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Flood-prone areas assessment using linear binary classifiers based on flood maps obtained from 1D and 2D hydraulic models

机译:基于线性二元分类器基于一维和二维水力模型获得的洪水图评估易发洪水区域

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摘要

The identification of flood-prone areas is a critical issue becoming everyday more pressing for our society. A preliminary delineation can be carried out by DEM-based procedures that rely on basin geomorphologic features. In the present paper, we investigated the dominant topographic controls for the flood exposure using techniques of pattern classification through linear binary classifiers based on DEM-derived morphologic features. Our findings may help the definition of new strategies for the delineation of flood-prone areas with DEM-based procedures. With this aim, local features-which are generally used to describe the hydrological characteristics of a basin-and composite morphological indices are taken into account in order to identify the most significant one. Analyses are carried out on two different datasets: one based on flood simulations obtained with a 1D hydraulic model, and the second one obtained with a 2D hydraulic model. The analyses highlight the potential of each morphological descriptor for the identification of the extent of flood-prone areas and, in particular, the ability of one geomorphologic index to represent flood-inundated areas at different scales of application.
机译:易发洪水区域的识别是一个至关重要的问题,对我们的社会而言,这一问题每天变得越来越紧迫。可以通过基于流域地貌特征的基于DEM的程序来进行初步划分。在本文中,我们使用基于DEM派生的形态特征的线性二元分类器通过模式分类技术研究了洪水泛滥的主要地形控制。我们的发现可能有助于基于基于DEM的程序来划定易发洪水地区的新策略。为此,考虑了通常用于描述流域水文特征的局部特征和复合形态学指标,以便确定最重要的特征。对两个不同的数据集进行分析:一个基于基于一维水力模型获得的洪水模拟的数据集,第二个基于二维水力模型获得的数据集。这些分析突出了每种形态学特征在识别易发洪灾地区范围方面的潜力,尤其是一种地貌指数能够代表不同应用规模的洪水泛滥地区的能力。

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