Title: Combining Generalized Likelihood Uncertainty Estimation (GLUE) and Bayesian Model Averaging (BMA) to Account for Conceptual Model Uncertainty in Groundwater Modelling
Authors: ROJAS RodrigoFEYEN LUCDASSARGUES Alain
Citation: Proceedings of the 6th International Conference on Calibration and Reliability in Groundwater Modelling: Credibility in Modelling vol. 1 p. 1-6
Publisher: Geological Survey of Denmark and Greenland (GEUS)
Publication Year: 2007
JRC N°: JRC43542
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC43542
Type: Contributions to Conferences
Abstract: Conceptual model uncertainty is one of the most difficult problems to deal with in the practice of groundwater modelling. In recent years, several methodologies, based on the construction and calibration of alternative models, have been proposed to face this problem. In this article, a more general and flexible approach than those previously developed is described. We achieve this combining the generalized likelihood uncertainty estimation (GLUE) and the Bayesian model averaging (BMA) methodologies. Implementing the GLUE methodology ensures that a large set of acceptable simulators, i.e., conceptual models and parameter sets, are included in the analysis, therefore, avoiding compensation of the conceptual model errors and biased parameter estimates. Implementing the BMA approach allows the inclusion of previous knowledge about the system and the obtaining of consensus multi-model predictions. Preliminary results show that the approach provides a general and flexible framework to account for predictive uncertainty due to the specification of alternative conceptual models.
JRC Institute:Institute for Environment and Sustainability

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