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Analysis of extreme flooding events through a calibrated 1D/2D coupled model: the case of Barcelona (Spain)
Author(s) -
Beniamino Russo,
David Sunyer,
Marc Velasco,
Slobodan Djordjević
Publication year - 2014
Publication title -
journal of hydroinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.654
H-Index - 50
eISSN - 1465-1734
pISSN - 1464-7141
DOI - 10.2166/hydro.2014.063
Subject(s) - sanitary sewer , terrain , flooding (psychology) , flood myth , surface runoff , storm , environmental science , hydrology (agriculture) , computer science , event (particle physics) , culvert , civil engineering , meteorology , engineering , geotechnical engineering , cartography , environmental engineering , geography , archaeology , psychotherapist , biology , physics , quantum mechanics , psychology , ecology
This paper presents the results of a calibrated 1D/2D coupled model simulating surface and sewer flows in Barcelona. The model covers 44 km2 of the city land involving 241 km of sewers. It was developed in order to assess the flood hazard in the Raval district, historically affected by flooding during heavy rainfalls. Special attention was paid to the hydraulic characterization of the inlet systems (representing the interface between surface and underground flows), through experimental expressions used to estimate the effective runoff flows into the sewers in case of storms. A 2D unstructured mesh with more than 400,000 cells was created on the basis of a detailed digital terrain model. The model was calibrated and validated using four sets of well-recorded flooding events that occurred in 2011. The aim of this paper is to show how a detailed 1D/2D coupled model can be adequately calibrated and validated using a wide set of sewer sensors and post-event collected data (videos, photos, emergency reports, etc.). Moreover, the created model presents significant computational time savings via parallel processing and hardware configuration. Considering the computational performances achieved, the model can be used for real-time strategies and as the core of early warning systems.

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