Osmond, D.L., Cabrera, M.L., Feagley, S.E., Hardee, G.E., Mitchell, C.C., Moore, P.A., Mylavarapu, R.S., Oldham, J.L., Stevens, J.C., Thom, W.O., Walker, F. and Zhang, H. (2006) Comparing Ratings of the Southern Phosphorus Indices. Journal of Soil and Water Conservation, 61, 325-337.

has been cited by the following article:

• TITLE: Using Crop Management Scenario Simulations to Evaluate the Sensitivity of the Ohio Phosphorus Risk Index

  AUTHORS: Elizabeth A. Dayton, Christopher H. Holloman, Sakthi Subburayalu, Mark D. Risser

  KEYWORDS: Ohio P Index, Sensitivity Analysis, P Index Simulations, RUSLE2 Simulations, Crop Management Simulations

  JOURNAL NAME: Journal of Environmental Protection, Vol.8 No.2, February 21, 2017

  ABSTRACT: Phosphorus (P) risk indices are commonly used in the USA to estimate the field-scale risk of agricultural P runoff. Because the Ohio P Risk Index is increasingly being used to judge farmer performance, it is important to evaluate weighting/scoring of all P Index parameters to ensure Ohio farmers are credited for practices that reduce P runoff risk and not unduly penalized for things not demonstrably related to runoff risk. A sensitivity analysis provides information as to how sensitive the P Index score is to changes in inputs. The objectives were to determine 1) which inputs are most highly associated with P Index scores and 2) the relative impact of each input variable on resultant P Index scores. The current approach uses simulations across 6134 Ohio point locations and five crop management scenarios (CMSs), representing increasing soil disturbance. The CMSs range from all no-till, which is being promoted in Ohio, rotational tillage, which is a common practice in Ohio to full tillage to represent an extreme practice. Results showed that P Index scores were best explained by soil test P (31.9%) followed by connectivity to water (29.7%), soil erosion (13.4%), fertilizer application amount (11.3%), runoff class (9.5%), fertilizer application method (2.2%), and finally filter strip (2.0%). Ohio P Index simulations across CMSs one through five showed that >40% scored 45 points (very high). Given Ohio water quality problems, the Ohio P Index needs to be stricter. The current approach is useful for Ohio P Index evaluations and revision decisions by spatially illustrating the impact of potential changes regionally and state-wide.