Revisiting methodologies for damages caused by flooding across water sources, damage categories, and spatio-temporal scale

During the past two decades Denmark has experienced a dramatic increase in annual damages from flooding. Multiple cloudbursts, one of which was registered as the most costly natural hazard event in Northern Europe that year, several sea surges and the wettest winter season ever recorded, leading to excessive floodings in lowlying areas and fluvial flooding. This increase in occurences of floods is expected to further accelerate in the coming decades, leading also to a drastic increase in compound events, i.e. several phenomena occurring simultaneously exacerbating the flood event. Measures to keep societal risks at acceptable levels are highly needed. When designing strategies and concrete measures theoretically calculated damages given flood events are critical.

The dominating existing paradigms for assessing cost given events is to generate damage-depth curves for each type of flooding and cost category. The curves are assessed based on either a bottom-up approach based on e.g. asset characteristics (e.g. buildings in UK) or top-down approaches based on insurance claims, surveys or other aggregate data (e.g. Germany and Denmark). Both bottom-up and top-down approaches have shortcomings, the first method is based on assumptions that are difficult to verify and the second is based on data that are often biased and difficult to achieve because of restrictions in GDPR-regulation, privileged information held by private companies, and that the value of many assets cannot be assessed on a free economic market. Further, both approaches fail to capture essential characteristics of the damage costs, notably that the damage is dependent on the source of the flooding which in many cases in the future will be compound events and hence a function of two or more distinctly different damage-depth curves. The interplay between different cost categories are also often ignored.

The current project aims at generating knowledge that enable unifying damage-depth curves across water sources and damage categories. This will be done by combining desktop studies with novel uses of data collected at both governmental agencies and private entities such as insurance companies. However, important extensions to the traditional frameworks will be to include an assessment of how the damage-depth relationships is expected to change over time. Many analyses ignore the learnings and adaptations that will occur in the future and that recovery periods may be extensive and lead to societies that are either more or less resilient based on the strategy for recovery. Most notable is the assumption that an asset will suffer the same economic damage now and in the future even though the flood frequency will in some cases change from 1 in 50 years to every year. In these cases the damage from each event will undoubtedly decrease. A more explicit incorporation of the disaster management cycle into the assessments will also allow for a more realistic assessment of damages as they become more and more severe in a given region and larger events with longer recovery periods will be more prevalent.