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Evaluation of some rapid flood forecast models: TOPMODEL MARINE

机译:评估一些快速洪水预报模型:TOPMODEL和MARINE

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摘要

The characterization of flash flood is an opened subject. We can notice several characteristics. The precipitation responsible of their formation are violent and intense; catchments concerned are small or medium; the surface runoff is the main flood generator; and the infiltration plays a role in the losses evaluation of the rain measured. To simulate and to forecast such events, we use two deterministic, distributed and conceptual models : TOPMODEL and MARINE. MARINE is an operational and robust tool for flash flood forecasting already implemented in National Flood Forecast Service in order to be tested. It should supply pertinent data about the flood evolution for people responsible of forecast and should be applicable even for sparse historical and observed data with the integration of data from space imagery. The choice of the physical processes responsible of the rapid flood generation, adopted in these models, are very different. On the one hand the saturated contributive surfaces are modeled through the TOPMODEL concept; and on the other hand the rooting of the surface runoff is the factor determining of the flood genesis in the rainfall - runoff MARINE. To try to understand which is more appropriated than the other to simulate those particular floods, these two models are tested on two small French Mediterranean catchments for rapid floods that occurred recently. The calibration of these models is delicate, because the parameters have to keep physical meaning. Furthermore, we plan their use in real time forecasting.
机译:洪水泛滥的特征是一个尚未解决的问题。我们可以注意到几个特征。造成它们形成的降水猛烈。有关集水区是中小型的;地表径流是主要的洪灾发源地。入渗在测雨损失评估中发挥作用。为了模拟和预测此类事件,我们使用两个确定性,分布式和概念性模型:TOPMODEL和MARINE。 MARINE是用于洪水洪水预报的可操作且功能强大的工具,已在国家洪水预报服务中实施以进行测试。它应为负责预报的人员提供有关洪水演变的相关数据,并且即使将稀疏的历史和观测数据与来自空间影像的数据集成在一起,也应适用。这些模型中采用的导致快速洪水发生的物理过程的选择有很大不同。一方面,通过TOPMODEL概念对饱和贡献面进行建模;另一方面,地表径流的生根是决定降雨-径流海洋的洪水成因的因素。为了试图理解哪个模型比另一个模型更适合于模拟那些特定的洪水,在两个小的法国地中海小流域针对最近发生的快速洪水测试了这两个模型。这些模型的校准非常精细,因为参数必须保留物理意义。此外,我们计划将其用于实时预测。

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