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To efficiently manage water resources in agriculture, the hydrologic model HYDRUS-1D and the crop growth model WOFOST were coupled to improve crop production prediction through accurate simulations of actual transpiration with a root water uptake method and soil moisture profile with the Richards equation during crop growth. An inverse modeling method, the shuffled complex evolution algorithm, was used to identify soil hydraulic parameters for simulating the soil moisture profile. The coupled model was validated by experimental study on irrigated wheat (Triticum aestivum L.) in the middle reaches of the Heihe River, northwest China, in a semiarid and arid region. Good agreement was achieved between the simulated actual evapotranspiration, soil moisture, and crop production and their respective field measurements under a realistic irrigation scheme. A water stress factor, actual root uptake with potential transpiration, is proposed as an indicator to guide irrigation. Numerical results indicated that the irrigation scheme guided by the water stress factor can save 27% of irrigation water compared with the current irrigation scheme. Based on the calibrated model, uncertainty and sensitivity analysis methods were used to predict the risk of wheat production loss with decreasing irrigation and to study the effects of coupled model parameters and environmental factors on wheat production. The analysis revealed that the most suitable groundwater depth for wheat growth is 1.5 m. These results indicate that the coupled model can be used for analysis of schemes for saving water and study of the interaction between crop growth and the hydrologic cycle.