Back
 ENG  Vol.13 No.8 , August 2021
Modeling of Different Irrigation Methods for Maize Using AquaCrop Model: Case Study
Abstract: Modeling of irrigation methods is one of the most important techniques that contribute to the future of modern agriculture. This will conserve water as water scarcity is a major threat for agriculture. In this study, AquaCrop model was used to model different irrigation methods of maize in field trails in Al-Yousifya, 15 km Southwest of Baghdad. Field experiments were conducted for two seasons during 2016 and 2017 using five irrigation methods including furrow, surface drip and subsurface drip with three patterns of emitter depth (10, 20 and 30 cm) irrigation. AquaCrop simulations of biomass, grain yield, harvest index and water productivity were validated using different statistical parameters under the natural conditions obtained in the study area. For 2016 and 2017 seasons, results of R2 were 0.98 and 0.99, 0.99 and 0.99, 0.99 and 0.97, and 0.8 and 0.73 for biomass, grain yield, harvest index and water productivity, respectively. The study has conducted that simulation using AquaCrop is considered very efficient tool for modeling of different irrigation applications for maize production under the existing conditions in the central region of Iraq.
Cite this paper: Thamer, T. , Nassif, N. , Almaeini, A. , Al-Ansari, N. and Hassan, D. (2021) Modeling of Different Irrigation Methods for Maize Using AquaCrop Model: Case Study. Engineering, 13, 472-492. doi: 10.4236/eng.2021.138034.
References

[1]   Ewaid, S.H., Kadhum, S.A., Abed, S.A. and Salih, R.M. (2019) Development and Evaluation of Irrigation Water Quality Guide Using IWQG V. 1 Software: A Case Study of Al-Gharraf Canal, Southern Iraq. Environmental Technology & Innovation, 13, 224-232. https://doi.org/10.1016/j.eti.2018.12.001

[2]   Hirich, A., Ragab, R., Choukr-Allah, R. and Rami, A. (2014) The Effect of Deficit Irrigation with Treated Wastewater on Sweet Corn: Experimental and Modeling Study Using SALTMED Model. Irrigation Science, 32, 205-219.
https://doi.org/10.1007/s00271-013-0422-0

[3]   Iraqi Ministry of Planning (2017) Agricultural Sector Production Report, Water and Land, Animal and Plant Production. Iraqi Ministry of Planning.

[4]   Chandra, R., Takeuchi, H. and Hasegawa, T. (2012) Methane Production from Lignocellulosic Agricultural Crop Wastes: A Review in Context to Second Generation of Biofuel Production. Renewable and Sustainable Energy Reviews, 16, 1462-1476.
https://doi.org/10.1016/j.rser.2011.11.035

[5]   Ibrahim, F. and de Niamey, U.A.M. (2020) Scheduling Supplementary Irrigation for Maize Production: Analysis of the Requirements for Climate Smart Farming for Rural Development. Open Access Library Journal, 7, 1-16.
https://doi.org/10.4236/oalib.1106942

[6]   Al-Maeini, A.H. and Nehaba, R.S. (2007) Effect of Irrigation Frequency and Plant Distribution on the Growth and Yield of Corn (Zea mays L). Anbar Journal of Agricultural Sciences, 5, 85-100.

[7]   Erkossa, T., Awulachew, S.B. and Aster, D. (2011) Soil Fertility Effect on Water Productivity of Maize in the Upper Blue Nile Basin, Ethiopia. Agricultural Sciences, 2, 238.
https://doi.org/10.4236/as.2011.23032

[8]   Beyranvand, H., Farnia, A., Nakhjavan, S.H. and Shaban, M. (2013) Response of Yield and Yield Components of Maize (Zea mayz L.) to Different Bio Fertilizers. International Journal of Advanced Biological and Biomedical Research, 1, 1068-1077.

[9]   Alfalahi, A.A., Al-Abodi, H.M.K., Abdul Jabbar, B.K., Muhdi, A.M. and Sulman, K.A. (2015) Scheduling Irrigation as a Water Saving Practice for Corn (Zea mays L.) Production in Iraq. IInternational Journal of Applied Agricultural Sciences, 1, 55-59.
https://doi.org/10.11648/j.ijaas.20150103.12

[10]   Farooq, M., Hussain, M., Ul-Allah, S. and Siddique, K.H. (2019) Physiological and Agronomic Approaches for Improving Water-Use Efficiency in Crop Plants. Agricultural Water Management, 219, 95-108.
https://doi.org/10.1016/j.agwat.2019.04.010

[11]   Valipour, M., Sefidkouhi, M.A.G. and Eslamian, S. (2015) Surface Irrigation Simulation Models: A Review. International Journal of Hydrology Science and Technology, 5, 51-70. https://doi.org/10.1504/IJHST.2015.069279

[12]   Mistry, P., Akil, M., Suryanarayana, T.M.V. and Parekh, F.P. (2017) Evaluation of Drip Irrigation System for Different Operating Pressures. International Journal of Advance Engineering and Research Development, 1, 63-69.

[13]   Lamm, F.R., Bordovsky, J.P., Schwankl, L.J., Grabow, G.L., Enciso-Medina, J., Peters, R.T., Colaizzi, P.D., Trooien, T.P. and Porter, D.O. (2012) Subsurface Drip Irrigation: Status of the Technology in 2010. Transactions of the ASABE, 55, 483-491.
https://doi.org/10.13031/2013.41387

[14]   Akumaga, U., Tarhule, A. and Yusuf, A.A. (2017) Validation and Testing of the FAO AquaCrop Model under Different Levels of Nitrogen Fertilizer on Rainfed Maize in Nigeria, West Africa. Agricultural and Forest Meteorology, 232, 225-234.
https://doi.org/10.1016/j.agrformet.2016.08.011

[15]   de la Casa, A., Ovando, G., Bressanini, L. and Martínez, J. (2013) Aquacrop Model Calibration in Potato and Its Use to Estimate Yield Variability under Field Conditions. Atmospheric and Climate Sciences, 3, 397-407.
https://doi.org/10.4236/acs.2013.33041

[16]   Raja, W.R., Habib, K., and Purshotum, S. (2018) Validating the AquaCrop Model for Maize under Different Sowing Dates. Water Policy, 20, 826-840.
https://doi.org/10.2166/wp.2018.123

[17]   Jin, X., Li, Z., Feng, H., Ren, Z. and Li, S. (2020) Estimation of Maize Yield by Assimilating Biomass and Canopy Cover Derived from Hyperspectral Data into the AquaCrop Model. Agricultural Water Management, 227, Article ID: 105846.
https://doi.org/10.1016/j.agwat.2019.105846

[18]   Heng, L.K., Hsiao, T., Evett, S., Howell, T. and Steduto, P. (2009) Validating the FAO AquaCrop Model for Irrigated and Water Deficient Field Maize. Agronomy Journal, 101, 488-498. https://doi.org/10.2134/agronj2008.0029xs

[19]   Greaves, G.E. and Wang, Y.M. (2016) Assessment of FAO AquaCrop Model for Simulating Maize Growth and Productivity under Deficit Irrigation in a Tropical Environment. Water, 8, 557. https://doi.org/10.3390/w8120557

[20]   Sandhu, R. and Irmak, S. (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 Conditions. Agricultural Water Management, 224, Article ID: 105753.
https://doi.org/10.1016/j.agwat.2019.105753

[21]   Abedinpour, M., Sarangi, A., Rajput, T.B.S., Singh, M., Pathak, H. and Ahmad, T. (2012) Performance Evaluation of AquaCrop Model for Maize Crop in a Semi-Arid Environment. Agricultural Water Management, 110, 55-66.
https://doi.org/10.1016/j.agwat.2012.04.001

[22]   Khalaf, A.A. and Ham, D.S.A.D. (2019) Assessment of Aquacrop Model in Prediction Maize Hybirds Yield by Simulation Production under Deficit Irrigation. Journal of Duhok University, 22, 7-23. https://doi.org/10.26682/avuod.2019.22.1.2

[23]   Shah, A.H., Khan, M.F. and Khaliq, A. (2003) Genetic Characterization of Some Maize (Zea mays L.) Varieties Using SDS-PAGE. Asian Journal of Plant Sciences, 2, 1188-1191. https://doi.org/10.3923/ajps.2003.1188.1191

[24]   Zhao, Y., Li, F., Wang, Y. and Jiang, R. (2020) Evaluating the Effect of Groundwater Table on Summer Maize Growth Using the AquaCrop Model. Environmental Modeling & Assessment, 25, 343-353.
https://doi.org/10.1007/s10666-019-09680-y

[25]   Wolka, K., Biazin, B., Martinsen, V. and Mulder, J. (2021) Soil and Water Conservation Management on Hill Slopes in Southwest Ethiopia. II. Modeling Effects of Soil Bunds on Surface Runoff and Maize Yield Using AquaCrop. Journal of Environmental Management, 296, Article ID: 113187.
https://doi.org/10.1016/j.jenvman.2021.113187

[26]   Ran, H., Kang, S., Li, F., Du, T., Tong, L., Li, S., Zhang, X., et al. (2018) Parameterization of the AquaCrop Model for Full and Deficit Irrigated Maize for Seed Production in Arid Northwest China. Agricultural Water Management, 203, 438-450.
https://doi.org/10.1016/j.agwat.2018.01.030

[27]   He, Q., Li, S., Hu, D., Wang, Y. and Cong, X. (2020) Performance Assessment of the AquaCrop Model for Film-Mulched Maize with Full Drip Irrigation in Northwest China. Irrigation Science, 39, 277-292.
https://doi.org/10.1007/s00271-020-00705-z

[28]   SAS, J. (2012) Statistical Analysis System. v. 10.0. 2, Cary, North Carolina.

[29]   Ibrahim, H.I. and Juma, S.S. (2021) Effect of Mineral Fertilization and Humic Acids on Availability of NPK in Soil and Maize Growth. Annals of the Romanian Society for Cell Biology, 25, 11414-11418.

[30]   Vermeiren, L. and Jobling, G.A. (1980) Localized Irrigation: Design, Installation, Operation, Evaluation. FAO, Rome.

[31]   Kovda, V.A., Berg, C.V.D. and Hagan, R.M. (1973) Irrigation, Drainage and Salinity: An International Source Book. FAO, Rome.

[32]   Allen, R.G., Pereira, L.S., Raes, D. and Smith, M. (1998) Crop Evapotranspiration Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper No. 56, FAO, Rome.

[33]   Howell, C.R. (2003) Mechanisms Employed by Trichoderma Species in the Biological Control of Plant Diseases: The History and Evolution of Current Concepts. Plant disease, 87, 4-10. https://doi.org/10.1094/PDIS.2003.87.1.4

[34]   Katerji, N., Campi, P. and Mastrorilli, M. (2013) Productivity, Evapotranspiration, and Water Use Efficiency of Corn and Tomato Crops Simulated by AquaCrop under Contrasting Water Stress Conditions in the Mediterranean Region. Agricultural Water Management, 130, 14-26.
https://doi.org/10.1016/j.agwat.2013.08.005

[35]   Willmott, C.J. (1982) Some Comments on the Evaluation of Model Performance. Bulletin of the American Meteorological Society, 63, 1309-1313.
https://doi.org/10.1175/1520-0477(1982)063<1309:SCOTEO>2.0.CO;2

[36]   Hsiao, T.C., Heng, L., Steduto, P., Rojas-Lara, B., Raes, D. and Fereres, E. (2009) Aqua-Crop—The FAO Crop Model to Simulate Yield Response to Water: III. Parameterization and Testing for Maize. Agronomy Journal, 101, 448-459.
https://doi.org/10.2134/agronj2008.0218s

[37]   Steduto, P., Hsiao, T.C., Raes, D. and Fereres, E. (2009) AquaCrop—The FAO Crop Model to Simulate Yield Response to Water: I. Concepts and Underlying Principles. Agronomy Journal, 101, 426-437.
https://doi.org/10.2134/agronj2008.0139s

[38]   Mebane, V.J., Day, R.L., Hamlett, J.M., Watson, J.E. and Roth, G.W. (2013) Validating the FAO AquaCrop Model for Rainfed Maize in Pennsylvania. Agronomy Journal, 105, 419-427. https://doi.org/10.2134/agronj2012.0337

[39]   Wu, D., Xu, X., Chen, Y., Shao, H., Sokolowski, E. and Mi, G. (2019) Effect of Different Drip Fertigation Methods on Maize Yield, Nutrient and Water Productivity in Two-Soils in Northeast China. Agricultural Water Management, 213, 200-211.
https://doi.org/10.1016/j.agwat.2018.10.018

[40]   Mansour, H.A., Hu, J., Pibars, S., Bao, H. F. and Liang, C. (2019) Effect of Pipes Installation by Modified Machine for Subsurface Drip Irrigation System on Maize Crop Yield Costs. Agricultural Engineering International: CIGR Journal, 21, 98-107.

[41]   Wang, D., Li, G., Mo, Y., Zhang, D., Xu, X., Wilkerson, C.J. and Hoogenboom, G. (2021) Evaluation of Subsurface, Mulched and Non-Mulched Surface Drip Irrigation for Maize Production and Economic Benefits in Northeast CHINA. Irrigation Science, 39, 159-171. https://doi.org/10.1007/s00271-020-00692-1

[42]   Stricevic, R., Cosic, M., Djurovic, N., Pejic, B. and Maksimovic, L. (2011) Assessment of the FAO AquaCrop Model in the Simulation of Rainfed and Supplementally Irrigated Maize, Sugar Beet and Sunflower. Agricultural Water Management, 98, 1615-1621. https://doi.org/10.1016/j.agwat.2011.05.011

[43]   Babel, M.S., Deb, P. and Soni, P. (2019) Performance Evaluation of AquaCrop and DSSAT-CERES for Maize under Different Irrigation and Manure Application Rates in the Himalayan Region of India. Agricultural Research, 8, 207-217.
https://doi.org/10.1007/s40003-018-0366-y

[44]   Anzoua, K.G., Junichi, K., Toshihiro, H., Kazuto, I. and Yutaka, J. (2010) Genetic Improvements for High Yield and Low Soil Nitrogen Tolerance in Rice (Oryza sativa L.) under a Cold Environment. Field Crops Research, 116, 38-45.
https://doi.org/10.1016/j.fcr.2009.11.006

[45]   Guo, D., Zhao, R., Xing, X. and Ma, X. (2020) Global Sensitivity and Uncertainty Analysis of the AquaCrop Model for Maize under Different Irrigation and Fertilizer Management Conditions. Archives of Agronomy and Soil Science, 66, 1115-1133.
https://doi.org/10.1080/03650340.2019.1657845

[46]   Paredes, P., de Melo-Abreu, J.P., Alves, I. and Pereira, L.S. (2014) Assessing the Performance of the FAO AquaCrop Model to Estimate Maize Yields and Water Use under Full and Deficit Irrigation with Focus on Model Parameterization. Agricultural Water Management, 144, 81-97.
https://doi.org/10.1016/j.agwat.2014.06.002

[47]   Zhu, X., Xu, K., Liu, Y., Guo, R. and Chen, L. (2021) Assessing the Vulnerability and Risk of Maize to Drought in China Based on the AquaCrop Model. Agricultural Systems, 189, Article ID: 103040. https://doi.org/10.1016/j.agsy.2020.103040

 
 
Top