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

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  • Seyed Ahmadi
  • Elnaz Mosallaeepour
  • Ali Kamgar-Haghighi
  • Ali Sepaskhah

Abstract

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. Copyright Springer Science+Business Media Dordrecht 2015

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  • Seyed Ahmadi & Elnaz Mosallaeepour & Ali Kamgar-Haghighi & Ali Sepaskhah, 2015. "Modeling Maize Yield and Soil Water Content with AquaCrop Under Full and Deficit Irrigation Managements," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2837-2853, June.
  • Handle: RePEc:spr:waterr:v:29:y:2015:i:8:p:2837-2853
    DOI: 10.1007/s11269-015-0973-3
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    5. Qaisar Saddique & Huanjie Cai & Jiatun Xu & Ali Ajaz & Jianqiang He & Qiang Yu & Yunfei Wang & Hui Chen & Muhammad Imran Khan & De Li Liu & Liang He, 2020. "Analyzing adaptation strategies for maize production under future climate change in Guanzhong Plain, China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(8), pages 1523-1543, December.
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    8. Tsakmakis, I.D. & Gikas, G.D. & Sylaios, G.K., 2021. "Integration of Sentinel-derived NDVI to reduce uncertainties in the operational field monitoring of maize," Agricultural Water Management, Elsevier, vol. 255(C).
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    10. Dhouib, M. & Zitouna-Chebbi, R. & Prévot, L. & Molénat, J. & Mekki, I. & Jacob, F., 2022. "Multicriteria evaluation of the AquaCrop crop model in a hilly rainfed Mediterranean agrosystem," Agricultural Water Management, Elsevier, vol. 273(C).
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    12. Sandhu, Rupinder & Irmak, Suat, 2019. "Performance of AquaCrop model in simulating maize growth, yield, and evapotranspiration under rainfed, limited and full irrigation," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    13. Feng, Dingrui & Li, Guangyong & Wang, Dan & Wulazibieke, Mierguli & Cai, Mingkun & Kang, Jing & Yuan, Zicheng & Xu, Houcheng, 2022. "Evaluation of AquaCrop model performance under mulched drip irrigation for maize in Northeast China," Agricultural Water Management, Elsevier, vol. 261(C).
    14. Martins, Minella A. & Tomasella, Javier & Rodriguez, Daniel A. & Alvalá, Regina C.S. & Giarolla, Angélica & Garofolo, Lucas L. & Júnior, José Lázaro Siqueira & Paolicchi, Luis T.L.C. & Pinto, Gustavo , 2018. "Improving drought management in the Brazilian semiarid through crop forecasting," Agricultural Systems, Elsevier, vol. 160(C), pages 21-30.
    15. Tsakmakis, I.D. & Kokkos, N.P. & Gikas, G.D. & Pisinaras, V. & Hatzigiannakis, E. & Arampatzis, G. & Sylaios, G.K., 2019. "Evaluation of AquaCrop model simulations of cotton growth under deficit irrigation with an emphasis on root growth and water extraction patterns," Agricultural Water Management, Elsevier, vol. 213(C), pages 419-432.
    16. Yuan, Chengfu & Feng, Shaoyuan & Huo, Zailin & Ji, Quanyi, 2019. "Effects of deficit irrigation with saline water on soil water-salt distribution and water use efficiency of maize for seed production in arid Northwest China," Agricultural Water Management, Elsevier, vol. 212(C), pages 424-432.
    17. Fawen Li & Dong Yu & Yong Zhao, 2019. "Irrigation Scheduling Optimization for Cotton Based on the AquaCrop Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 39-55, January.
    18. Sandhu, Rupinder & Irmak, Suat, 2019. "Assessment of AquaCrop model in simulating maize canopy cover, soil-water, evapotranspiration, yield, and water productivity for different planting dates and densities under irrigated and rainfed cond," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    19. Tan, Shuai & Wang, Quanjiu & Zhang, Jihong & Chen, Yong & Shan, Yuyang & Xu, Di, 2018. "Performance of AquaCrop model for cotton growth simulation under film-mulched drip irrigation in southern Xinjiang, China," Agricultural Water Management, Elsevier, vol. 196(C), pages 99-113.
    20. Zenebe, Mara Getachew & Fleskens, Luuk & Ritsema, Coen & Steenbergen, Frank, 2022. "Basin-wide productivity and livelihood analysis of flood-based agricultural systems in African drylands: A case study in the Fogera floodplain," Agricultural Water Management, Elsevier, vol. 261(C).
    21. Tinashe Lindel Dirwai & Aidan Senzanje & Tafadzwanashe Mabhaudhi, 2021. "Calibration and Evaluation of the FAO AquaCrop Model for Canola ( Brassica napus ) under Varied Moistube Irrigation Regimes," Agriculture, MDPI, vol. 11(5), pages 1-18, May.
    22. Zhang, Junpeng & Li, Kejiang & Gao, Yang & Feng, Di & Zheng, Chunlian & Cao, Caiyun & Sun, Jingsheng & Dang, Hongkai & Hamani, Abdoul Kader Mounkaila, 2022. "Evaluation of saline water irrigation on cotton growth and yield using the AquaCrop crop simulation model," Agricultural Water Management, Elsevier, vol. 261(C).
    23. Ahmadi, Seyed Hamid & Solgi, Shahin & Sepaskhah, Ali Reza, 2019. "Quinoa: A super or pseudo-super crop? Evidences from evapotranspiration, root growth, crop coefficients, and water productivity in a hot and semi-arid area under three planting densities," Agricultural Water Management, Elsevier, vol. 225(C).
    24. Marjan Aziz & Sultan Ahmad Rizvi & Muhammad Sultan & Muhammad Sultan Ali Bazmi & Redmond R. Shamshiri & Sobhy M. Ibrahim & Muhammad A. Imran, 2022. "Simulating Cotton Growth and Productivity Using AquaCrop Model under Deficit Irrigation in a Semi-Arid Climate," Agriculture, MDPI, vol. 12(2), pages 1-18, February.
    25. Zhang, Ting & Zuo, Qiang & Ma, Ning & Shi, Jianchu & Fan, Yuchuan & Wu, Xun & Wang, Lichun & Xue, Xuzhang & Ben-Gal, Alon, 2023. "Optimizing relative root-zone water depletion thresholds to maximize yield and water productivity of winter wheat using AquaCrop," Agricultural Water Management, Elsevier, vol. 286(C).

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