Abstract: An AquaCrop model has been used to simulate the crop growth of the mulched farmland in the arid regions of Northwest China. This study aims to optimize the film-mulched maize growth dynamics for high adaptability and accuracy. Four-year field experiments (2018, 2019, 2023, and 2024) were conducted with three treatments: flat planting without film mulching (NM), flat planting with full film mulching (PM), and full film double ridge furrow sowing (BM). The temperature compensation was proposed to adjust the external meteorological inputs. A compensation coefficient was derived from the relationship between soil and air temperature under mulched conditions. The individual coefficients in the different growth stages were determined to compare with those in the entire growth period; Alternatively, temperature source replacement was implemented to replace daily extreme air temperatures with daily extreme soil temperatures, in order to directly deduce the model. The performance of the improved model was finally evaluated on the simulated and observed canopy cover, biomass, and yield using root mean square error (RMSE) and normalized root mean square error (NRMSE). The results showed that there was a significant correlation between the 20 cm soil and air temperature (P < 0.05) for the NM, PM, and BM treatments, with the determination coefficients (R²) ranging from 0.56 to 0.92. The mean slopes of the linear regression equations for the NM, PM, and BM were 0.77, 0.86, and 0.80, respectively. Compared with the NM, the warming performance was more pronounced under PM, followed by BM. Moreover, the PM and BM treatments significantly increased to accumulate the surface soil temperature, particularly from the seedling stage to pre-tasseling. There was a significantly different soil-air temperature in this period. The substantial compensation was then obtained to calculate the growing degree days. The heat accumulation was accelerated to shorten the duration from seedling emergence to tasseling. In both PM and BM treatments, the temperature compensation coefficient from sowing to seedling emergence (1.23-1.76) was greater than that from seedling emergence to tasseling (0.50-0.67). Moreover, the overall temperature compensation increment from sowing to tasseling (0.70-1.54 °C) was intermediate between that from sowing to seedling emergence (1.12-5.12 °C) and from seedling emergence to tasseling (0.57-1.13 °C). According to the temperature compensation, the NRMSE of canopy cover, biomass, and yield for the PM and BM treatments over four growing seasons was reduced from 3.1%-15.7%, 11.0%-20.6%, and 10.9-20.9% in the original model to 1.7%-10.2%, 10.3%-18.1%, and 3.7%-20.1%, respectively, with the maximum NRMSE improvement of 16.5%, in order to effectively enhance the simulation accuracy of mulched maize growth. With the temperature source replacement, the simulated biomass and yield NRMSE for the PM and BM treatments were improved from 11.0%-20.6% and 10.9%-23.0% in the original model to 10.3%-18.1% and 1.4%-17.4%, respectively. Compared with the temperature compensation approach, the temperature source replacement further reduced the biomass RMSE and NRMSE by 0-0.6 t/hm² and 0-4.1%, while the yield RMSE and NRMSE by 0-0.8 t/hm² and 0-7.9%, respectively. The accuracy of the AquaCrop model was enhanced to simulate the growth and development of the mulched maize, indicating more precise predictions of the growth dynamics. Both approaches were significantly improved to simulate the dynamic variations in the biomass and yield. The better performance was confirmed to incorporate the mulching-induced warming. The applicability of the model was extended to mulched agriculture in arid regions. The finding can also provide a reliable quantitative tool to evaluate the different mulching patterns and practices.