Application of CSM-CERES-Maize model in optimizing irrigated conditions

Maize is one of the main cereal crops in Pakistan with sensitivity to drought at various developmental stages known to influence the yield. The impact of variable weather conditions on maize yield can be analyzed with crop simulation models. The CSM-CERES-Maize model has been widely used to assess irrigation strategies for maize. This research was conducted to test the CSM-CERES-Maize model for its ability to accurately predict maize biomass and grain yield under water limiting and non-limiting conditions in semiarid conditions. Four growth stage-based irrigation treatments and two potential soil moisture deficit-based treatments were defined. During model calibration, the simulated maximum leaf area index (LAI), total dry matter (TDM), and grain yield were all within 10% of observed values. During model evaluation, there was generally satisfactory agreement between observed and simulated values for two hybrids (Monsanto-919 and Pioneer-30Y87) with the model showing variability of -17.9-20.0%, -9.2-14.3%, and -19.6-19.9% for maximum LAI, TDM, and grain yield, respectively, for the two hybrids among various treatments. The CERES-Maize model was useful in providing information to decision-making regarding diverse irrigation regimes at the farm level in a semiarid environment.