The effects of climate change on yield and quality for different climate regions had high uncertainty. Risk assessment is an effective measure to assess the seriousness of the projected impacts for decision-makers. The modified quality model was used to simulate integrated impacts of climate change, environment and management on wheat yield and quality. Then, the Canadian Earth System Model (CanESM2) was used to forecast the daily meteorological data, and Statistical Down Scaling Model was used for downscaling. CERES-Wheat was combined with the forecasted meteorological data to simulate the future wheat yield and grain protein concentration (GPC). The risk of wheat yield and quality in three climatic regions of Shaanxi combined with two climate change scenarios of CanESM2 were assessed. Temperature increased 0.22-3.34 °C and precipitation increased 10-60 mm for RCP4.5 and RCP8.5. Elevated temperature and precipitation had positive effects on yield in all regions. The yield risk of most regions with climate change decreased 3.8%-25.1%. The GPC risk of all regions with climate change decreased 7.3%-27.2%. Irrigation decreased yield risk greatly in all regions, while had totally different effects for the three climatic regions. Yield risk with irrigation decreased 37.7%-52.1% in different climate. In contrast to previous studies, GPC risk with irrigation increased greatly 25.8%-28.9% in humid region, 3.9%-8.8% in sub-humid region, and decreased 37.7%-52.1% in semi-arid region. Climate change decreased yield risk and GPC risk together. While irrigation decreased yield risk greatly in all regions, had totally different effects for the three climatic regions.

Flour yield determined the profitability of flour mill, but the intrinsic variability of the grain makes it very complex to analysis and estimate wheat grain flour yield. Simulation for flour yield attributes offer considerable advantages in flour mill, if reliable predictions of flour yield can be provided, because the wheat grain characteristics can be tested before milling. If this is possible, the characteristics thus observed could be quantified more reliably and objectively by Structural Equation Modelling (SEM). SEM was used to look for the most important wheat grain characteristics on flour yield, and then these wheat grain characteristics were used to simulate flour yield. Furthermore, the regressive equation was verified by the field experiment. The coefficient of variation of grain characteristics was low and distributed rather closely. The results of SEM showed that test weight had the most significantly effects on flour yield, followed by the hardness index. Test weight and hardness index could excellently estimate flour yield by multiplicative effect of test weight and hardness index, and which could determine 68% of the variation in flour yield. The simulation result can not only predict flour yield, but also look for the important grain characteristics for the flour yield.