AUTHOR=Quagliolo Carlotta , Comino Elena , Pezzoli Alessandro TITLE=Experimental Flash Floods Assessment Through Urban Flood Risk Mitigation (UFRM) Model: The Case Study of Ligurian Coastal Cities JOURNAL=Frontiers in Water VOLUME=3 YEAR=2021 URL=https://www.frontiersin.org/journals/water/articles/10.3389/frwa.2021.663378 DOI=10.3389/frwa.2021.663378 ISSN=2624-9375 ABSTRACT=

Cities are vulnerable to extreme weather events, particularly by considering flash flood risk as a result of even more short-duration intensive rainfall. In the context of climate change, compound flooding due to simultaneous storm surges and increased runoff may further exacerbate the risk in coastal cities, and it is expected to be frequent and severe across several European urban areas. Despite this increasing evidence, the spatial knowledge of the hazardous events/vulnerabilities through modelling scenarios at the urban level is quite unexplored. Moreover, flood-prone areas often do not correspond to the traditional flood risk classification based on predicted return-period. The result that huge impacts (human losses and damages) occur everywhere throughout the city. Consequently, this new challenge requires stormwater flooding mitigation strategies to adapt to cities while mainstreaming urban flood resilience. In this paper, we considered the Urban Flood Risk Mitigation model through the employment of the open-source tool—Integrated Evaluation of Ecosystem Services and Trade-off (InVEST)—developed by the Natural Capital Project, integrated into a GIS environment. The model application in the three urban coastal territory of the Liguria Region (Italy) estimated the amount of runoff due to two extreme rainfall events for each watershed considered. These index calculation results help define examples of Natural Water Retention Measures (NWRM) per land-use type as resilient solutions by addressing site-specific runoff reduction. Local sensitivity analysis was finally conducted to comprehend the input parameter's influence of rain variation on the model.