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Modeling Maize Yield and Soil Water Content with AquaCrop Under Full and Deficit Irrigation Managements

The AquaCrop model was used to simulate maize growth and soil water content under full and deficit irrigation managements as 1.2, 1, 0.8, and 0.6 of the potential crop water requirement. Generally, the RMSEs in simulating soil water content in calibration and validation were 0.01–0.039 and 0.012–0.0...

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Bibliographic Details
Published in:Water resources management 2015-06, Vol.29 (8), p.2837-2853
Main Authors: Ahmadi, Seyed Hamid, Mosallaeepour, Elnaz, Kamgar-Haghighi, Ali Akbar, Sepaskhah, Ali Reza
Format: Article
Language:English
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Summary:The AquaCrop model was used to simulate maize growth and soil water content under full and deficit irrigation managements as 1.2, 1, 0.8, and 0.6 of the potential crop water requirement. Generally, the RMSEs in simulating soil water content in calibration and validation were 0.01–0.039 and 0.012–0.037 m 3 m −3 , respectively, that overall corresponds to 3–14 % error. For the in-season biomass development, the RMSEs in calibration varied between 2.16 and 2.73 Mg ha −1 , while they varied between 1.97 and 5.19 Mg ha −1 in validation for the four irrigation managements. The model showed poor performance for simulating biomass late in the season under deficit irrigation managements. The RMSEs of final grain yield simulation were 0.71 and 1.77 Mg ha −1 that corresponded to 7 and 18 % error in calibration and validation, respectively. Likewise, the RMSEs for simulating the final biomass in calibration and validation were 1.29 and 2.21 Mg ha −1 that equals to 6 and 10 % error, respectively. Results demonstrated that AquaCrop is a useful decision-making tool for investigating deficit irrigations and maize growth in the region. However, in agreement with the findings in earlier studies on AquaCrop, the model showed insufficient accuracy in simulating final grain yield and biomass under moderate to severe water stresses. It is suggested that AquaCrop would benefit of including some calibrating parameters about the root distribution pattern in the soil because it is a water-driven model and highly depends on the accurately simulated water uptake from the soil profile.
ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-015-0973-3