Agricultural irrigation water shortages are a significant concern for water and food security. However, few studies have improved our understanding of seasonal irrigation water deficit (IWD) and its influencing factors. In this study, we used a well-calibrated coupled carbon-water model (PML-V2) and the bias-corrected output of a hydrological model (WaterGAP 2.2d), along with remote sensing data, to quantify the amount and trend of IWD from 2003-2018 in northern China, a region experiencing severe water scarcity. We also identified the dominant factors influencing IWD by setting up five simulation scenarios. The results revealed that the IWD exhibited notable temporal-spatial heterogeneity across northern China. The highest levels of IWD occurred in spring in Huang-Huai-Hai Plain and Loess Plateau and in summer in Arid/Semi-arid North region. From 2003-2018, the IWD exhibited a significant increasing trend (0.20 mm month(-1) year(-1), p < 0.05) across northern China. We determined that changes in planting structure had the most important impact on IWD, whereas precipitation had the least impact within the entire region. However, the dominant drivers varied by region: climate was the primary driver in Northeast Plain (53%) and in Huang-Huai-Hai Plain (47%), whereas planting structure was the primary driver in Loess Plateau (53%) and in Arid/Semi-arid North region (89%). Our findings enhance the understanding of IWD conditions and their dominant drivers in northern China, providing valuable insights for irrigation water management and crop system adjustments to ensure water and food security.