Kheir, A., Hassan, M. (2016). Performance Assessment of the Fao Aquacrop Model for Maize Yield, Biomass and Water Productivity Along the River Nile, Egypt. Journal of Soil Sciences and Agricultural Engineering, 7(10), 721-728. doi: 10.21608/jssae.2016.40363
A. Kheir; M. Hassan. "Performance Assessment of the Fao Aquacrop Model for Maize Yield, Biomass and Water Productivity Along the River Nile, Egypt". Journal of Soil Sciences and Agricultural Engineering, 7, 10, 2016, 721-728. doi: 10.21608/jssae.2016.40363
Kheir, A., Hassan, M. (2016). 'Performance Assessment of the Fao Aquacrop Model for Maize Yield, Biomass and Water Productivity Along the River Nile, Egypt', Journal of Soil Sciences and Agricultural Engineering, 7(10), pp. 721-728. doi: 10.21608/jssae.2016.40363
Kheir, A., Hassan, M. Performance Assessment of the Fao Aquacrop Model for Maize Yield, Biomass and Water Productivity Along the River Nile, Egypt. Journal of Soil Sciences and Agricultural Engineering, 2016; 7(10): 721-728. doi: 10.21608/jssae.2016.40363
Performance Assessment of the Fao Aquacrop Model for Maize Yield, Biomass and Water Productivity Along the River Nile, Egypt
1Soils, Water and Environment Research Institute; Agricultural Research Center, Giza, Egypt.
2Field Crops Research Institute; Agricultural Research Center, Giza, Egypt.
Abstract
Different three maize field experiments represent the main agro ecological zones (Sakha, Giza and Qena), including full and deficit irrigation, were conducted in Egypt along the river Nile. The last updated version of AquaCrop model was evaluated with maize yield and water productivity under different irrigation water treatments (1.2, 1, 0.8 and 0.6 from actual evapotranspiration ETc). The model was evaluated after parameterization using field observations relative to canopy cover (CC), total biomass and yield data as well as using conservative parameters. The treatments show highly agreement between measured and simulated values of CC except the highest severe irrigation treatment (I4). The determination coefficients are higher (R2>60), thus indicating that the CC model explains significantly the variance of observed CC values. Also, estimated errors are then small, with RMSE ranging between (0.3 to 13%), and d varying between 0.6 and 0.98. Also, the agreement between simulated and observed maize grain yield, final biomass and water productivity were good with R2, RMSE and d. Results cleared that the model is considered a good decision support tool for exploring irrigation management and maize production in Egypt. Nevertheless, the model showed slightly uncertainty specially under sever deficit irrigation. It is supposed that, AquaCrop would be useful if it included some calibrated parameters about root distribution system in soil, because it is a water driven model and relies mainly on soil water balance and uptake.
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