Optimization of irrigation scheduling for maize in arid regions Northwest China based on water stress diagnosis in models.

Water stress is an important factor affecting maize yield in arid areas. By optimizing the irrigation scheduling for maize based on water stress conditions, precise and efficient irrigation could be achieved. Based on the sensitivity analysis, calibration, and validation of parameters in the Soil Water Air Plant (SWAP) model, a SWAP-IES assimilation simulation system was constructed by integrating SWAP and IES (Iterative ensemble smother). The water stress coefficient Ws was calculated to reflect the water stress status experienced by maize throughout its entire growth period, and the irrigation amount and cycle of the experimental design were adjusted according to Ws. During the calibration and validation process, the SWAP model achieved a high level of accuracy in simulating maize LAI, plant height, biomass, and yield, with NRMSE ranging from 8.01% to 18.37%. The experiment showed that the Ws of maize in each treatment had remained below 1 throughout the entire growth period, indicating that the maize had been in a state of water stress, especially after 80 days of emergence, with Ws ranging from 0.07-0.60. According to different strategies, the optimized maize irrigation quota in the Yellow River irrigation area of Ningxia was 357.29 mm - 462.55 mm, and the irrigation water utilization efficiency was 2.82 kg/m3 - 3.37 kg/m3, achieving the goal of water conservation and high efficiency.