An analysis of Italian damage data to economic activities

The study of flood impacts on the different sectors that compose the built environment and the society is crucial to implement actions of prevention, mitigation, and cautious planning. In such a context, the sector of businesses assumes a critical role, both for its importance for the wellbeing of the society and because of the high losses it suffers in case of inundations. Nevertheless, flood damage modelling to businesses is still a challenging task: the large number of different commercial activities, their specific geographical and economic contexts and the few observed damage data are just some of the reasons for that. In Italy, for example, a shared methodology to assess damage to enterprises is not present; building knowledge about types and dimensions of impacts of flood events to economic activities is then even more impelling. This contribution presents the analysis of about a thousand observed damage records regarding industrial and commercial activities, collected by four research groups after different flood events in Italy: the inundation occurred in the town of Lodi (Lombardia Region) in 2002, the one in Sardegna Region in 2013, and the floods caused in the Emilia-Romagna Region by Secchia (2014) and Enza (2017) Rivers. Data retrieved from the local and regional authorities responsible for damage compensation present different levels of detail and aggregation, according to the case study investigated. In all cases, they refer to the direct damage only and, for each case study, they have been first organised according to the activity types (e.g. trade, manufacturing, construction, finance) and per affected components: i.e. structure, equipment and stock. Data analysis has been led by some questions, we identified as key to start developing knowledge for damage modelling:  are there similarities in the different case studies? Which are the more affected business sectors in case of flood? Which component suffers the highest damage among structure, equipment, and stock? Is there an empirical trend of damage with hazard parameters? Results were first compared with the socio-economic context of the affected area, to have a first confirmation of data quality and reliability; then, the analysis focused on searching information and relationships between damage and activity type, activity dimension and water level. Results support the identification of the more vulnerable elements within the business sector, orienting modellers’ and decision-makers’ choices.