E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||12|
|Section||Hazard analysis and modelling|
|Published online||20 October 2016|
Can bed-load help to validate hydrology studies in mountainous catchment? The case study of the Roize (Voreppe, France)
Université Grenoble Alpes, Irstea, UR ETGR, 2 rue de la Papeterie - BP 76, F-38402 St-Martin-d’Hères, France
a Corresponding author: firstname.lastname@example.org
Larges uncertainties are attached to hazard prediction in mountain streams, because of some limitations in our knowledge of physical processes, and overall, because of the lack of measurements for validation. This is particularly true for hydrological data, making the hydrology assessment of a mountain river a very difficult task, usually associated with large uncertainties. On the other hand, contrarily to lowland rivers, bed-load in mountain streams is often trapped in mitigation-structures, such as open check dams. This study aims to take advantage of these additional information for compensating the general lack of hydrological data, in order to converge toward a comprehensive diagnosis of the catchment hydrological behavior. A hydrology and sediment transport study has been done on the Roize torrent (16.1-km2 - Voreppe - 38-FR). After a classical historical study, a regional analysis of raingauges and water-discharge-stations situated in the calcareous north Pre-Alps massifs of the Vercors, Chartreuse and Bauges has been done. A catchment geomorphology study has been performed to get insight about the Roize torrential activity and sediment transport. The volumes of bed-load transported each year on average and during extreme floods have been computed using the estimated hydrology. The good bed-load predictions compare to the volume dredged in the Voreppe sediment trap are considered an indirect validation of the hydrology study.
© 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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