{"refrec":{"BRefID":321741,"RR":"<b>Mustafa, S.M.T; Nossent, J.; Ghysels, G.; Huysmans, M.</b> (2020). Integrated Bayesian Multi-model approach to quantify input, parameter and conceptual model structure uncertainty in groundwater modeling. <i>Environ. Model. Softw. 126</i>: 104654. <a href=\"https://dx.doi.org/10.1016/j.envsoft.2020.104654\" target=\"_blank\">https://dx.doi.org/10.1016/j.envsoft.2020.104654</a>","BEntID":315181,"PublicFlag":1,"CheckedFlag":0,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>Environ. Model. Softw. 126</i>: 104654. <a href=\"https://dx.doi.org/10.1016/j.envsoft.2020.104654\" target=\"_blank\">https://dx.doi.org/10.1016/j.envsoft.2020.104654</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Mustafa, S.M.T; Nossent, J.; Ghysels, G.; Huysmans, M.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Mustafa, S.M.T <i>et al.</i>","Englishabstract":"A flexible Integrated Bayesian Multi-model Uncertainty Estimation Framework (IBMUEF) is presented to simultaneously quantify conceptual model structure, input and parameter uncertainty of a groundwater flow model. In this fully Bayesian framework, the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm with a novel likelihood function is combined with Bayesian Model Averaging (BMA). Four alternative conceptual models, representing different geological representations of an overexploited aquifer, have been developed. 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