Coupling and testing a new soil water module in DSSAT CERES-Maize model for maize production under semi-arid condition

• Developing a new version of CSM-CERES-Maize model by coupling SWAP and DSSAT package.
• Make an improvement in simulation of both averaged and final biomass for silage corn.
• Make an improvement in simulation of soil moisture in non-deficit condition.

Process-oriented crop simulation models are valuable tools for representing our understanding of the current and future states of a cropping system. The main objective of this research was to couple the Cropping System Model-(CSM)-Crop-Environment Resource Synthesis (CERES)-Maize (CSM-CERES-Maize) with the Soil, Water, Atmosphere, and Plant (SWAP) model in order to benefit from the advantages of both models. A new model was developed by replacing a simplified version of the SWAP with WatBal and SPAM modules of the Decision Support System for Agrotechnology Transfer (DSSAT) version 4.0. In this hybrid model, the CERES-Maize supplied the SWAP model with plant growth variables. Meanwhile, the SWAP model provided the CERES-Maize model with daily evapotranspiration, soil water content, and root water uptake. The model was then validated with a dataset including four irrigation levels (two deficit levels along with one full and one over-irrigation level), and three nitrogen levels (0, 150, and 200 kg/ha nitrogen) obtained from a field experiment in 2003 and 2004. The root mean square errors (RMSE) across all treatments in the simulation of final biomass were, respectively, 1175 and 2148 kg/ha in the first year and 1274 and 1514 kg/ha in the second year for the hybrid and original version of CERES-Maize model. Average RMSE for two non-water stress treatments was 1.29 and 1.35 cm in the simulation of soil water content for hybrid and original models, respectively. In general, our findings indicated that the new hybrid model was fairly successful in biomass simulation, which was due to better soil water simulations of all four irrigation levels except severe deficit irrigation.