Emulator-based optimization of APSIM-Sugar using the results of sensitivity analysis performed with the software GEM-SA

In most countries where sugarcane is grown, new sugarcane varieties are frequently introduced to the market; however, the existing crop models are not frequently updated. Therefore, experiments are needed to parameterize and optimize crop and cultivar-specific parameters of crop models. In this study, we used GEM-SA -generated output files of a study conducted to perform emulator-based sensitivity analysis of the APSIM-Sugar model using GEM-SA software. We compared the accuracy of simulations performed with optimized parameters using four methods: (1) optimization of 26 parameters of the APSIM-sugar model, (2) optimization of the six most sensitive parameters of the APSIM-sugar model, (3) emulator-based optimization of 26 parameters of the APSIM-sugar model, and (4) emulator-based optimization of the six most sensitive parameters. We also evaluated the computational expensiveness of these optimization methods. The results showed that the emulator-based optimization methods provided fast results compared to optimization using APSIM simulations. Moreover, the emulator-based optimization of the six selected most sensitive parameters (which took only a few minutes) provided almost similar simulation results to those obtained with all optimized parameters using APSIM optimization, which took days. Considering the accuracy and computational complexity, we propose to perform the optimization of the most sensitive parameters using an emulator-based approach. Since the sensitivity analysis results were used in this study, this optimization process could be directly coupled with the emulator-based sensitivity analysis explained by Gunarathna et al. (2019c).