Building-scale flood loss estimation through enhanced vulnerability pattern characterization: application to an urban flood in Milano, Italy

Abstract

Abstract. The vulnerability of flood-prone areas is determined by the susceptibility of the exposed assets to the hazard. It is a crucial component in risk assessment studies, both for climate change adaptation and disaster risk reduction. In this study, we analyse patterns of vulnerability for the residential sector in a frequently hit urban area of Milano, Italy. The conceptual foundation for a quantitative assessment of the structural dimensions of vulnerability is based on the modified Source-Pathway-Receptor-Consequence model. This conceptual model is used to improve the parameterization of the flood risk analysis describing: (i) hazard scenarios definition performed by hydraulic modelling based on past event data (Source estimation) and morphological features and land use evaluation (Pathway estimation); (ii) the exposure and vulnerability assessment which consists of recognizing elements potentially at risk (Receptor estimation) and event losses (Consequence estimation). The structural dimension of vulnerability is mapped at building level and used in loss estimation for the residential sector at meso and micro-scale. Results produces accurate estimates of the flood characteristics, with mean error in flood depths estimation in the range 0.2–0.3 m and provide a basis to obtain site-specific damage curves and damage mapping. Findings show that the nature of flood pathways varies spatially and is influenced by landscape characteristics and alters vulnerability spatial distribution and hazard propagation. At the mesoscale, the ‘Continuous urban fabric’ Urban Atlas 2018 land-use class with the occurrence of at least 80 % of soil sealing shows higher absolute damage values. At microscale, evidence demonstrated that even events with moderate magnitude in terms of flood depth in a complex urbanized area may cause more damage than it would expect.

Flood Damage Assessment: A Review of Microscale Methodologies for Residential Buildings

“…However, various researchers [10,23,[38][39][40][41] have noted that there is a persistent need to bridge the gaps in achieving a reliable and accurate damage model. Such impediments include limited data availability; damage variations within building classes; limited knowledge of the model building, geometries of the building and flood parameters; uncertainties, and validation of models.…”