Measuring floods by their scars: toward a data-driven flood severity scale

This paper proposes a systematic impact-based classification of the severity of flood events through the introduction of a flood severity (FLOSEV) scale. To classify and compare extreme events, the authors argue that it is useful to rely on metrics that capture impacts, noting that for floods, assessing and comparing “magnitude” is often problematic because peak discharge data are frequently unavailable, incomplete, or difficult to relate to a meaningful river section. The FLOSEV scale was developed using the AVI (Aree Vulnerate Italiane) database, an extensive collection of flood and landslide events in Italy spanning centuries, with a systematic inventory from the early 1900s. 

The paper finds that the resulting scale distinguishes five levels of severity, producing a quasi-logarithmic distribution in which each level contains approximately an order of magnitude more events than the one above. The proposed criteria attribute recent major floods to reasonable classes, supporting the robustness and practical relevance of the scale. The authors conclude that FLOSEV provides “a simple and flexible framework” for comparing flood impacts across space and time and is particularly useful where instrumental hydrological data are lacking. They recommend exploring its application in other geographical contexts and disaster databases, while acknowledging the need to adapt some damage indicators to different data structures.