Sensitivity Analysis of the WOFOST Crop Model Parameters Using the EFAST Method and Verification of Its Adaptability in the Yellow River Irrigation Area, Northwest China

Abstract

Sensitivity analysis, calibration, and verification of crop model parameters improve crop model efficiency and accuracy, facilitating its application. This study selected five sites within the Ningxia Yellow River Irrigation Area. Using meteorological data, soil data, and field management information, the EFAST (Extended Fourier Amplitude Sensitivity Test) method was used to conduct first-order and global sensitivity analyses of spring wheat parameters in the WOFOST (World Food Studies Simulation) Model. A Structural Equation Model (SEM) analyzed the contribution of crop parameters to different simulation indices, with parameter sensitivity rankings being discussed under varying water supply and climate conditions. Finally, the adapted WOFOST model was employed to assess its applicability in the Ningxia Yellow River Irrigation Area. TMNFTB3.0 (correction factor of total assimilation rate at 3 °C), SPAN (life span of leaves growing at 35 °C), SLATB0 (specific leaf area in the initial period), and CFET (correction factor transpiration rate) showed higher sensitivity index for most simulation indices. Under the same meteorological conditions, different water supply conditions have a limited impact on crop parameter sensitivity, mainly affecting leaf senescence, leaf area, and assimilate conversion to storage organs. The corrected crop parameters significantly enhanced the wheat yield simulation accuracy by the WOFOST model (ME = 0.9964; RMSE = 0.2516; MBE = 0.1392; R2 = 0.0331). The localized WOFOST model can predict regional crop yield, with this study providing a theoretical foundation for its regional application, adjustment, and optimization.