Rapid assessment of flood susceptibility in urbanized rivers using digital terrain data: Application to the Arno river case study (Firenze, northern Italy)

As a result of the recent acquisitions of detailed geographic data in fluvial environments this study proposes an analytical procedure in a GIS environment for an easy, rapid and cost-effective evaluation of flood susceptibility within urban and sub-urban areas. The method, based on data gathering in various public offices and possibly integrating missing geomorphologic information with new records, has been tested in a real case study in central Italy from which operational instructions could be extrapolated for other similar areas in the world. A long reach of the Arno river, which is currently the most important national hydraulic emergency area in terms of civil protection, was selected for this purpose. The measured dike heights, extrapolated from a geographic database previously created by the authors on behalf of the Provincia di Firenze administration, were compared with the results of hydraulic modeling conducted by the Arno River Basin Authority in which water flood levels were simulated for various return periods. This data comparison has allowed us to identify critical points for overflow hazard. In addition, the flood discharges provided by the same model were related to the freeboard typically used in river hydraulics for the major Italian watercourses (1.00 m for a 200-year flood). A deeper analysis of the flood susceptibility was subsequently carried over to the urban area of Firenze. A model of the surface hydrological flows concentrated on the historic center has provided a comprehensive response of this area to the sudden appearance of abundant surface-water flows. The behavior of the urban water circulation in terms of path and areas involved were promptly identified with great precision during normal flow conditions of the Arno in the event of river obstruction at bridges and in case of undifferentiated runoff out from the riverbed. (C) 2014 Elsevier Ltd. All rights reserved.