E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||8|
|Section||Hazard analysis and modelling|
|Published online||20 October 2016|
Stochastic rainfall fields time-series for probabilistic flood hazard assessment
Irstea, Hydrology-Hydraulics Research Unit, Centre de Lyon-Villeurbanne, 5 rue de la Doua, BP 32108, 69616 Villeurbanne Cedex, France
a Corresponding author: firstname.lastname@example.org
Probabilistic flood hazard assessment are usually carried out through juxtaposed reach-wise hydraulic simulations, using as input “representative” hydrographs for the studied return periods - at least by their peak discharge. However, reach-wise approaches have drawbacks, especially in the presence of natural or man-made singularities. An approach based on continuous simulation is developed to better assess flood hazard at the scale of the catchment and of the flood regime. A stochastic rainfall fields generator yields continuous times series, thus keeping the variability of the rainfall fields. Catchment-wise rainfall-runoff modelling, completed when necessary by a hydraulic model, allows to reproduce the individual and combined response of each feature to a heterogeneous rainfall event. The current CPU performances allow to process long rainfall time-series, but the codes have to be adapted to deal with unusually long input and output files. Local flood quantiles are then derived from discharge time-series, and flooding probability can be derived from local inundation frequency. This approach can be used in all contexts, urban floods or catchment-scale management; the modules have just to be chosen accordingly. This approach offers many perspectives, and in particular to better estimate local expected annual damages using damages time-series and multivariate damage curves.
© 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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