Submitted to: Kentucky Water Resources Research Institute Symposium
Publication Type: Proceedings
Publication Acceptance Date: 2/17/2012
Publication Date: 3/19/2012
Citation: Bolster, C.H. 2012. The potential for using a P loss model to improve the accuracy of the Kentucky phosphorus index. Kentucky Water Resources Research Institute Symposium. 31-32.
Interpretive Summary: The phosphorus (P) Index is an assessment tool developed to identify fields which are most vulnerable to P loss. The U.S. Department of Agriculture’s Natural Resource Conservation Service (USDA-NRCS) has currently revised its 590 Nutrient Management Conservation Standard and as part of this revision, USDA-NRCS is requesting that states test the accuracy of their P index. Recent analyses have shown that there exists several limitations with the KY P Index indicating the need to update and revise the KY P Index. This study proposes a method for modifying the KY P Index using output from an empirically-based P loss model.
Technical Abstract: The phosphorus (P) Index is an assessment tool developed to identify fields which are most vulnerable to P loss by accounting for the major source and transport factors controlling P movement in the environment. The Kentucky P Index was developed over 10 years ago and since its inception; a significant amount of research investigating the factors governing P loss at the field scale has been published. The KY P Index, however, has not been updated to stay current with the literature. A recent analysis showed that there exists several limitations with the Index, including how each factor in the Index is weighted, the lack of terms to account for planned P application rates, and the use of land cover and field slope as surrogates for erosion rather than erosion rates as derived from RUSLE. Furthermore, a recent comparison between measured P runoff collected from sites in North Carolina and Georgia and estimates of P risk obtained with 12 southern P Indices showed that the KY P Index provided some of the poorest estimates of P loss risk of all the P Indices tested. These studies highlight the need to update and revise the KY P Index to better reflect the current state of the science. This study proposes a method for modifying the KY P Index by correlating it with output from an empirically-based P loss model.