Abstract: There are many parameters in the ecosystem model.The variability of parameters at different space-time scales resulted in uncertainties.The uncertainty analysis of parameters could help to understand the structure of the model deeply and improve the reliability of the model predictions.The Vegetation Interface Processes(VIP) model is an ecohydrology dynamic model,which includs energy budget,hydrology cycle,absorption and transformation of carbon and nitrogen in the terrestrial ecosystem.In this paper,the generalized likelihood uncertainty estimation(GLUE) methodology was used to analyze the uncertainty of the parameters.In the VIP model,we chose eight parameters,which came from the crop growth module,soil water dynamic process and photosynthesis module.An index of agreement was chosen to be the likelihood weight.The field data(LAI,biomass,soil water content etc.) in the North China Plain were used.The results showed that maximum catalytic activity of Rubisco,saturated water content and field capacity were sensitive parameters,which influenced the value of likelihood weight greatly.The others were non-sensitive parameters.Almost all the observations approached were included in the confidence interval with the 95% confidence level,which indicated that better simulations could be got by calibrating the model parameters.

Key words: GLUE methodology, GLUE methodology, VIP model, Prediction uncertainty, Sensitive parameters