Component-based flood vulnerability modelling for cultural heritage buildings

Flooding is among the most common and damaging natural hazards at the global level, which has prompted governments and international institutions to adopt measures towards the reduction of flood risk. Among them is the development of flood risk assessments and flood risk management plans with a particular emphasis on cultural heritage, not only due to its significance for society but also because of its particularly high vulnerability. In order to quantify flood risk and define prioritization and management plans for a given set of cultural heritage assets, vulnerability models that allow estimating and comparing the impacts of floods at an asset-by-asset level are required. However, there is currently a lack of approaches in the literature to achieve this. This study proposes a synthetic, component-based modelling framework to perform detailed vulnerability analyses of cultural heritage buildings, including their contents. The framework combines an assessment of the flood susceptibility of each building component, based on its type of material or technique, and a simple evaluation of its relative value within the asset, in order to define asset-specific flood vulnerability functions. These may then be used to support semi-quantitative probabilistic flood risk assessments for multiple exposed assets. The framework is illustrated through an application to two Portuguese churches.

Automated summary

Flooding is a common and damaging natural hazard globally, leading to measures to reduce flood risk at governmental and international levels. This study proposes a component-based modelling framework for detailed vulnerability analyses of cultural heritage buildings, combining assessment of flood susceptibility of building components and evaluation of their relative value within the asset to define asset-specific flood vulnerability functions. It aims to support semi-quantitative probabilistic flood risk assessments for multiple exposed assets.