An Early Warning System for Urban Fluvial Floods Based on Rainfall Depth–Duration Thresholds and a Predefined Library of Flood Event Scenarios: A Case Study of Palermo (Italy)

Author:

Pumo Dario1ORCID,Avanti Marco1,Francipane Antonio1ORCID,Noto Leonardo V.1ORCID

Affiliation:

1. Dipartimento di Ingegneria, Università degli Studi di Palermo, Viale delle Scienze, Ed. 8, 90128 Palermo, Italy

Abstract

Several cities are facing an increasing flood risk due to the coupled effect of climate change and urbanization. Non-structural protection strategies, such as Early Warning Systems (EWSs), have demonstrated significant potential in mitigating hydraulic risk and often become the primary option when the implementation of structural measures is impeded by the complexities of urban environments. This study presents a new EWS designed specifically for fluvial floods in the city of Palermo (Italy), which is crossed by the Oreto River. The system is based on the preliminary definition of various Flood Event Scenarios (FESs) as a function of typical precursors, such as rainfall forecasts, and antecedent wetness and river flow conditions. Antecedent conditions are derived from real-time water stage observations at an upstream river section, while rainfall forecasts are provided by the Italian National Surveillance Meteorological Bulletins with a preannouncement time of up to 36 h. An innovative feature of the system is the use of rainfall Depth–Duration Thresholds to predict the expected hydrograph peak, significantly reducing warning issuing times. A specific FES, immediately accessible from a pre-built library, can be linked to any combination of precursors. Each FES predicts the timing and location of the first points of flooding; flood-prone areas and water depths; and specific hazard maps for elements typically exposed in cities, such as people, vehicles, and buildings. The EWS has been tested on a historical flood event, demonstrating satisfactory accuracy in reproducing the location, extent, and severity of the flood.

Publisher

MDPI AG

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