BMP Project Status and Overview

1. BMP Project Statusand Overview Tom Simpson Sarah Weammert University of Maryland Mid Atlantic Water Program sweammer@umd.edu 301-405-1215 Forestry Workgroup July 16, 2007

2. Presentation Outline • Process Overview • Explanation of Approach • Recommended efficiencies • Cover Crops • Buffers • Next Steps • Discussion

3. Process • Scientific Literature Search • Development of Practice Definition and Efficiency • Review • Documentation and Reporting

4. Field and Pasture Erosion Control Practices Conservation Tillage Off-stream Watering Practices Buffers Cover Crops Forest Harvesting Practices Wetland Restoration and Creation Urban wet ponds and wetlands Urban erosion and sediment control Dry detention ponds and hydrodynamic structures Dry extended detention basins Urban stream restoration Year One BMPs

6. Desired outcome of BMP review and revisions • Develop BMP definition and efficiency that reflects what field implementation • Revise efficiency, as needed, to be as close as possible to what occurs under average implementation and O&M with widespread adoption, accounting for variability across space and time • Generate efficiencies that can be used in CBP WSM Ph5 for calibration and to estimate both progress and scenario reductions as close as possible to what will occur

7. Uses of BMP efficiencies • Tributary Strategies • Trading • TMDLs • MS4 Permits? • Conservation Effect Assessment Project • Used by states and feds across country

8. WSM BMP efficiencies • Realistic estimates of actual performance • Not designed to be: • Aspirational • Promotional • Maintenance of status quo (unchangeable) • Designed to be applied in an adaptive management framework

9. National Academy of Sciences, National Research Council, 2004 “Adaptive management does not postpone actions until ‘enough’ is known about a managed ecosystem (Lee, 1999), but rather is designed to support action in the face of the limitations of scientific knowledge and the complexities and stochastic behavior of large ecosystems (Holling, 1978). Adaptive management aims to enhance scientific knowledge and thereby reduce uncertainties. Such uncertainties may stem from natural variability and stochastic behavior of ecosystems and the interpretation of incomplete data (Parma et al., 1998; Regan et al., 2002), as well as social and economic changes and events (e.g., demographic shifts, changes in prices and consumer demands) that affect natural resources systems.

10. Buffers • Developer- Carrie Graff; Reviewer – Richard Lowrance and Judy Okay • UMD contracted with Graff, Limnotech Inc., to run the Riparian Ecosystem Management Model for grass and forested buffers. • Delays in and questions about model input data and questions about input hydrology (gw flux) have raised questions about • Met with experts in mid-June to discuss

11. REMM-Grass Riparian Buffers • REMM was run for grass buffers in representative settings in two hydrogeomorphic regions: the Great Valley (Shenandoah) and the Eastern Shore (Talbot County, MD). Time and funding precluded more runs. Propose to extrapolate for other regions. . Location%N reduction%P reduction Shenandoah high till 46.7 32.9 Shenandoah low till 80.3 43.2 Talbot high till 71.5 29.3 Talbot low till 54.9 35.0

12. Riparian Forest Buffers • REMM was run for same areas with same assumptions as for grass. For the Shenandoah, only results from buffers treating high till cropland have not been received. • The results for the forested buffers are shown below. Location%N reduction%P reduction Shenandoah high till 78.7 27.3 Shenandoah low till Talbot high till 82.1 29.1 Talbot low till 91.2 36.9

13. Meetings/discussions • Richard Lowrance, ARS-Tifton, Andrew Sharpley, U. Ark., Judy Meyer, UGA • Deanna Osmond, NC State • Greg McCarty, Dean Hively and others, ARS-Beltsville

14. Lowrance, Sharpley and Meyer • Agreed that N should be 30-40% and P 20-30%, vary by geomorphic regions but • Lowrance changed mind upon return home and suggested values similar to current • Sharpley had no comment on N but questioned DRP removal by buffers • Simpson raised question of P accumulation in buffer making it a source of P in future based on P site index work

15. Osmond, NC • NC had set buffer N efficiencies of 75-85% based on limited research data • In 1996, established buffer research watershed and monitored at different times throughout last 10 years • Data support 30% N reduction but have revised state efficiencies to 20-60% based on buffer width to promote wider buffers and to “soften” change • Their data suggest buffers are a source of P over time, not a sink, so do not give buffers a P efficiency

16. McCarty, Hively and others at Beltsville • Monitored “OPE-3” watershed field and exisitng buffer for ~8 years • Found non uniform gw and sw flow through field and buffer • Upwelling in buffer represented major discharge areas • One site was 0.06% of total riparian area but contributed 10-15% of flow and 30-40% of NO3

17. BMP Project Recommendation • Adapt current hydrogeomorphic region buffer N efficiencies to account for scaling up, spatial and temporal variability and non-uniform flow • Quantitative data is limited but based on NC and Beltsville may be >50% • Given limited data, recommend adjusting current efficiencies by 20-33% as interim measure • Keep grass as 70% of forest for N • Make P efficiencies same for grass and forest and a range of 25-40% across regions

18. Conclusions so far • Have much better understanding of BMPs, definitions and efficiencies • Review was needed for a long time • Proposed definitions and efficiencies are more accurate, realistic and defensible than current ones • Many BMP specific experts involved • Adjustments may cause some reduction in modeled BMP implementation progress This is a successful adaptive management approach and the world is again watching us and following our lead