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Bayesian estimation of uncertainty in runoff prediction and the value of data : an application of the GLUE approach.

Freer, Jim and Beven, Keith J. and Ambroise, Bruno (1996) Bayesian estimation of uncertainty in runoff prediction and the value of data : an application of the GLUE approach. Water Resources Research, 32 (7). pp. 2161-2173. ISSN 0043-1397

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Abstract

This paper addresses the problem of evaluating the predictive uncertainty of TOPMODEL using the Bayesian Generalised Likelihood Uncertainty Estimation (GLUE) methodology in an application to the small Ringelbach research catchment in the Vosges, France. The wide range of parameter sets giving acceptable simulations is demonstrated, and uncertainty bands are presented based on different likelihood measures. It is shown how the distributions of predicted discharges are non-Gaussian and vary in shape through time and with discharge. Updating of the likelihood weights using Bayes equation is demonstrated after each year of record and it is shown how the additional data can be evaluated in terms of the way they constrain the uncertainty bands.

Item Type: Article
Journal or Publication Title: Water Resources Research
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Departments: Faculty of Science and Technology > Lancaster Environment Centre
ID Code: 22032
Deposited By: ep_ss_importer
Deposited On: 17 Feb 2009 16:51
Refereed?: Yes
Published?: Published
Last Modified: 26 Jul 2012 15:55
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/22032

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