Foxtail millet (Setaria italica), an ancient crop native to Northwest China, exhibits exceptional drought tolerance ecological adaptability, making it a strategic crop for sustainable agriculture under increasing water scarcity. However, the absence of reliable crop models tailored to foxtail millet limits precision irrigation management. This study establishes the first comprehensive parameter set for foxtail millet in the AquaCrop model and develops optimized irrigation strategies to enhance water use efficiency in water limited regions. A two-year deficit irrigation experiment (2022-2023) was conducted in Ningxia, China, using 9 irrigation treatments to calibrate and validate the AquaCrop-OS model. Key farmland state variables, including biomass, canopy cover, soil moisture, and yield, were monitored. Using 20-year meteorological data (1998-2017), 625 irrigation scenarios with stage-specific soil water thresholds were simulated to optimize trigger levels for four growth phases: emergence, expansion, maturity, and senescence. The AquaCrop model demonstrated high accuracy in simulating foxtail millet growth, with biomass, canopy cover, yield, and soil water storage (R-2 > 0.85, NRMSE < 10%) well estimated in validation period. Soil water simulations were reliable, with R-2 ranging from 0.75 to 0.97, though slight underestimations occurred under extreme drought treatments. Long-term simulations identified the optimal irrigation trigger thresholds for the four growth stages were 0%, 60%, 15%, and 0% of total available water (TAW) depletion, respectively. This strategy achieved a mean yield of 5.73 tha(- 1) and water productivity (WP) of 1.46 kgm(- 3), significantly improving yield stability while maintaining a multi-year average net irrigation water requirement (NIR) of only 69 mm. At the same time, the coefficient of variation (CV) reduced from 23.33% to 5.77% compared to rainfed conditions. Overall, this study provides the first validated AquaCrop parameter set for foxtail millet and introduces a threshold-triggered irrigation strategy that balances yield and water productivity. The approach offers a scalable solution for precision water management in arid regions, supporting climate-resilient millet production. Future work should integrate multi-stress factors and validate strategies under extreme climatic conditions.