Skip to main navigation Skip to search Skip to main content

Applicability of Models to Predict Phosphorus Losses in Drained Fields: A Review

  • David E. Radcliffe
  • , D. Keith Reid
  • , Karin Blombäck
  • , Carl H. Bolster
  • , Amy S. Collick
  • , Zachary M. Easton
  • , Wendy Francesconi
  • , Daniel R. Fuka
  • , Holger Johnsson
  • , Kevin King
  • , Mats Larsbo
  • , Mohamed A. Youssef
  • , Alisha S. Mulkey
  • , Nathan O. Nelson
  • , Kristian Persson
  • , John J. Ramirez-Avila
  • , Frank Schmieder
  • , Douglas R. Smith

Publication: Contribution to journal › Journal article › peer-review

Abstract

Most phosphorus (P) modeling studies of water quality have focused on surface runoff loses. However, a growing number of experimental studies have shown that P losses can occur in drainage water from artificially drained fields. In this review, we assess the applicability of nine models to predict this type of P loss. A model of P movement in artificially drained systems will likely need to account for the partitioning of water and P into runoff, macropore flow, and matrix flow. Within the soil profile, sorption and desorption of dissolved P and filtering of particulate P will be important. Eight models are reviewed (ADAPT, APEX, DRAINMOD, HSPF, HYDRUS, ICECREAMDB, PLEASE, and SWAT) along with P Indexes. Few of the models are designed to address P loss in drainage waters. Although the SWAT model has been used extensively for modeling P loss in runoff and includes tile drain flow, P losses are not simulated in tile drain flow. ADAPT, HSPF, and most P Indexes do not simulate flow to tiles or drains. DRAINMOD simulates drains but does not simulate P. The ICECREAMDB model from Sweden is an exception in that it is designed specifically for P losses in drainage water. This model seems to be a promising, parsimonious approach in simulating critical processes, but it needs to be tested. Field experiments using a nested, paired research design are needed to improve P models for artificially drained fields. Regardless of the model used, it is imperative that uncertainty in model predictions be assessed.
Original languageEnglish
Pages (from-to)614-628
Number of pages15
JournalJournal of Environmental Quality
Volume44
Issue number2
DOIs
Publication statusPublished - 2015

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation
  2. SDG 15 - Life on Land
    SDG 15 Life on Land

Cite this