Embracing Equifinality with Efficiency:Limits of Acceptability Sampling Using the DREAM(LOA) algorithm

Vrugt, J. A. and Beven, Keith John (2018) Embracing Equifinality with Efficiency:Limits of Acceptability Sampling Using the DREAM(LOA) algorithm. Journal of Hydrology, 559. pp. 954-971. ISSN 0022-1694

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Official URL: https://doi.org/10.1016/j.jhydrol.2018.02.026

Abstract

This essay illustrates some recent developments to the DiffeRential Evolution Adaptive Metropolis (DREAM) MATLAB toolbox of Vrugt, 2016 to delineate and sample the behavioural solution space of set-theoretic likelihood functions used within the GLUE (Limits of Acceptability) framework (Beven and Binley, 1992; Beven and Freer, 2001; Beven, 2006 ; Beven et al., 2014). This work builds on the DREAM(ABC) algorithm of Sadegh and Vrugt, 2014 and enhances significantly the accuracy and CPU-efficiency of Bayesian inference with GLUE. In particular it is shown how lack of adequate sampling in the model space might lead to unjustified model rejection.

Item Type:

Journal Article

Journal or Publication Title:

Journal of Hydrology

Additional Information:

This is the author’s version of a work that was accepted for publication in Journal of Hydrology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Hydrology, 559, 2018 DOI: 10.1016/j.hydrol.2018.02.026

Uncontrolled Keywords:

/dk/atira/pure/subjectarea/asjc/2300/2312

Subjects:

Departments:

Faculty of Science and Technology > Lancaster Environment Centre

ID Code:

123541

Deposited By:

ep_importer_pure

Deposited On:

27 Feb 2018 09:56

Refereed?: