N and P Reduction Estimation

1. N and P Reduction Estimation Consider complete range of management and structural practices Models vs. Measurements Iowa results where possible Capturing mean and range of published results Not a meta-modeling exercise Spatial resolution – Reliance on GIS Imperfect knowledge of current practices (where are we starting?)

2. Consider complete range of management and structural practices Drainage management Cover crops Living mulches Energy crops Land retirement Bioreactors Wetlands Vegetated buffers • Fertilizer rate, placement, timing, form • Precision agriculture • Nitrification inhibitors • Soil testing • Manure management • Extended rotations • Tillage

3. N and P Reduction Estimation Consider complete range of management and structural practices Models vs. Measurements Iowa results where possible Capturing mean and range of published results Not a meta-modeling exercise Spatial resolution – Reliance on GIS Imperfect knowledge of current practices (where are we starting?)

4. Models vs. Measurements APEX Gleams ADAPT WEPP • RZWQM • Drainmod • SWAT • AGNPS

5. N and P Reduction Estimation Consider complete range of management and structural practices Models vs. Measurements Iowa results where possible Capturing mean and range of published results Not a meta-modeling exercise Spatial resolution – Reliance on GIS Imperfect knowledge of current practices (where are we starting?)

6. Iowa results where possible Nitrate-N leaching losses due to winter cover crops (adapted in part from Meisinger et al., 1991). Reference Location Cover crop N Leaching Reduction Morgan et al., 1942 Connecticut, U.S. Rye 66% Karraker et al., 1950 Kentucky, U.S. Rye 74% Nielsen and Jensen, 1985 Denmark Ryegrass 62% Martinez and Guirard, 1990 France Ryegrass 63% Staver and Brinsfield, 1990 Maryland, U.S. Rye 77% McCracken et al., 1994 Kentucky, U.S. Rye 94% Wyland et al., 1996 California, U.S. Rye 65 - 70% Brandi-Dohrn et al., 1997 Oregon, U.S. Rye 32 - 42% Ritter et al., 1998 Delaware, U.S. Rye 30% Kaspar et al., 2007 Iowa, U.S. Rye 61% Strock et al., 2004 Minnesota, U.S. Rye 13% Kladivko et al., 2004 Indiana, U.S. Winter wheat 61%

7. N and P Reduction Estimation Consider complete range of management and structural practices Models vs. Measurements Iowa results where possible Capturing mean and range of published results Not a meta-modeling exercise Spatial resolution – Reliance on GIS Imperfect knowledge of current practices (where are we starting?)

8. Capturing mean and range of published results • Not a meta-modeling exercise

9. N and P Reduction Estimation Consider complete range of management and structural practices Models vs. Measurements Iowa results where possible Capturing mean and range of published results Not a meta-modeling exercise Spatial resolution – Reliance on GIS Imperfect knowledge of current practices (where are we starting?)

10. Spatial resolution– Reliance on GIS County level estimates GIS estimates Drained land Existing riparian buffers Crop rotations Land cover • Tillage practices • Fertilizer rates

11. N and P Reduction Estimation Consider complete range of management and structural practices Models vs. Measurements Iowa results where possible Capturing mean and range of published results Not a meta-modeling exercise Spatial resolution – Reliance on GIS Imperfect knowledge of current practices (where are we starting?)

12. Imperfect knowledge of current practices “Universal NO3 response curve”

13. Imperfect knowledge of current practices “Universal NO3 response curve”

14. Imperfect knowledge of current practices “Universal NO3 response curve”

15. N and P Reduction Estimation Consider complete range of management and structural practices Models vs. Measurements Iowa results where possible Capturing mean and range of published results Not a meta-modeling exercise Spatial resolution – Reliance on GIS Imperfect knowledge of current practices (where are we starting?)