Phosphorus Indices: Why We Need to Take Stock of How We Are Doing

Abstract

Many states have invested significant resources to identify components of their Phosphorus (P) Index that reliably estimate the relative risk of P loss and incentivize conservation management. However, differences in management recommendations and manure application guidelines for similar field conditions among state P Indices, coupled with minimal reductions in the extent of P-impaired surface waters and soil test P (STP) levels, led the U.S. Natural Resources Conservation Service (NRCS) to revise the 590 Nutrient Management Standard. In preparation for this revision, NRCS requested that a review of the scientific underpinnings and accuracy of current P Indices be undertaken. They also sought to standardize the interpretation and management implications of P Indices, including establishment of ratings above which P applications should be curtailed. Although some states have initiated STP thresholds above which no application of P is allowed, STP alone cannot define a site's risk of P loss. Phosphorus Indices are intended to account for all of the major factors leading to P loss. A rigorous evaluation of P Indices is needed to determine if they are directionally and magnitudinally correct. Although use of observed P loss data under various management scenarios is ideal, such data are spatially and temporally limited. Alternatively, the use of a locally validated water quality model that has been shown to provide accurate estimates of P loss may be the most expedient option to conduct Index assessments in the short time required by the newly revised 590 Standard.

Improved APEX Model Simulation of Buffer Water Quality Benefits at Field Scale

“…Vegetative strips placed within (upland buffers) or at the edge of a field are effective conservation measures to reduce sediment and nutrient loadings from agricultural fields (Lowrance et al, 1984;Dillaha et al, 1989;Schmitt et al, 1999;Lee et al, 2000). Given the limits of measured data, process-based models may be an alternative for estimating long-term sediment and phosphorus (P) losses (Sharpley et al, 2012). Models could be used to extend existing measured data to provide quantitative estimates of runoff, sediment, and P loss under alternative weather scenarios and/or varying management at one site, or under varying soils, topography, and climate across a region.…”

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

“…Based on the agronomic approach used 32.2% percent of point locations allowed for no P applications, however, in the current P Index, there is no actual prohibition against additional P application until a very high (>45 points) score is reached. This illustrates that, currently, for Ohio, the P Index approach could be perceived as less restrictive with regards to P application than an agronomic approach [8] [9]. For example under the current Ohio P Index weighting a Bray-P1 STP of 150 mg·kg −1 would result in only 10.5 points.…”

“…A revised P Index needs to be more broadly useful by providing information regarding field-scale P runoff risk to all Ohio farmers not only those applying manure/biosolids. As P indices are increasingly being used to judge farmer performance [7] [8] [9] [10] it is imperative to evaluate weighting/scoring of all components carefully so farmers will be credited for management practices that reduce runoff risk and not unduly penalized for things they cannot control or are not demonstrably related to runoff risk. Refinements in the current approach are not only helpful with an evaluation of the current Ohio P Index but will assist with revision decisions by spatially illustrating the impact of potential changes regionally and state-wide.…”

“…In response to water quality concern, there is an increased emphasis on the use of state P indices in the recently revised USDA Natural Resources Conservation Service (USDA-NRCS) Practice Standard Code 590, Nutrient Management [7] [8] [9] [10] which considers both crop production and P runoff risk. Lemunyon and Gilbert [11] first introduced the P risk index approach as a qualitative estimate of P runoff risk based on field characteristics and farmer management practices.…”

“…Comparing multiple state P Index weighting/scoring and interpretation for the same sets of field data has revealed substantial differences [13] [17] among state P indices. Ideally, weightings should be evaluated based on measured P runoff data [9]. Field work currently underway in Ohio should be able to better inform weighting/scorings as they are related to P loss.…”