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Abstract. Cropping system models are considered useful tools to estimate the impact of climate and environment on agriculture production, and to improve the management of agricultural systems. These crop models are calibrated and evaluated before applying to a new geographical location. In this study, two process based crop models APSIM and CERES-Wheat models were selected to determine their feasibility to simulate the wheat crop production in Guanzhong Plain in China by using calibration, evaluation and sensitivity analysis with experimental local data. Crop models were calibrated by adopting standard procedure and protocols. Models performance was evaluated based on the criteria of statistical analysis including coefficient of determination (R²), normalized root mean square error (nRMSE), and d-index. Experimental data was collected from a past study conducted in the same Guanzhong Plain where different irrigation and nitrogen levels treatments were tested during wheat growing season of 2009-2010, 2010-2011 and 2011-2012. APSIM and CERES-Wheat model calibration results of grain yield, biomass, and leaf area index varied between 1.4-14.1 % during three growing seasons. During calibration, APSIM grain yield was underestimated than CERES-Wheat while biomass and leaf area index was overestimated than CERES-Wheat model. APSIM and CERES-Wheat during the evaluation simulated aboveground biomass, grain yield, LAI, canopy nitrogen, cumulative evapotranspiration, water use efficiency and nitrogen fertilizer productivity, and deviations from the observed were reasonable with nRMSE less than 21%. Sensitivity analysis of both models showed that grain yield in CERES-Wheat was more sensitive to field capacity and in APSIM grain yield was quite sensitive to nitrogen application rate. Mean ensemble model results showed reduced uncertainty for different crop parameter, especially the grain yield differences were reduced by 0.73-4.1% compared to observed yield. Therefore, it can be concluded, that both APSIM and CERES models seem to be suitable for simulating wheat crop parameters in Guanzhong Plain based on calibration, evaluation, sensitivity analysis and ensemble model approach.