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Title: Prediction of NO3-N losses in surface runoff from a field with seepage zones using GLEAMS and RZWQM

Author
item CHINKUYU, ADION - MD DEPT. OF ENVIRONMENT
item MEIXNER, THOMAS - UNIV. OF AZ
item Gish, Timothy
item NEJADHASHEMI, AMIR - UNIV. OF MD

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/20/2006
Publication Date: 1/20/2007
Citation: Chinkuyu, A., Meixner, T., Gish, T.J., Nejadhashemi, A. 2007. Prediction of N03-N losses in surface runoff from a field with seepage zones using GLEAMS and RZWQM. Transactions of the American Society of Agricultural and Biological Engineers. 49(6):1779-1790.

Interpretive Summary: Two water quality models, the Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) and the Root Zone Water Quality Model (RZWQM) were used to predict daily and monthly nitrate concentrations and losses in surface runoff from an agricultural field with seepage zones. Seepage zones are common in agricultural lands bordering riparian wetlands and signify a process whereby subsurface water reemerges to the surface. Neither model predicted daily or monthly nitrate concentrations well. However, GLEAMS and RZWQM did a better job of predicting monthly and daily nitrate runoff losses. Furthermore, GLEAMS performed relatively better than the RZWQM though neither models performance was statistically satisfactorily. Since neither model simulated monthly nitrate 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.

Technical Abstract: 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 (NO3-N) concentrations and losses in surface runoff from an agricultural field with seepage zones. Three statistical terms were used to evaluate model performance, relative percent error, the coefficient o determination, and the index of agreement. Results show that calibrated GLEAMS and RZWQM where poor predictors of daily or monthly NO3-N concentrations in surface runoff from a field with seepage zones. Although GLEAMS and RZWQM performed about the same in predicting daily nitrate losses, GLEAMS was much better at predicting monthly nitrate runoff losses. Since neither model simulated monthly NO3-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.