This study evaluates the AquaCrop model for simulating grain yield and biomass of barley in the Sistan region, considering water resource limitations and varying climatic conditions. Data from four farms in the Zahak and Hirmand counties (Research Center, Khwaja Ahmad, Zurabad, and Deh-Laghari) were used over two cropping seasons (2023–2024 and 2024–2025). Three planting date scenarios—early (November 6), mid-season (December 6), and late (January 5)—and three irrigation levels (full irrigation, 25% deficit irrigation, and 50% deficit irrigation) were considered. Simulation results showed that the AquaCrop model can predict grain yield and biomass with high accuracy. During calibration, the R² values for grain yield and biomass ranged from 0.96 to 0.97, and during validation, R² ranged from 0.94 to 0.98 for grain yield and from 0.90 to 0.92 for biomass. The high coefficients of determination and low error statistics indicated that the model successfully simulated grain yield and biomass with strong accuracy. The sensitivity analysis indicated that canopy transpiration coefficient (Kc), normalized water productivity (WP*), and reference harvest index (HIo) were the most influential parameters in the model. Furthermore, the irrigation and planting date scenarios showed that in wet years, a 25% reduction in irrigation decreased yield by 5–7%. In normal years, reducing irrigation by 25% and 50% led to a 13–20% reduction in yield, and in dry years, a 25–50% reduction in irrigation caused a 45–48% decrease in grain yield.