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Detection of structural inadequacy in process-based hydrological models : a particle-filtering approach.

Smith, Paul and Beven, Keith J. and Tawn, Jonathan A. (2008) Detection of structural inadequacy in process-based hydrological models : a particle-filtering approach. Water Resources Research, 44 (1). W01410. ISSN 0043-1397

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Abstract

In recent years, increasing computational power has been used to weight competing hydrological models in a Bayesian framework to improve predictive power. This may suggest that for a given measure of association with the observed data, one hydrological model is superior to another. However, careful analyses of the residuals of the model fit are required to propose further improvements to the model. In this paper we consider an alternative method of analyzing the shortcomings in a hydrological model. The hydrological model parameters are treated as varying in time. Simulation using a particle filter algorithm then reveals the parameter distribution needed at each time to reproduce the observed data. The resulting parameter, and the corresponding model state, distributions can be analyzed to propose improvements to the hydrological model. A demonstrative example is presented using rainfall-runoff data from the Leaf River, United States. This indicates that even when explicitly representing the uncertainty of the observed rainfall and discharge series, the technique shows shortcomings in the model structure.

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
Faculty of Science and Technology > Mathematics and Statistics
ID Code: 27354
Deposited By: Mr Richard Ingham
Deposited On: 20 Oct 2009 10:26
Refereed?: Yes
Published?: Published
Last Modified: 09 Apr 2014 20:29
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/27354

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