Vulnerability curves vs. vulnerability indicators: application of an indicator-based methodology for debris-flow hazards

Abstract. The assessment of the physical vulnerability of elements at risk as part of the risk analysis is an essential aspect for the development of strategies and structural measures for risk reduction. Understanding, analysing and, if possible, quantifying physical vulnerability is a prerequisite for designing strategies and adopting tools for its reduction. The most common methods for assessing physical vulnerability are vulnerability matrices, vulnerability curves and vulnerability indicators; however, in most of the cases, these methods are used in a conflicting way rather than in combination. The article focuses on two of these methods: vulnerability curves and vulnerability indicators. Vulnerability curves express physical vulnerability as a function of the intensity of the process and the degree of loss, considering, in individual cases only, some structural characteristics of the affected buildings. However, a considerable amount of studies argue that vulnerability assessment should focus on the identification of these variables that influence the vulnerability of an element at risk (vulnerability indicators). In this study, an indicator-based methodology (IBM) for mountain hazards including debris flow (Kappes et al., 2012) is applied to a case study for debris flows in South Tyrol, where in the past a vulnerability curve has been developed. The relatively "new" indicator-based method is being scrutinised and recommendations for its improvement are outlined. The comparison of the two methodological approaches and their results is challenging since both methodological approaches deal with vulnerability in a different way. However, it is still possible to highlight their weaknesses and strengths, show clearly that both methodologies are necessary for the assessment of physical vulnerability and provide a preliminary "holistic methodological framework" for physical vulnerability assessment showing how the two approaches may be used in combination in the future.