Integrated Bayesian Multi-model approach to quantify input, parameter and conceptual model structure uncertainty in groundwater modeling

Mustafa, SyedNossent, JiriGhysels, GertHuysmans, Marijke2021-02-132021-02-132020-04Mustafa, S, Nossent, J, Ghysels, G & Huysmans, M 2020, 'Integrated Bayesian Multi-model approach to quantify input, parameter and conceptual model structure uncertainty in groundwater modeling', Environmental Modelling and Software, vol. 126, 104654. https://doi.org/10.1016/j.envsoft.2020.1046541364-8152https://hdl.handle.net/2164/15863We thank Prof. Jasper Vrugt from University of California, Irvine, USA for his advice on the implementation of BMA. A draft version of a conference abstract appears online at AgEng2018.com but has not been published. The data used in this study are summarized and presented in the figures, tables, references and supporting information and will be available from the authors upon request (syed.mustafa@vub.be).172065434engConceptual model structure uncertaintyBayesian approachinput uncertaintyBayesian model averaginguncertainty quantificationgroundwater flow modelENSEMBLEMANAGEMENTUncertainty quantificationDROUGHTFLOWPREDICTIONGroundwater flow modelInput uncertaintyFRAMEWORKBASINMONTE-CARLO-SIMULATIONSELECTIONWATERTA Engineering (General). Civil engineering (General)SoftwareEcological ModellingEnvironmental EngineeringTAIntegrated Bayesian Multi-model approach to quantify input, parameter and conceptual model structure uncertainty in groundwater modelingJournal article10.1016/j.envsoft.2020.104654http://www.scopus.com/inward/record.url?scp=85079656289&partnerID=8YFLogxK126