Parametric Analysis of Urban Flood Risk Based on 'Shallow Water' Model; A Real Case at Small Scale

In this paper, we examined the increased risk of urban flooding due to incorrect or insufficient maintenance of small hydrological basins. In particular, the effects of a peak rainfall event on a water drainage canal near to a town in central Italy were considered. By means of the RiverFlow2D commercial computational software, the Shallow water technique was chosen, which is based on the Finite Volume Element and on the Godunov-Riemann technique. We also experimented with parallel computing, by performing the same calculations with GPUs (Graphics Processing Units) and we were able to significantly reduce the total time by 80 times. The study area is located in Pianello di Ostra district (Ancona, Marche, Italy). The peak rain data, which is publicly available, were recorded by the Corinaldo pluviometric station (9.1 km from the area) between April 26th and May 2nd 2014 and it caused a subsequent flooding event lasting two days. We integrated pluviometric data with available cartography, a rigorous site inspection, interviews with inhabitants and a high-resolution topographic survey (30 x 30 cm) acquired with a drone. To process rainfall data, we selected the Curve-Number (CN) empirical method, developed by the USDA Natural Resources Conservation Service (SCS). The parametric simulations on Fosso della Trocca basin were performed considering both pre-flooding maintenance state, with obstructions of the channel and the presence of a small bridge, and optimal maintenance state, with no obstructions and no bridge. The computer-simulated depth of the flooding water was compatible with what was observed during the real flood. Thus, the effects of increasingly intense rainfall events were estimated. However, we found that threshold values exist above which no ordinary maintenance is sufficient to avoid flooding phenomena.