| Summary: | Fluvial fooding continues to be a process that has a major impact on society, the environment and the economy. Although its natural triggering factors, the spatial confguration of exposure and vulnerability is expected to play a relevant role in explaining the damage records. The starting point of this research is the use of existing food susceptibility, exposure and social vulnerability mapping, produced at the parish level, as input data in a Classifcation and Regression Trees’ (CART) model. Two models were ran, autonomously, that use two databases of food damage as dependent variables: one including the human damages (fatalities, missing, injured, displaced and evacuated people) from food events—the DISASTER database; another one that sums the DISASTER cases and the lower impact damages (damages to roads, railroads and buildings). The results show a quite distinct classifcation of parishes, whether one database is used or the other. The DISASTER database reveals susceptibility as the most relevant food risk driver in explaining the damage patterns, while the database with all the food cases identifes exposure as the more relevant driver. In the end, the degree of damages as documented in databases is conditioned by the geographical distribution and overlay confguration of the three food risk drivers. Finally, the CART classifcation groups are analyzed at the light of the European Union’s Floods Directive areas of signifcant potential food risk. This analysis showed that the Directive’s parishes are interpreted diferently—in terms of their positioning in face of the risk drivers—which is explained by the use of distinct impacting-criteria in the construction of the food damage databases.
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