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Optimal Cross-sectional Sampling for River Modelling with Bridges: an Information Theory-based Method
Sapienza Univ Roma, Dipartimento Ingn Civile Edile & Ambientale, Rome, Italy..
UNESCO IHE, Hydroinformat Chair Grp, Delft, Netherlands..
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
Sapienza Univ Roma, Dipartimento Ingn Civile Edile & Ambientale, Rome, Italy..
2016 (English)In: Proceedings Of The International Conference On Numerical Analysis And Applied Mathematics 2015 (ICNAAM-2015), 2016, 430004Conference paper (Refereed)
Abstract [en]

The description of river topography has a crucial role in accurate one-dimensional (1D) hydraulic modelling. Specifically, cross-sectional data define the riverbed elevation, the flood-prone area, and thus, the hydraulic behavior of the river. Here, the problem of the optimal cross-sectional spacing is solved through an information theory-based concept. The optimal subset of locations is the one with the maximum information content and the minimum amount of redundancy. The original contribution is the introduction of a methodology to sample river cross sections in the presence of bridges. The approach is tested on the Grosseto River (IT) and is compared to existing guidelines. The results show that the information theory-based approach can support traditional methods to estimate rivers' cross-sectional spacing.

Place, publisher, year, edition, pages
2016. 430004
AIP Conference Proceedings, ISSN 0094-243X ; 1738
Keyword [en]
hydraulic modelling, cross sections, flood, information theory, optimization, genetic algorithm
National Category
Oceanography, Hydrology, Water Resources
URN: urn:nbn:se:uu:diva-306072DOI: 10.1063/1.4952217ISI: 000380803300438ISBN: 9780735413924 (print)OAI: oai:DiVA.org:uu-306072DiVA: diva2:1039669
International Conference on Numerical Analysis and Applied Mathematics (ICNAAM), SEP 23-29, 2015, Rhodes, GREECE
Available from: 2016-10-25 Created: 2016-10-24 Last updated: 2016-10-25Bibliographically approved

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