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This article in AJ

  1. Vol. 91 No. 2, p. 212-219
     
    Received: Dec 2, 1996
    Published: Mar, 1999


    * Corresponding author(s): farahani@lily.aerc.colostate.edu
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doi:10.2134/agronj1999.00021962009100020007x

Seasonal Evaluation of the Root Zone Water Quality Model in Colorado

  1. Hamid J. Farahani ,
  2. Gerald W. Buchleiter,
  3. Lajpat R. Ahuja,
  4. Gary A. Peterson and
  5. Lucretia A. Sherrod
  1. U SDA-ARS, Great Plains Systems Res. Unit, 301 S. Howes, Fort Collins, CO 80522
    D ep. of Soil and Crop Sciences, Colorado State Univ., Fort Collins, 80526

Abstract

Abstract

Evaluation of agricultural simulation models against field observations is needed to gauge their usefulness. This study was conducted to assess the ability of the Root Zone Water Quality Model (RZWQM) to simulate dryland and irrigated corn (Zea mays L.) production systems in semiarid eastern Colorado. The model was first parameterized for corn using field data from a single season. Different parameters were identified for irrigated and dryland corn. The parameterized model was run on independent data sets from the following year (irrigated) and different soils and sites (dryland) and model results were compared with field measurements. Differences between modeled and measured components of soil water content, evapotranspiration, grain yield and biomass, and crop N uptake ranged from 1 to 23% in the dryland study and from 1 to 28% in the irrigated study. On a seasonal basis, model estimates of seepage below the root zone were within 3% of measured values, while NO3−N leaching was overpredicted by 79%. Note that model parameterization relied solely on single-season data. This could potentially produce bias in parameter values due to the narrowness of the prevailing conditions during that single season. For this reason and for the purpose of using the model to assess the long-term impact of alternative practices, further work on parameterization and evaluation of the model needs to focus on using experimental observations from multiple seasons.

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