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Journal of Environmental Quality Abstract - Short Communications

Simulating Nitrate-Nitrogen Concentration from a Subsurface Drainage System in Response to Nitrogen Application Rates Using RZWQM2


This article in JEQ

  1. Vol. 41 No. 1, p. 289-295
    Received: June 3, 2011

    * Corresponding author(s): Zhiming.Qi@ars.usda.gov
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  1. Zhiming Qi *a,
  2. Liwang Maa,
  3. Matthew J. Helmersb,
  4. Lajpat R. Ahujaa and
  5. Robert W. Malonec
  1. a USDA–ARS, Agricultural Systems Research Unit, Fort Collins, CO 80526
    b Dep. of Agricultural and Biosystems Engineering, Iowa State Univ., Ames, IA 50011
    c USDA–ARS, National Lab. for Agriculture and the Environment, Ames, IA 50011. Assigned to Associate Editor Nathan Nelson


Computer models have been widely used to evaluate the impact of agronomic management on nitrogen (N) dynamics in subsurface drained fields. However, they have not been evaluated as to their ability to capture the variability of nitrate-nitrogen (NO3–N) concentration in subsurface drainage at a wide range of N application rates due to possible errors in the simulation of other system components. The objective of this study was to evaluate the performance of Root Zone Water Quality Model2 (RZWQM2) in simulating the response of NO3–N concentration in subsurface drainage to N application rate. A 16-yr field study conducted in Iowa at nine N rates (0–252 kg N ha−1) from 1989 to 2004 was used to evaluate the model, based on a previous calibration with data from 2005 to 2009 at this site. The results showed that the RZWQM2 model performed “satisfactorily” in simulating the response of NO3–N concentration in subsurface drainage to N fertilizer rate with 0.76, 0.49, and −3% for the Nash-Sutcliffe efficiency, the ratio of the root mean square error to the standard deviation, and percent bias, respectively. The simulation also identified that the N application rate required to achieve the maximum contaminant level for the annual average NO3–N concentration was similar to field-observed data. This study supports the use of RZWQM2 to predict NO3–N concentration in subsurface drainage at various N application rates once it is calibrated for the local condition.

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