Abstract: Water and nitrogen are the key influencing factors on the N₂O emissions in the farmland ecosystem cycle, particularly in the dry wheat fields. However, it is often required for the accurate and rapid analysis of the parameter sensitivity in the crop model, in order to enhance the model efficiency and application. This study aims to explore the sensitivity of water and nitrogen factors to the output variables, including the N₂O emission parameters in the agricultural production systems simulator (APSIM) crop model. The extended Fourier amplitude sensitivity Test (EFAST) was employed to verify the simulation. The spring wheat variety, 'Dingxi 35' was taken as the research subject. Five gradients of nitrogen application were set as 0, 55, 110, 150, and 220 kg/hm². Additionally, three gradients of supplemental irrigation were set as 0, 50, and 100 mm. A global sensitivity analysis was conducted on the nine parameters of the crop variety, thirteen soil parameters, and four meteorological parameters related to the soil N₂O emissions in dryland wheat fields within the APSIM model. The results indicated that the photoperiodic sensitivity index (PS) was the most sensitive parameter to the N₂O emissions under different water and nitrogen treatments. The average values in the global sensitivity index of the PS were 0.518, 0.548, and 0.57, respectively. Their sensitivity decreased with the increasing nitrogen application, whereas, there was an increase with the supplemental irrigation. Furthermore, the soil bulk density (BD) was identified as the most sensitive parameter on the N₂O emissions in dry wheat fields under water and nitrogen conditions. The average values in the global sensitivity index of the BD were 0.324, 0.301, and 0.427, respectively. Overall, their sensitivity increased with the higher nitrogen application rates and supplemental irrigation. The maximum daily temperature (Max) was found to be the most sensitive meteorological parameter to the N₂O emissions. The average values in the global sensitivity index of Max were 0.554, 0.477, and 0.537, respectively. Their sensitivity generally decreased with the increasing nitrogen application rates, but there was a trend of the first decreasing and then increasing with the supplemental irrigation rates. Notably, there was a great variation in the meteorological parameters on the much smaller values of the N₂O flux output in the APSIM model, compared with the crop variety and soil parameters. This finding can provide valuable insights into the sensitivity contributions of the soil N₂O emission parameters in the APSIM model. A theoretical basis can also offer a strong reference to calibrate the parameters for applicability and simulation accuracy in the study area. Additionally, the scientific foundation can be gained for water and nitrogen management in dry wheat fields.