Context. Investigating agronomic responses of dryland maize (Zea mays L.) systems under global change could provide important insights in designing climate-resilient cropping systems.

Aims and methods. In this study, we integrated Agricultural Production Systems sIMulator (APSIM) with Representative Concentration Pathways 8.5 and 20 Global Climate Models to systematically: (1) calibrate and validate APSIM using large-field study conducted in East-Central Texas; (2) evaluate the impacts of climate change on maize productivity and risks; and (3) investigate the variations in growth stage lengths.

Key results. Results indicated that APSIM simulated grain yield, biomass production, precipitation productivity (PP; kg ha^-1 mm^-1) and developmental stage transition agreed well with observation (NRMSE < 14.9%). Changes in temperature and precipitation shortened growing seasons and affected available water, resulting in widely varied yield and PP. Mean grain yield changed from -34.8 to +19.7%, mean PP were improved 9.2-36.5%. The grain production could be maintained at least the standard of 75% of historical in most cases, but with greater risks for achieving higher threshold (50% of baseline). Finally, simulations indicated shortened days (4-13 days) for reaching key developmental stages for maize.

Conclusions and implications. The results advocate adoptions of management practice that incorporating early sowing, irrigations at sowing/VT stages, and selections of late-maturing cultivars for better sustainability and higher productivity.