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Updates to the Annual P Loss Estimator (APLE) model.

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The Annual P Loss Estimator (APLE) model now estimates runoff and accounts for input uncertainties using the Curve Number method and Monte Carlo simulations. This provides a more realistic prediction of phosphorus loss and soil test P changes.

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Area of Science:

  • Agricultural Science
  • Environmental Modeling
  • Soil Science

Background:

  • The Annual P Loss Estimator (APLE) is a user-friendly, empirical model for predicting phosphorus (P) loss and soil test P changes.
  • APLE's limitations include the inability to calculate runoff and its deterministic nature, which ignores input uncertainties.

Purpose of the Study:

  • To enhance the APLE model by incorporating runoff estimation and uncertainty analysis.
  • To provide users with a more realistic assessment of P loss and soil test P dynamics.

Main Methods:

  • Modified APLE (ver. 3.0) to include runoff estimation via the Curve Number method.
  • Implemented Monte Carlo simulations to quantify model input uncertainties.
  • Applied the revised model to P loss and soil test P data from Mississippi and Maryland.

Main Results:

  • The updated APLE successfully estimated runoff and quantified uncertainties in P loss predictions.
  • Case studies demonstrated the model's utility in assessing P dynamics under different scenarios.
  • Incorporating uncertainty analysis yielded a more realistic understanding of model performance.

Conclusions:

  • The revised APLE (ver. 3.0) offers improved P loss and soil test P change estimations by integrating runoff calculation and uncertainty analysis.
  • This enhanced model provides valuable insights for agricultural management and environmental protection.
  • The approach highlights the importance of accounting for uncertainties in environmental modeling.