E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||12|
|Section||Forecasting and warning|
|Published online||20 October 2016|
Integrated representation of hydropower facilities in an operational flood warning system for a mountainous watershed
1 Université Grenoble Alpes, LTHE, CS 40700, 38058 Grenoble Cedex 9, France
2 DREAL Auvergne-RhôneAlpes, PR service, PCAdN, 17 Bd Joseph Vallier, 38040 Grenoble Cedex 9, France
3 EDF/DTG, 21 Avenue de l’Europe, 38000 Grenoble, France
a Corresponding author: email@example.com
An integrated flood forecasting system adapted to mountain basins is under construction at the flood forecasting service of the French Northern Alps (SPCAN), whose jurisdiction area covers the whole Isère River basin (12000km2). Most parts of this area are harnessed for hydropower production, thus modifying flows at all the main sections of the stream network. A semi-distributed conceptual modeling approach was chosen for predicting warning levels at daily time step. Before giving results on the strategic warning point of Montmèlian, simulations on two representative sub-basins of about 1000 km2 are detailed. The first sub-basin includes the large Sautet dam, on the Drac River. The second, on the Isère River, includes the large dam of Tignes and is characterized by multiple diversions. The influence of hydroelectric facilities was analyzed for reconstituting natural flows. Then, a two-steps modeling strategy was deployed: firstly, natural reconstituted flows were simulated; next, the effect of hydroelectric works was introduced, considering the operating status of the main reservoirs and of the water intakes, the latter being aggregated together as a unique equivalent device. While keeping a reasonable level of model complexity, the developed tool provides accurate simulations of observed flood events and is planned to be further used in real-time.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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