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Title: Using the annual phosphorus loss estimator (APLE) model to evaluate the University of Maryland phosphorus management tool

item FIORELLINO, N - University Of Maryland
item MCGRATH, J - University Of Maryland
item VADAS, P - Desiderio Finamore Veterinary Research Institute (FEPAGRO)
item Bolster, Carl
item COALE, F - University Of Maryland

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 8/27/2013
Publication Date: 11/8/2013
Citation: Fiorellino, N.M., Mcgrath, J.M., Vadas, P.A., Bolster, C.H., Coale, F.J. 2013. Using the annual phosphorus loss estimator (APLE) model to evaluate the University of Maryland phosphorus management tool. ASA-CSSA-SSSA Annual Meeting Abstracts. Abstract.

Interpretive Summary:

Technical Abstract: Maryland’s phosphorus site index (PSI) has been used to guide management decisions to minimize the potential for P loss from agricultural fields in Maryland since the adoption of the Water Quality Improvement Act of 1998. The index was recently revised and renamed the University of Maryland Phosphorus Management Tool (UM PMT) and the most significant change was from a multiplicative model to a component model. The original index summed all P sources factors and then summed all P transport factors separately, then multiplied the combined source factors by the combined transport factors. In the UM PMT, a separate component, comprised of the P source and the specific P transport pathway, is calculated for surface-dissolved, subsurface-dissolved, and sediment-bound P, and then all three components are summed to provide the total score. The modifications to the PSI were based on a dataset of 391 fields visited statewide with soil samples, physical characteristics, and nutrient management data collected. The Annual Phosphorus Loss Estimator (APLE) model is a field-scale P loss quantification tool and has been used to assign weighting coefficients to P indices in other states, and was used to evaluate the UM PMT and assign weighting coefficients to the sediment-bound P and surface-dissolved P components. A simulated dataset of 10,000 points across Maryland was created to perform the evaluation. The dataset contained all variables required to run the Maryland PSI, UM PMT, and APLE. Values were assigned to points using a uniform distribution and then the points were joined with county-specific soils data. APLE scores will be regressed against sediment-bound and surface-dissolved P loss scores for the simulated dataset, weighting coefficients will be assigned, and Maryland PSI, UM PMT, and UM PMT with weighting coefficients will be run on collected dataset of 391 fields for comparison.