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Global sensitivity analysis (SA) has become an efficient way to identify the most influential parameters on model results. However, the effects of cultivar variation and specific-stage variations of climate conditions on model outputs still remain unclear. In this study, 30 indica hybrid rice cultivars were simulated in the CERES-Rice model; then the Sobol’ method was used to perform a global SA on 16 investigated parameters for three model outputs (anthesis day, maturity day, and yield). In addition, we also compared the differences in the sensitivity results under four specific-stage variations (vegetative phase, panicle-formation phase, ripening phase, and the whole growth season) of climate conditions. The results indicated that (1) parameter Tavg, G4, and P2O are the most influential parameters for all model outputs across cultivars during the whole growth season; (2) under the vegetative-phase variation of climate parameters; the variability of model outputs is mainly controlled by parameter P2O and Tavg; (3) under the panicle-formation-phase or ripening-phase variation of climate parameters, parameter P2O was the dominant variable for all model outputs; (4) parameter PORM had a considerable effect (the total sensitivity index, STi; STi&gt;0.05) on yield regardless of the various specific-stage variations of the climate parameters. Findings obtained from this study will contribute to understanding the comprehensive effects of crop parameters on model outputs under different cultivars and specific-stage variations of climate conditions.

Global Sensitivity Analysis for CERES-Rice Model under Different Cultivars and Specific-Stage Variations of Climate Parameters