Irrigation buffers climate influence: Stable parameter sensitivities in APSIM-wheat under warm-temperate monsoon conditions

Sensitivity analysis is essential for prioritizing crop model parameters and improving calibration efficiency. Sensitivities can shift with water and nitrogen availability, but whether they remain stable under interannual climate variability when irrigation buffers water stress is unknown. Here, we conducted a Sobol global sensitivity analysis of APSIM-Wheat grain yield using daily climate records for 2000–2025 at Xinxiang, China, a representative warm-temperate, semi-humid East Asian monsoon site in the North China Plain wheat belt, under regionally typical farmer-managed irrigation. Total sensitivity indices (STi) differed markedly among cultivar parameters: initial_tpla was most influential (STi>0.8), followed by fr_lf_sen_rate and node_sen_rate (STi=0.7–0.8). photop_sens and grains_per_gram_stem showed moderate sensitivity (STi=0.6–0.7), whereas tt_end_of_juvenile and max_grain_size were lower (STi=0.55–0.6); y_rue was least sensitive (STi=0.45). Regressing annual STi against rainfall, maximum/minimum temperature, and solar radiation indicated weak and statistically non-significant relationships (|r|≤0.37, p ≥ 0.07). This stability occurred despite substantial interannual climate variability over the 25-year period, suggesting that parameter sensitivities were largely robust to interannual climate fluctuations, primarily because farmer irrigation consistently buffered water-stress variability. Moreover, Si/STi<0.5 for all parameters highlights that yield responses were dominated by parameter interactions rather than single-parameter effects. Overall, in warm-temperate, semi-humid monsoon wheat systems, yield calibration should prioritize canopy development and senescence parameters over climate-specific retuning, providing practical guidance for efficient and transferable APSIM-Wheat cultivar calibration under climate variability.