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

Optimal cross-sectional sampling for river modelling with bridges: an information theory-based method / Ridolfi, E; Alfonso, L.; Di Baldassarre, G.; Napolitano, Francesco. - CD-ROM. - 1738:(2016), pp. 1-4. (Intervento presentato al convegno International Conference of Numerical Analysis and Applied Mathematics 2015, ICNAAM 2015 tenutosi a Rodos Palace Hotel, Greece nel 2015) [10.1063/1.4952217].

Optimal cross-sectional sampling for river modelling with bridges: an information theory-based method

Ridolfi, E;NAPOLITANO, Francesco
2016

Abstract

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
2016
International Conference of Numerical Analysis and Applied Mathematics 2015, ICNAAM 2015
cross sections; flood; genetic algorithm; hydraulic modelling; information theory; optimization; Physics and Astronomy (all)
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Optimal cross-sectional sampling for river modelling with bridges: an information theory-based method / Ridolfi, E; Alfonso, L.; Di Baldassarre, G.; Napolitano, Francesco. - CD-ROM. - 1738:(2016), pp. 1-4. (Intervento presentato al convegno International Conference of Numerical Analysis and Applied Mathematics 2015, ICNAAM 2015 tenutosi a Rodos Palace Hotel, Greece nel 2015) [10.1063/1.4952217].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/885229
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