7 0.9 0.9

Total (43) 600.7 83.6 138.9 517.1 461.8

05120115

Large (1) 5.5 0.4 0.6 5.2 4.9

Medium (5) 3.5 0.2 0.4 3.2 3.1

Small (10) 1.0 0.2 0.2 0.9 0.8

Total (16) 10.0 0.8 1.2 9.3 8.8

05120201

Large (16) 707.7 117.9 185.3 589.8 522.4

Medium (62) 57.6 12.6 19.2 45.0 38.4

Small (79) 3.1 1.0 1.3 2.0 1.8

Total (157) 768.3 131.5 205.8 636.9 562.6

05120202

Large (5) 226.4 47.6 68.6 178.8 157.7

Medium (15) 25.3 2.9 4.8 22.4 20.5

Small (22) 2.0 0.3 0.4 1.7 1.6

Total (42) 253.6 50.8 73.8 202.8 179.8

05120203

Large (2) 8.9 1.3 2.2 7.6 6.7

Medium (13) 9.8 1.2 1.9 8.6 7.9

Small (15) 0.6 0.1 0.2 0.5 0.5

Total (30) 19.3 2.6 4.3 16.7 15.0

05120204 (Driftwood)

Large (4) 40.4 6.1 10.1 34.3 30.3

Medium (20) 15.4 2.2 3.6 13.2 11.8

Small (30) 0.9 0.3 0.4 0.6 0.5

Total (54) 56.7 8.6 14.0 48.1 42.7

05120205

Large (2) 27.9 3.7 6.2 24.2 21.7

Medium (7) 6.6 1.1 1.8 5.4 4.8

Small (5) 0.2 0.1 0.1 0.1 0.0

Total (14) 34.6 5.0 8.1 29.7 26.5

05120206

Large (1) 6.7 2.1 3.5 4.6 3.2

Medium (11) 2.9 1.0 1.2 2.0 1.7

Small (11) 0.9 0.2 0.3 0.7 0.6

Total (23) 10.5 3.2 4.9 7.2 5.5

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HUC_8 Facility Size

Estimated Existing Loads

Loads Assuming Discharge

Value of 0.3 mg/L

Loads Assuming Discharge

Value of 0.5 mg/L Annual Load

Reductions (Tons) @ 0.3

Annual Load Reductions (Tons) @ 0.5

Annual Load (Tons)

Annual Load (Tons)

Annual Load (Tons)

05120207

Large (1) 9.6 0.6 1.1 9.0 8.6

Medium (19) 17.0 3.1 4.6 13.9 12.4

Small (15) 1.7 0.2 0.4 1.5 1.3

Total (35) 28.3 4.0 6.0 24.3 22.3

05120208

Large (2) 12.9 5.9 9.6 7.1 3.3

Medium (22) 14.3 2.9 4.7 11.4 9.6

Small (28) 0.9 0.3 0.4 0.6 0.5

Total (52) 28.2 9.1 14.7 19.1 13.5

05120209

Large (1) 6.6 1.0 1.7 5.6 5.0

Medium (7) 8.7 1.0 1.7 7.7 7.1

Small (9) 0.6 0.1 0.1 0.5 0.5

Total (17) 16.0 2.1 3.4 13.9 12.5

3.7.2 Existing Wastewater Treatment and Estimated Upgrade Costs

Estimating potential credit demand goes beyond estimating the necessary pollutant load reductions to meet the TN and TP permit effluent limitation scenarios. It also involves understanding the existing type of treatment and which facilities might choose to upgrade their control technologies to meet the more stringent permit effluent limitations. The Project Team conducted an analysis of the type of wastewater treatment and the cost to upgrade. This analysis is part of the Characterization of Wabash River Nutrient Loads technical memorandum found in Appendix C.

The level of new pollutant control measures needed to meet nutrient reductions specified by TMDLs or other regulatory drivers will be dependent upon each treatment plant’s current operations and the cost associated with the most likely control measure (e.g., biological phosphorus removal). Information on the type of wastewater treatment used by plants within the Wabash River watershed was obtained from the Clean Watersheds Needs Survey (CWNS) for the entire watershed. For the Driftwood and Tippecanoe subwatersheds, the Project Team supplemented CWNS information with data from a review of actual NPDES permits.

Information from the CWNS places facilities under the category of Secondary Wastewater Treatment or the category of Advanced Wastewater Treatment. Secondary treatment typically requires a treatment level that produces an effluent quality of less than 30 mg/L of both BOD5 and total suspended solids (secondary treatment levels required for some lagoon systems may be less stringent). In addition, the secondary treatment must remove 85 percent of BOD5 and total suspended solids from the influent wastewater. A facility is considered to have Advanced Wastewater Treatment if its permit includes one or more of the following: BOD less than 20 mg/L; Nitrogen Removal; Phosphorous Removal; Ammonia Removal; Metal Removal; Synthetic Organic Removal.

Table 9 summarizes the CWNS information for all of the facilities in the Wabash River watershed. It indicates that 21 percent of the facilities have advanced treatment, 14 percent are known to have secondary treatment, and no information is available for 65 percent of the facilities. Because the CWNS

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focuses on larger facilities, and because smaller facilities are less likely to have advanced treatment, it is probable that the majority of the facilities with no information do not use advanced treatment.

Table 9. Summary of CWNS information for all facilities in the Wabash River watershed.

Treatment Level Number of Facilities Percent

Advanced Treatment 211 21%

Secondary 144 14%

No Information 666 65%

Total Facilities in Watershed 1021 100%

Note: the number of facilities in the CWNS (1021) differs from the number obtained by combining the data from IDEM and IEPA (943). The source of the discrepancy is unknown but may be due to the timing of when the two data sets were created.

Table 10 summarizes the indicators of advanced treatment and shows that only a small proportion (10%) of the facilities have limits for phosphorus and nitrogen (not including ammonia).

Table 10. Indicators associated with advanced treatment facilities in the Wabash River watershed.

Advance Indicators Number of Facilities Percent

BOD 164 77.7%

Nitrogen 1 0.5%

BOD, Nitrogen 1 0.5%

BOD, Phosphorus 2 0.9%

BOD, Ammonia 26 12.3%

BOD, Phosphorus, Ammonia 17 8.1%

Total 211 100.0%

Table 11 summarizes the type of treatment by HUC and indicates that HUCs 05120201, 05120202, and 05120111 have the most facilities with advanced treatment. The cities of Terra Haute, Bloomington, Indianapolis, Anderson, and Muncie are located in these HUCs.

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Table 11. Summary of treatment type by HUC.

HUC 8 Advanced Treatment Secondary Treatment No CWNS

Information

05120101 8 5 49

05120102 3 2 14

05120103 9 4 26

05120104 3 4 18

05120105 3 2 6

05120106 (Tippecanoe)

8 5 35

05120107 5 4 20

05120108 8 3 12

05120109 7 7 37

05120110 2 1 7

05120111 13 5 36

05120112 8 10 43

05120113 4 8 16

05120114 6 12 25

05120115 1 8 7

05120201 33 9 115

05120202 13 4 25

05120203 8 1 21

05120204 (Driftwood) 8 4 42

05120205 5 0 9

05120206 4 1 18

05120207 5 2 28

05120208 10 6 36

05120209 2 3 12

Total 176 110 657

A more detailed analysis was performed to determine the type of treatment for facilities in the Tippecanoe and Driftwood watersheds (which are being modeled in SWAT to support the feasibility study).

The CWNS information for the 92 facilities in these two watersheds is shown in Table 12. Seventeen of the facilities have advanced treatment, nine have secondary treatment, and treatment type was not reported for 66 facilities.

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Table 12. Summary of 2008 CWNS permit information for facilities in the Tippecanoe and Driftwood

watersheds.

Watershed Permit Type

WWTP or Other

Present Treatment Level Present Advance Indicators

Number of Facilities

Tippecanoe (05120106)

Major Other No Info No Info 2

Major WWTP Advanced Treatment BOD (Biochemical Oxygen Demand)

2

Minor Other No Info No Info 23

Minor Other Secondary No Info 1

Minor WWTP Advanced Treatment Ammonia Removal, BOD (Biochemical Oxygen Demand)

1

Minor WWTP Advanced Treatment BOD (Biochemical Oxygen Demand)

5

Minor WWTP Advanced Treatment BOD (Biochemical Oxygen Demand), Ammonia Removal

1

Minor WWTP No Info No Info 3

Minor WWTP Secondary No Info 4

Driftwood (05120204)

Major Other No Info No Info 1

Major WWTP Advanced Treatment BOD (Biochemical Oxygen Demand)

3

Major WWTP Secondary No Info 1

Minor Other No Info No Info 34

Minor WWTP Advanced Treatment BOD (Biochemical Oxygen Demand)

4

Minor WWTP Advanced Treatment BOD (Biochemical Oxygen Demand), Ammonia Removal

1

Minor WWTP No Info No Info 3

Minor WWTP Secondary No Info 3

Of the 92 facilities, the Project Team was able to obtain permits for the 31 facilities that are WWTP within the watershed. These permits indicate that the following specific types of treatment methods are used within the watershed (either individually or in combination with one another):

trickling filters

activated sludge (including extended aeration and oxidation)

discharge waste stabilization lagoons

Out of these only the activated sludge systems can effectively be retrofit for biological nitrogen removal. Therefore, the trickling filter and lagoon treatment processes will require an expansion to reduce nutrient in their effluent.

All 31 facilities are required to report CBOD5 and ammonia values, 21 of the facilities have permitted ammonia limits, and only one facility has a phosphorus limit (Table 13).

Based on the lack of TN or TP limits in the available permits, and the types of treatment processes specified in the CWNS and the collected permits, it appears that almost none of the facilities in the Driftwood and Tippecanoe are targeting the treatment of TN or TP. The facilities that are treating for ammonia (via nitrification) likely do not include technology for denitrification or phosphorus removal.

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Upgrades would therefore be necessary to provide enhanced nutrient removal (ENR) for TN and TP removal.

Table 13. Permit limit summaries for facilities in the Driftwood and Tippecanoe watersheds.

Permit Limit No Designation in CWNS Secondary Advanced

Design Flow (MGD) 0.024 to 0.2 0.08 to 5.13 0.08 to 5.13

Monthly Average CBOD5 – Summer (mg/L) 12 to 25 20 to 25 10 to 25

Monthly Average CBOD5 – Winter (mg/L) 12 to 25 25 15 to 30

Weekly Average CBOD5 – Summer (mg/L) 18 to 40 30 to 40 15 to 40

Weekly Average CBOD5 – Winter (mg/L) 18 to 40 40 23 to 45

Monthly Average Ammonia – Summer (mg/L) 1.3 to 9.4 1.5 to 9.6 1.1 to 8.6

Monthly Average Ammonia – Winter (mg/L) 2 to 10.8 2.2 to 10.4 1.6 to 11

Weekly Average Ammonia – Summer (mg/L) 2 to 14.1 2.2 to 14.4 1.6 to 12.9

Weekly Average Ammonia – Winter (mg/L) 3 to 16.2 3.3 to 15.6 2.4 to 16.5

Phosphorus Limit (mg/L) N/A N/A 1

To understand potential credit demand, it is necessary to understand the estimated costs for upgrading technology to provide ENR for TN and TP removal. This section of the report provides estimated costs for upgrading permitted WWTPs in the Driftwood and Tippecanoe watersheds to enhanced nutrient ENR for reducing TN and TP effluent loads. The costs are based only on cited literature and the information available in the CWNS and the permits and are intended solely to inform the feasibility study. Actual upgrade costs vary widely, depending on a great number of factors, including:

actual target effluent concentrations for nitrogen and phosphorus;

existing facilities’ suitability for various types of upgrades;

various wastewater characteristics, including influent TP and TN concentrations, influent rbCOD:TP and BOD:TN ratios, alkalinity levels, actual flow and constituent concentrations and their hourly, daily, and seasonal variations;

various operating characteristics, including ambient temperatures, mixed liquor characteristics, and plant configuration and control methods;

local labor, material, and operational costs which may vary significantly over time; and

financing terms.

The cost estimates are intended only as a general guide for order-of-magnitude cost ranges for various upgrade options. More detailed, plant-specific analyses are necessary to determine whether WQT would be a more cost-effective option for reducing nutrient loading. In particular, WQT may be advantageous for:

long-term compliance and cost savings;

short-term compliance for the useful life of the facility or when other regulatory requirements will be better understood in regards to needed upgrades;

variance or compliance schedule justification;

small or difficult to upgrade facilities; and

future growth in fully capped watersheds.

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The analysis of permits showed that WWTPs in the Driftwood and Tippecanoe subwatersheds span a variety of process types for permitted flow rates ranging from about 24,000 gallons per day (gpd) to 5.0 million gallons per day (MGD). For the purposes of this evaluation, the secondary (i.e., biological) treatment process identified in the permits for each of these plants was used to categorize the WWTP as either an “activated sludge” system or a “lagoon/trickling filter” system. The reason that this simple categorization was chosen is because activated sludge systems are generally relatively simple to convert to biological nutrient removal (BNR) systems (by adding anaerobic and/or anoxic reactors), while lagoons and trickling filters generally require more extensive secondary treatment system modifications to be upgraded to BNR. A number of specific treatment process were listed in the permits for WWTPs categorized as “activated sludge” systems, including “extended aeration”, “oxidation ditch”, “waste stabilization”, “sequencing batch reactor”, and “activated sludge” or “conventional activated sludge”. The numbers of facilities in each of these two main categories across a range of flow rates are summarized in Table 14.

Based on this summary of the characteristics of WWTPs in the target watersheds, seven generic WWTPs (design flow/system type) were used to evaluate the range of potential costs that may be required to upgrade WWTPs in the Driftwood and Tippecanoe watersheds to nitrogen removal, phosphorus removal, or both. The generic WWTPs simulated in the cost analysis are also identified in Table 14. The design flow of each simulated plant is roughly equal to the average flow rate for the WWTPs in a given flow range.

Table 14. Summary of facility type and flows for WWTPs included in Driftwood and Tippecanoe nutrient

removal analysis

Flow Range (MGD)

Activated Sludge (AS) Lagoon/Trickling Filter (TF)

# Facilities

Total Flow (MGD)

Simulation Plant

# Facilities

Total Flow (MGD) Simulation Plant

<0.1 5 0.26 0.05 MGD AS 4 0.21 0.05 MGD Lagoon

0.1 to 0.5 9 2.35 0.3 MGD AS 5 1.29 0.3 MGD Lagoon

0.5 to 1.0 2 1.59 0.75 MGD AS 0 0.00 --

1.0 to 4.0 0 0.00 -- 2 5.15 2.5 MGD TF

>4.0 4 21.13 5.0 MGD AS 0 0.00 --

In addition to the variety of process types and flow ranges identified in Table 14, for each simulation plant a number of different nutrient removal upgrade options were evaluated. In general, selection of the specific nutrient removal upgrade options simulated was based on the availability of cost information for those options, as found in the literature. Based on the review of relevant literature and previous nutrient removal experience, the Project Team selected two generic levels of treatment for nitrogen removal and two levels of treatment for phosphorus removal for the cost analysis. These levels are as follows:

TN1. The “low enhanced nutrient removal (ENR)” treatment level for nitrogen (or TN1) can be met by adding anoxic reactors (along with nitrified mixed liquor recycle lines) prior to the existing secondary treatment process (“pre-anoxic”) or adding post-secondary anoxic treatment (typically using filters supplemented with an external carbon source), for denitrification. Land application of effluent was also designated as a potential option for the TN1 treatment level, with nitrogen removal attributed to both nitrification/denitrification processes and vegetative

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uptake and sequestration (Crites and Tchobanoglous 1998). These processes have been documented to meet a TN of 10 mg/l reliably, but may be designed to meet lower TN levels.

TN2. The “high ENR” treatment level for nitrogen (or TN2) requires both pre- and post-secondary anoxic reactors and has been demonstrated as capable of achieving effluent TN concentrations below 5 mg/l (typically, 2-3 mg/l).

TP1. The “low ENR” level for phosphorus (TP1), which requires an effluent TP of 1 mg/l or less, can be met using enhanced biological phosphorus removal (EBPR), typically involving the addition of anaerobic “selector” reactors prior to the secondary treatment unit, or using alum, which is typically dosed between the secondary treatment process and the secondary clarifier (but potentially in other configurations), for precipitating phosphorus.

TP2. The “high ENR” treatment level for phosphorus (TP2) requires either multi-point alum addition or EBPR with single- or multi-point alum addition and enhanced solids removal processes can be used to reach TP levels below 0.5 mg/l, often down to 0.1 mg/l or lower. Land application systems are also well documented to be able to meet TP2 treatment levels.

These treatment levels are summarized in Table 15, along with the assumptions for influent and baseline (i.e., effluent levels in the absence of ENR) concentrations. For the purposes of the cost analysis, the Project Team assumed a baseline TN concentration of 25 mg/l and TP concentration of 4 mg/l, the midpoints of the ranges shown in Table 15. In the cost calculations, these represent the assumed average effluent concentrations for the WWTPs prior to implementing an ENR process.

Another important implicit assumption in all of the cost calculations is that existing secondary treatment processes are nitrifying or can be made to nitrify – that is, they are sufficient to convert the majority of influent organic nitrogen and ammonia to nitrate, such that denitrification retrofits would be effective upgrade options. It is important to note that, even under a WQT approach to meeting TN reductions, participating WWTPs would still need to meet existing or revised water quality based effluent discharge limits for ammonia, a potentially mobile and toxic wastewater constituent. Under a WQT approach, nitrifying WWTPs would continue to discharge TN in the form of nitrate at non-toxic levels.

Table 15. Summary of ENR treatment levels and assumptions for WWTP upgrade simulations

TN TP

Treatment Level Effluent AS options

Lagoon/ TF options Effluent AS options Lagoon/TF options

None (influent) 25-35 mg/l 4-8 mg/l

Baseline (no ENR)

20-30 mg/l 2-6 mg/l

Low ENR (1)

5-10 mg/l Pre- or post-anoxic retrofit or land application

Post-anoxic replacement or land application

0.5-1 mg/l EBPR or single-point alum retrofit

EBPR replacement or single-point alum retrofit

High ENR (2)1

<5 mg/l Pre-/Post-anoxic retrofit

Post-anoxic replacement

<0.5 mg/l EBPR and/or multi-point alum retrofit or land application

EBPR replacement and/or multi-point alum retrofit or land application

1 Enhanced solids removal also generally required for the high ENR process upgrades, particularly for TP removal

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Table 16 summarizes the characteristics of all applicable permutations of the TN and TP treatment levels as used in the cost analysis and provides a guide to the color coded rows in Table 17 through Table 23, which present the results of the upgrade cost analyses.

Table 16. Color coding of ENR treatment levels for Tables 17-23

Treatment Level Effluent TN Effluent TP Color Coding

TN1 5-10 mg/l -- Pink

TP1 -- 0.5-1 mg/l Blue

TN2 <5 mg/l -- Tan

TP2 -- <0.5 mg/l Olive

TN1/TP1 5-10 mg/l 0.5-1 mg/l Green

TN1/TP2 5-10 mg/l <0.5 mg/l Purple

TN2/TP2 <5 mg/l <0.5 mg/l Aqua

Note that the calculations for cost per pound (cost/#) removed that are summarized in Table 17 through Table 23 use the actual effluent TN and TP treatment levels indicated in the cost reference cited, while also assuming that the design/permitted flows are the actual plant flows (this assumption has little bearing on capital costs, but does affect O&M cost estimates). To be consistent with the basis used in U.S. EPA’s nutrient removal reference document (U.S. EPA 2008), the Project Team converted all costs to annual costs assuming 20-year financing terms and a 6 percent interest rate. Additionally, all costs in Table 17 through Table 23 are presented in 2011 dollars using the latest ENR construction cost index (9011, March 2011) as a basis for adjusting the costs generated from the various sources indicated in the tables. Finally, note that where costs per pound removed are presented in Table 17 through Table 23, total costs are used in all calculations. Accordingly, it is difficult to compare the cost per pound of TP removed for a TN1/TP1 system with the cost per pound of TP removed for a TP1 system, for example, since the former number includes costs necessary for TN removal in addition to TP removal, while the latter number would be only associated with TP removal.

Table 17 and Table 18 provide estimated costs for 0.05 MGD activated sludge and lagoon upgrade options, respectively. Note that the cost estimates for the single-point alum addition upgrade option may be biased high, as the capital costs cited by Keplinger, et al. (2003) were significantly higher than those cited in comparable references addressing single-point alum treatment (i.e., as summarized in Table 19 and Table 21).

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Table 17. 0.05 MGD activated sludge ENR upgrade options and costs

Upgraded Process

Annual Cost ($/yr)

Treatment Level Cost

Reference TN TP $/# TN $/# TP $/#

TN+TP

MLE – added anoxic zone 36,074 10 mg/l 2 mg/l 15.80 118.51 13.94 Foess (1998)1

Single-point alum addition 90,296

0.75 mg/l

182.54 182.54 Keplinger (2003)2

MLE + denitrification filters 59,636 6 mg/l 1 mg/l 20.53 130.01 17.73 Foess (1998)3

Land app. – spray irrigation 152,167 10 mg/l 0.1 mg/l 66.65 256.35 52.90 Buchanan (2010)4

Land app. – drip irrigation 82,891 10 mg/l 0.1 mg/l 36.35 139.79 28.85 Buchanan (2010)4

1 Used present worth costs for 50,000 gpd anoxic tank for MLE upgrade retrofit system (option R1)

2 Used average capital and O&M costs for Iredell (0.25 MGD), Valley Mills (0.81 MGD), and Hico (0.87 MGD) plant single-point alum

addition upgrades, normalized as unit costs ($/gpd capacity) 3 Used present worth costs for 50,000 gpd deep bed denitrification filter upgrade retrofit system (option R2)

4 Used model-simulated costs for 50,000 gpd systems installed in loam soils (per NRCS Web Soil Survey data for area) and added

capital costs for land acquisition (assuming $5,000/acre) and a 25% allowance for various professional fees, both of which are not included in the model

Table 18.

0.05 MGD lagoon ENR upgrade options and costs

Upgraded Process

Annual Cost ($/yr)

Treatment Level Cost

Reference TN TP $/# TN $/# TP $/#

TN+TP

New MLE system 181,133 10 mg/l 2 mg/l 79.34 595.03 70.00 Foess (1998)1

Single-point alum addition 90,296

0.75 mg/l

182.54 182.54 Keplinger (2003)2

New MLE + denitrification filters

203,661 6 mg/l 1 mg/l 70.42 446.02 60.82 Foess (1998)3

Land app. – spray irrigation

152,167 10 mg/l 0.1 mg/l 66.65 256.35 52.90 Buchanan (2010)4

Land app. – drip irrigation 82,981 10 mg/l 0.1 mg/l 36.35 139.79 28.85 Buchanan (2010)4

1 Used present worth costs for 50,000 gpd MLE process system (option 1)

2 Used average capital and O&M costs for Iredell (0.025 MGD), Valley Mills (0.081 MGD), and Hico (0.087 MGD) plant single-point

alum addition upgrades, normalized as unit costs ($/gpd capacity) 3 Used present worth costs for 50,000 gpd MLE and deep-bed filtration process system (option 6)

4 Used model-simulated costs for 50,000 gpd systems installed in loam soils (per NRCS Web Soil Survey data for area) and added

capital costs for land acquisition (assuming $5,000/acre) and a 25% allowance for various professional fees, both of which are not included in the model

The results presented in Table 17 and Table 18 indicate that for 0.05 MGD activated sludge systems, secondary treatment upgrades and alum addition would typically be most cost effective, while comparably-sized lagoon systems may be cost-effectively upgraded for ENR via land application.

Table 19 and Table 20 provides estimated costs for 0.3 MGD activated sludge and lagoon upgrade options, respectively, with average costs for each treatment level provided where more than one option is presented. As indicated above, the average cost estimates for the single-point alum addition upgrade option may be biased high, as the capital costs cited by Keplinger, et al. (2003) were significantly higher than those cited by CH2M-Hill (2010) and others for single-point alum treatment.

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Table 19. 0.3 MGD activated sludge ENR upgrade options and costs

Upgraded Process Annual

Cost ($/yr)

Treatment Level Cost

Reference TN TP $/# TN $/# TP $/#

TN+TP

Single-point alum addition 214,146

1 mg/l

78.16 78.16 Keplinger (2003)2

Single-point alum addition 10,552

1 mg/l

3.85 3.85 CH2M Hill (2010)3

TP1 AVERAGE 112,349

41.01 41.01

Not specified 154,196 3 mg/l

7.67

7.67 Colorado (2010)4

Multi-point alum addition 157,473

0.1 mg/l

44.21 44.21 CH2M Hill (2010)3

Not specified 269,758

0.1 mg/l

75.74 75.74 Colorado (2010)4

TP2 AVERAGE 213,616

59.98 59.98

Not specified 212,0771

10 mg/l 1 mg/l 15.48 77.41 12.90 U.S. EPA (2007)5

Not specified 469,8841

6 mg/l 0.8 mg/l 27.08 160.79 23.18 M&E (2008)6

TN1/TP1 AVERAGE 340,9811

21.28 119.10 18.04

Land app. – spray irrigation 910,143 10 mg/l 0.1 mg/l 66.44 255.54 52.73 Buchanan (2010)

7

Land app. – drip irrigation 483,498 10 mg/l 0.1 mg/l 35.30 135.75 28.01 Buchanan (2010)7

TN1/TP2 AVERAGE 696,821

50.87 195.65 40.37

1 Capital costs only. O&M costs not included.

2 Used average capital and O&M costs for Valley Mills (0.081 MGD), Hico (0.087 MGD), and Clifton (0.328 MGD) plant single-point

alum addition upgrades, normalized as unit costs ($/gpd capacity) 3 Used average total life cycle costs for Oakley (0.25 MGD), Coalville (0.35 MGD), and Fairview (0.375 MGD) activated sludge plant

upgrades, normalized as unit costs ($/gpd capacity) 4 Used average capital and O&M costs for 0.1 MGD plant upgrades from Table 6 of paper, normalized as unit costs ($/gpd capacity)

5 Used average unit capital costs for BNR upgrades based on MD and CT WWTPs for flow range of >0.1-1.0 MGD ($6,972,000/mgd

capacity) 6 Used capital cost equation for BNR upgrades in PA for WWTPs <10 MGD (cost, $M = 2.643 +2.156MGD)

7 Used model-simulated costs for 300,000 gpd systems installed in loam soils (per NRCS Web Soil Survey data for area) and added

capital costs for land acquisition (assuming $5,000/acre) and a 25% allowance for various professional fees, both of which are not included in the model

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Table 20. 0.3 MGD lagoon ENR upgrade options and costs

Upgraded Process Annual Cost

Treatment Level Cost

Reference TN TP $/# TN $/# TP $/# TN+TP

New MLE system 352,708 3 mg/l

25.75

25.75 CH2M Hill

(2010)2

Single-point alum 80,433

1 mg/l

29.36 29.36 CH2M Hill

(2010)2

Single-point alum 214,146

1 mg/l

78.16 78.16 Keplinger (2003)3

TP1 AVERAGE 147,290

53.76 53.76

Multi-point alum + filters 307,001

0.1 mg/l

86.20 86.20 CH2M Hill

(2010)2

Not specified 269,758

0.1 mg/l

75.74 75.74 Colorado (2010)4

TP2 AVERAGE 288,380

80.97 80.97

Not specified 212,0771

10 mg/l 1 mg/l 15.48 77.41 12.90 U.S. EPA (2007)5

Not specified 469,884 6 mg/l 0.8 mg/l 27.08 160.79 23.18 M&E (2008)6

TN1/TP1 AVERAGE 340,9811

119.10 18.04

Land application - spray 910,143 10 mg/l 0.1 mg/l 66.44 255.54 52.73 Buchanan

(2010)7

Land application - drip 483,498 10 mg/l 0.1 mg/l 35.30 135.75 28.01 Buchanan

(2010)7

TN1/TP2 AVERAGE 696,821

195.65 40.37

1 Capital costs only. O&M costs not included.

2 Used average total life cycle costs for 0.55 MGD lagoon retrofits, normalized as unit costs ($/gpd capacity)

3 Used average capital and O&M costs for Valley Mills (0.081 MGD), Hico (0.087 MGD), and Clifton (0.328 MGD) plant single-point

alum addition upgrades, normalized as unit costs ($/gpd capacity) 4 Used average capital and O&M costs for 0.1 MGD plant upgrades from Table 6 of paper, normalized as unit costs ($/gpd capacity)

5 Used average unit capital costs for BNR upgrades based on MD and CT WWTPs for flow range of >0.1-1.0 MGD ($6,972,000/mgd

capacity) 6 Used capital cost equation for BNR upgrades in PA for WWTPs <10 MGD (cost, $M = 2.643 +2.156MGD)

7 Used model-simulated costs for 300,000 gpd systems installed in loam soils (per NRCS Web Soil Survey data for area) and added

capital costs for land acquisition (assuming $5,000/acre) and a 25% allowance for various professional fees, both of which are not included in the model

The results presented in Table 19 and Table 20 indicate that at these relatively low design flows, land application may be a cost-effective ENR upgrade option, compared with more traditional secondary treatment upgrades or multi-point alum addition, as needed to achieve comparably low TP levels.

Table 21 provides estimated costs for 0.75 MGD activated sludge upgrade options, with average costs for each treatment level provided where more than one option is presented. Because the costs cited by Keplinger (2003) were significantly higher than those cited by CH2M-Hill (2010) and U.S. EPA (2008) for single-point alum treatment, the Keplinger data was not used in the average cost calculation for TP1 treatment level upgrade options.

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Table 21. 0.75 MGD activated sludge ENR upgrade options and costs

Upgraded Process Annual Cost

($/yr)

Treatment Level Cost

Reference TN TP $/# TN $/# TP $/#

TN+TP

MLE – added anoxic zone 72,554 10 mg/l

2.12

2.12 CH2M Hill (2010)3

Single-point alum addition 390,779

1 mg/l

57.05 57.05 Keplinger (2003)4

EBPR or single-point alum addition

29,232

1 mg/l

4.27 4.27 CH2M Hill (2010)3

Fermenter addition 28,942

0.5 mg/l

3.62 3.62 U.S. EPA (2008)5

Single-point alum addition 60,853

0.5 mg/l

7.62 7.62 U.S. EPA (2008)5

Fermenter and filter addition

60,358

0.5 mg/l

7.55 7.55 U.S. EPA (2008)5

TP1 AVERAGE 44,8461

5.77 5.77

Phased Isolation Ditch retrofit

69,016 3 mg/l

1.37

1.37 U.S. EPA (2008)5

MLE retrofit 111,316 3 mg/l

2.22

2.22 U.S. EPA (2008)5

Step-feed retrofit 111,316 3 mg/l

2.22

2.22 U.S. EPA (2008)5

Denitrification filter retrofit 230,053 3 mg/l

4.58

4.58 U.S. EPA (2008)5

TN2 AVERAGE 130,425

2.60

2.60

EBPR + multi-stage alum + filters

166,445

0.1 mg/l

18.69 18.69 CH2M Hill (2010)3

Fermenter, filter, and alum addition

118,242

0.1 mg/l

13.28 13.28 U.S. EPA (2008)5

Multi-point alum and filter addition

134,321

0.1 mg/l

15.09 15.09 U.S. EPA (2008)5

TP2 AVERAGE 139,669

15.69 15.69

Not specified 530,0912

10 mg/l 1 mg/l 15.48 77.39 12.90 U.S. EPA (2007)6

Not specified 557,904

6 mg/l 0.8 mg/l 12.86 76.36 11.01 M&E (2008)7

TN1/TP1 AVERAGE 543,9982

14.17 76.88 11.96

Land application - spray 2,275,356 10 mg/l 0.1 mg/l 66.44 255.54 52.73 Buchanan (2010)8

Land application - drip 1,169,997 10 mg/l 0.1 mg/l 34.16 131.40 27.11 Buchanan (2010)8

TN1/TP2 AVERAGE 1,722,677

50.30 193.47 39.92

Phased Isolation Ditch retrofit

238,958 3 mg/l 0.1 mg/l 4.76 26.84 4.04 U.S. EPA (2008)5

5-stage act. sludge + alum retrofit

271,611 3 mg/l 0.1 mg/l 5.41 30.50 4.59 U.S. EPA (2008)5

Alum addition + denitrification filter

352,253 3 mg/l 0.1 mg/l 7.01 39.56 5.96 U.S. EPA (2008)5

TN2/TP2 AVERAGE 287,607

5.73 32.30 4.86

1 Average does not include Keplinger data

2 Capital costs only. O&M costs not included.

3 Used average total life cycle costs for Fairview (0.375 MGD), Moroni (0.9 MGD), Hyrum City (1.3 MGD), and Tremonton (1.9 MGD)

activated sludge plant upgrades, normalized as unit costs ($/gpd capacity) 4 Used average capital and O&M costs for Hico (0.087 MGD), Clifton (0.328 MGD), and Meridian (0.36 MGD) plant single-point alum

addition upgrades, normalized as unit costs ($/gpd capacity) 5 Used extrapolated life cycle costs per MG treated for retrofit options, normalized to $/gpd capacity

6 Used average unit capital costs for BNR upgrades based on MD and CT WWTPs for flow range of >0.1-1.0 MGD ($6,972,000/mgd

capacity) 7 Used capital cost equation for BNR upgrades in PA for WWTPs <10 MGD (cost, $M = 2.643 +2.156MGD)

8 Used model-simulated costs for 750,000 gpd systems installed in loam soils (per NRCS Web Soil Survey data for area) and added

capital costs for land acquisition (assuming $5,000/acre) and a 25% allowance for various professional fees, both of which are not included in the model

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The results presented in Table 21 indicate that at these somewhat higher design flows, traditional secondary treatment upgrades or alum addition are more cost effective than land application for achieving very low TP levels.

Table 22 provides estimated costs for 2.5 MGD trickling filter upgrade options, with average costs for each treatment level provided where more than one option is presented. For this higher flow rate, we assumed that land application would no longer be a viable upgrade option.

Table 22. 2.5 MGD trickling filter ENR upgrade options and costs

Upgraded Process

Annual Cost ($/yr)

Treatment Level Cost

Reference TN TP $/# TN $/# TP $/#

TN+TP

New MLE system 163,852 10 mg/l

1.44

1.44 CH2M Hill

(2010)2

New phased isolation ditch system

376,001 5 mg/l

2.47

2.47 U.S. EPA (2008)3

New MLE system 1,009,265 5 mg/l

6.63

6.63 U.S. EPA (2008)3

New SBR system 1,128,002 5 mg/l

7.41

7.41 U.S. EPA (2008)3

New 4-stage bardenpho system

1,385,265 5 mg/l

9.10

9.10 U.S. EPA (2008)3

TN1 AVERAGE 812,477

5.41

5.41

New A/O system 811,098

1 mg/l

35.53 35.53 U.S. EPA (2008)3

Single-point alum addition 144,841

1 mg/l

6.34 6.34 CH2M Hill

(2010)2

Single-point alum addition 168,211

0.5 mg/l

6.32 6.32 U.S. EPA (2008)4

New A/O w/fermenters 841,054

0.5 mg/l

31.58 31.58 U.S. EPA (2008)3

New A/O w/fermenters + filters

989,475

0.5 mg/l

37.15 37.15 U.S. EPA (2008)3

New mod UCT w/fermenters + filters

1,504,002

0.5 mg/l

56.47 56.47 U.S. EPA (2008)3

New 5-stage bardenpho w/filters

1,553,476

0.5 mg/l

58.32 58.32 U.S. EPA (2008)3

TP1 AVERAGE 858,880

33.10 33.10

New denitrification filters 662,948 3 mg/l

3.96

3.96 U.S. EPA (2008)4

New A/O w/fermenters + filters + alum

1,137,896

0.1 mg/l

38.34 38.34 U.S. EPA (2008)3

Multi-stage alum addition with filters

1,307,813

0.1 mg/l

44.06 44.06 CH2M Hill

(2010)2

New A/O with fermenters, filters, alum

1,137,490

0.1 mg/l

38.33 38.33 U.S. EPA (2008)3

Multi-point alum addition with filters

395,790

0.1 mg/l

13.34 13.34 U.S. EPA (2008)4

TP2 AVERAGE 994,747

33.52 33.52

New A/O system 3,860,366 10 mg/l 1 mg/l 33.82 169.09 28.18 Jiang et al

(2004)5

Not specified 441,4891

10 mg/l 1 mg/l 3.87 19.34 3.22 U.S. EPA (2007)6

Not specified 1,039,337

6 mg/l 0.8 mg/l 7.19 42.68 6.15 M&E (2008)7

New 3-stage UCT system 1,345,686 5 mg/l 1 mg/l 8.84 58.94 7.69 U.S. EPA (2008)3

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Upgraded Process

Annual Cost ($/yr)

Treatment Level Cost

Reference TN TP $/# TN $/# TP $/#

TN+TP

New step feed AS system 900,422 5 mg/l 1 mg/l 5.92 39.44 5.14 U.S. EPA (2008)3

New 5-stage Bardenpho 1,434,739 5 mg/l 0.5 mg/l 9.43 53.86 8.02 U.S. EPA (2008)3

TN1/TP1 AVERAGE 1,503,673

11.51 63.89 9.73

New A/A/O with alum + filters 5,301,614 3.5 mg/l 0.1 mg/l 32.40 178.63 27.43 Jiang et al

(2004)5

Alum addition with denitrification filters

989,475 3 mg/l 0.1 mg/l 5.91 33.34 5.02 U.S. EPA (2008)4

New phased isolation ditch+alum+filters

722,317 3 mg/l 0.1 mg/l 4.31 24.34 3.66 U.S. EPA (2008)3

New SBR + alum + fiters 1,236,844 3 mg/l 0.1 mg/l 7.39 41.67 6.28 U.S. EPA (2008)3

New 5-stage Bardenpho + alum + filters

1,682,108 3 mg/l 0.1 mg/l 10.05 56.67 8.53 U.S. EPA (2008)3

TN2/TP2 AVERAGE 1,986,472

12.01 66.93 10.18

1 Capital costs only. O&M costs not included.

2 Used average total life cycle costs for Tremonton (1.9 MGD), Snyderville (2.4 MGD), and Magna (3.3 MGD) activated sludge plant

upgrades, normalized as unit costs ($/gpd capacity) 3 Used interpolated life cycle costs per MG treated for expansion options, normalized to $/gpd capacity

4 Used interpolated life cycle costs per MG treated for retrofit options, normalized to $/gpd capacity

5 Interpolated between 1 MGD and 10 MGD de novo plant options

6 Used average unit capital costs for BNR upgrades based on MD and CT WWTPs for flow range of >1.0-10.0 MGD

($1,742,000/mgd capacity) 7 Used capital cost equation for BNR upgrades in PA for WWTPs <10 MGD (cost, $M = 2.643 +2.156MGD)

The results presented in Table 22 indicate that for replacement systems associated with trickling filter upgrades at these higher design flows, the additional costs associated with higher levels of ENR (e.g., TN1/TP1->TN2/TP2) are relatively modest.

Table 23 provides estimated costs for 5 MGD activated sludge upgrade options, with average costs for each treatment level provided where more than one option is presented. As for the 2.5 MGD option, for this higher flow rate, we assumed that land application would no longer be a viable upgrade option.

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Table 23. 5 MGD activated sludge ENR upgrade options and costs

Upgraded Process Annual

Cost

Treatment Level Cost

Reference TN TP $/# TN $/# TP $/#

TN+TP

MLE – added anoxic zone 457,869 10 mg/l

2.01

2.01 CH2M Hill

(2010)2

Single-point alum addition 271,677

1 mg/l

5.95 5.95 CH2M Hill

(2010)2

Fermenter addition 118,737

0.5 mg/l

2.23 2.23 U.S. EPA (2008)3

Single-point alum addition 237,474

0.5 mg/l

4.46 4.46 U.S. EPA (2008)3

Fermenter addition with filters 316,632

0.5 mg/l

5.94 5.94 U.S. EPA (2008)3

TP1 AVERAGE 236,130

4.65 4.65

Phased isolation ditch retrofit 336,422 3 mg/l

1.00

1.00 U.S. EPA (2008)3

MLE retrofit 554,106 3 mg/l

1.65

1.65 U.S. EPA (2008)3

Step feed retrofit 554,106 3 mg/l

1.65

1.65 U.S. EPA (2008)3

Denitrification filters 1,048,844 3 mg/l

3.13

3.13 U.S. EPA (2008)3

TN2 AVERAGE 623,370

1.86

1.86

EBPR + multi-point alum addition and filters

1,721,904

0.1 mg/l

29.01 29.01 CH2M Hill

(2010)2

Fermenter addition with alum and filters

504,632

0.1 mg/l

8.50 8.50 U.S. EPA (2008)3

Multi-point alum addition with filters

653,054

0.1 mg/l

11.00 11.00 U.S. EPA (2008)3

TP2 AVERAGE 959,863

16.17 16.17

A/O retrofit + alum addition 518,769 10 mg/l 1 mg/l 2.27 11.36 1.89 Jiang et al(2005)4

Not specified 882,9781

10 mg/l 1 mg/l 3.87 19.34 3.22 U.S. EPA (2007)5

Not specified 1,699,014

6 mg/l 0.8 mg/l 5.88 34.88 5.03 M&E (2008)6

TN1/TP1 AVERAGE 1,033,587

4.01 21.86 3.38

A/A/O system + alum + filters 2,383,485 3.5 mg/l 0.1 mg/l 7.28 40.15 6.17 Jiang et al

(2005)4

PID retrofit 1,068,633 3 mg/l 0.1 mg/l 3.19 18.00 2.71 U.S. EPA (2008)3

5-stage w/chem P 1,286,318 3 mg/l 0.1 mg/l 3.84 21.67 3.26 U.S. EPA (2008)3

Alum addition w/denitrification filters

1,484,213 3 mg/l 0.1 mg/l 4.43 25.00 3.77 U.S. EPA (2008)3

TN2/TP2 AVERAGE 1,555,662

4.69 26.21 3.98

1 Capital costs only. O&M costs not included.

2 Used average total life cycle costs for Payson (4.5 MGD), Brigham (6 MGD), and Spanish Fork (6 MGD) activated sludge plant

upgrades, normalized as unit costs ($/gpd capacity) 3 Used interpolated life cycle costs per MG treated for retrofit options, normalized to $/gpd capacity

4 Interpolated between 1 MGD and 10 MGD retrofit plant options

5 Used average unit capital costs for BNR upgrades based on MD and CT WWTPs for flow range of >1.0-10.0 MGD

($1,742,000/mgd capacity) 6 Used capital cost equation for BNR upgrades in PA for WWTPs <10 MGD (cost, $M = 2.643 +2.156MGD)

The results presented in Table 23 indicate that for a 5 MGD activated sludge upgrade, the cost increase associated with meeting a TP2 standard versus TP1 are significant, although the potential cost increase associated with meeting high versus low ENR combined TN/TP standards are less pronounced.

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3.8 Potential Credit Supply

Estimation of potential credit supply from agricultural reductions was assessed using two models: SPARROW and SWAT. The SPARROW loads are based on those published by USGS whereas the Project Team set up and calibrated the SWAT model for the Tippecanoe and Driftwood River watersheds. Evaluation of both models was required to increase the resolution of watershed assessment procedures at scale. Results from the SPARROW model are provided in Table 24 and Table 25 for TN and TP, respectively. SPARROW model estimates of agricultural NPS loading are provided in Table 26.

The SPARROW model estimates for the Wabash River watershed indicate a substantial amount of TN and TP are generated within and exported at the mouth of each 8-Digit HUC. Each HUC estimate is independent of the upstream loading passing through the HUC. The estimated loading from all land use categories and all HUCs is 923,700 pounds TN and 87,900 pounds TP per year.

The estimated cumulative agricultural loading that was generated by the model within each 8-Digit HUC and exported at the mouth is 762,200 pounds of TN and 79,500 pounds of TP per year. The maximum standard error (combined fertilizer and manure related standard errors) is 5 percent for TN and 26 percent for TP. The average maximum standard error estimate is 2 percent for TN and 9 percent for TP.

The use of average results does not provide sufficient resolution or information on spatial variability. WQT program frameworks target optimum sites that generate economical transactions. Using an average pound per acre estimate helps illustrate the limited usefulness of the results. The entire watershed has approximately 21,088,000 acres. Using these figures, the average loading from agricultural land uses in the watershed is 0.04 and 0.002 pounds per acre for TN and TP, respectively. Assuming an average BMP reduction of 20 percent, it would take approximately 125 acres to generate 1 pound of TN load reduction. A finer resolution can capture the spatial variability. Targeting fields that have higher reduction capability has the potential to provide more economical transactions. In addition, the SPARROW model estimates already include reductions attributable to attenuation dynamics within each 8-Digit HUC.

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Table 24. Total Nitrogen Exported at the Mouth of 8-Digit HUC Watersheds, Independent of Upstream Watershed Loading (USGS, 1997).

Watershed Subwatershed HUC Sq. Miles Acres

1997 SPARROW Estimated Total

Nitrogen Exported (Pounds)

Average Pounds/Acre

Wabash Upper Wabash 5,120,101 1,589 1,016,960 57,591 0.06

Wabash Salamonie 5,120,102 552 353,280 9,357 0.03

Wabash Mississinewa 5,120,103 842 538,880 24,311 0.05

Wabash Eel 5,120,104 829 530,560 14,527 0.03

Wabash Middle Wabash-Deer 5,120,105 652 417,280 30,828 0.07

Wabash Tippecanoe 5,120,106 1,960 1,254,400 46,838 0.04

Wabash Wildcat 5,120,107 813 520,320 29,088 0.06

Wabash Middle Wabash-Little Vermilion 5,120,108 2,287 1,463,680 73,067 0.05

Wabash Vermilion 5,120,109 1,439 920,960 37,090 0.04

Wabash Sugar 5,120,110 808 517,120 20,979 0.04

Wabash Middle Wabash-Busseron 5,120,111 2,019 1,292,160 61,710 0.05

Wabash Embarras 5,120,112 2,442 1,562,880 82,977 0.05

Wabash Lower Wabash 5,120,113 1,321 845,440 65,194 0.08

Wabash Little Wabash 5,120,114 2,148 1,374,720 48,280 0.04

Wabash Skillet 5,120,115 1,049 671,360 17,211 0.03

Patoka-White Upper White 5,120,201 2,754 1,762,560 66,439 0.04

Patoka-White Lower White 5,120,202 1,675 1,072,000 48,900 0.05

Patoka-White Eel 5,120,203 1,195 764,800 16,309 0.02

Patoka-White Driftwood 5,120,204 1,154 738,560 36,800 0.05

Patoka-White Flatrock-Haw 5,120,205 586 375,040 23,203 0.06

Patoka-White Upper East Fork White 5,120,206 811 519,040 26,845 0.05

Patoka-White Muscatatuck 5,120,207 1,143 731,520 25,199 0.03

Patoka-White Lower East Fork White 5,120,208 2,025 1,296,000 36,035 0.03

Patoka-White Patoka 5,120,209 859 549,760 24,873 0.05

Total 32,950 21,088,000 923,652 0.04

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Table 25. Total Phosphorus Exported at the Mouth of 8-Digit HUC Watersheds, Independent of Upstream Watershed Loading (USGS, 1997).

Watershed Subwatershed HUC Sq. Miles Acres

1997 SPARROW Estimated Total

Phosphorus Exported (Pounds)

Total Phosphorus

Average Pounds/Acre

Wabash Upper Wabash 5120,101 1,589 1,016,960 5,571 0.0028

Wabash Salamonie 5120102 552 353,280 843 0.0011

Wabash Mississinewa 5120103 842 538,880 2,293 0.0020

Wabash Eel 5120104 829 530,560 1,503 0.0015

Wabash Middle Wabash-Deer 5120105 652 417,280 3,326 0.0042

Wabash Tippecanoe 5120106 1,960 1,254,400 3,338 0.0012

Wabash Wildcat 5120107 813 520,320 3,413 0.0035

Wabash Middle Wabash-Little Vermilion 5120108 2,287 1,463,680 5,474 0.0012

Wabash Vermilion 5120109 1,439 920,960 2,711 0.0007

Wabash Sugar 5120110 808 517,120 2,261 0.0020

Wabash Middle Wabash-Busseron 5120111 2,019 1,292,160 4,594 0.0009

Wabash Embarras 5120112 2,442 1,562,880 6,300 0.0015

Wabash Lower Wabash 5120113 1,321 845,440 5,758 0.0019

Wabash Little Wabash 5120114 2,148 1,374,720 4,357 0.0013

Wabash Skillet 5120115 1,049 671,360 1,204 0.0006

Patoka-White Upper White 5120201 2,754 1,762,560 5,130 0.0010

Patoka-White Lower White 5120202 1,675 1,072,000 4,353 0.0018

Patoka-White Eel 5120203 1,195 764,800 1,507 0.0008

Patoka-White Driftwood 5120204 1,154 738,560 3,070 0.0015

Patoka-White Flatrock-Haw 5120205 586 375,040 2,290 0.0026

Patoka-White Upper East Fork White 5120206 811 519,040 2,627 0.0024

Patoka-White Muscatatuck 5120207 1,143 731,520 2,606 0.0015

Patoka-White Lower East Fork White 5120208 2,025 1,296,000 2,669 0.0011

Patoka-White Patoka 5120209 859 549,760 2,252 0.0022

Total 32,950 21,088,000 79,452 0.0411

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Table 26. SPARROW model estimates of agricultural NPS loading

Watershed Subwatershed HUC

Agricultural Total

Nitrogen Exported (Pounds)

Total Nitrogen Maximum

Standard Error

Agricultural Total Phosphorus

Exported (Pounds)

Total Phosphorus Maximum

Standard Error

Wabash Upper Wabash 5120101 49,815 1% 5,571 4%

Wabash Salamonie 5120102 8,098 5% 843 26%

Wabash Mississinewa 5120103 21,120 2% 2,293 9%

Wabash Eel 5120104 12,503 3% 1,503 14%

Wabash Middle Wabash-Deer 5120105 26,686 1% 3,326 6%

Wabash Tippecanoe 5120106 38,985 1% 3,338 7%

Wabash Wildcat 5120107 25,415 1% 3,413 6%

Wabash Middle Wabash-Little Vermilion 5120108 58,534 1% 5,474 5%

Wabash Vermilion 5120109 30,400 4% 2,711 15%

Wabash Sugar 5120110 18,428 2% 2,261 10%

Wabash Middle Wabash-Busseron 5120111 52,001 2% 4,594 7%

Wabash Embarras 5120112 69,343 1% 6,300 4%

Wabash Lower Wabash 5120113 55,613 2% 5,758 5%

Wabash Little Wabash 5120114 42,586 1% 4,357 5%

Wabash Skillet 5120115 14,542 5% 1,204 23%

Patoka-White Upper White 5120201 48,112 1% 5,130 6%

Patoka-White Lower White 5120202 39,288 1% 4,353 5%

Patoka-White Eel 5120203 13,672 4% 1,507 16%

Patoka-White Driftwood 5120204 31,043 2% 3,070 8%

Patoka-White Flatrock-Haw 5120205 20,024 2% 2,290 10%

Patoka-White Upper East Fork White 5120206 22,596 2% 2,627 8%

Patoka-White Muscatatuck 5120207 18,745 2% 2,606 9%

Patoka-White Lower East Fork White 5120208 24,266 1% 2,669 8%

Patoka-White Patoka 5120209 20,584 2% 2,252 10%

Total 762,200

79,452

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The Wabash River watershed has significant variability in characteristics that promote or reduce NPS nutrient loading. For example, the variation in land use and vegetative cover is illustrated in Figure 5. Additionally, variations in Indiana animal livestock density estimated using 2007 Indiana Agricultural receipts are presented for beef cattle in Figure 6 and dairy cattle in Figure 7.

Figure 6. Number of Beef Cattle per Subwatershed within the Wabash-Patoka Watershed.

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Figure 7. Number of Dairy Animals per Subwatershed within the Wabash-Patoka watershed.

Metrological conditions also vary significantly across the watershed, with the range of average annual precipitation for 1961 to 1990 generally increases traveling from north to south by approximately 10 inches per year (Oregon Climate Service, 1995). According to a USGS study the average runoff from 1975-2004 increases in a general pattern from north to south ranging from 10 to 18 inches per year (USGS, 2008). The ability for an agricultural field to supply nutrient credits is dependent on these and other physical, chemical and biological characteristics.

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To illustrate the benefits of using a smaller scale model for estimating nutrient loads, a limited SWAT 2009 model was developed for the Driftwood (05120204) and Tippecanoe (05120106) watersheds. The model was set up for agricultural land use, forestry and urban runoff were estimated beginning with default values. Another constraint is that point source data was not readily available. The model was then calibrated and validated using hydrology records from USGS stations across a 13-year period (1997-2009) with a 3-year equilibration period. The calibration was completed using the limited water quality data from STORET and USGS and a weight of evidence approach based on other regional model results. The SWAT model calibration and validation results are provided in Appendix D. The model is limited by lack of sufficient operational practice information (e.g., nutrient application rates and methods), lack of point source data and lack of water quality data for calibration. However, the model and resulting outputs are considered sufficient for this preliminary evaluation.

Three scenarios for BMPs were created to test each BMP independently for the ability to reduce TN and TP. The three BMPs that were tested are as follows: 1) no-till residue management, 2) filter strips, and 3) cover crops. These three BMPs are not the only practices that can be used to generate nutrient load reductions. These BMPs were selected based on several factors: 1) the three practices provide a range of nutrient load reduction results, 2) the SWAT 2009 model construct manages operational BMPs easier than structural and/or bank stabilization BMPs, and 3) the input data for gully corrections and bank stabilization was not readily available. The NRCS1 definition of each BMP is provided below (Indiana state office of the NRCS, electronic Field Office Tech Guide. Accessed April 12, 2011 at http://efotg.sc.egov.usda.gov//efotg_locator.aspx):

Filter strips: A strip or area of herbaceous vegetation that removes contaminants from overland flow.

Cover Crops: Grasses, legumes, forbs, or other herbaceous plants established for seasonal cover and other conservation purposes.

No-till Residue: Managing the amount, orientation and distribution of crop and other plant residues on the soil surface year-round, while growing crops in narrow slots, or tilled or residue free strips in soil previously untilled by full-width inversion implements.

A fourth BMP, nutrient management, was considered. Individual field data was not available to determine the range of nutrients currently applied and the percent of fields within each range. Therefore a nutrient management scenario was not fully completed. Nutrient management is critical to successful systems of BMP implementation as discussed in the Final Report of the Lake Erie Millennium Network Synthesis Team (Lake Erie Millennium Network Synthesis Team, 2010). In this final report the findings indicate:

There is no agronomic benefit to applying P fertilizer when STP levels reach 60 mg/kg Mehlich 3 P. Considering this benchmark, the occurrence of soil samples exceeding 60 mg/kg Mehlich 3 P was < 20% for 19 counties, 20 to 40% for 28 counties, and > 40% in 4 counties. Across the fifty counties, STP levels that are >60 mg/kg occur 30% of the time. (p. 10)

And,

Large additions of fertilizer or manure may change the soil mechanisms controlling P mobility by overwhelming a soil’s ability to moderate P solubility resulting in a dominant P mineral phase,

1 Indiana State office of the NRCS, electronic Field Office Technical Guide. Accessed April 12, 2011 at

http://efotg.sc.egov.usda.gov//efotg_locator.aspx

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from the amendment (fertilizer/manure), controlling P solubility. This is an important finding because it suggests that management of soils with a low to moderate STP may need to be considered differently than soils with high STP. It may be misleading to lump them together and attempt to predict runoff P at low to moderate STP levels using models developed where sites with very high STP are included, because the mechanisms controlling P solubility (transport risk) are different. (p. 8)

The presence of high phosphorus applications (manure and/or fertilizer) occur 30 percent of the time in Ohio. A similar expectation might be made for Indiana. Nitrogen variability is demonstrated in a Purdue University Extension Agronomy Guide (Purdue University, 2005).

Table 27. General Guidelines for Interpreting NO3-N Concentrations in Tile Drainage Water1.

(Purdue University, 2005)

NO3 –N Concentration (ppm) Interpretation

< 5 Native grassland, CRP land, alfalfa, managed pastures

5-10

Row crop production on mineral soil without N fertilizer Row crop production with N applied at 45 lbs/acre below economically optimum N Rate

2

Row crop production with successful winter crop to “trap” N

10 - 20 Row crop production with N applied at optimum N rate Soybeans

> 20

Row crop production where:

N applied exceeds crop need

N applied not synchronized with crop need

Environmental conditions limit crop production and N fertilizer use efficiency

Environmental conditions favor greater than normal mineralization of soil organic matter

1 General guidelines for interpreting NO3-N concentrations in tile drainage water. The interpretation is derived from numerous

studies conducted throughout the cornbelt and highlights land management strategies commonly found in association with a concentration measured in tile as the tile leaves the edge of field. 2 Economically optimum N rate is the rate that maximizes the return on investment in N fertilizer and therefore may be slightly lower

than the N rate that maximizes crop yield.

However, the rates of manure and fertilizer applications within a subwatershed are not well documented in public records. Information like phosphorus soil testing is not available on a field-by-field basis, this is considered confidential information by many programs including those in the Federal Farm Bill. Pragmatic estimation of the TN and TP reductions from nutrient management without ranges of current practices prevents this practice from being accurately estimated.

3.8.1 Filterstrip Treatment Efficiency Results Table 28 for the Driftwood subwatershed, and

Table 29 for the Tippecanoe subwatershed, provide reduction results for implementing filter strips on the edges of row cropped lands.

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Table 28. Filterstrip Treatment Efficiency Results at the Subwatershed Scale, in Percent, Driftwood Watershed.

Subwatershed

Sediment (in short tons) TP (in lbs) TN (in lbs)

3 Baseline 63,614.45 98,693.56 870,782.44

Filterstrip 45,438.97 74,860.31 702,915.79

% change -28.57 -24.15 -19.28

8 Baseline 125,460.07 278,662.35 2,467,305.30

Filterstrip 101,835.68 231,564.60 2,168,099.61

% change -18.83 -16.90 -12.13

23 Baseline 49,719.55 110,996.66 1,325,192.57

Filterstrip 39,227.43 90,869.64 1,096,201.60

% change -21.10 -18.13 -17.28

Table 29. Filterstrip Treatment Efficiency Results at the Subwatershed Scale, in Percent, Tippecanoe Watershed.

Subwatershed

Sediment (in short tons) TP (in lbs) TN (in lbs)

15 Baseline 8,413 30,564 364,300

Filterstrip 5,978 22,871 289,526

% change -28.9 -25.2 -20.5

28 Baseline 8,533 39,186 2,220,708

Filterstrip 6,677 30,921 1,849,657

% change -21.8 -21.1 -16.7

34 Baseline 46,706 83,358 873,397

Filterstrip 35,049 64,522 702,124

% change -25.0 -22.6 -19.6

To further refine the analysis the Project Team focused on the range of variability as much as the average results. Using field runoff projections for filter strips a percent reduction available from the BMP was completed in three Driftwood subwatersheds. This watershed was selected to evaluate at the field level due it having larger variability in the subwatershed results. This estimate still includes some use of averaging. The SWAT model groups common parcels that have like soils and land use. These groupings are referred to as hydrologic resource units (HRU). The groupings range from hundreds to thousands of acres each. For agricultural row cropping the HRU categorization considers the soil characteristics, crop rotation make up, cropping tillage implements and timing of passes and the nutrient application rates and methods. The variability in these physical and cultural settings, in addition to climate and other factors described above, introduces a range of uncertainty in credit estimation at the watershed scale. To overcome this, implement passes selected to simulate no-till, mulch till and conventional tillage settings were based on the Indiana State Department of Agriculture conservation tillage data2 were analyzed. SWAT model scenarios for the corn-soybean rotations assessed BMP treatment efficiencies. In the Driftwood subwatersheds only the highest residue rates (simulated by no-till) or the lowest residue rates (simulated by conventional moldboard plow implement passes) exist.

Filter strip treatment efficiencies for nitrogen and phosphorus are listed in Table 30. NPS load reductions are in the range of 18 to 23 percent for nitrogen and 19 to 31 percent reduction of phosphorus. The

2

Indiana State Department of Agriculture (ISDA) - 2007 Conservation Tillage Data by county- Available at: http://www.in.gov/isda/2354.htm

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filter strip average nitrogen reduction is 20.7 percent with a standard deviation of 1.3 percent. For phosphorus the average reduction is 25.3 percent with a standard deviation of 3 percent. An area weighted mean in reduction is 19.6 and 22.7 percent respectively for nitrogen and phosphorus. Therefore, a conservative treatment efficiency value would be 20 percent for nitrogen and 22 percent for phosphorus.

Table 30. Filterstrip Treatment Efficiency Results in Percent, Field Scale Results, Driftwood Watershed.

Corn – Soybean Tillage Practice Subwatershed HRU (acres)

Nitrogen Percent Reduction

Phosphorus Percent

Reduction

No-till Corn & Drilled Soybeans

1 1 (3,113) 21 24

1 3 (1,637) 21 25

4 45 (1039) 22 27

9 107 (3011) 21 25

Conventional Tillage of Corn & Soybeans

1 2 (564) 23 31

1 4 (3,630) 20 24

4 44 (1,864) 20 24

4 48 (1,316) 21 27

Conventional Till Corn & No-till Drilled

Soybeans

1 5 (960) 22 30

4 47 (1,844) 21 25

4 49 (3,423) 20 23

9 108 (15,664) 18 19

9 109 (4,108) 19 25

3.8.2 Cover Crop Treatment Efficiency Results

Fall rye cover crop plantings were simulated across corn-soybean rotation row crops in subwatersheds 3, 8 and 23 in the Driftwood Watershed and 19, 30 and 34 in the Tippecanoe Watershed. In Table 31, the reduction results for the Driftwood subwatersheds are provided. Comparing these to the Tippecanoe subwatershed results, provided in Table 32, indicates a larger range of variability than that found in the filter strip investigation. The substantial variability in treatment efficiency can be partially explained by the similarity of residue management and cover cropping. The cover crop leaves residue in the field over winter periods. In fields with high residue management the reductions are usually lower. But the previous use of high residue tillage practices does not fully explain the variability. This is evident in the variability that exists within Tables 32 and 33. Specifically, the variability found in the conventional tillage corn no-till drill soybean category indicates the influence other factors have on the performance of cover cropping. Soil types, rate and timing of nutrients and year-to-year variability can all add to the variability in performance. Having optimum weather conditions allows the cover crop roots to keep nutrients closer to the surface. However, in different years wet weather or poor timing can lead to the nutrients leaching past the root zone prior to the uptake by the cover crop. Table 10 demonstrates an overall higher treatment efficiency gained by cover crops in the Tippecanoe subwatersheds. However, the variability still exists.

Table 33 indicates the range of variability in the Driftwood subwatersheds is from 6 to 47 percent for nitrogen reductions. The average is 25.7 percent with a standard deviation of 13.3 percent. The area weighted mean is 18.7 percent reduction in nitrogen. For phosphorus reductions the range is from 8 to

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53 percent with an average of 22.6 percent and a standard deviation of 12.6 percent. The phosphorus area weighted mean is 28 percent.

Table 34 indicates the range of variability in the Tippecanoe subwatersheds is from 12 to 53 percent for nitrogen reductions. The average is 32.3 percent with a standard deviation of 11.3 percent. The area weighted mean is 34.1 percent reduction in nitrogen. For phosphorus reductions the range is from 5 to 48 percent with an average of 23.6 percent and a standard deviation of 12.3 percent. The phosphorus area weighted mean is 26.6 percent.

Selecting a common value to use across the Wabash River watershed (intended for this project only) requires being conservative when assessing these watershed tables. A conservative treatment efficiency to use for cover crops would be 12 percent for nitrogen and 10 percent for phosphorus in the Driftwood and 21 percent for nitrogen and 10 percent for phosphorus in the Tippecanoe. Therefore, a conservative overall Wabash River watershed treatment efficiency factor for cover crops can be 12 percent for nitrogen and 10 percent for phosphorus. This estimate is for extrapolation purposes only. It is evident that there are settings where the average results greatly exceed these low estimates. As such all 8-digit HUC watersheds can be expected to have a fraction of row cropped acres that will generate load reductions substantially greater than these estimates used for a conservative credit supply calculation.

Table 31. Cover Crop Treatment Efficiency Results in Percent at the Subwatershed level, Driftwood Watershed.

Subwatershed

Sediment (in short tons) TP (in lbs) TN (in lbs)

3 Baseline 47,523.19 46,417.47 606,466.57

Cover crop 35,965.97 36,931.85 456,404.85

% change -24.32 -20.44 -24.74

8 Baseline 53,811.47 57,150.39 982,454.42

Cover crop 41,817.83 47,331.51 970,886.99

% change -22.29 -17.18 -1.18

23 Baseline 170,780.14 623,550.71 7,812,374.37

Cover crop 165,272.36 612,790.28 7,788,234.26

% change -3.23 -1.73 -0.31

Table 32. Cover Crop Treatment Efficiency Results in Percent at the Subwatershed level, Tippecanoe Watershed.

Subwatershed

Sediment (in short tons) TP (in lbs) TN (in lbs)

19 Baseline 124,082 867,469 14,102,017

Covercrop 117,937 850,727 13,451,474

% change -5.0 -1.9 -4.6

30 Baseline 13,303 109,721 2,379,021

Covercrop 10,644 83,631 1,401,823

% change -20.0 -23.8 -41.1

34 Baseline 46,706 83,358 873,397

Covercrop 30,093 56,904 542,834

% change -35.6 -31.7 -37.8

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Table 33. Cover Crop Treatment Efficiency Results in Percent, Driftwood Subwatersheds.

Corn – Soybean Tillage Practice Subwatershed HRU (acres)

Nitrogen Percent Reduction

Phosphorus Percent

Reduction

No-till Corn & Drilled Soybeans

3 39 (2980) 11 10

8 103 (1,363) 6 8

Conventional Tillage of Corn & Soybeans

8 102 (8,031) 8 53

23 227 (607) 47 33

23 228 (438) 25 15

23 229 (643) 47 33

23 230 (345) 36 30

Conventional Till Corn & No-till Drilled

Soybeans

3 38 (3801) 28 19

3 40 (3,439) 22 18

3 41 (3,311) 25 18

23 231 (578) 26 18

23 232 (1,168) 27 16

Table 34. Cover Crop Treatment Efficiency Results in Percent, Tippecanoe Subwatersheds.

Corn – Soybean Tillage Practice Subwatershed HRU (acres)

Nitrogen Percent Reduction

Phosphorus Percent

Reduction

No-till Corn & Drilled Soybeans

19 212 (16,793) 31 19

19 213 (10,574) 23 15

19 216 (6,370) 12 5

30 291 (17,525) 20 22

34 330 (2,105) 21 16

34 336 (4,463) 23 9

Conventional Tillage of Corn & Soybeans

19 217 (3,171) 35 19

30 292 (6,546) 21 19

30 293 (11,438) 34 14

34 331 (4,674) 35 22

34 334 (1,896) 34 22

34 335 (2,459) 36 24

34 337 (3,673) 33 22

Conventional Till Corn & No-till Drilled

Soybeans

19 214 (5,850) 42 41

19 215 (8,409) 50 40

30 290 (23,325) 53 48

34 332 (7,983) 46 44

34 333 (4,516) 45 44

3.8.3 No-till Residue Treatment Efficiency Results

The subwatershed treatment efficiency results for no-till residue management in the Driftwood subwatersheds are given in Table 35 and Table 36. Many forms of residue management exist. The no-till, ridge-till and strip-till management systems all leave substantially more residue on the field than mulch till (typically chisel plowing once and minimal disc passes) or conventional moldboard plow. Moldboard plowing, a form of conventional tillage, typically leaves less than 5 percent residue on the field.

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Table 35. No-till Residue Management Treatment Efficiency Percents at the

Subwatershed level, Driftwood Watershed.

Subwatershed

Sediment (in short tons) TP (in lbs) TN (in lbs)

3 Baseline 47,523.19 46,417.47 606,466.57

Residue 44,038.62 41,952.67 651,088.95

% change -7.33 -9.62 7.36

8 Baseline 53,811.47 57,150.39 982,454.42

Residue 47,686.51 51,264.50 1,086,082.03

% change -11.38 -10.30 10.55

23 Baseline 170,780.14 623,550.71 7,812,374.37

Residue 168,340.21 617,180.62 7,958,735.41

% change -1.43 -1.02 1.87

Table 36. No-till Residue Management Treatment Efficiency Percents at the

Subwatershed level, Tippecanoe Watershed.

Subwatershed

Sediment (in short tons) TP (in lbs) TN (in lbs)

19 Baseline 124,082 867,469 14,102,017

Covercrop 117,937 850,727 13,451,474

% change -5.0 -1.9 -4.6

30 Baseline 13,303 109,721 2,379,021

Covercrop 10,644 83,631 1,401,823

% change -20.0 -23.8 -41.1

34 Baseline 46,706 83,358 873,397

Covercrop 30,093 56,904 542,834

% change -35.6 -31.7 -37.8

Residue management alters the hydrologic pathway of the precipitation. The residue on the field traps more rainfall and snowmelt on the field slightly increasing the infiltration. An increase in nitrogen loading is observed. High residue management also is shown to increase nitrogen loading in both watersheds. Nitrogen is a soluble parameter and increased infiltration associated with high residue tillage can increase the drainage tile loading of nitrates (Pennsylvania State University, 1996).

The results of evaluating the range of phosphorus reductions at the HRU level in the Driftwood subwatersheds are provided in Table 37. The field delivery to streams ranges from 11 to 15 percent. The average reduction is 12.6 percent with a standard deviation of 1.2 percent. The area weighted mean is 10.3 percent. A conservative estimate for phosphorus reductions would be 10 percent.

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Table 37. No-till Residue Management Treatment Efficiency Results in Percent, Driftwood Watershed.

Corn – Soybean Tillage Practice Subwatershed HRU (acres)

Nitrogen Reduction (Percent)

Phosphorus Reduction (Percent)

Conventional Tillage of Corn & Soybeans

8 102 (8,031) -7 11

23 227 (607) -2 13

23 228 (438) -3 12

23 229 (643) -1 11

23 230 (345) 0 15

Conventional Till Corn & No-till Drilled

Soybeans

3 38 (3801) -9 12

3 40 (3,439) -7 12

3 41 (3,311) -2 13

8 104 (9,953) -10 13

8 105 (1,845) -5 14

23 231 (578) -5 12

23 232 (1,168) -5 13

3.8.4 Estimation of the Watershed Potential Reductions in Nitrogen and Phosphorus

Agricultural credit supply can be estimated using the nutrient reduction estimates, number of row cropped acres and a typical loading rate. The 2008 National Land Cover Data Set was used to supply estimates of corn and soybean acres within each 8-Digit HUC. This data is provided in Table 38. The number of producers that are willing to participate further reduces the number of acres enrolled. A low end range of estimates is provided based on 10, 25 and 35 percent producer involvement. This limitation is applied for three main reasons: 1) not every producer is willing to participate in WQT programs, 2) not every acre in the watershed is capable of generating the load rates identified from this analysis, and 3) the lower estimate of participation better reflects a mature WQT program selection process targeting sites that provide higher credits per dollar.

Using the SWAT model estimates of current per acre loading, confirmed by comparisons with regional studies (USGS, 1997), (Smith, 2008) the TN loading for row crop agriculture can be conservatively estimated at 30 lbs TN /acre (33.6 kg TN /ha) and 3 lbs TP/acre (3.4 kg TP/ha).

Estimation of the volume of credits that can now be generated based on the pound per acre reduction potential. The three BMPs evaluated demonstrate that a BMP exists that will provide substantial watershed reduction potential by using only a fraction of the row cropped land within the watershed. The following estimates have not assigned a baseline condition or a trade ratio. Therefore, these are reported to provide the potential to supply agricultural NPS credits. The full trade ratio and baseline discussion will follow in later sections. The BMP evaluation summary of credits (i.e., pounds per acre without considering baselines or trade ratios) is as follows:

Filter strips: Approximately 240 TN credits and 26.4 TP credits. A filter strip acre serves 40 acres of row crop (SWAT 2009 default application). The nitrogen reduction credit is based on 30 lbs TN/acre of runoff at 20 percent treatment efficiency serving 40 acres. The phosphorus reduction

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credit is based on 3 lbs TP/acre runoff loading treated at a 22 percent efficiency serving 40 acres.

Table 38. Annual Nutrient Load Reduction Potential, Wabash River Watershed 8-digit HUC Subwatersheds.

(Assuming a 10 and 25 Percent Participation of Agricultural Row Cropped Acres, 20 Percent Reductions, and 40 lbs TN/acre and 3 lbs TP/acre Loading Rates.)

Assuming 20% Removal and 10% Producer

Participation

Assuming 20% Removal and 25% Producer

Participation

Wabash River Watershed

8-digit HUCs Corn1 Soybeans

1

Total Corn and

Bean Acres

TN Reduction

TP Reduction

TN Reduction

TP Reduction

Patoka 60,230 48,101 108,331 64,999 6,500 162,497 16,250

Eel 157,185 173,854 331,039 198,623 19,862 496,559 49,656

Mississinewa 145,656 187,385 333,041 199,825 19,982 499,562 49,956

Tippecanoe 507,145 310,764 817,909 490,745 49,075 1,226,864 122,686

Middle Wabash-Little Vermilion

495,346 407,851 903,197 541,918 54,192 1,354,796 135,480

Sugar 181,053 168,888 349,941 209,965 20,996 524,912 52,491

Embarras 507,303 493,372 1,000,675 600,405 60,041 1,501,013 150,101

Upper East Fork White

119,568 135,259 254,827 152,896 15,290 382,241 38,224

Lower White 158,550 173,803 332,353 199,412 19,941 498,530 49,853

Middle Wabash-Deer 183,536 115,514 299,050 179,430 17,943 448,575 44,858

Little Wabash 287,852 369,529 657,381 394,429 39,443 986,072 98,607

Upper White 347,017 402,364 749,381 449,629 44,963 1,124,072 112,407

Wildcat 197,126 168,787 365,913 219,548 21,955 548,870 54,887

Lower East Fork White

85,544 81,640 167,184 100,310 10,031 250,776 25,078

Eel 144,053 148,398 292,451 175,471 17,547 438,677 43,868

Vermilion 380,112 317,559 697,671 418,603 41,860 1,046,507 104,651

Upper Wabash 272,719 319,122 591,841 355,105 35,510 887,762 88,776

Muscatatuck 79,822 112,163 191,985 115,191 11,519 287,978 28,798

Flatrock-Haw 133,588 133,083 266,671 64,999 6,500 162,497 16,250

Middle Wabash-Busseron

333,446 286,934 620,380 198,623 19,862 496,559 49,656

Skillet 101,355 154,546 255,901 199,825 19,982 499,562 49,956

Lower Wabash 232,214 183,031 415,245 490,745 49,075 1,226,864 122,686

Salamonie 95,113 131,535 226,648 541,918 54,192 1,354,796 135,480

Driftwood 196,508 218,206 414,714 209,965 20,996 524,912 52,491 12008 National Land Cover Data Set

Cover Crops: Approximately 3.6 TN credits and 0.3 TP credits. The nitrogen reduction credit is based on 30 lbs of TN/acre runoff treated at 12 percent efficiency. The phosphorus reduction credit is based on 3 lb TP/acre treated at 10 percent efficiency.

No-till Residue: Approximately 0.3 TP credits. One acre of moldboard plow conversion to no-till residue management practices increases nitrogen loading to the watershed. However, in phosphorus limited freshwaters this practice provides similar results to that of implementing

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cover cropping. The phosphorus reduction credit is based on 3 lb TP/acre treated at 10 percent efficiency.

Potential agricultural credit supply is provided in Table 38. The table is based on availability of BMPs that supply a 20 percent reduction of the 30 lbs TN/acre rate and a 20 percent reduction of the 3 lbs TP/acre. The acreage considered in the estimate of supply is limited to 10 or 25 percent of corn and soybean acres in the watershed.

In summary, the amount of potential to reduce agricultural row crop nonpoint source nutrient loading is ample. The forecasted potential for nutrient reductions is based on very conservative estimates. The conservative assumptions include:

The ability to generate 20 percent reductions across the watershed is predicated by:

1. The BMPs options available are many times greater than those assessed

2. The variability within each BMP assessed indicates that even the poorer performing BMPs have substantial opportunities to outperform the conservative estimates if placed in the right setting

3. Field scale calculations, based on site-specific information, combined with a targeting framework in the WQT program will prioritize site selection

Agricultural land management other than corn and soybean acres can be used to generate credits

Estimate of nutrient runoff loading rates agrees well with regional research

Low producer participation levels used to generate cumulative numbers

The expected availability of load reduction to generate WQT credits is higher than Table 14 indicates.

3.9 Potential stakeholder participation

3.9.1 Water Quality Trading Feedback: Regulated Point Sources

On September 21, 2010, CTIC presented information on the project to approximately 60 participants at the Indiana Water Environment Seminar. With assistance from the Project Team, CTIC developed a survey to assess those wastewater treatment plant representatives’ knowledge, perceptions and opinions on water quality trading.

On Jun 14, 2011, CTIC sent emails to 24 of those present at the seminar, asking each to respond to the survey electronically.

On July 11, 2011, CTIC contacted these same 24 waste water treatment plant representatives with a reminder to complete the online survey. Twenty-four percent of those surveyed responded. Appendix E contains the survey questions and responses.

Duke Energy submitted the following statement regarding water quality trading:

Duke Energy endorses the concept of water quality trading. This tool can be an important option for nutrient standard compliance in the future. Municipalities, utilities, other dischargers, and agriculture could potentially benefit greatly with this program by keeping costs low and improving water quality and the environment. Duke

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Energy will continue to be engaged by offering expertise and monitoring the progress of the issues associated with water quality trading.

3.9.2 Water Quality Trading Feedback: Farmer Focus Group

On March 25, 2011, CTIC held a farmer focus group meeting in Greenfield, IN which lies in the Driftwood River watershed. Fifteen farmers, agribusiness, agriculture media and watershed group representatives attended. Jim Klang of Kieser and Associates, LLC presented information on water quality trading and fielded questions from the group.

Questions asked at the focus group and the associated answers are presented below.

Q: How will water quality be measured if farm ground is split between two watershed boundaries?

A: This will be specified by those developing the program.

Q: Many farmers have at least some best management practices in place. How can the farmer benefit from those practices previously implemented?

A: This will be specified by those developing the program.

Q: Would pollution control agencies require/drive a program such as this? What is the Indiana Department of Environmental Management’s incentive to support a program like this?

A: The federal Environmental Protection encourages states to develop nutrient standards for water quality. Some states have approved nutrient management standards, such as Wisconsin, which has approved nutrient standard for lakes. The Indiana Department of Environmental Management has not developed nutrient management standards, nor has the Illinois Environmental Protection Agency.

Q: How will urban pollutants be addressed? At what watershed scale (hydrologic unit code) can these programs work?

A: This will be specified by those developing the program. The program should be built to avoid “hot spots.”

Q: If farmers are upstream of the regulated facility, can they sell credits?

A: Most likely. This will be specified by those developing the program.

Q: Is there a program such as this in place in Indiana?

A: Not at this time.

Q: What are the regulated facilities expecting with regard to a program like this? Are they ready to talk about a program like this in real terms?

A: Many regulatory agencies are watching how existing programs function, because they expect nutrient standards will be imposed in the future.

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Questions posed to the audience:

Q: Are you comfortable with the environmental protection aspect of a program such as this?

A: It depends on the accuracy of the models that measure water quality results.

Q: Who are you comfortable with coming onto your land to check best management practice performance?

A: Crop consultants or USDA Natural Resources Conservation Service representatives.

Q: Would you be comfortable with a requirement that directs management practice inspection?

A: If the inspection process is transparent. For example, the farmer needs to know exactly what will be assessed. Farmer costs related to inspections should be known.

4. Putting It All Together – Market Analysis and Trading Considerations

This section synthesizes the information presented in Section Two and provides a summary of findings and recommendations related to overall WQT market feasibility in the Wabash River watershed.

4.1 Pollutant Loads

The timing of upgrades, design capacity of the facility, and treatment technologies selected are important factors that determine the economic and performance capability for point source entities to become credit generators. Therefore, while there is a strong potential for point source to point source trading to be effective in the Wabash River watershed a more detailed assessment of options based on the newly required effluent limits will be necessary.

4.2 Regulatory Drivers

As discussed in Section 3.1.1., Indiana’s current water quality standards and nutrient permit limits provide a regulatory incentive for trading based only on TMDLs developed to protect the narrative water quality standards. However, the regulatory forecast for numeric nutrient criteria indicates that nutrient criteria will emerge within the next decade. These effluent limits will likely affect permit limits once these new standards are approved. Knowing these regulatory changes are likely to occur within the next 3-5 years, stakeholders do have a strong reason to consider water quality trading now as a potential tool for achieving permit limits in the future.

4.3 Trade Ratios

A load reduction from one source, at a remote location, must provide equal or greater environmental protection for the water resource. A watershed understanding aids the WQT managers when developing a program. For example, an understanding of the natural nutrient attenuation that occurs on the land and in the streams, lakes and rivers prior to reaching the protected water resource allows appropriate factors to be considered. A trade ratio refers to an explicit factor that is applied to either or both the

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buyer and seller. According to the Water Quality Trading Toolkit for Permit Writers development of trade ratios should consider the following elements when being developed:

Location Factors and/or Delivery Ratios: address the differences in attenuation of nutrients when discharges occur at spatially different points. A location factor addresses the attenuation of the nutrients being traded between the buyer’s or seller’s discharge point and the downstream water resource being protected. A delivery ratio addresses the attenuation that occurs between the buyer’s and seller’s discharge points when the seller is upstream.

Equivalency Factors: address the differences in environmental stress that slight differences in discharged pollutant forms or interaction between multiple stressors have on a water resource. For instance, in nutrient trading a buyer may discharge a higher level of bioavailable phosphorus forms than the agricultural nonpoint source runoff discharge being offered as an offset. Other programs trading to relieve impairments with multiple stressors develop ratios for each stressor based on how the parameters interact within that specific watershed setting.

Uncertainty Factors: address the introduced variability, errors and lack of understanding that WQT programs work with on a daily basis. Uncertainty occurs from many sources. A few main components that introduce uncertainty into WQT transactions are: 1) from analytical errors when collecting and testing water quality samples, 2) from stochastic variability in discharger loading, climatic events and nonpoint source settings, 3) credit estimation tools, such as models, that introduce simplifications of the real world, and 4) errors in watershed understandings within the current day best available science.

Policy Factors: address the socio-political elements watershed and WQT decisions makers implement to address equity issues, incentivize good behavior, advance watershed goals or provide disincentives for less desirable practices.

Addressing these components can be done by assigning one or more factors to the buyer and others to the seller or as a block in one trade ratio. The Ohio EPA Water Quality Trading Rules3 require point source to point source trading to use a ratio where “one pound of pollutant reduction equals one pound of water quality credit for that pollutant”. For nonpoint source generated credits for point source discharges the trade ratio must be:

1) When there is not an approved TMDL, be calculated using a trading ratio where two pounds of pollutant reduction equals one pound of water quality credit for that pollutant; or

2) When there is an approved TMDL, be calculated using a trading ratio where three pounds of pollutant reduction equals one pound of water quality credit for that pollutant.

The rules also allow the director to consider or impose other alternative trade ratios based on watershed, habitat restoration or other considerations.

The draft Water Quality Trading Rules in Minnesota4 quantified phosphorus based risk trade ratios. The Minnesota Pollution Control Agency (MPCA) defined the risk trade ratio as a factor that addresses the total of all risks associated with trading. The point source to point source trades when dealing with an upstream seller are to use a one credit sold to 1.1 credit purchased ratio. For downstream sellers the

3 Ohio EPA Division of Surface Water OAC Chapter 3745-5 Water Quality Trading; available at

http://www.epa.ohio.gov/dsw/rules/3745_5.aspx 4 Minnesota Pollution Control Agency Draft Water Quality Trading Rules and Statement of Needs and Reasonableness; available

at: http://www.pca.state.mn.us/index.php/water/water-permits-and-rules/water-rulemaking/water-quality-trading-rule-development.html#draftrule

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ratio increases requiring 1.4 credits to be purchased. For nonpoint source generated credits the risk trade ratio is one credit sold to 2.5 credits purchased. In addition, every trade shall include an environmental factor (a policy factor) where the buyer must purchase an additional ten percent of credits that are not available for use.

These states are examples of regulatory authorities that have evaluated their watershed settings and the potential beneficial use of WQT for achieving the water quality protection goals. The state then created the more simplified method of a combined trade ratio to roll out watershed implementation when using WQT.

4.3.1 Location Factors and Delivery Ratios

The location factors and delivery ratios are watershed specific attenuation coefficients. The need to use a location factor and/or delivery ratio also depends on the methods used to define the environmental credit value. Upland delivery ratios may be necessary if the load reduction estimation tools do not predict an edge of field result or the fields being credited are not adjacent to waterbodies. Channel attenuation addressed by delivery ratios (assimilation losses between upstream credit generators and downstream buyers) may not be required if the WQT program addresses losses via a location factor for both the buyer and seller. Because an actual WQT framework is not set the location factor method will be used in the feasibility evaluation.

This section explains the method used to determine the WQT location factor for each watershed. The location factor is determined by applying values of nutrient loading predicted by the USGS SPARROW model results (USGS, 2009). The model estimates the fraction of incremental nutrient load delivered to the Gulf from upstream watersheds. Incremental loading is defined as the amount of Nitrogen/Phosphorus generated in an individual watershed that arrives at the Gulf of Mexico. This percentage can be used to determine location factors for each watershed and can assist programs attempting to protect both the Gulf of Mexico and upstream waters.

As water travels downstream, interaction with the surroundings causes nutrients to be naturally removed from the stream. Water entering streams near the Gulf has less time to interact with its surroundings than water entering farther upstream. In most cases, the percentage of nutrients that reach the Gulf is higher for water that enters streams near the Gulf compared to water that enters upstream watersheds. However, the SPARROW model sometimes predicts that a downstream watershed has a lower percentage of delivered incremental loads than an upstream watershed. This could be caused by error in the model or individual watershed characteristics, including lakes, wetland impoundments, and poor hydrologic connectivity in the local watershed. Such characteristics allow more nutrients to be assimilated than would otherwise occur in the stream channel. In order to conservatively represent the most restrictive watershed, all of the best-fit lines were adjusted down to include the lowest incremental watershed results. This reduced the risk of creating nutrient hotspots by applying a more conservative location factor that did not overestimate natural attenuation in any watershed. According to Bill Franz5, U.S. EPA Region V, project manager for the SPARROW modeling, U.S. EPA contracts with USGS a 12-digit HUC output from SPARROW will be available in 2011. This will allow finer resolution to be applied using this technique.

Figures 1-17 graphically show how the SPARROW data was adjusted to determine the location factor. The percentage values provided by the SPARROW model are fitted with a trend line (y1) that best

5 Bill Franz, personal communication, May 25, 2010, Chicago, IL

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represents the linear nature of the data. If a point is below the best fit line, it is being credited with more natural nutrient attenuation than is actually predicted in that watershed. To correct this characteristic for the mainstem of the watershed and its larger tributaries, the trend line is adjusted down to the lowest point to assure an individual watershed‘s percentage is not over-estimated. The resulting best fit line (y2) provides a conservative estimate of a watershed’s nutrient load delivery.

Within an 8-digit HUC the attenuation factor in subwatersheds is already addressed by the channel process based estimates of SWAT. Prior to the SPARROW update a linear interpolation of the current SPARROW model results could be used. Or to calculate location factors using a step wise process, factors for the subwatersheds can be determined by running the watershed assessment model with multiple scenarios. The scenarios are designed to evaluate the change in loading at the mouth given a change in loading at each subwatershed (entered one at a time).

Review of the SPARROW data indicates the maximum phosphorus attenuation rate between Wabash 8-digit HUC watersheds is 49 percent; total nitrogen maximum is 44 percent. Both of these maximums occur when the Salamonie River loading travels to the confluence of the Wabash River with the Ohio River. More commonly, headwaters to confluence based loading losses are approximately 20 percent. Based on these tables, for the purposes of evaluating feasibility the near-field trading will apply a 10 percent location factor and far-field transactions are assigned a 25 percent factor. This reflects the midrange of possible values for each situation.

4.3.2 Equivalency Factors

Equivalency factors address a generated credit reduction providing the same level of stressor impact relief on the water body being protected. This includes addressing potential differences in nutrient bioavailability. This feasibility study provides an in depth review of the potential for differences between buyer and seller’s discharged nutrients and the characteristics affecting nutrient bioavailability in each.

Phosphorus:

While it is possible for a WQT program to require statistical sampling of discharges to determine their bioavailability this may not be cost effective or necessary. Instead an understanding of the forms of phosphorus discharged and the percentages within the total phosphorus discharged can inform the bioavailable estimate. NPS runoff may be assessed using this same breakdown. Addressing fresh water eutrophication in the Midwest is a concern of many states. The Minnesota legislature pursued a desire to better understand the stressors that lead to eutrophication by commissioning a report entitled “Detailed Assessment of Phosphorus Sources to Minnesota Watersheds”. The oversight task was assigned to the Minnesota Pollution Control Agency. This study contained a technical memorandum that defines the expected variability of phosphorus bioavailability found in different sources (Barr, 2004). The memorandum results are summarized in Table 1 below.

Bioavailability equivalence can be determined by dividing the bioavailability of the two sources to achieve a ratio. The denominator of the ratio is the equivalence fraction of the buyer discharge. This ratio can then be used to provide the WQT program with an equivalence discount factor. Table 1 indicates the most likely estimate of phosphorus bioavailability of a source, as well as, the range of expected variability. Combining the finding in Table 39 creates a list of probable equivalency factors. The equivalency factors for various trades are provided below:

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Point source to point source domestic WWTPs trades is 85.5 / 85.5 or 1.0 with the likely range of variability in these transactions is expected to be plus or minus 10 percent

Equivalence factor in point‐point domestic WWTP selling to industrial WWTP trades is 85.5 / 88 or 0.97 with a likely range of variability of approximately 15 percent

The equivalence factor in domestic point source and agricultural nonpoint sources (fertilizer based) trades are 58 / 85.5 or 0.68 with a range of expected variability of approximately 20 percent

The equivalence factor in industrial point sources and agricultural nonpoint sources (fertile based) is 58 / 88 or 0.66 with a likely range of variability of approximately 25 percent

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Table 39. Estimates of phosphorus bioavialability fractions for specific source categories.

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For agricultural row cropping sites that have a historic manure application rate greater than agronomic recommended rates forms of phosphorus have higher fractions of bioavailability. The recommended factors are:

Domestic wastewater point source with ‐ agricultural nonpoint; 80 / 85.5 or 0.94 with a likely variability of 10 percent

Industrial point source and agricultural nonpoint sources; 80 / 88 or 0.91 with a likely variability

of 25 percent

The range of variability is also presented. However, in a WQT program that has multiple buyers and sellers the range of likely variability of the program can be expected to decrease. The weighted average of bioavailability fractions from a source type will begin to converge towards the most likely value provided by the thorough review of research studies.

Nitrogen:

Bioavailability of Total Nitrogen (TN) can also be characterized by understanding the forms of nitrogen in the discharges. TN consists of dissolved and particulate nitrogen forms. However, nitrogen forms are further subdivided into inorganic and organic forms of dissolved and organic nitrogen. The dissolved inorganic nitrogen (DIN) forms (NO2, NO3 and NH4) are 100 percent bioavailable (Berman and Chava, 1999). However, independent study findings regarding the bioavailability of organic nitrogen, dissolved inorganic nitrogen (DON) and particulate organic nitrogen (PON) result in a wide range of results. The predictability of bioavailability ranges becomes more difficult due to the aquatic life response varying substantially from setting to setting. This variability may be, in part, due to how bioavailability testing is based on algal bioassays (Seitzinger et al., 2002). DON in freshwater riverine systems was historically thought to be only available to bacterial uptake rather than direct algal uptake. When considering the Wabash and Mississippi River settings research is further complicated by the limited laboratory or bioassay testing methods being applied – these laboratory tests are run over a three week incubation period (Urgun-Demirtas et al, 2008)(Berman and Chava, 1999). The nutrient spiraling occurring in the Mississippi Basin can occur over a substantially longer time period. These systems have trading options both longer and shorter than this lab period.

Research indicates that humic systems release more of the DON than previously thought, when studied across a summer period. Up to 20 percent of the DON can be photoammoniafied (Bushaw, 1996 and Dagg and Breed, 2003). Near field trading programs may trap DON and PON for a larger periods of time (e.g., when summer low flow pools develop) exposing the DON and PON to photochemical breakdown, zooplankton grazing and bacterial uptake resulting in NH4-N or NO3release. Summarizing these studies, nonpoint source DIN is assumed to be 100 percent bioavailable while DON and PON collectively can be conservatively estimated at 20 percent bioavailable across the summer period. This is a conservative estimate as it does not account for the bacterial and zooplankton uptake.

Nonpoint Source Dominated Stream Considerations

Research indicates a broad range of ratios comparing stream total nitrogen to DON. Seitzinger et al. indicated a literature review ranging from 10 to 80 percent (Seitzinger et al, 2002). Assessing the cropping and pasture runoff forms must consider the pathway of the nitrogen loading. Surface runoff is generally made up of a high fraction of organic nitrogen while tile water and groundwater recharge to the stream consists primarily of DIN. A reach’s unique loading ratio of tile and surface runoff determine the bioavailability. According to Goolsby et al. (USGS, 1999) the Wabash River mainstem has a 63

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percent DIN and 37 percent DON make up from 1980 to 1996. Combining these two assessments, the stream fractions of inorganic and organic and bioavailability of each, the total nitrogen bioavailability of crop and pasture sources can be conservatively estimated (i.e., the crop ratio of DON to TN will be lower than the River mainstem fraction. DIN bioavailability (63 percent times 100 percent bioavailable) plus organic nitrogen bioavailability (37 percent times 20 percent bioavailable) equals approximately 70 percent of the total nitrogen that is bioavailable in the system.

Wastewater Effluent Nitrogen Bioavailability

Determining the bioavailability of WWTP nitrogen must also be done. Assessing the same forms of nitrogen (e.g., particulate and dissolved and further subdivided into inorganic and organic) the inorganic fractions are assumed to be 100 percent bioavailable. Literature indicates from review of data from WWTPs that secondary effluent WWTPs that denitrify have DON percentages around 10% of the total nitrogen discharged (Pehlivanoglu, 2004). However, advanced treatment with low nitrogen below 3 mg/l increases the fraction of DON in the total nitrogen to be 40 to 50 percent of total nitrogen (Chandran, 2010). These values indicate approximately 92 percent of the discharged secondary effluent is bioavailable. A conservative assumption for the secondary plants would therefore be 90 percent bioavailable. BNR facilities would have a 60 percent bioavailable fraction.

4.3.3 Uncertainty Factors

The introduced uncertainty must be addressed to ensure WQT programs are as protective of the environment as onsite upgrades at the treatment facility. Methods to address the uncertainty include assigning a high conservative margin of safety to assure all factors are addressed. However, this can be costly and may eliminate the economic value of trading. Another approach is to assess the range of variability of the crediting method itself. This includes assessing variability in the input factors, the possible errors or variability possible when running the crediting estimation method, and the trade ratio components.

With today’s computing power a WQT program can run a jackknifing or Monte Carlo statistical test relatively inexpensively. Jackknifing tests inform program managers by removing the variability in key inputs one at a time and checking for response sensitivity. Monte Carlo assessments assign a range of variability and standard deviation for each input and begin simulation runs using expected values for inputs. Then large series of simulations (e.g., 10,000) are run using a randomly generated list of inputs using the defined range of variability for each as limiting conditions. These tests inform the WQT managers on the range of and probability of canceling or compounding errors. These tests can also be used with a sensitivity analysis to inform a manager which inputs need the most attention to detail. If a credit estimation result is very sensitive to a single parameter and field testing of that parameter is inexpensive (e.g., $15 soil phosphorus test) then a field protocol can be instituted that will decrease the introduced uncertainty. Otherwise a margin of safety is provided to address the introduced uncertainty.

It is important to consider that WQT is not a watershed diagnostic tool, it is a flexible compliance alternative. As such the methods used to set NPDES permit limits prior to WQT implementation can be used to inform the WQT program. Assumptions made in TMDLs, existing watershed planning work and modeling all can be used to guide the decisions for addressing uncertainty. WQT programs may experience a bias that the results of WQT must be iron clad, when the NPDES permit process itself is based on numerous assumptions or simplifications reflecting the best available science. As such to maintain cost-effective alternatives the WQT program managers should work to minimize the use of

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overly conservative uncertainty factors. This includes recognition of the conservative assumptions used in the credit estimation method itself. For instance the Region V model or STEP-L field reduction calculators used in the Midwest only credit sediment attached nutrients. These models do not credit soluble nutrient loading reductions. This can be used as an implicit margin of safety within the program.

For this feasibility assessment the point source loading is based on monitoring. Even though analytical and collection errors may exist, this is the compliance attainment regulatory measurement method. As such no uncertainty factor is necessary. Nonpoint source credit generation experiences possible introduced uncertainty in the estimates of field loading and reduction.

Direct margins of safety are necessary for the credits estimates of base loading and potential for reduction:

As discussed in Section 3.7, the estimates of loading from SPARROW are extremely well justified, a 10 percent factor is to be used for this input component when developing the uncertainty factor.

The BMP reduction estimates are based on averages within the subwatersheds; this is an implicit margin of safety. However, limitations in input data availability require the consideration of additional margins of safety. The evaluation will apply an additional XX percent uncertainty factor for this component due to modeling limitations.

The prior factors are considered as direct margins of safety applied to loading predictions. The following components are discussed recognizing that for trade ratio applications the margin of safety is being applied to a discount factor. These trade ratio factors are multipliers of the load reduction estimate. As such a margin of safety on the discount factor must consider the introduced error or uncertainty, and the magnitude of the reduction in credit value the factor applies. For example, a discount factor is applied linearly within the crediting method. This factor introduces variability with a maximum range of 25 percent. The expected value of the discount factor is 20 percent. Therefore, the maximum introduced variability is 25 percent of 20 percent; an uncertainty factor value of 5 percent can be considered sufficient.

The bioavailability factors are based on conservative estimates from peer reviewed literature. These factors have a typical maximum range of plus or minus 10 percent variability from the expected value. The bioavailability factors for nonpoint source trading introduce a maximum discount of 38 percent. Ten percent of this discount is approximately 4 percent.

Location factors developed are based on the SPARROW model (USGS, 2008) for far-field estimates and on the implicit algorithms of the SWAT model results already assigned an uncertainty factor above. The far field location factor estimates used in this study are based on Table 2 for TN and Table 3 for TP. The SPARROW model is based on regressions calibrated with water quality and quantity monitoring station data. The range of the 95 percent confidence interval improves as the setting location moves closer in proximity to the Ohio River. As such, the maximum margin of safety for this method is 38 percent for nitrogen and 56 percent for TP. If the watersheds are closer to the Ohio River the results are typically around 10 to 20 percent for TN and 10 to 15 percent for TP. Therefore, for far field trading the median value of 26 percent rounded down to 25 percent for TN and 20 percent for TP is recommended. The reduction from maximum to median is justifiable based on the natural tendency for buyers to look for cost effective solutions. For near field trading, these estimates are based on linear reductions and the fact that Wabash subwatersheds are hydrologically interconnected.

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Therefore, the 10 percent discount factor is recognized to have a maximum rounded value of 50 uncertainty requiring a 5 percent uncertainty factor.

Policy Factors are socio-politically derived and applied after the crediting estimation method. As such no uncertainty factor is required.

The final determination of uncertainty factors considers the individual component factors and solves for a reasonable overall factor considering implicit conservative assumptions and canceling errors. To apply these factors in an easy to use format the results below are discussed by round up to the next five percent mark. Resulting uncertainty factor estimates are as follows:

Loading estimates: 10 percent for SPARROW estimations

Loading estimates: 30 percent for SWAT model estimations

Bioavailability factors: 5 percent

Location factors: 25 percent for far-field and a 5 percent factor for near-field

To account for the probability of self canceling errors using a statistical analysis would require a larger population of credit generation sites than available in this preliminary assessment. The feasibility assessment will use conservative factors to evaluate potential, not to recommend final factors. It is recommended that a multidiscipline advisory committee made up of local experts be used to establish and vet the WQT program framework if chosen. The expected values used in the credit estimation process will depend on the credit estimation tools selected. This credit supply assessment applied methods/tools which are not typical of credit estimation techniques used in the field. Watershed models assess larger areas and inform supply volume potential and attenuation concerns. Field models provide better resolution necessary to factor in site-specific characteristics in order to optimize compliance offset opportunities.

A conservative uncertainty factor based on lack of recognition of self canceling errors and using a compounding uncertainty values the near field trading uncertainty factor at 50 percent and the far-field uncertainty factor at 70 percent.

As stated above the uncertainty with point source to point source trading will only be affected by bioavailability factors (nonexistent for municipal plants trading with municipal plants) and location factor uncertainty of 5 percent for near field and 25 percent for far field.

4.3.4 Policy Factors

Policy factors can include net benefit factors assuring that when allowing the flexible compliance alternative of WQT there is an increased reduction in the pollutant parameter being traded. Other policy factors may be considered by program managers to address equity issues such as cost, incentivize BMPs that provide ancillary benefits such as habitat or target a specific subwatershed over another. In addition, policy factors have been used to bring buyers to the table early in the program as in the Great Miami WQT program6. For this feasibility study a net benefit factor for the water resource will be applied. As illustrated by the MPCA draft WQT rules, a commonly used net benefit factor is ten percent.

6 Miami Conservancy District. Great Miami River Watershed Water Quality Credit Trading Program Operations Manual,

available at: http://www.miamiconservancy.org/water/documents/TradingProgramOperationManualFeb8b2005secondversion.pdf

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The final trade ratio used on the credit supply side will be:

Bioavailability discount factor for phosphorous: 32 percent for sites without heavy manure applications; 6 percent for sites with historically heavy manure application issues.

Bioavailability discount factors for nitrogen: 22 percent for municipal systems achieving secondary treatment requirements (equals one minus the ratio of 70 percent for NPS bioavailability divided by 90 percent bioavailability or secondary effluent)

Near field location factors: 10 percent

Far field location factors: 25 percent

Near field uncertainty factors: 50 percent

Far field uncertainty factors: 70 percent

4.3.5 Supply Trade Ratios

The point source - nonpoint source trade ratio for supply calculations results in a cumulative discount factor of:

Near field trading:

o 92 percent for non-manure related phosphorus locations, and

o 70 percent for phosphorus sites with historically heavy manure applications

o 82 percent for all nitrogen applications

The above near field factors are rounded up to require two pounds of credit purchased for every one pound discharged. The estimated load reduction value will be divided by two.

Far field trading:

o 127 percent for phosphorus non-manure related locations

o 101 percent for phosphorus credits generated at sites with historically high manure applications

o 117 percent for all nitrogen applications

The above far field factors are rounded up to require 2.3 pounds purchased for every pound offset. The estimated load reduction value will be divided by 2.3.

The point source to point source feasibility assessment will be based on:

Near field trading will be 15 percent

Far field trading will be 38 percent (rounded up to 40 percent)

The estimated supply side value will be divided by 1.15 and 1.4 respectively.

4.3.6 Buyer Trade Ratios

The buyer must apply the net benefit policy factor to the purchases of credits. Therefore, every pound of nutrient discharge being offset will require 1.1 pounds of credit purchases.

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4.4 Baselines

Determining when a source is eligible to generate and use credits is an important element of water quality trading. The point at which a source is eligible to participate is referred to as a baseline. Different baselines exist for credit buyers and sellers. According to U.S. EPA’s Water Quality Trading Toolkit for NPDES Permit Writers, baselines are the requirements that a source would be subject to in the absence of water quality trading. For point sources that want to generate and sell credits, the baseline is the point source’s most stringent NPDES permit limit. This can be a water quality-based effluent limit (WQBEL). Point sources that want to buy credits to meet a WQBEL must first achieve a level of treatment equal to their categorical technology-based effluent limits (TBEL). U.S. EPA does not allow trading to meet a TBEL. For nonpoint sources that want to generate and sell credits, methods to establish baselines vary depending on existing rules (i.e., state or local statutes and ordinances) and whether an approved TMDL with a load allocation exists. In the absence of an approved TMDL with a load allocation, nonpoint sources that want to sell credits must first meet state or local requirements. If no state or local requirements exist, a nonpoint source can use existing practices as its applicable baseline (e.g., based on a 3-year history the producer must install an additional best management practice to generate a pollutant load reduction). Baselines have the potential to affect credit supply within a water quality trading market. Rigorous baselines for credit sellers could limit the number of credits available or price the reduction credits beyond the buyer’s range of willingness to pay.

In the Wabash River watershed, there are different potential baselines to consider given the current TMDL, the anticipated changes to water quality standards – and thus, NPDES permit effluent limits – and Gulf of Mexico hypoxia goals. Table 40 summarizes the current load allocations and which will be the required future baselines for nonpoint sources in the Wabash River watershed under Indiana’s existing nutrient benchmarks and potential new numeric nutrient criteria.

Table 40. Current and Potential Future Point and Nonpoint Source Baselines in the Wabash River watershed

Type of Source

Baselines

Under Current Nutrient Benchmarks Potential Under New WQSs Hypoxia Goals TMDL Permits Pre-Attainment Post-Attainment

TN TP TN TP TN TP TN TP TN TP

Credit Sellers

Point Source

No reductions

4% Monitoring Monitoring Permit compliance schedule

Permit compliance schedule

3/5/8 mg/L

0.3 mg/L 45% 45%

Nonpoint Source

No reduction

4% N/A; consider approved WMPs

N/A; consider approved WMPs

Interim baselines

Interim baselines

New TMDL targets

New TMDL targets

45% 45%

Credit Buyers

Point Source

No reductions

4% Monitoring Monitoring Permit compliance schedule

Permit compliance schedule

3/5/8 mg/L

0.3 mg/L 45% 45%

Under the current nutrient benchmarks, the 2006 Wabash River watershed TMDL identifies a four percent reduction in TP and no reductions in TN for tributaries and subwatersheds discharging to the mainstem of the Wabash River. The permits issued to point sources under the current nutrient

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benchmarks contain monitoring requirements for TP and TN; therefore, there is no WQBEL to serve as a point source baseline for water quality trading in the Wabash.

Assuming that there will be changes to Indiana’s WQSs that will result in numeric nutrient criteria, baselines for point sources will change dramatically. Once IDEM adopts new numeric nutrient criteria, this will trigger a change in NPDES permit effluent limits. IDEM will have to reissue NPDES permits to contain WQBELs to meet the new numeric nutrient criteria. The Project Team assumes that new numeric nutrient criteria will result in WQBELs ranging from 3, 5, or 8 mg/L for TN and 1, 0.5, or 0.3 mg/L for TP. Any point sources that want to generate credits will first have to meet this more stringent baseline. It is assumed that reissued NPDES permits will contain a compliance schedule that requires permittees to meet the new WQBELs within the permit period.

Although nonpoint sources are not permitted, changes to Indiana’s WQSs could affect the baseline for nonpoint source sellers, as well. A change in WQSs could trigger the need to modify TMDL targets used to generate the allocations in the 2006 Wabash River watershed TMDL. This would lead to changes in load allocations and nonpoint source targets used in Section 319 watershed management plans. Both of these changes could alter the baseline for nonpoint source sellers.

The 2008 Gulf of Mexico Hypoxia Action Plan provides an additional reduction goal for point sources and nonpoint sources. These reduction goals may serve as a baseline for nonpoint source sellers. How this particular 45 percent reduction goal is implemented, however, could affect the nature of the nonpoint source baseline. It is important to remember that trading offers watershed managers an opportunity to accelerate early implementation of effluent limits and nonpoint source BMPs. A baseline that seems onerous for nonpoint source sellers could deter participation in trading and prevent sources from achieving early water quality improvements. Tailoring the baseline for nonpoint sources in a way that guarantees water quality benefits and promotes participation could create a win-win situation for the Wabash River watershed and the achievement of hypoxia goals. The Wisconsin DNR prepared a WQT framework that recognizes that portions of their required agricultural NPS management requirements are limited by cost share funding resources (WI DNR 2011). The WQT framework recommends WQT funding to be considered an equivalent source of funding. The Ag producer then can generate interim credits for five years to bring the field down to a Phosphorus Index (PI) rating of 6 and long-term credits for reductions beyond the PI rating of 6. For example, a site generates 18 credits per acre to reduce from a PI of 10 down to a PI of 1. The site receives 8 interim credits for five years, and then these credits are no longer eligible for use. The remaining 10 credits can be used indefinitely.

Likewise, IDEM could create a Gulf of Mexico state strategy that provides a time line for interim measurable milestones. The 45 percent goal could be divided into five nine year periods with an additional nine percent reduction goal added each period. The eligibility to generate WQT credits could then use the current interim measurable milestone as a baseline for generation credits. If the first nine years of compliance with the measurable milestone was eligible to generate WQT credits, agricultural producers would be afforded another incentive to protect the Gulf of Mexico.

For trading to take place in some watershed, regulators need to consider adoption thresholds of current requirements and decide if interim milestones are an option. If decision makers prevent WQT credit generation prior to complete attainment of TMDL load allocations (i.e., without allowing for interim measurable milestone goals) then the utility of WQT to advance TMDL implementation will be dampened.

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WQT programs across the nation use several alternatives for setting baseline requirements:

A three or five year cropping history

TMDL load allocation requirements

Local rules and ordinances requiring conservation measures

These baseline considerations are described in narrative and numeric forms. Examples include threshold measures like Phosphorus Index performance in Wisconsin or TMDL implementation plans that describe approved BMP lists.

To create a WQT framework within the Wabash River watershed, a significant effort will need to be invested in identifying appropriate and equitable eligibility requirements. These requirements will need to be vetted and tested for integration into existing programs and policies. For the purpose of this feasibility study, the policies limiting baseline requirement are assumed to be moderately restrictive to show potential supply of credits using a reasonably expected outcome of policy considerations.

4.5 Supply Side Credit Generation

Evaluating implementation and opportunity costs of BMPs is critical for determining the potential economic benefits of WQT and conveying these benefits to wastewater treatment facility representatives and farmers. This section provides the results of an annual payment analysis for three different BMPs. The three BMPs assessed are cover crops, residue management, and filter strips. Each BMP has a different life cycle, each with associated opportunity costs, establishment costs, operation and maintenance (O&M) schedules and replacement costs. To overcome the difference in schedules and pricing a Life Cycle Cost (LCC) analysis was used. The LCC analysis begins with a present worth calculation which provides a present day equivalent cost for each BMP. The present worth analysis considers all expenditures made, including: 1) current investments, 2) annual payments, and 3) one time future payments. This present worth analysis was performed using a three percent inflation factor and a 20-year BMP implementation period, including replacement costs if BMP design life is less than 20 years. The LCC analysis then converts the present worth into a twenty-year annual payment assuming a five percent discount factor.

4.5.1 Determination of Costs

The BMP establishment costs are gathered from the USDA NRCS Indiana payment schedules for the 2011 Environmental Quality Incentives Program (EQIP) program. This farm bill program provides 50 percent of the establishment cost of the BMP and an O&M payment for agricultural conservation. The EQIP payment schedule is provided on a BMP unit cost basis. The cost information for the three BMPs evaluated here are presented on an acre unit basis.

WQT trading is a market based program. The price paid for a credit will be determined by what the market will bear. The buyer desires the lowest cost available but only has control of the maximum payment that will be made. The seller considers the value of the BMP not only for installation cost reimbursement, but also for production goals, quality of life and future opportunities that may be lost if the land is tied up in a contract.

These factors were considered in a report completed for the Great Miami WQT program. A payment comparison between EQIP and WQT was performed by Kieser & Associates, LLC (Kieser & Associates, 2008) for several BMPs common to both programs in the area. The findings indicate that the WQT

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payments are very comparable with the EQIP payments. Still, the market pricing for this robust trading program has ample supply of producers interested in using the WQT program which includes a reverse auction prioritization of proposals. The reverse auction method sets a window of time that the round of BMP proposals will be accepted in. The proposals are submitted and prioritized on a dollar per combined nitrogen and phosphorus credit basis. The lowest unit price proposals are awarded up to the round cap on investment costs. Because the payments made by EQIP and WQT are so comparable, other reasons to participate in WQT programs exist. In addition, a few producers were noted that entered into a WQT contract below the EQIP equivalent payment because the producer desired the BMP for more than monetary reasons. The Kieser report lists several considerations why a producer would select WQT programs instead of EQIP. WQT payments are sometimes more attractive to a producer as transactions can be set up to have more flexibility in the added value uses of the land. For example, WQT provides flexible contract lengths. This gives the farmer the ability to enter and leave the market on their terms. Another benefit is that a producer can sign up a few or all acres into the BMP, while certain EQIP practices specify maximum land enrollment caps for farmers to receive payments. Some BMP’s payment schedules in EQIP end after three years. This period is considered sufficient for transition into practices like No-till. In WQT a high residue practice can be signed up for a much longer-term payment because the focus is on nutrient reduction. Vegetative seed mix requirements are less stringent than those specified by EQIP and allow more flexibility in both planting and uses. For instance a farmer participating in WQT can utilize other added value uses like haying to subsidize BMP costs.

Based on these considerations the economic feasibility determination for WQT in the Wabash watershed will consider a range of annual payments. This will enable the evaluation of market conditions to occur by informing the reader regarding the range and breakpoints to indicate where an adequate supply of nutrient credits exist. The BMP cost schedule will include several scenarios of payments:

50 percent of establishment, plus O&M (equivalent to EQIP payment schedules)

100 percent of establishment costs, plus O&M

100 percent of establishment costs, O&M plus an opportunity cost of $4 per bushel corn

100 percent of establishment costs, O&M plus an opportunity cost of $8 per bushel corn

Costs of lost opportunities are assessed in this analysis by determining the net profit from corn row cropping. Revenue lost is determined assuming a yield of 161 bushels per acre (bu/ac) for corn rotation on fields with average soil productivity (Purdue University, 2011). Corn costs of $4 and $8 per bushel were used to illustrate the fluctuating corn market in recent years (current corn costs of 7.70 $/bu have nearly doubled from 2 years ago). The opportunity cost was evaluated on a per acre basis using 2011 forecasted corn production input costs (Purdue University, 2011).

In addition to these assessments the cost analysis includes a discussion of BMPs installed on marginal riparian lands. It is only in the last decade that many producers have been able to use yield monitors on combines to consider marginal lands differently. Using scales at a grain coop will only provide a producer with an acre average yield. A yield monitor on a combine provides producers and technical service providers real time results. The producer can witness reductions in yield on much smaller strips of land. The marginal land’s yield loss can be due to many reasons; saturated soils, compaction, poor fertility or erosion. The cost analysis for riparian marginal lands in this assessment assumes a 25 percent reduction in yield (121 bu/ac). Based on 2011 input costs, a yield of 121 bushels/acre of corn that sells for $4/bushel will not recoup the cost of the investment. Therefore, investing the land into an alternative crop like supplemental haying, as part of a WQT program, could be more profitable.

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4.5.2 Present Worth Cost Analysis

Using establishment costs, O&M costs, and opportunity costs, the present worth cost of each BMP is determined. Costs are analyzed over a 20-year period, using an inflation rate of 3 percent to project future annual costs. Consistent with costs and production yields discussed above, present worth costs are on a per-acre basis. Present values from all cost categories are calculated and added in order to determine the total present value.

4.5.3 Life Cycle Cost Analysis

The life cycle cost (LCC) analysis for the BMP scenarios provides an estimate of the average annual cost of each BMP. The LCC of each BMP was determined by annualizing the total present worth cost. Considerations in calculating the LCC include installation, replacement, operation and maintenance, and opportunity costs. Installation and O&M costs were referenced from the NRCS 2011 EQIP Payment Schedule7 and from the IN Average Annual Cost Calculator8. A summary of these costs is provided in Table 41. Credit production per acre of BMP was calculated using SWAT model results, BMP treatment efficiencies, and the number of acres treated per acre of BMP. A summary of credits produced per acre of BMP can be seen in

Table 42. An inflation rate of 3 percent and discount factor of 5 percent was included in the annualized life cycle cost. The cost per credit of each BMP was then determined by multiplying the BMP cost per acre by the credits generated per acre. A summary of credits generated per acre and the cost per acre of each BMP scenario can be seen in

Table 43.

Table 41. 2011 Indiana EQIP General Eligible Practices

BMP Scenario

EQIP Payment Actual Cost Life Span O&M Yield Loss

[$/ac] [$/ac] [yr] [%] [bu/ac]

Filter strips (Prime land) 351 702 10 2% 161

Filter strips (Marginal land) 351 702 10 2% 121

Cover Crop 31 62 1 1% -8

Residue Management 21 42 1 0% 6

Table 42. Summary of Credit Production per Acre of BMP

BMP Scenario

Lbs / Acre Treatment Efficiency

Acres Served per BMP Acre

Credits / Acre of BMP

TN TP TN TP TN TP Combined

Filter Strips (Prime) 30 3 0.2 0.22 40 240 26.4 266.4

Filter Strips (Marginal) 30 3 0.2 0.22 40 240 26.4 266.4

Cover crops 30 3 0.12 0.1 1 3.6 0.3 3.9

Residue Management

3

0.1 1

0.3

7 Available at the Indiana NRCS website: http://www.in.nrcs.usda.gov/programs/eqip/2011_EQIP_General_Practice_Details.pdf

8 Available at the Indiana NRCS website: http://efotg.sc.egov.usda.gov//efotg_locator.aspx

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Table 43. Summary of BMP Credit Production and Annualized Life Cycle Cost per Acre

BMP Scenario

Credits / Acre of BMP

Cost / Acre

No Opportunity Cost Opportunity Cost Included

TN TP Combined 50% (EQIP Equivalent) Full Cost $4.00 / bu $6.00 / bu $8.00 / bu

Filter Strips (Prime)

240 26.4 266.4 $59.29 $118.58 $291.79 $704.29 $1,116.79

Filter Strips (Marginal)

240 26.4 266.4 $59.29 $118.58 $85.54 $394.92 $704.29

Cover Crops 3.6 0.3 3.9 $42.60 $85.19 $44.20 $23.70 $3.21

Residue Management

0.3 $28.59 $57.17 $103.29 $126.35 $149.41

3% inflation rate

5% discount factor

Land use not included in LCC analysis

Indiana EQIP payment used as 50% of establishment costs

O&M costs referenced from Indiana EQIP

4.5.4 Filter Strips

Filter strips utilizing warm season grasses have an EQIP payment rate of $351 per acre, corresponding with an actual establishment cost of $702. Filter strip opportunity costs have been analyzed under the following two scenarios: 1) installation on prime farm land (161 bu/ac) and 2) installation on marginal farmland with an associated 25 percent reduction in yield (121 bu/ac). Filter strips have a life span of 10 years and therefore are replaced once during the 20 year time period. They also have a yearly 2% O&M cost. When analyzed assuming installation on prime farm land, the per acre life cycle cost is in excess of $1000 when corn prices are relatively high (See Table 43). However, a filter strip as evaluated by the SWAT model reduces nutrients from 40 acres of land. Therefore, the volume of credits generated will offset the apparently high annual costs. Installation of filter strips on marginal farmland could be more appealing for farmers as planting corn on marginally productive land can result in income losses due to lower yields and the same variable and overhead costs. A summary of annualized life cycle costs per credit for filter strips installed on prime and marginal farm lands can be seen in Table 44 and Table 45 respectively.

Table 44. Summary of Annualized Life Cycle Cost per Credit: Filter Strips (Prime Land)

Payment Scenario

Cost / Credit

TN TP Combined

50% Cost (EQIP Equivalent) $0.25 $2.25 $0.22

Full Cost $0.49 $4.49 $0.45

Full + Opportunity Cost

$4 / bu $1.22 $11.05 $1.10

$6 / bu $2.93 $26.68 $2.64

$8 / bu $4.65 $42.30 $4.19

A filterstrip serves 40 acres of row crop (SWAT2009 default application).

The nitrogen credited reduction is based on the 16 lbs TN/acre at 20 percent treatment efficiency of 40 acres.

The phosphorus credited reduction is based on a 4 lbs TP/acre loading treated at a 22 percent efficiency over 40 acres.

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Table 45. Summary of Annualized Life Cycle Cost per Credit: Filter Strips (Marginal Land)

Payment Scenario

Cost / Credit

TN TP Combined

50% Cost (EQIP Equivalent) $0.25 $2.25 $0.22

Full Cost $0.49 $4.49 $0.45

Full + Opportunity Cost

$4 / bu $0.36 $3.24 $0.32

$6 / bu $1.65 $14.96 $1.48

$8 / bu $2.93 $26.68 $2.64

A filterstrip serves 40 acres of row crop (SWAT2009 default application).

The nitrogen credited reduction is based on the 16 lbs TN/acre at 20 percent treatment efficiency of 40 acres.

The phosphorus credited reduction is based on a 4 lbs TP/acre loading treated at a 22 percent efficiency over 40 acres.

4.5.5 Cover Crops

Cover crops have an EQIP payment rate of $31 per acre, corresponding to an assumed establishment cost of $62 per acre (actual costs vary from site to site). For corn production, implementation of cover crop practices is projected to increase crop yield by 8 bushels/acre (Mannering 2007). Therefore, there is no opportunity cost associated with cover crops when used in continuous corn scenarios. Rather, there is a net gain in crop yields and a subsequent increase in commodity revenue. Cover crops have a life span of 1 year and therefore include a yearly replacement cost, as well as a yearly 1 percent O&M cost. Due to the increase in corn yield, cover crops are an economically viable BMP and therefore an attractive and practical choice for farmers. When analyzed using a relatively high commodity price ($8/bu), the increased corn yield nearly pays for the entire practice cost, yielding an annualized life cycle cost of $3.21 per acre. A summary of annualized life cycle costs per credit for cover crops can be seen in Table 46.

Table 46. Summary of Annualized Life Cycle Cost per Credit: Cover Crops

Payment Scenario

Cost / Credit

TN TP Combined

50% Cost (EQIP Equivalent) $11.83 $141.99 $10.92

Full Cost $23.66 $283.97 $21.84

Full + Opportunity Cost

$4 / bu $12.28 $147.34 $11.33

$6 / bu $6.58 $79.01 $6.08

$8 / bu $0.89 $10.69 $0.82

The nitrogen credited reduction is based on 16 lbs of TN/acre treated at 12 percent efficiency.

The phosphorus credited reduction is based on 4 lb TP/acre treated at 10 percent efficiency.

4.5.6 Residue Management

No-till and strip-till residue management has an EQIP payment rate of $21 per acre, corresponding to an actual establishment cost of $42 per acre. No-till corn has been found to have a 4 percent lower yield than conventional tillage yields. However, no-till corn grown in rotation with soybeans was found to have comparable yields to that of conventional tillage (Purdue 2011). Assuming that the crop is continuous corn, a 4 percent reduction in the 161 bu/ac yield would correspond with a 6 bu/ac yield loss. This practice has a life span of 1 year, requiring a yearly replacement cost. However, there is no

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additional O&M cost associated with the practice. A summary of annualized life cycle costs per credit for residue management can be seen in Table 47.

Table 47. Summary of Annualized Life Cycle Cost per Credit: Residue Management

Payment Scenario

Cost / Credit

TN TP Combined

50% Cost (EQIP Equivalent)

$95.29

Full Cost

$190.57

Full + Opportunity Cost

$4 / bu

$344.30

$6 / bu

$421.17

$8 / bu

$498.03

One acre of moldboard plow conversion to no-till residue management practices increases nitrogen loading to the watershed.

However, in phosphorus limited freshwaters this practice provides similar results to that of implementing cover cropping.

The phosphorus credited reduction is based on 4 lb TP/acre treated at 10 percent efficiency.

4.6 Differences in Control Costs

Economic incentive is a key factor that influences whether WQT is likely to generate participation in a watershed. Without adequate economic incentive, there is no market-based driver for buyers and sellers to engage in a trade. Section 3.6 discusses potential credit demand, including the associated estimated cost per pound of TN and TP reduction through technology upgrades. This information becomes more meaningful when compared to the NPS BMP estimated costs presented in Section 4.5. Tables 48–50 present this cost comparison by size and treatment level.

The information under the median estimated upgrade costs aggregates information found in the upgrade options and cost tables in Section 3.6. It is important to note that the facility size categories of small, medium, and large do not directly align with the size categories used in the upgrade option and cost tables. This is also true for treatment levels. The Project Team used the size ranges and treatment levels most closely related. As a result, the TN treatment level of 8 mg/L in the tables below reflects the upgrade costs associated with a 10 mg/L treatment level used to develop the upgrade estimated costs in Section 3.6.

For purposes of comparison, the NPS BMP estimated costs associated with cover crops and filter strips were used to show a range of BMP costs. This information comes from the annualized life cycle cost per credit tables presented in Section 4.5.

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Table 48. Comparison of Potential Estimated Upgrade Costs and NPS BMP Costs for Small (<.3 MGD) Facilities by

Treatment Level

Treatment Level

Median Estimated Upgrade Costs $/lb

Reduction (Min-Max)

Median NPS BMP Estimated Cost Per $/lb Reduction (Min-Max)

Potential Cost Margin at a 2:1

Trade Ratio $/credit

1

(Minimum Cost of Supply

2) Cover Crop Filter Strips

TP

0.3 mg/L $198.07

($139.79-$256.35) $141.99 ($10.69-$283.97)

$11.05 ($2.25-$42.30)

$175.97 ($193.57)

0.5 mg/L $182.54

(sole value) $160.44

($178.04)

TN

3 mg/L N/A

$11.83 ($0.89-$23.66)

$1.22 ($0.25-$4.65)

N/A

5 mg/L $45.48

($20.53-$70.42) $23.38

($40.98)

8 mg/L $51.50

($15.80-$79.34) $29.40

($47.00)

TN+TP

TN1 (5-10 mg/l) TP2 (<0.5 mg/l)

$40.88 ($28.85-$52.90) $10.92

($0.82-$21.84) $1.10

($0.22-$4.19)

$18.78 ($36.38)

TN2 (<5 mg/l) TP2 (<0.5 mg/l)

N/A N/A

1Potential cost margin determined by doubling the lowest NPS BMP median cost value and subtracting this from the median per

pound estimated cost of the WWTPs. (This reflects a 2:1 trade ratio applied in the WQT program) 2Minimum cost of supply reflects the minimum NPS reduction cost doubled to reflect a 2:1 trade ratio subtracted from the median

per pound estimated cost of the WWTPs.

Table 49. Comparison of Potential Estimated Upgrade Costs and NPS BMP Costs for Medium (.3 MGD – 5 MGD)

Facilities by Treatment Level

Treatment Level

Median Estimated Upgrade Costs $/lb

Reduction (Min-Max)

Median NPS BMP Estimated Cost Per $/lb Reduction (Min-Max)

Potential Cost Margin at a 2:1

Trade Ratio $/credit

1

(Minimum Cost of Supply

2) Cover Crop Filter Strips

TP

0.3 mg/L $39.56 ($13.28-$255.54) $141.99

($10.69-$283.97) $11.05

($2.25-$42.30)

$17.46 ($35.06)

0.5 mg/L $39.92 ($3.62-$160.79)

$17.82 ($35.42)

TN

3 mg/L $5.66 ($1.37-$32.40)

$11.83 ($0.89-$23.66)

$1.22 ($0.25-$4.65)

$3.22 ($5.16)

5 mg/L $8.13 ($2.47-$27.08)

$5.69 ($7.63)

8 mg/L $24.65 ($1.44-$66.44)

$22.21 ($24.15)

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Treatment Level

Median Estimated Upgrade Costs $/lb

Reduction (Min-Max)

Median NPS BMP Estimated Cost Per $/lb Reduction (Min-Max)

Potential Cost Margin at a 2:1

Trade Ratio $/credit

1

(Minimum Cost of Supply

2) Cover Crop Filter Strips

TN+TP

TN1 (5-10 mg/l) TP2 (<0.5 mg/l)

$28.01 ($27.11-$52.73) $10.92

($0.82-$21.84) $1.10

($0.22-$4.19)

$25.81 ($27.57)

TN2 (<5 mg/l) TP2 (<0.5 mg/l)

$5.49 ($3.66-$27.43)

$3.29 ($5.05)

1Potential cost margin determined by doubling the lowest NPS BMP median cost value and subtracting this from the median per

pound estimated cost of the WWTPs. (This reflects a 2:1 trade ratio applied in the WQT program) 2Minimum cost of supply reflects the minimum NPS reduction cost doubled to reflect a 2:1 trade ratio subtracted from the median

per pound estimated cost of the WWTPs.

Table 50. Comparison of Potential Estimated Upgrade Costs and NPS BMP Costs for Large (>5 MGD) Facilities by

Treatment Level

Treatment Level

Median Estimated Upgrade Costs $/lb

Reduction (Min-Max)

Median NPS BMP Estimated Cost Per $/lb Reduction (Min-Max)

Potential Cost Margin at a 2:1

Trade Ratio $/credit

1

(Minimum Cost of Supply

2) Cover Crop Filter Strips

TP

0.3 mg/L $21.67 ($8.50-$40.15) $141.99

($10.69-$283.97) $11.05

($2.25-$42.30)

$0.43 ($17.17)

0.5 mg/L $5.20 ($2.23-$34.88)

-$16.90 ($0.70)

TN

3 mg/L $3.16 ($1.00-$4.43)

$11.83 ($0.89-$23.66)

$1.22 ($0.25-$4.65)

$0.72 ($2.66)

5 mg/L $5.88 (sole value)

$3.44 ($5.38)

8 mg/L $2.27 ($2.01-$3.87)

-$0.17 ($1.77)

TN+TP

TN1 (5-10 mg/l) TP2 (<0.5 mg/l)

N/A $10.92

($0.82-$21.84) $1.10

($0.22-$4.19)

N/A

TN2 (<5 mg/l) TP2 (<0.5 mg/l)

$3.52 ($2.71-$6.17)

$1.32 ($3.08)

1Potential cost margin determined by doubling the lowest NPS BMP median cost value and subtracting this from the median per

pound estimated cost of the WWTPs. (This reflects a 2:1 trade ratio applied in the WQT program) 2Minimum cost of supply reflects the minimum NPS reduction cost doubled to reflect a 2:1 trade ratio subtracted from the median

per pound estimated cost of the WWTPs.

As shown in the Tables 48–50, facilities within the small category (<.3 MGD), have the greatest median estimated upgrade costs across all TN and TP treatment levels. When these median estimated upgrade costs are compared to NPS BMP median estimated cost per pound reduction, it is clear that the potential cost margin is significant, particularly for potential TP treatment levels. These tables also show

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that there are medium and large facilities that could benefit from efficient WQT to meet more stringent permit effluent limits.

To evaluate where WQT might effectively assist with cost effective nutrient reductions within the Wabash River watershed it is helpful to look across the subwatersheds. An evaluation of potential demand comparisons to the potential supply provides a reasonable maximum number of entities that can benefit from participating in WQT. Table 51 and Table 52 compare point source demand and NPS supply for TP and TN by subwatershed.

Table 51. Resulting demand and supply factoring in estimated cost margins for each TP permit effluent scenario

HUC_8 Facility Size

Annual Load Reductions (Tons)

@ 0.3

Annual Load Reductions (Tons)

@ 0.5

Estimated Credit Supply @ 20% Adoption and 2:1 Trade

Ratio (Tons)

05120101

Medium (15) 15.8 13.9

22.2

Small (39) 1.8 1.7

Total (54) 17.6 15.6

05120102

Medium (7) 5.9 5.2

33.9

Small (11) 0.4 0.4

Total (18) 6.3 5.6

05120103

Medium (21) 11.7 10.2

12.5

Small (16) 0.8 0.7

Total (37) 12.5 10.9

05120104

Medium (8) 9.2 8.4

12.4

Small (15) 0.6 0.5

Total (23) 9.8 8.9

05120105

Medium (7) 4.8 4.2

11.2

Small (4) 0.2 0.2

Total (11) 5.0 4.4

05120106 (Tippecanoe)

Medium (18) 15.3 13.5

30.7

Small (28) 0.8 0.7

Total (46) 16.1 14.2

05120107

Medium (10) 6.1 5.3

13.7

Small (16) 1.7 1.6

Total (26) 7.8 6.9

05120108

Medium (11) 18.7 17.3

33.9

Small (8) 0.3 0.3

Total (19) 19.0 17.6

05120109

Medium (13) 15.8 15.0

26.2

Small (30) 0.1 0.1

Total (43) 15.9 15.1

05120110

Medium (2) 0.8 0.7

13.1

Small (8) 0.4 0.3

Total (10) 1.1 1.0

05120111

Medium (22) 41.4 38.7

12.4

Small (23) 0.4 0.3

Total (45) 41.8 39.0

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HUC_8 Facility Size

Annual Load Reductions (Tons)

@ 0.3

Annual Load Reductions (Tons)

@ 0.5

Estimated Credit Supply @ 20% Adoption and 2:1 Trade

Ratio (Tons)

05120112

Medium (20) 15.4 14.3

37.5

Small (36) 0.5 0.5

Total (56) 15.9 14.8

05120113

Medium (10) 10.1 9.2

30.7

Small (17) 0.7 0.6

Total (27) 10.8 9.8

05120114

Medium (12) 21.7 20.6

24.7

Small (25) 0.9 0.9

Total (37) 22.6 21.5

05120115

Medium (5) 3.2 3.1

12.5

Small (10) 0.9 0.8

Total (15) 4.1 3.9

05120201

Medium (62) 45.0 38.4

28.1

Small (79) 2.0 1.8

Total (141) 47.0 40.2

05120202

Medium (15) 22.4 20.5

12.5

Small (22) 1.7 1.6

Total (37) 24.1 22.1

05120203

Medium (13) 8.6 7.9

11.0

Small (15) 0.5 0.5

Total (28) 9.1 8.3

05120204 (Driftwood)

Medium (20) 13.2 11.8

13.1

Small (30) 0.6 0.5

Total (50) 13.8 12.3

05120205

Medium (7) 5.4 4.8

4.1

Small (5) 0.1 0.0

Total (12) 5.6 4.8

05120206

Medium (11) 2.0 1.7

9.6

Small (11) 0.7 0.6

Total (22) 2.7 2.3

05120207

Medium (19) 13.9 12.4

7.2

Small (15) 1.5 1.3

Total (34) 15.4 13.7

05120208

Medium (22) 11.4 9.6

6.3

Small (28) 0.6 0.5

Total (50) 12.0 10.1

05120209

Medium (7) 7.7 7.1

4.1

Small (9) 0.5 0.5

Total (16) 8.2 7.6

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Table 52. Resulting demand and supply factoring in cost margins for each TN permit effluent scenario

HUC_8

Facility Size (# of

facilities)

Annual Load Reduction Estimated Credit Supply @ 20% Adoption and 2:1 Trade Ratio

(Tons) (Tons) @ 3

mg/L (Tons) @ 5

mg/L (Tons) @ 8

mg/L

05120101

Medium (15) 113.7 94.7 66.3 221.9

Small (39) 8.7 7.3 5.3

Total (54) 122.4 102.0 71.6

05120102

Medium (7) 46.3 38.7 27.2

338.7

Small (11) 2.0 1.7 1.3

Total (18) 48.3 40.4 28.5

05120103

Medium (21) 95.7 80.0 56.5

124.9

Small (16) 5.8 4.9 3.4

Total (37) 101.5 84.9 59.9

05120104

Medium (8) 51.6 43.4 31.1

124.1

Small (15) 3.9 3.2 2.3

Total (23) 55.5 46.6 33.4

05120105

Medium (7) 33.9 28.3 19.8

112.1

Small (4) 1.4 1.1 0.8

Total (11) 35.3 29.4 20.6

05120106 (Tippecanoe)

Medium (18) 107.0 89.6 63.7

306.7

Small (28) 8.9 7.4 5.2

Total (46) 115.9 97.0 68.9

05120107

Medium (10) 47.6 39.8 28.0

137.2 Small (16) 7.4 6.2 4.3

Total (26) 55.0 46.0 32.3

05120108

Medium (11) 97.2 83.0 61.7

338.7 Small (8) 2.1 1.8 1.2

Total (19) 99.3 84.8 62.9

05120109

Medium (13) 64.4 56.3 44.2

261.6 Small (30) 0.5 0.4 0.3

Total (43) 64.9 56.7 44.5

05120110

Medium (2) 5.3 4.4 3.1

131.2 Small (8) 2.8 2.3 1.6

Total (10) 8.1 6.7 4.7

05120111

Medium (22) 199.2 171.6 130.0

124.1 Small (23) 2.7 2.3 1.6

Total (45) 201.9 173.9 131.6

05120112

Medium (20) 79.5 68.8 52.7 375.3

Small (36) 2.0 1.7 1.4

Total (56) 81.5 70.5 54.1

05120113

Medium (10) 59.6 50.5 36.7

306.7

Small (17) 3.0 2.6 2.0

Total (27) 62.6 53.1 38.7

05120114

Medium (12) 89.4 78.7 62.6

246.5

Small (25) 4.1 3.6 2.8

Total (37) 93.5 82.3 65.4

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HUC_8

Facility Size (# of

facilities)

Annual Load Reduction Estimated Credit Supply @ 20% Adoption and 2:1 Trade Ratio

(Tons) (Tons) @ 3

mg/L (Tons) @ 5

mg/L (Tons) @ 8

mg/L

05120115

Medium (5) 13.1 11.6 9.3

124.9

Small (10) 3.7 3.2 2.6

Total (15) 16.8 14.8 11.9

05120201

Medium (62) 433.7 362.3 255.2

281.0

Small (79) 16.8 14.0 9.8

Total (141) 450.5 376.3 265.0

05120202

Medium (15) 152.1 133.5 105.4

124.6

Small (22) 8.1 6.9 5.1

Total (37) 160.2 140.4 110.5

05120203

Medium (13) 50.1 42.8 31.9

109.7

Small (15) 2.8 2.3 1.6

Total (28) 52.9 45.1 33.5

05120204 (Driftwood)

Medium (20) 83.7 70.2 49.9

131.2

Small (30) 4.2 3.5 2.5

Total (50) 87.9 73.7 52.4

05120205

Medium (7) 38.2 31.8 22.3

40.6

Small (5) 0.4 0.3 0.2

Total (12) 38.6 32.1 22.5

05120206

Medium (11) 20.5 17.1 12.0

95.6

Small (11) 4.7 3.9 2.7

Total (22) 25.2 21.0 14.7

05120207

Medium (19) 92.6 77.5 54.8

72.0

Small (15) 8.2 6.9 5.1

Total (34) 100.8 84.4 59.9

05120208

Medium (22) 110.7 92.7 65.7

62.7

Small (28) 4.4 3.7 2.6

Total (50) 115.1 96.4 68.3

05120209

Medium (7) 41.9 35.3 25.3

40.6

Small (9) 2.3 2.0 1.6

Total (16) 44.2 37.3 26.9

The values in Tables 50 and 51 are based on a 2:1 trading ratio and 20 percent farmer participation. The tables illustrate adequate NPS capacity to supply all 357 small facilities with TP and TN credits. The table also highlights subwatersheds in red where the NPS credit supply estimates are insufficient for all of the remaining medium size facility potential demand. However, WQT could still benefit numerous medium size entities. For example, an analysis of the TP credits remaining after the small facility demand has been met suggests that 404 of the 466 medium sized facilities could be supplied with an adequate number of TP credits. Similarly, for the most restrictive TN effluent limit, adequate credit supply could still benefit 433 of the 466 facilities.

These results do not reflect the facilities that would not participate or who would be eliminated from WQT participation due to a variety of issues (e.g., variability in costs between facilities, remaining useful life of a facility, risk averse management styles, or location of facility in a headwaters area). In addition these tables do not estimate the potential benefits from combining point source credit supply with

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nonpoint source supply. To do these assessments spatial analysis of locations (both point source and nonpoint source) would have to be done.

4.7 Other Trading Considerations

The preliminary findings in this report indicate WQT for TN and TP would both be environmentally protective and economically viable for many entities within the Wabash watershed. Additional benefits of trading when compared with investing in on-site technology include:

Providing longer planning and construction schedules: Long-term WQT would provide substantial economic opportunity for some entities. For point sources with tight compliance schedules that prevent adequate planning time or that delay upgrades to realize the full useful life of the existing facility, WQT becomes a means to address short-term needs for nutrient reductions. In addition, when appropriate, WQT provides leverage for facilities engaging in NPDES variance requests. In these settings, WQT can provide a level of nutrient reduction that demonstrates the permittee’s goodwill.

Allows facilities to consider partial treatment options: The economic analysis indicates many sites will be able to achieve many nutrient effluent limits by upgrading with BNR technologies. However, the assessment did not comprehensively detail other economically beneficial settings due to lack of site-specific information. Certain circumstances will occur where BNR treatment is insufficient to achieve compliance goals. In this setting a financial assessment of the cost of the additional treatment units required for the new restrictive limits (e.g., chemical precipitants and/or filters) versus the use of WQT credits may be performed. The assessment may find that a combination of treatment technology and WQT credits is the most cost effective. An added benefit of using a combined compliance approach is that these facilities need to purchase fewer credits than facilities using WQT to meet their entire nutrient reduction requirement.

Additional environmental gains: NPS BMPs used in WQT credit supply provide other pollutant reductions and produce other ancillary environmental benefits. Examples are riparian buffers and introducing perennial cash crops into the field rotation. Both BMPs would provide nutrient credit generation. The added benefits of these BMPs are reductions in sediment and potentially bacteria loading. Other benefits in physical parameters would be produced by introducing water storage back into the watershed, which would result in hydrograph dampening. Temperature gains from the shading effects of some BMPs could benefit aquatic life and increase dissolved oxygen concentrations in the water.

Compliance program managers can use WQT programs: Compliance excursions can be managed by requiring the violator to purchase a sum of WQT credits.

Third party purchasers retiring credits: Entities who wish to retire a portion of the watershed’s nutrient loading could be allowed access to credit purchases.

Options for watershed management: WQT provides additional opportunities within a watershed to target difficult settings. This can be accomplished by building incentives into the WQT program that give preferences to BMPs that increase habitat, target subwatersheds or reward other desired attributes.

Allowing for future growth in fully allocated watersheds: Managing future growth issues in a fully allocated watershed is on the horizon if not already here in many regions in the U.S. WQT can be used to relieve some of the pressure water resource protection places on expanding or existing NPDES dischargers and new entities wishing to operate in the watershed. Offsetting

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loads through WQT can work hand-in-hand with technology advances and reuse alternatives. Having more alternatives in the tool box provides for individual choices and flexibility to overcome site-specific challenges.

Flexible Contracts: WQT provides more flexibility when compared with some public conservation funding programs like EQIP and other cost-share opportunities. WQT focuses on measureable water quality improvements compared to other conservation programs which can be holistic in nature. Examples of flexibility include length of contract, no caps on the number of acres that can be enrolled, less restrictive seed mixtures and value added opportunities. Value added opportunities are illustrated by a filter strip example. WQT contracts can reduce restrictions on cash cropping when the grass is used for hay. The net return from haying of buffers is an opportunity cost that is not removed. Other examples are stacking of ecosystem service payments from events such as selling hunting rights or biomass production.

Accelerating implementation schedules: By introducing alternative funding to NPS entities and reducing the cost of compliance for permittees, implementation plans and other water quality efforts benefit from WQT. WQT also attracts additional adopters due to its increased contracting flexibility regarding implementation restrictions and issues of timing.

4.7.1 Attributes to Consider to Improve the Potential for Success

WQT programs operate at the cross roads of two busy thoroughfares. WQT can be viewed simultaneously as a market-based program and an environmental protection program. When assessed using market-based criteria, the trading program must address stability issues common to other marketplaces. When assessed using environmental criteria, WQT must contain provisions that provide assurances that water quality protection is first and foremost the objective of the program.

The following list outlines program considerations and options that take into account the four main stakeholder categories engaged in WQT program operations or appraisals. The four stakeholder groups in the Wabash watershed are:

Buyers of credits: NPDES permit representatives

Sellers of credits: Either NPDES permit representatives or agricultural producers

Regulatory agencies: The delegated Clean Water Act officials

Concerned third parties: Entities concerned about environmental and/or farm sustainability

Each of these audiences views the development and operation of a WQT program and weighs the progress against their list of critical elements. Some of the elements of one stakeholder group overlap with other groups. Some critical elements are unique to the group’s self-interest. For instance, credit pricing can cause tension between buyers and sellers. The simplest example of this is when buyers desire the lowest price per credit possible versus sellers which desire the highest payment for BMP implementation as possible. Buyers control the maximum purchase price and sellers control the minimum purchase price. A marketplace is successful when it produces a product for sale that is priced (including a profit margin) within the buyer’s willingness to pay range. This simple example touches upon two more perceptions where internal conflicts arise between some stakeholder groups. The first is the perception held by a few that nobody should profit from protecting the environment. The second is that an environmental commoditization is not holistic. In other words, a market based on phosphorus credit transactions promotes NPS reductions above or at the expense of habitat creation.

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These concerns, and others, can be fully addressed or reasonably managed by identifying the concerns germane to the setting and structuring the WQT program framework to include the correct provisions that will balance stakeholder interests that are vital to success. Fortunately, WQT does not require the impossible goal of appealing to all. Instead, WQT development must recognize which issues create veto circumstances (e.g., regulatory authority denying program elements), a reduction in participation (e.g., a buyer’s mistrust of the negotiation process), or introduction of controversy (e.g., a third party successfully creating doubt around the program’s ability to protect the water resource). The following two sections identify concerns and management options that can be considered during development of a WQT framework to provide for environmental protection and market stability.

4.7.2 Environmental Protection

Environmental protection is a prerequisite of NPDES permits. NPDES WQT permits can be expected to receive a more than fair share level of scrutiny. As explained previously, no NPDES permit can cause or contribute to a water quality violation. The ability for a WQT program to provide for environmental protection affects how every stakeholder will accept or reject the program. Using an information protocol and a weight of evidence process, WQT program managers can navigate through this uncharted frontier. The following list identifies the information protocol questions and provides suggestions on how they may be addressed:

What are the water quality goals that the trading program will execute?

o WQT is a NPDES permit compliance option. As such, the minimum goal is to comply with the permit effluent limits assigned to the discharge under conventional treatment circumstances.

o WQT can be a means to accelerate other environmental efforts. WQT can, up to a certain point, target hard to reach areas, advance habitat protection and assist with pollutant reductions in other parameters than those being traded. Pricing is critical in a market-based system. If too many watershed management goals are placed on WQT programs the market price become the limiting element.

The WQT program managers must be objective and keep in mind that WQT will not work in all watersheds. A small watershed scale program must answer the questions: 1) Are there sufficient supply options for the demand? and 2) Will water quality violations occur? Larger watershed programs need to address the same questions but may decide to restrict the program to certain subwatersheds depending on the findings. The weight of evidence approach can assist with identifying these potentially deal-breaking constraints.

The weight of evidence approach (or, sometimes referred to as multiple lines of evidence) is explained in the U.S. EPA guidance manual for biotic impairments entitled CADDIS: The Causal Analysis/Diagnosis Decision Information System (U.S. EPA, 2000). The process fosters appropriate decision making using multiple reasonable opinions to form a consensus. A weight of evidence approach applies the best available science to the setting and makes decisions based upon the current understanding. Decisions can be made based on three different outcomes. The first is a causal linkage based on hard evidence that environmental protection is provided. For instance, the credit equation in point source to point source trading is based on monitored results. The second outcome is proof that the environmental protection is not provided by hard science. For instance, monitoring indicates that use of credits generated by downstream sources will contribute to a local water quality violation that exists between the buyer and seller. Finally, the third outcome is when the watershed understanding is incomplete but

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a reasonable resolution exists. For instance, a lack of adequate monitoring to assess the resource conditions and partition sources and source reduction capability can be overcome when using standard NPS tools and reasonable margins of safety. If the outcome of the element being assessed does not result in any of these three findings, the team must revisit the topic and data seeking a means to resolve the gap in watershed understanding.

Fortunately an increased level of watershed understanding is emerging. More and more data sets are available to use in this process. Data sets include water quality and quantity monitoring, land use data, modeling, benchmarking salient WQT programs and reviewing local conservation office conservation assessment tools. Sources of information include federal and state agencies like U.S. EPA, NRCS, USGS, IDEM, IEPA, DNR and research from land grant colleges such as Purdue University and University of Illinois.

The weight of evidence process will assist with identifying and prioritizing concerns. The process also advances use of the best available science to address these concerns. The weight of evidence context can include:

Keeping decisions local

Supporting the local decisions with the use of an interdisciplinary team of experts

Creating a transparent communication process to provide access to the stakeholders

Involve the regulating agencies and

Identifying and involving champions from each stakeholder category (preferably selecting individuals that have a history of building unity and being reasonable).

The weight of evidence process is based on a logic decision tree. Sometimes the flow path can be iterative. It supports decision making using the following steps:

Identifying each information protocol question

Prioritizing the questions and issues

Assessing the available data on the topic (monitoring and benchmarking)

Create and review a list of options to address the question at hand

Determine if the current data validates the suggested option (resulting in moving on to the next issue) or rejects it (resulting in the selection of another option)

When the evaluation is inconclusive, use of a “reasonableness test” begins

o The multiple discipline expert panel reviews the findings and gaps in understanding

o Recommend an affordable direction (e.g., developing a credit estimation method based on watershed modeling or use of acceptable currently used standard methods like NRCS NPS assessment tools)

o Testing and identifying the uncertainty in the selected option

o Determining adequate margins of safety that provide for both the protection goals and economic viability using an objective judgment on reasonableness

It may be important to support this process through efforts to educate the public on the issues at hand, communicate the findings and solicit comments and feedback.

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By keeping the decisions local, involving the regulatory staff and inviting in regional experts, a pragmatic solution can evolve when perfect science and understanding do not exist. In these circumstances the WQT program can operate simultaneously with collection and evaluation of more data and periodically considering investing in better tools as part of a planned adaptive management approach. The WQT program should be integrating these assessments with other watershed programs so that the coordination becomes mutually beneficial.

4.7.3 Market Stability

Market stability can be thought of as a three legged stool. One leg is long-term demand for the product. The second is the ability to supply the product at an adequate price. And the third is confidence in the product being what it claims to be. Anyone who has purchased a large ticket item like a used car or home understands there is a long-term risk with that investment. WQT trading also has a level of risk and liability with its investment. Objectively recognizing this aspect of market-based systems allows methods for management of risk to be introduced into the program framework. Fortunately, WQT markets are not free market economies and operate under a regulated or quasi regulated marketplace structure. This fact allows for risk and liability to be controlled to a certain extent.

The following concerted efforts bring market stability to WQT programs and should be considered when selecting the trading program frameworks described in Section 5.3.

Keeping the decisions local: This element enhances the local stakeholder involvement and influence when assessing watershed management, additional conservation issues and equity.

Transparent decision making: This element allows for opportunities for trust in the process to develop between all engaged stakeholders.

WQT programs take time to develop: Having the necessary administrative infrastructure in place early is paramount to success. In situations where NPDES permit limits have tight compliance schedules the permittee cannot afford to wait for a WQT program to develop. Considering the time it takes to construct BMPs and establish vegetation, acquiring adequate levels of credits for compliance could take some time. Having a sufficient compliance schedule to allow for NPS BMP implementation could preclude using of a portion of the compliance schedule window to develop the program. Likewise, the program experiences the most efficient use when it is developed slightly ahead of demand and does not exist too long without use and support.

Including adaptive management at scheduled times: This process provides for two critical issues. The first is acknowledgement of the program’s limitations and the program provides a means to address them over time. The second issue is structuring change at predictable intervals so that entities are comfortable with large, long-term investments in the marketplace.

Use of locally developed infrastructure: This point leverages existing networks that have already been developed. Business relationships develop trust and confidence in the partnership typically across several years. Conservation decision making is no different. By engaging the current conservation service providers, a producer’s anxiety can be reduced.

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Recognition of the complexity of WQT and the need for simplicity: WQT trading is a complex program that crosses over multiple disciplines. The protection of water quality must be provided at a level of sufficient rigor, yet the delivery of the program must be simple. The program must be simple enough to not take up too much time but at the same time it must be complete enough to explain the process at a level that is transparent. One successful way to manage this is poll the community of buyers and seller and find out who they trust to operate the program. This consideration overlaps well with the last item. If there is confidence established in the local service providers for both buyer and seller, then the program can leverage that confidence by training the trainer to deliver the program marketing. Guiding questions include:

o What is the level of capability that local service providers have to operate credit estimation tools?

o What level of compensation is a fair service provider’s fee?

The consideration and answers to these questions will allow for opportunities to create market frameworks that minimize transaction fees.

Identify the regulatory agency concerns: Regulatory agencies have complete veto authority over the use of WQT in the permits they issue. Finding out the concerns the agency has is essential to program success. Limitations in accepting WQT programs include: a) lack of trust in the science, b) lack of resources available within the agency to adequately assess all of the program elements, and c) having confidence the reporting and compliance program will work. By identifying early which of these and other critical issues are of concern to agency staff, effective problem solving can begin. Identifying appropriate and objective partners can be a potential solution (e.g., MCD uses both Ohio DNR and county SWCD staff to evaluate and audit agricultural BMP implementation for Ohio EPA review) (MCD, 2001)(Ohio DNR, 2011).

4.7.4 Water Quality Trading Framework Options for Compliance Mechanisms

Managing NPDES permit compliance is riskier when working with NPS for at least two substantial reasons. First, land use conservation measures experience episodic and catastrophic events that may render a BMP or management measure useless or inadequate for a period of time. Secondly, participants are liable for their operation but turn the evaluation and control of success over to other parties. Existing programs have confronted these issues and developed the following compliance assurance mechanisms:

Replacement/correction windows:

o Ohio EPA rules section 3745-5-12 (Ohio EPA, 2007) allows a ninety day correction window for which crediting contracts are not revoked if reported in a timely manner.

o Pennsylvania Department of Environmental Protection (PADEP) plans to exercise enforcement discretion with respect to permittees in the year which credits are determined to be invalid, as long as (1) the credit failure is not due to negligence or willfulness on the part of the permittee and (2) the permittee replaces the credits for future compliance periods (PADEP, 2008).

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o West Virginia trading guidelines allow a period where buyers may purchase contemporaneous credits after the averaging period if it is discovered the compliance measures were deficient.

Insurance pools: MCD (MCD, 2001) and (PADEP) (PADEP, 2008) provide for market stability by creating insurance pools of back up credits.

Broadening the compliance period: WI DNR and the Chesapeake Bay programs have extended the NPS averaging period to be based on annual average credit results.

Benchmarking other successful WQT programs can provide examples of market stabilizing mechanisms like these for the WQT framework decision makers.

5. Next Steps for Water Quality Trading in the Wabash River Watershed

As stated in the introduction, a WQT feasibility study provides insight as to where WQT might encounter barriers in a particular watershed and what type of trading framework might be most appropriate based on the sources with the greatest potential for participation. It is an initial step in investigating the potential for WQT success in a watershed. Based on the information compiled and analyzed for the Wabash River watershed, the Project Team has developed recommendations on next steps for moving WQT beyond the feasibility assessment phase. These next steps include conducting more in-depth outreach and education with stakeholders, prioritizing subwatersheds for future analysis, and exploring the potential WQT frameworks that could be effective in the Wabash River watershed. These recommendations are discussed in more detail below.

5.1 Outreach and Education

Understanding the attitudes and perceptions of key stakeholders towards WQT is essential to determining the potential success of this water quality management tool. This feasibility analysis obtained informal input from regulators, point sources, and agricultural landowners through personal communications, focus groups, and online surveys. However, much more in-depth outreach and education would be necessary with these key stakeholder groups to move WQT forward in the Wabash River watershed.

5.1.1 Regulators

Trades involving NPDES point sources would require support from IDEM, specifically staff involved in water quality standards and assessment, NPDES permitting, and enforcement. As a result, it is imperative to engage IDEM in discussions about moving the concept of WQT in the Wabash River watershed beyond the feasibility phase. Outreach to IDEM could include presenting the findings of the WQT feasibility analysis, discussing concerns about the use of WQT now and in the future, and highlighting potential water quality benefits. IDEM holds the key to the drivers necessary for WQT (e.g., numeric nutrient criteria, more stringent NPDES permit effluent limits, modified TMDL targets). Without the agency’s support, it will prove challenging to move WQT forward toward program development and implementation.

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5.1.2 Point sources

Even with the appropriate drivers in place, WQT will not take off in the Wabash River watershed without support from regulated point sources. Concerns about aspects of WQT such as risk management and transaction costs could limit participation. Outreach to point sources within the Wabash River watershed should present the findings of the WQT feasibility analysis, but also illicit feedback on point sources’ perspectives of WQT and potential barriers to participation. Point source involvement in WQT program design and development will also help to generate support and trust in the process and could lead to greater participation.

5.1.3 Agricultural landowners

Without adequate credit supply, WQT would not be feasible. An adequate credit supply for point source-to-nonpoint source trading will depend on participation from agricultural landowners. Issues related to WQT such as credit verification, certification, and liability often serve as barriers to agricultural landowner participation. Through outreach and education, agricultural landowners can gain a better understanding of how WQT works and their role in the process. Identifying the factors that would influence the agricultural community’s willingness to participate and crafting solutions to existing challenges would be a key goal of outreach to this stakeholder group.

5.2 Prioritized Subwatershed for Future Analysis

The pollutant and economic suitability findings indicate an ample credit supply and demand exists for WQT in each subwatershed within the Wabash River watershed. There is sufficient technical support and economic incentives to invest in WQT in the future as demand drivers emerge. Watershed managers deciding to develop a WQT program can review the findings of this report and fit the findings to the scale of the proposed WQT program. Decision makers would need to vet the economics and supply capabilities based upon better site-specific data and conditions. Current policies and rules and physical characteristics of the local watershed also need to be taken into account. These important steps enhance the ability of a WQT program to integrate with other watershed activities. These steps can be informed by the outreach and education process described in Section 5.1. However, WQT legal and technical complexities go beyond the outreach efforts and need to address the program framework details using pragmatic solutions tailored to the watershed.

WQT does not have to engage every member of the watershed to be beneficial for advancing watershed nutrient reduction goals. However, an entity’s ability to block or advance WQT efforts can vary. Entities with the ability to either stop or host WQT efforts include the regulatory agencies, current conservation service providers and third parties likely to generate lawsuits or contentious comments during the NPDES permit public review periods. Likewise, an assessment of the likely number of buyers willing to participate can be used to select and justify the level of funding necessary for the program set up.

The following summary of elements can be used to inform decision makers where sufficient synergy for each program principle may exist:

Regulatory agency

o Concerns, enthusiasm or hesitancies from agency

o Ability to allocate resources to participate in a program

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o Whether limitations on agency resources will be an issue (e.g. can this be alleviated by assigning WQT administration roles to other governmental or non-governmental units, such as NRCS?)

o Other identified procedural limitations

Demand side

o Level of WQT educational efforts and awareness in the watershed

o The number of entities interested in a WQT program

o The trading scale desired (e.g., one permit, a small second or third order watershed or a larger watershed/basin)

o Expected timing of the new nutrient effluent restrictions (e.g., will WQT program development be completed in time to meet the buyers’ compliance schedules?)

o Third party entities that can be trusted to find, aggregate and document NPS credits

o The current decision support tools/procedures for legal requirements, tracking and reporting and their availability for WQT programs

Supply side

o Indications of the farmers’ willingness to participate

o Producers’ trust for sharing information to implement the program (e.g., identifying farm options, divulging site data, recommending pricing, inspecting and reporting)

o Availability of decision support tools for crediting and administration

Third party involvement

o Interest and/or concerns with WQT activities

o Identifying available experts and champions

o The basis of any concerns

o Ways in which concerns can be reasonably addressed

Desired development structure

o Preferred framework organization

o Identify position roles and responsibilities

o Find entity or organization that could/should host the program

These considerations of socio-political of a best fit are provided to assist program decision makers in selecting high potential watersheds as they advance into the next phase of trading development.

5.3 Trading Program Frameworks

Moving from the WQT feasibility analysis phase to the WQT program design phase involves determining the type of trading program framework that would work in the Wabash River watershed. At a very basic level, WQT can involve point-to-point source trades or point source-to-nonpoint source trades. But within those two broad categories, there are different framework options for implementing trading. U.S. EPA describes the different types of WQT frameworks that are options for Wabash River watershed stakeholders and IDEM to consider. These frameworks are briefly summarized below. More information can be found in U.S. EPA’s Water Quality Trading Toolkit for NPDES Permit Writers.

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5.3.1 Point-to-Point Source WQT Frameworks

According to U.S. EPA, point-to-point source trading is “relatively straightforward, easily measurable, and directly enforceable (U.S. EPA 2007).” Because trading for both partners is reflected in NPDES permits, regulators tend to feel a higher level of comfort with this type of trading. Under this category, trading can include single point-to-point source trades, multiple facility point source trading, or a point source credit exchange.

5.3.2 Point-to-Nonpoint Source WQT Frameworks

Under this category of trading, point sources are often able to meet more stringent permit effluent limits at a relatively cheaper cost. U.S. EPA states that for this category of WQT, “extra care should be taken to ensure that nonpoint source load reduction uncertainty is addressed (U.S. EPA 2007).” The WQT feasibility analysis for the Wabash River watershed addresses the issue of uncertainty in the discussion on trade ratios in Section 4.3. Point-to-nonpoint source WQT frameworks include:

Single point source-nonpoint source trades; where the permittee can find the NPS credits or use a middleman/broker to provide credits from a site (includes the use of electronic tools to find trades

Single or multiple point source-nonpoint source trades using an aggregator; where use of the middleman collects and sells cumulative larger blocks of credits to the buyer

Nonpoint source credit exchange, where the exchange host purchases credits from one or more sites to dispense among buyers

5.4 Conclusion

The WQT pollutant and economic feasibility study findings indicate that the Wabash River watershed has a high potential for WQT to provide substantial economic and environmental benefits in the future. The beneficial attributes found in this report include the ability to provide small to medium wastewater facilities with economical and relevant compliance options to address future nutrient effluent limit requirements. This can be done using WQT which provides opportunities to enhance the holistic conservation efforts associated with implementation of nutrient reduction goals. When considering implementing a WQT program, managers are encouraged to review this report and make final programmatic decisions based upon the site-specific information and scale of the specific location. Program set up expenses for WQT can be expected to be more affordable when the program is developed to provide services for multiple entities. Lastly, program development phase can be expected to take a couple of years to complete. The program development phase can be coordinated with the future nutrient water quality criteria development processes and state Gulf of Mexico hypoxia action strategies. Until these demand drivers emerge, the use of WQT programs will most likely be limited to watersheds with a narrative based nutrient TMDL.

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Appendix A: Letter to Illinois EPA from USEPA

Appendix B: Wabash River Watershed TMDL Reduction Summaries and Wasteload Allocations (WLAs)

Appendix C: Characterization of Wabash River Nutrient Loads

Appendix D: Compilation of Nonpoint Source Analysis Technical Memos

Appendix E: Point Source Survey Results

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