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  • 标题:Stochastic rainfall fields time-series for probabilistic flood hazard assessment
  • 本地全文:下载
  • 作者:Christine Poulard ; Christine Poulard ; Etienne Leblois
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2016
  • 卷号:7
  • 页码:1-8
  • DOI:10.1051/e3sconf/20160704022
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要: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.
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