Application of the generalized likelihood uncertainty estimation (GLUE) approach for assessing uncertainty in hydrological models: A review

Mirzaei, M. and Huang, Y.F. and El-Shafie, A. and Shatirah, A. (2015) Application of the generalized likelihood uncertainty estimation (GLUE) approach for assessing uncertainty in hydrological models: A review. Stochastic Environmental Research and Risk Assessment, 29 (5). pp. 1265-1273. ISSN 1436-3240

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Abstract

The generalized likelihood uncertainty estimation (GLUE) technique is an innovative uncertainty method that is often employed with environmental simulation models. Over the past years, hydrological literature has seen a large increase in the number of papers dealing with uncertainty. There are now a lot of citations to their original paper which illustrates GLUE tremendous impact. GLUE's popularity can be attributed to its simplicity and its applicability to nonlinear systems, including those for which a unique calibration is not apparent. The GLUE was introduced for use in uncertainty analysis of watershed models has now been extended well beyond rainfall-runoff watershed models. Given the widespread adoption of GLUE analyses for a broad range or problems, it is appropriate that the validity of the approach be examined with care. In this article, we present an overview of the application of GLUE for assessing uncertainty distribution in hydrological models particularly surface and subsurface hydrology and briefly describe algorithms for sampling of the prior parameter in hydrologic simulation models.

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Uncontrolled Keywords: Uncertainty, glue, hydrological modeling, rainfall-runoff modeling, water quality, groundwater, flood frequency estimation, water-quality, environmental systems, continuous simulation, input uncertainty, bayesian-analysis, chaohe basin, methodology, sensitivity, calibration,
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 20 Apr 2016 02:23
Last Modified: 20 Apr 2016 02:23
URI: http://eprints.um.edu.my/id/eprint/15788

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