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ABSTRACT
A groundwater field is a complex and open system. Groundwater simulation and prediction often deviated from true values, which is attributed to the uncertainty of groundwater modeling. The conceptual model (model struture) is one of the main sources of groundwater modeling uncertianty. In this study, the mean Euclidean distance (MED) between model simulations and observations is proposed to assess the integrated likelihood value of a conceptual model in Bayesian model averaging (BMA). Moreover, this proposed BMA method is compared with the traditional generalized likelihood uncertainty estimation (GLUE) BMA method by a synthetical groundwater model, and the characteristics of these two BMA methods are summarized.