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An entropy approach for the optimization of cross-section spacing for river modelling.

Authors :
Ridolfi, Elena
Alfonso, Leonardo
Di Baldassarre, Giuliano
Dottori, Francesco
Russo, Fabio
Napolitano, Francesco
Source :
Hydrological Sciences Journal/Journal des Sciences Hydrologiques. Jan2014, Vol. 59 Issue 1, p126-137. 12p.
Publication Year :
2014

Abstract

An accurate definition of river geometry is essential to implement one-dimensional (1D) hydraulic models and, in particular, appropriate spacing between cross-sections is key for capturing a river’s hydraulic behaviour. This work explores the potential of an entropy-based approach, as a complementary method to existing guidelines, to determine the optimal number of cross-sections to support 1D hydraulic modelling. To this end, given a redundant collection of existing cross-sections, a location subset is selected minimizing total correlation (as a measure of redundancy) and maximizing joint entropy (as a measure of information content). The problem is posed as a multi-objective optimization problem and solved using a genetic algorithm: the Non-dominated Sorting Genetic Algorithm (NSGA)-II. The proposed method is applied to a river reach of the Po River (Italy) and compared to standard guidelines for 1D hydraulic modelling. Cross-sections selected through the proposed methodology were found to provide an accurate description of the flood water profile, while optimizing computational efficiency. EditorD. Koutsoyiannis CitationRidolfi, E., Alfonso, L., Di Baldassarre, G., Dottori, F., Russo, F., and Napolitano, F., 2013. An entropy approach for the optimization of cross-section spacing for river modelling.Hydrological Sciences Journal, 59 (1), 126–137. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02626667
Volume :
59
Issue :
1
Database :
Academic Search Index
Journal :
Hydrological Sciences Journal/Journal des Sciences Hydrologiques
Publication Type :
Academic Journal
Accession number :
94856847
Full Text :
https://doi.org/10.1080/02626667.2013.822640