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Using EPIC model to manage irrigated cotton and maize


  • Ko, Jonghan
  • Piccinni, Giovanni
  • Steglich, Evelyn


Simulation models are becoming of interest as a decision support system for management and assessment of crop water use and of crop production. The Environmental Policy Integrated Climate (EPIC) model was used to evaluate its application as a decision support tool for irrigation management of cotton and maize under South Texas conditions. Simulation of the model was performed to determine crop yield, crop water use, and the relationships between the yield and crop water use parameters such as crop evapotranspiration (ETc) and water use efficiency (WUE). We measured actual ETc using a weighing lysimeter and crop yields by field sampling, and then calibrated the model. The measured variables were compared with simulated variables using EPIC. Simulated ETc agreed with the lysimeter, in general, but some simulated ETc were biased compared with measured ETc. EPIC also simulated the variability in crop yields at different irrigation regimes. Furthermore, EPIC was used to simulate yield responses at various irrigation regimes with farm fields' data. Maize required ~700mm of water input and ~650mm of ETc to achieve a maximum yield of 8.5Mgha-1 while cotton required between 700 and 900mm of water input and between 650 and 750mm of ETc to achieve a maximum yield of 2.0-2.5Mgha-1. The simulation results demonstrate that the EPIC model can be used as a decision support tool for the crops under full and deficit irrigation conditions in South Texas. EPIC appears to be effective in making long-term and pre-season decisions for irrigation management of crops, while reference ET and phenologically based crop coefficients can be used for in-season irrigation management.

Suggested Citation

  • Ko, Jonghan & Piccinni, Giovanni & Steglich, Evelyn, 2009. "Using EPIC model to manage irrigated cotton and maize," Agricultural Water Management, Elsevier, vol. 96(9), pages 1323-1331, September.
  • Handle: RePEc:eee:agiwat:v:96:y:2009:i:9:p:1323-1331

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    References listed on IDEAS

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    Cited by:

    1. Popova, Zornitsa & Pereira, Luis S., 2011. "Modelling for maize irrigation scheduling using long term experimental data from Plovdiv region, Bulgaria," Agricultural Water Management, Elsevier, vol. 98(4), pages 675-683, February.
    2. Jiang, Yiwen & Zhang, Lanhui & Zhang, Baoqing & He, Chansheng & Jin, Xin & Bai, Xiao, 2016. "Modeling irrigation management for water conservation by DSSAT-maize model in arid northwestern China," Agricultural Water Management, Elsevier, vol. 177(C), pages 37-45.
    3. repec:eee:agiwat:v:188:y:2017:i:c:p:115-125 is not listed on IDEAS
    4. Tatsumi, Kenichi, 2016. "Effects of automatic multi-objective optimization of crop models on corn yield reproducibility in the U.S.A," Ecological Modelling, Elsevier, vol. 322(C), pages 124-137.


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