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Parameter and modeling uncertainty simulated by GLUE and a formal Bayesian method for a conceptual hydrological model
Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan, China.
Department of Geosciences, University of Oslo, Norway.
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, Jiangsu, China.
Department of Biological and Agricultural Engineering, Texas A & M University, Scoates Hall,TAMU, USA.
2010 (English)In: Journal of Hydrology, ISSN 0022-1694, E-ISSN 1879-2707, Vol. 383, no 3-4, 147-155 p.Article in journal (Refereed) Published
Abstract [en]

Quantification of uncertainty of hydrological models has attracted much attention in hydrologic research in recent years. Many methods for quantification of uncertainty have been reported in the literature, of which GLUE and formal Bayesian method are the two most popular methods. There have been many discussions in the literature concerning differences between these two methods in theory (mathematics) and results, and this paper focuses on the computational efficiency and differences in their results, but not on philosophies and mathematical rigor that both methods rely on. By assessing parameter and modeling uncertainty of a simple conceptual water balance model (WASMOD) with the use of GLUE and formal Bayesian method, the paper evaluates differences in the results of the two methods and discusses the reasons for these differences. The main findings of the study are that: (1) the parameter posterior distributions generated by the Bayesian method are slightly less scattered than those by the GLUE method; (2) using a higher threshold value (>0.8) GLUE results in very similar estimates of parameter and model uncertainty as does the Bayesian method; and (3) GLUE is sensitive to the threshold value used to select behavioral parameter sets and lower threshold values resulting in a wider uncertainty interval of the posterior distribution of parameters, and a wider confidence interval of model uncertainty. More study is needed to generalize the findings of the present study. (C) 2010 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
2010. Vol. 383, no 3-4, 147-155 p.
Keyword [en]
Conceptual hydrological model, Uncertainty, Bayesian method, GLUE
National Category
Earth and Related Environmental Sciences
URN: urn:nbn:se:uu:diva-140463DOI: 10.1016/j.jhydrol.2009.12.028ISI: 000276532700001OAI: oai:DiVA.org:uu-140463DiVA: diva2:383663
Available from: 2011-01-05 Created: 2011-01-05 Last updated: 2013-01-29Bibliographically approved

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