In recent decades, floods have caused significant loss of human life as well as interruptions in economic and social activities in affected areas. In order to identify effective flood mitigation measures and to suggest actions to be taken before and during flooding, microscale risk estimation methods are increasingly applied. In this context, an implemented methodology for microscale flood risk evaluation is presented, which considers direct and tangible damage as a function of hydrometric height and allows for quick estimates of the damage level caused by alluvial events. The method has been applied and tested on businesses and residential buildings of the town of Benevento (southern Italy), which has been hit by destructive floods several times in the past; the most recent flooding occurred in October 2015. The simplified methodology tries to overcome the limitation of the original method—the huge amounts of input data—by applying a simplified procedure in defining the data of the physical features of buildings (e.g., the number of floors, typology, and presence of a basement). Data collection for each building feature was initially carried out through careful field surveys (FAM, field analysis method) and subsequently obtained through generalization of data (DGM, data generalization method). The basic method (FAM) allows for estimating in great detail the potential losses for representative building categories in an urban context and involves a higher degree of resolution, but it is time-consuming; the simplified method (DGM) produces a damage value in a shorter time. By comparison, the two criteria show very similar results and minimal differences, making generalized data acquisition most efficient.

In the latest decades, the impact of floods has generated an increase of loss of human lives, as well as the interruption of economic activities in the affected areas. In this context, we present an implemented methodology for micro-scale flood risk evaluation that considers direct and tangible damages as a function of the hydrometric height and allows for quickly estimates of the damage level caused by alluvial events. The method has been applied and tested for economic and residential buildings in the town of Benevento (southern Italy), which was hit by destructive floods in the past. As the limitation of this original method is connected to the huge amounts of input data, we tried to overcome this limit by applying a simplified procedure in defining the physical data of buildings (e.g. type of buildings, n° of floors, presence of cellar). More specifically, during data collection on building features, two different criteria were used:1) data were acquired through a careful field survey, and 2) data were obtained through the topographical database of the Campania region and through the generalization of heights for each type of building. Data obtained using the first criterion result in a highly accurate risk assessment but, at the same time, the method is non-immediate and time-consuming. On the other hand, the second one is more expeditious. By comparison, the two criteria show very similar results and minimal differences, making the generalized data acquisition the most expeditious. In conclusion, the basic method allows estimating highly detailed potential losses for representative buildings categories in the urban context, but involves a higher degree of resolution; the generalised method, instead, thought the simplification of the data, responds to the need of reaching in a short time a damage value extremely similar to the real one.