Prediction of NO 3-N losses in surface runoff from a field with seepage zones using GLEAMS and RZWQM

Adion Chinkuyu, Tom Meixner, Timothy Gish, Amir P. Nejadhashemi

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Seepage zones have been shown to be of critical importance in controlling contaminant export from agricultural watersheds. However, their impacts on water quality have not been effectively modeled. The Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) model and the Root Zone Water Quality Model (RZWQM) were used to predict daily and monthly nitrate-nitrogen (NO 3-N) concentration and loss in surface runoff from an agricultural field with seepage zones. The results of the study show that calibrated GLEAMS and RZWQM predicted daily NO 3-N concentration [index of agreement (D) > 0.57] in surface runoff from the field with seepage zones. Based on the different model evaluation techniques used in this study, both GLEAMS and RZWQM performed fairly well in assessing the effects of seepage zones on daily NO 3-N losses in surface runoff. However, GLEAMS (D = 0.93) performed relatively better than RZWQM (D = 0.45) in predicting NO 3-N loss in surface runoff on a monthly basis, while both GLEAMS and RZWQM performed equally well in predicting NO 3-N loss in surface runoff on a daily basis. Both models performed poorly in predicting NO 3-N concentration in surface runoff on a monthly basis (D < 0.44). Additionally, since neither model adequately simulated monthly NO 3-N concentration in surface runoff from the field with seepage zones, their ability in water quality modeling for such fields will be compromised, and further model evaluation and development is justified.

Original languageEnglish (US)
Pages (from-to)1779-1790
Number of pages12
JournalTransactions of the ASABE
Volume49
Issue number6
StatePublished - Nov 1 2006

Keywords

  • Model
  • NO -N
  • OPE
  • Runoff
  • Watershed

ASJC Scopus subject areas

  • Forestry
  • Food Science
  • Biomedical Engineering
  • Agronomy and Crop Science
  • Soil Science

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