Abstract
This paper introduces a numerical code, named MAGE and developed at INRAE Lyon, that is able to compute efficiently a flood propagation in a complex river network. MAGE solves the Barré-de-Saint–Venant equations using a finite difference method. It is applied to the Adour River located in the South–East of France. The Adour River is a tidal river with a pluvio-nival regime. It is characterized by a complex system of tributaries including mild-sloped tributaries (Upper Adour) and mountainous tributaries (Nive, Gave d’Oloron) and a significant influence of the tide in its downstream part. As a consequence, flood hazard is an important issue for the city of Bayonne located at the Adour-Nive confluence, approximately 6 km from the sea. The SPC (Flood Prevention Service) uses 1D modelling to possibly provide real time evaluation of the flood hazard (using the alertness colours) at Bayonne depending on a combination of upstream floods and tide. Presently, they used the 1D code MASCARET developed by EDF. A comparison is provided between results from MASCARET, MAGE, and water level measurements at different stations for typical floods. If both codes provide accurate results for a tidal regime at low discharge, they can deviate significantly for large flood where flood expansion zones are active. A system of storage area is implemented in the MAGE model to improve the model behaviour during large flood. Result accuracy are notably improved though some improvements could still be done locally. Eventually, results from MAGE code are significantly improved compared to those obtained with MASCARET. Also computation time are largely reduced; as an example, using a classic laptop (Intel Core i7, 7.7Go RAM), a 64 day time-series was modelled within 3 min using MAGE, against nearly 10 h using MASCARET. Thus, the MAGE model is a useful tool for real time modelling.
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Camenen, B., Faure, JB., Décanis, S., Dieval, L. (2022). A 1D Numerical Tool for Real Time Modelling of a Complex River Network. In: Gourbesville, P., Caignaert, G. (eds) Advances in Hydroinformatics. Springer Water. Springer, Singapore. https://doi.org/10.1007/978-981-19-1600-7_3
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DOI: https://doi.org/10.1007/978-981-19-1600-7_3
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