Abstract: Uncertainty in output of ORYZA2000 (a rice growth model) and sensitivities of model inputs were analyzed through global sensitivity analysis. The actual measured data was as the reference values, used for describing uncertainty in the model inputs. Results revealed high uncertainties in model output such as total above-ground dry matter (WAGT), leaf area index (LAI), leaf N content (NFLV) and weight of seed (WSO). The degree of variation in model outputs of LAI and WSO were more than 20% and 10% respectively. Among 17 analyzed inputs of ORYZA2000, the model variable of sowing time (EMD) had the highest index of sensitivity on model output. Errors in daily minimum temperature (TMIN), daily maximum temperature (TMAX) and daily sunshine hour (DHOUR), i.e. the driving variables of ORYZA200, had much influence on rice yield at mature. The fraction dry matter partitioned to leaves (FLVTB) had much effect on model outputs related to leaf and grain weight, so precision of FLVTB data should be put more attention for reducing uncertainty of yield estimation. The effects of integrating variables with 20% stochastic errors estimated from remote sensed on model outputs (WAGT and WSO) of ORYZA2000 were studied via global sensitivity analysis. Three scenarios of integrating variables (i.e. only LAI, only NFLV, or both of them) were simulated. Among three integrating scenarios, both LAI and NFLV simultaneously integrating with ORYZA2000 showed the highest adjusting effect on simulated WAGT and WSO, LAI alone showed the second highest, and NFLV alone showed the lowest. When WSO and WAGT are estimated integrating ORYZA2000 with variables inverted from remote sensing data, for all integrating scenarios remote sensing data on 70－80th day around after transplanting are more significant that need to be attained, and the remote sensing data before and after this time are also important and should be attained as well. Remote sensing data used for integrate with ORYZA2000 on the period of recovering after transplanting and the later mature of rice have no significance for WSO and WAGT estimation.