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The nitrogen (N) transport and transformation processes in rice field is more complex than that in dry land. Process-based soil-rice system model requires many input parameters and it is difficult to calibrate, which severely restricts the model application in rice production region. To improve the calibration efficiency and reduce uncertainty in simulations, both Morris and Sobol’ methods were used to analyze the global sensitivities of input parameters (soil hydraulic, crop, and N transformation parameters) of the WHCNS_Rice model and guide model calibration. Two years of rice field experiments were conducted in the middle reaches of the Yangtze River. Ponding water depth, evapotranspiration (ET), dry matter weight and crop N uptake were all collected and used to evaluate the model. Results showed that the selected sensitive parameters were almost consistent for two methods, but the Morris method could quickly and effectively screen out sensitive parameters with small calculation workload, which is an effective global sensitivity analysis method for the WHCNS_Rice model. Among all model input parameters, the soil hydraulic parameters and crop parameters had the greatest influence on the output variables of crop growth, water and N fates compared with N transformation parameters. Within the soil hydraulic parameters, saturated moisture, field capacity and saturated hydraulic conductivity of the plowpan were the most sensitive parameters. For crop parameters, LAI, yield, dry matter weight, crop N uptake and ET were sensitive to total accumulated temperature, maximum specific leaf area and crop coefficient in different periods. Among the N turnover parameters, only the first order kinetic constant for volatilization and the denitrification empirical coefficient had some effects on ammonia volatilization and denitrification processes, respectively. Based on the results of sensitivity analysis, the sensitive parameters were calibrated to minimize error between simulated and observed measurements. The results showed that the simulated dry matter weight, crop N uptake, ET and ponding water depth were in good agreement with the measured values. Both the slopes of the linear regression equation and correlation coefficients between the simulated and measured values were close to 1 (P<0.01), indicating that the model could be used to simulate soil water movement, soil N fates, and rice growth for paddy soil in the region. These results suggested that sensitivity analysis based on the Morris method can significantly improve the model calibration efficiency and reduce uncertainty in simulation, which provided technical support for parameter calibration and application of the process-based WHCNS_Rice model.