The increase in irrigated maize plantings in Northern China has increased the demand for irrigation water in the region, resulting in chronic water shortages in drier years. Efficient irrigation and water use are essential for the sustainable development and management of water resources in the area. This research applied DSSAT-maize in the Loess Plateau (Fenhe basin) to determine the suitable irrigation management and optimum sowing dates to ensure the stability of spring maize production. The model was calibrated using the full irrigation treatment of 2017–2019 growing seasons. Crop data, such as plant phenological phases, aboveground biomass, crop yield, and leaf area index, were used for model calibration. The calibration showed great consistency between the measured and simulated data, with nRMSE (normalized root mean square error) ranging from 0.77% to 21.6%. The field values of crop yield, aboveground biomass, LAI, soil water content, and water use efficiency were used to evaluate the calibrated model’s performance, the model evaluation was found to be satisfactory with acceptable nRMSE ranging from 1.9% to 25.3%. Optimum simulated sowing dates for increased productivity and water efficiency were between 15 and 25 May. The optimum irrigation timing and volume of irrigation water application were 85 mm at the tasseling phase and 85 mm at the grouting phase respectively. Therefore, the yield of maize can be increased by applying irrigation and altering the sowing date in case rainfall is insufficient to satisfy the water demand of the crops in the Fenhe basin.