【Objective】Climate change is likely to affect the crop yield, and in this paper we assess its impact on maize yield in Heihe Oasis in Northwest China based on the CCSM4 climate model.【Method】We applied the DSSAT-Maize model to Yingke Irrigation District - a typical irrigation district in the middle reach of the oasis of the Heihe River Watershed in Northwest China - to simulate the impact of RCP4.5 and RCP8.5 scenarios on maize production in the 21st century based on the CCSM4 climate provided by CMIP5. We then explored the optimal planting date to alleviate the impact of climate change.【Result】During maize growth period, temperature changed the most. It is estimated that by the end of the 21st century, the average temperature in the study area is likely to exceed 2.5 ℃under the RCP4.5 scenario and 7.3 ℃ under the RCP8.5 scenario. The simulated results showed that both yield and growth period of the maize will decrease under the two scenarios, especially under the RCP8.5 scenario in which the yield reduction was more remarkable. The maize yield under the RCP4.5 and RCP8.5 scenarios was estimated to reduce by about 15% and 29% respectively. Scenario simulation showed that the temperature was the main factor affecting the maize yield. The optimal average annual temperature for maize growth was around 7 ℃, and the yield of maize was negatively correlated with annual mean temperature when it exceeded 7 ℃, and the average temperature during the maize growth period was 10.5 ℃. We found that adjusting the sowing date could reduce the negative effects of climate change on maize yield. Simulated results from the DSSAT-Maize model showed that under climate change, for each 1 ℃ increase in the mean annual temperature from 7 to 12 ℃, its negative impact on maize yield could be reduced by shifting the sowing date to April 10th, April 8th, April 3th, March 30th, March 24th, and March 17th correspondingly.【Conclusion】Climate change will result in a reduction in maize production, but adjusting the snowing date will reduce its negative effect.