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Agronomy Journal Abstract -

Evaluation of the Root Zone Water Quality Model for Conditions in Central Nebraska


This article in AJ

  1. Vol. 91 No. 2, p. 201-211
    Received: Dec 2, 1996

    * Corresponding author(s): dmartin2@unl.edu
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  1. Derrel L. Martin  and
  2. Darrell G. Watts
  1. Dep. of Biological Systems Engineering, L.W. Chase Hall, Univ. of Nebraska, Lincoln, NE 68583-0726



The Root Zone Water Quality Model (RZWQM) was evaluated for a region that has a long history of irrigated corn (Zea mays L.). Imprecise irrigation and plentiful fertilizer applications have contributed to the buildup of NO3-N in ground water, where concentrations often exceed 30 mg L−1. Experiments were conducted to evaluate the effects of management practices on corn yield, N uptake, plant biomass, leaf area development, soil water content, and soil N. Fieldmeasured results from 1992 were used to calibrate RZWQM. The model was evaluated by simulating three irrigation levels and five fertilizer rates for 1993 and 1994. The model simulated the soil water pattern satisfactorily during most of the growing season; however, the simulated soil profile water content was lower than field conditions in the spring and fall. Transpiration appears to be excessive when the leaf area index (LAI) is small. Simulated yields exceeded measured values, with the largest errors for small fertilizer applications in 1993 and for large fertilizer applications in 1994. The mean error between measured and modeled yields was 2.9 Mg ha−1, with a root mean square error (RMSE) equal to 46% of the mean yield for all treatments over the 3 years. Estimates of LAI and aboveground biomass were closer to measured values, with mean errors of 5% for leaf area and 1% for biomass. The relative RMSE for LAI and biomass was 26 and 17%, respectively. The model underestimated aboveground N uptake, with a mean error of 25 kg N ha−1 and a relative RMSE of 41%. While development of the comprehensive RZWQM has been constructive, improvements are still needed. Excessive depletions in the spring and fall overstate storage of off-season precipitation, and this leads to underestimating annual leaching losses. Combining excessive yield predictions with low N uptake estimates exaggerates the N use efficiency. These discrepancies will have a profound effect on the simulated impact of management practices. Leaching losses and yield effects will be understated, which may lead to development of policies that affect producers more severely than the model implies.

Published by the Agric. Res. Div. of the Univ. of Nebraska as Journal Series no. 11988.

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