This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

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Abstract. Hazard assessment of shallow landslides represents an important aspect of land management in mountainous areas. Among all the methods proposed in the literature, physically based methods are the only ones that explicitly includes the dynamic factors that control landslide triggering (rainfall pattern, land-use). For this reason, they allow forecasting both the temporal and the spatial distribution of shallow landslides. Physically based methods for shallow landslides are based on the coupling of the infinite slope stability analysis with hydrological models. Three different gridbased distributed hydrological models are presented in this paper: a steady state model, a transient "piston-flow" wetting front model, and a transient diffusive model. A comparative test of these models was performed to simulate landslide occurred during a rainfall event (27-28 June 1997) that triggered hundreds of shallow landslides within Lecco province (central Southern Alps, Italy). In order to test the potential for a completely distributed model for rainfall-triggered landslides, radar detected rainfall intensity has been used. A new procedure for quantitative evaluation of distributed model performance is presented and used in this paper. The diffusive model results in the best model for the simulation of shallow landslide triggering after a rainfall event like the one that we have analysed. Finally, radar

[1] Grain size data from the deposit of the 1987 Val Pola rock avalanche (central Italian Alps) are compared with data concerning rock avalanching, rock fragmentation, and comminution. The Weibull distribution fits a small part of the entire particle-size distribution of debris samples, with a mean value of the curve shape factor of 0.54 ± 0.28. This is typical of multiple comminution, or fragmentation with much shearing. A fractal distribution fits over a greater size range. Computed fractal dimensions range between 1.3 and 3.2 within the deposit, with average values of about 2.6-2.7. These values cover the range between the theoretical values of the plane-of-weakness model (1.97) and the pillar-of-strength model (2.84) and are close to the theoretical value for the constrained comminution model (2.58). These suggest that both texturally mature and immature deposits are present and that more than a single comminution process acted during the rock avalanche motion. Variation of the grain size distribution within the deposit and grain size segregation show as trends in the fractal dimension and arise from variation in the fragmentation process. A variety of different physical and empirical laws suggest that 1-30% of the energy expended in the rock avalanche was consumed in fragmentation.

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Alluvial fan development in Alpine areas is often affected by catastrophic sedimentary processes associated with extreme floods events, causing serious risks for people living on the fans. Hazard assessment in these areas depends on proper identification of the dominant sedimentary processes on the fans.Data from a set of 209 alluvial fans from the central Alps of Italy are presented in this paper and analysed with the help of various statistical techniques (linear regression, principal components analysis, cluster analysis, discriminant analysis and logistic regression). First, we used modern sedimentary facies and historical records (flood events since 15th century), to distinguish between the two dominant sedimentary processes on alluvial fans: debris flows and streamflows. Then, in order to analyse the main controls on past and present fan processes, 36 morphological, geological and land-use variables were analysed. As with observations for arid-environment fans, catchment morphology is the most influential factor in the study area, whereas geology and land use are minor controls. The role of climatic change and landsliding within the catchments also seems to be very important and is discussed. Statistical techniques also help in differentiating groups of alluvial fans by sets of controlling factors, including stage and type of evolution. Finally, by using discriminant analysis and logistic regression, we classified alluvial fans according to the dominant sedimentary process, with a success rate ranging between 75 and 92 per cent.

Abstract. Rockfall risk analysis for mitigation action design requires evaluating the probability of rockfall events, the spatial probability and intensity of impacts on structures, their vulnerability, and the related expected costs for different scenarios. These tasks were integrated in a quantitative risk assessment procedure supported by 3D rockfall numerical modelling performed by the original code HY-STONE. The case study of Fiumelatte (Varenna, Italy), where a large rockfall in November 2004 resulted in 2 casualties, destruction of several buildings and damage to transportation corridors, is discussed. The numerical model was calibrated by a back analysis of the 2004 event, and then run for the whole area at risk by considering scenarios without protection (S0), with a provisional embankment (S1), and with a series of long-term protection embankments (S2). Computed impact energy and observed damage for each building impacted in 2004 were combined to establish an empirical vulnerability function, according to which the expected degree of loss for each element at risk was computed. Finally, costs and benefits associated to different protection scenarios were estimated, in order to assess both the technical performance and the cost efficiency of different mitigation options.