Global sensitivity analysis of CERES-Wheat model parameters

Crop growth models have been applied extensively in the regional crop yield prediction and estimation. It is very important to select the most sensitive model parameters for the model optimization and better model output. The Extend Fourier Amplitude Sensitivity Test (EFAST) was used to analyze the sensitivity of CERES-Wheat model parameters in a study region in Luoyang, Henan province. The sensitivity of crop and field management parameters were analyzed. The results show that these parameters including the interval between successive leaf tip appearances, days at optimum vernalizing temperature required to complete vernalization, percentage reduction in development rate in a photoperiod 10 hour shorter than the threshold relative to that at the threshold, standard kernel size under optimum conditions, kernel number per unit canopy weight at anthesis are the key sensitive parameters which should be firstly selected for the model localization. The optimal parameters selected for application of model in regional scale are planting date, planting density, fertilization date, planting depth and irrigation date. The research showed that the global sensitivity analysis in EFAST is effective for parameter selection in the crop growth model optimization to improve its performance at regional scale.