Using evaluated AquaCrop and Response Surface Method to determine optimum irrigation water and seeding density of wheat growing in a sprinkler irrigation system

Abstract

Abstract This study used AquaCrop to predict wheat grain yield under different irrigation and seeding densities. Experimental data from two successive growing seasons during 2004–2006 was used for model calibration and validation. After calibration, the model was used to predict grain yield for 47 years (1975–2021) with five seeding densities (120, 80, 160, 200, and 240 kg ha-1) and four irrigation schedules (7-, 10-, 13-, and 16-days interval). Predicted data were used to identify the optimal seeding density and irrigation water level. AquaCrop's simulations of grain yield, biomass, soil water content, evapotranspiration, and canopy cover were promising. Under extreme water stress, the model produced less reliable results. The RSM method determined the optimal seeding density and irrigation schedule to maximize crop yield and income per hectare. Results showed that 747, 198, and 747 mm of irrigation water and 211, 188, and 208 kg ha-1 of seeding density maximized wheat yield, water productivity, and profit per unit area, respectively. Additionally, 350 and 1230 mm of irrigation and rainfall and 162 and 212 kg ha-1 of seeding density were found to maximize water productivity and profit per unit area. Overall, this study demonstrates that the AquaCrop model can be used to accurately estimate wheat grain yield under different irrigation intensities and seeding densities, which can inform decisions on optimal irrigation and seeding practices for maximizing crop yield and profit.