The availability of new technologies far the measurement of surface elevation has addressed the lack of high-resolution elevation data, which has led to an increase in the attraction of automated procedures based on digital elevation models (DEMs) far hydrological applications, including the delineation of floodplains. In particular, the exposure to flooding may be delineated quite well by adopting a modified topographic index (TIm) computed from a DEM. The comparison of TI", and flood inundation maps (obtained from hydraulic simulations) shows that the portion of a basin exposed to flood inundation is generally characterized by a TIm higher than a given threshold, T (e.g., equal to 2.89 far DEMs with cell size of 20 m). This allows the development of a simple procedure far the identification of flood-prone areas that requires only two parameters far the calibration: the threshold T and the exponent of TIm' Because the modified topographic index is sensitive to the spatial resolution of the DEM, the optimal scale of representation for the performance of the method is investigated. The procedure is tested on the Arno River Basin by using the existing documentation of flood inundations produced by the Arno River Basin Authority for calibration and validation. This approach is applied on Il subcatchments with areas ranging from 489-6,929 km

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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 floodprone 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.

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