Modelling dissolved phosphorus losses from accumulated soil phosphorus and applied fertilizer and manure for a national risk indicator

Author:

Reid Keith1,Schneider Kimberley2

Affiliation:

1. Science and Technology Branch, Agriculture and Agri Food Canada, 174 Stone Road W., Guelph, ON N1G 4S9, Canada.

2. Department of Plant Agriculture, University of Guelph, Guelph, ON N1G 2W1, Canada.

Abstract

Balancing the weighting of various components of phosphorus loss in models is a critical but often overlooked step in accurate estimation of risk of P loss under field conditions. This study compared the P loss coefficients used to predict dissolved P losses from desorption from accumulated P in the soil, and those incidental to applications of P as fertilizer or manure, with extraction coefficients determined from actual P losses reported in literature for sites in Canada, with the addition of some sites with similar soils and climate from some northern states. The extraction coefficients for dissolved P measured in runoff water were 6.5× greater in year-round edge-of-field (EoF) measurements than in runoff boxes, indicating that models using P extraction coefficients derived from runoff box experiments will be underestimating the magnitude of losses from P accumulation in soil. Differences among the measurement methods (runoff box, rainfall simulator, or EoF) were not evident for incidental losses from applied P, but current models appear to overpredict the losses of applied P. Good agreement between measured and predicted dissolved P (DP) concentrations using the equations in the Annual Phosphorous Loss Estimator model were achieved by applying coefficients of 0.275 to the fertilizer equations and 0.219 to the manure equations, implying that 72.5% of fertilizer P and 78% of manure P are not available for runoff. This study underlines the importance of considering the relative weights of the various components of P loss as new models are developed and validated.

Publisher

Canadian Science Publishing

Subject

Soil Science

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