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Abstract. The occurrence of debris flows has been recorded for more than a century in the European Alps, accounting for the risk to settlements and other human infrastructure that have led to death, building damage and traffic disruptions. One of the difficulties in the quantitative hazard assessment of debris flows is estimating the run-out behavior, which includes the run-out distance and the related hazard intensities like the height and velocity of a debris flow. In addition, as observed in the French Alps, the process of entrainment of material during the run-out can be 10-50 times in volume with respect to the initially mobilized mass triggered at the source area. The entrainment process is evidently an important factor that can further determine the magnitude and intensity of debris flows. Research on numerical modeling of debris flow entrainment is still ongoing and involves some difficulties. This is partly due to our lack of knowledge of the actual process of the uptake and incorporation of material and due the effect of entrainment on the final behavior of a debris flow. Therefore, it is important to model the effects of this key erosional process on the formation of runouts and related intensities. In this study we analyzed a debris flow with high entrainment rates that occurred in 2003 at the Faucon catchment in the Barcelonnette Basin (Southern French Alps). The historic event was back-analyzed using the Voellmy rheology and an entrainment model imbedded in the RAMMS 2-D numerical modeling software. A sensitivity analysis of the rheological and entrainment parameters was carried out and the effects of modeling with entrainment on the debris flow run-out, height and velocity were assessed.

Future trends in debris flow activity are constructed based on bias-corrected climate change projections using two meteorological proxies: daily precipitation and Convective Available Potential Energy (CAPE) combined with specific humidity for two Alpine areas. Along with a comparison between proxies, future number of days with debris flows are analyzed with respect to different regional and global climate models, Representative Concentration Pathways (RCPs), and area for quantile mapping. Two different base periods are also analyzed, as debris flows were observed on only 6 (17) days between 1950 and 1979, yet on 18 (49) days between 1980 and 2009 for Fella River, NE Italy (Barcelonnette, SE French Alps). For both areas, future climate projections vary between no change up to an increase of 6.0 % per decade in days with debris flow occurrences towards the end of 21st century. In Barcelonnette, the base period and proxy have a bigger impact on the future number of debris flow days than the climate model or RCP used. In Fella River, the base period, RCP, and proxy used define the future range. Therefore the selection of proxy, base period and downscaling technique should be carefully considered for future climate change impact studies concerning debris flow activity and associated fast-moving landslides.

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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