Abstract

Calibrating process-based crop models in a timely manner is often challenging due to the extensive range of parameters involved. Sensitivity analysis (SA) is a useful practice for analyzing model uncertainty in these parameters. In this study, the Morris and extended Fourier Amplitude Sensitivity Test (E-FAST) methods were employed in sub-model level experiments. The yield outputs of WOFOST model under different climate conditions were used to evaluate the impact of altering model parameters in the modeling of Lycium barbarum L. The results indicate that parameters associated with CO2 assimilation rate, leaf area expansion and thermal time during specific periods have a significant impact on the simulated yield. The sensitive parameter rankings obtained from E-FAST exhibited good concordance across each planting site, and both SA methods consistently revealed similar rankings. This study provided a strategy to efficiently verify the applicability of new crop model parameters in different regions.

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