Multi-scale debris flow vulnerability assessment and direct loss estimation of buildings in the Eastern Italian Alps

Ciurean R.L.; Hussin H.; van Westen C.J.; Jaboyedoff M.; Nicolet P.; Chen L.; Frigerio S.; Glade T., 2017, Multi-scale debris flow vulnerability assessment and direct loss estimation of buildings in the Eastern Italian Alps, Natural hazards (Dordr.) (2017): 1–29. doi_10.1007/s11069-016-2612-6,
URL: http://www.cnr.it/prodotto/i/360283

Vulnerability assessment, as a component of the consequence analysis, represents a fundamental stage in the risk assessment process because it relates the hazard intensity to the characteristics of the built environment that make it susceptible to damage and loss. The objective of this work is to develop a quantitative methodology for vulnerability and loss assessment of buildings exposed to debris flows and apply it to a study area in NE Italy at local and regional scale. Using existing conceptual models of vulnerability and loss, this paper seeks to identify solutions for maximizing the information gained from limited observational damage data and a heterogeneous building data set. Two vulnerability models are proposed_ Model 1 is based on the generation of empirical vulnerability curves using observed intensities; Model 2 takes into account multiple resistance characteristics of buildings and uses modeled debris flow intensities. The process intensity descriptor in both cases is debris flow height. The vulnerability values obtained with the local (Model 1) and regional (Model 2) models are further multiplied with the building value to calculate the minimum and maximum loss for each building in the study area. Loss is also expressed as cumulative probability calculated with Model 1 using a Monte Carlo sampling technique. The methodology is applied in the Fella River valley (northeastern Italian Alps), a region prone to multiple mountain hazards. Uncertainties are expressed as minimum and maximum values of vulnerability, market values and loss. The results are compared with relevant published vulnerability curves and historical damage reports.

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