Abstract. The use of different methods for physical flood vulnerability assessment has
evolved over time, from traditional single-parameter stage–damage curves to
multi-parameter approaches such as multivariate or indicator-based models.
However, despite the extensive implementation of these models in flood risk
assessment globally, a considerable gap remains in their applicability to
data-scarce regions. Considering that these regions are mostly areas with a
limited capacity to cope with disasters, there is an essential need for
assessing the physical vulnerability of the built environment and
contributing to an improvement of flood risk reduction. To close this gap, we
propose linking approaches with reduced data requirements, such as
vulnerability indicators (integrating major damage drivers) and damage
grades (integrating frequently observed damage patterns). First, we present
a review of current studies of physical vulnerability indicators and flood
damage models comprised of stage–damage curves and the multivariate methods that have been applied to predict damage grades. Second, we propose a new
conceptual framework for assessing the physical vulnerability of buildings
exposed to flood hazards that has been specifically tailored for use in data-scarce
regions. This framework is operationalized in three steps: (i) developing a
vulnerability index, (ii) identifying regional damage grades, and (iii) linking resulting index classes with damage patterns, utilizing a synthetic
“what-if” analysis. The new framework is a first step for enhancing flood
damage prediction to support risk reduction in data-scarce regions. It
addresses selected gaps in the literature by extending the application of the
vulnerability index for damage grade prediction through the use of a
synthetic multi-parameter approach. The framework can be adapted to
different data-scarce regions and allows for integrating possible modifications
to damage drivers and damage grades.