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Water shortage is a chronic problem in arid Northwest China, where agriculture cannot exist without irrigation. Efficient irrigation and water uses are important to sustainable development and management of water resources in the region. This paper applied DSSAT-maize v4.5 to the Yingke Irrigation District in the middle reach oasis of the Heihe River Watershed in Northwest China to explore the optimal irrigation strategies under different climatic conditions, and to improve the beneficial water consumption and reduce non-beneficial water consumption while maintaining yields at the same time. The model was first calibrated based on the crop yield, phenological phases and soil water content data, and good agreements were achieved between the simulated and observed data in both the calibration and validation periods. In the calibration period, the simulated maize phenological phases differed by two days of the observed phases, and nRMSE (normalized root mean square errors) for grain yield was 6%. In the validation period, the values of nRMSE of yield were 4.95% in 2006 and 2.96% in 2008, respectively, while the RMSE for soil water content ranged from 0.118 to 0.046. Subsequently the calibrated model was used to simulate the effects of planting dates and different irrigation treatments on maize yield and the potentially reduced water amount was calculated. Results show that in the Yingke Irrigation District, the best planting dates range from early April to mid-April, and the best irrigation periods are the jointing and tassel phases. The optimal irrigation amounts vary under different climatic conditions, ranging from about 1000 m(3)/ha, to 4200 m(3)/ha, and to 4800 m(3)/ha in wet, normal and dry years respectively. Nearly half of the irrigation amount could be reduced under the simulated irrigation schedule for the district. Once validated by field tests, the simulated irrigation scenarios would provide partial basis for effective water resources management in the study area. (C) 2016 Elsevier B.V. All rights reserved.