An advanced regularization methodology for use in watershed model calibration

Doherty, J. E. and Skahill, B. E. (2006) An advanced regularization methodology for use in watershed model calibration. Journal Of Hydrology, 327 3-4: 564-577.


Author Doherty, J. E.
Skahill, B. E.
Title An advanced regularization methodology for use in watershed model calibration
Journal name Journal Of Hydrology   Check publisher's open access policy
ISSN 0022-1694
Publication date 2006
Sub-type Article (original research)
DOI 10.1016/j.jhyrol.2005.11.058
Volume 327
Issue 3-4
Start page 564
End page 577
Total pages 14
Editor C Neal (Editor-in-Chief)
M Sophocleous (Editor-in-Chief)
R Krzysztofowicz (Editor-in-Chief)
Place of publication Amsterdam
Publisher Elsevier Science Bv
Collection year 2006
Language eng
Subject C1
290800 Civil Engineering
770602 Land and water management
Abstract A calibration methodology based on an efficient and stable mathematical regularization scheme is described. This scheme is a variant of so-called Tikhonov regularization in which the parameter estimation process is formulated as a constrained minimization problem. Use of the methodology eliminates the need for a modeler to formulate a parsimonious inverse problem in which a handful of parameters are designated for estimation prior to initiating the calibration process. Instead, the level of parameter parsimony required to achieve a stable solution to the inverse problem is determined by the inversion algorithm itself. Where parameters, or combinations of parameters, cannot be uniquely estimated, they are provided with values, or assigned relationships with other parameters, that are decreed to be realistic by the modeler. Conversely, where the information content of a calibration dataset is sufficient to allow estimates to be made of the values of many parameters, the making of such estimates is not precluded by preemptive parsimonizing ahead of the calibration process. White Tikhonov schemes are very attractive and hence widely used, problems with numerical stability can sometimes arise because the strength with which regularization constraints are applied throughout the regularized inversion process cannot be guaranteed to exactly complement inadequacies in the information content of a given calibration dataset. A new technique overcomes this problem by allowing relative regularization weights to be estimated as parameters through the calibration process itself. The technique is applied to the simultaneous calibration of five subwatershed models, and it is demonstrated that the new scheme results in a more efficient inversion, and better enforcement of regularization constraints than traditional Tikhonov regularization methodologies. Moreover, it is argued that a joint calibration exercise of this type results in a more meaningful set of parameters than can be achieved by individual subwatershed model calibration. (c) 2005 Elsevier B.V. All rights reserved.
Keyword Engineering, Civil
Geosciences, Multidisciplinary
Water Resources
Regularization
Calibration
Watershed Modeling
Inverse Problems
Parameters
Regionalization
Optimization
Inference
Q-Index Code C1

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Civil Engineering Publications
2007 Higher Education Research Data Collection
 
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Created: Wed, 15 Aug 2007, 08:24:29 EST