The purpose of our work was to determine, within the southern region (AL, AR, FL, GA, KY, LA, MS, NC, OK, SC, TN, and TX), the feasibility of using different models to determine potential phosphorus loss from agricultural fields in lieu of phosphorus indices.
We have collected water quality and land use data from plot- and field-scale experiments throughout the South (AR, GA, MS, NC, OK, and TX). The water quality data provide information on runoff rates, phosphorus concentrations, and phosphorus loads. The land use data provide information on both management practices, including the amount of phosphorus applied as fertilizer and/or manure and tillage, as well as inherent properties such as rainfall, soil series, etc. Once we obtained this information, we used the data to run the Agricultural Policy / Environmental eXtender (APEX), Texas BMP Evaluation Tool (TBET), and Annual Phosphorus Loss (APLE) models, in both uncalibrated and calibrated modes.
Models predicted runoff accurately, but were unable to predict sediment or phosphorus losses accurately in many cases. Not surprisingly, models performed better when calibrated but even so predictions were problematic for particular locations and constituents (e.g. runoff in NC under no-tillage conditions and sediment at many sites).
We continue to determine factors affecting the poor predictions of certain constituents (e.g. sediment or phosphorus) in different data sets and models. Calibration will continue for APEX and TBET. In addition, state phosphorus indices are being run for each data set. The results from each state’s phosphorus index will be compared against the modeled data as well as other state indices in order to learn if models such as APEX, TBET, and/or APLE can better determine field phosphorus losses than the indices. Final recommendations will be provided to USDA-NRCS.
Deanna Osmond, Professor, NC State University, Soil Science Department email@example.com
David Radcliffe and Adam Forsberg (University of GA), John Ramirez-Avila (MSU), Carl Bolster (ARS); Dan Storm and Aaron Mittelstet (OSU)
This is part of a symposium.
Thanks to our sponsor, USDA-NRCS grant 69-3A75-12-182.
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