Gestion de l'incertitude et de l'ignorance, dans l'évaluation de la probabilité de déclenchement des éboulements rocheux

National audienceThe general methodology for landslide risk management can be applied to rock falls. The uncertainties which affect the failure hazard characterization are described. They explain that the rupture probability is usually estimated in a qualitative way. New approaches are proposed for a quantitative evaluation of rock fall hazard. For a diffuse hazard, failure frequency and impact frequency downslope can be quantified. The failure probability for localized hazards is difficult to estimate. Coupling the classical qualitative geomechanical approach with the frequency based historical approach allows to verify the plausibility of previsions. A quantitative geomechanical approach can be envisaged in some cases where the internal structure of the rock wall is sufficiently known, but it must be associated with an historical one

Quantitative assessment of diffuse rock fall hazard along a cliff foot

International audienceMany works have shown that the relation between rock fall frequency and volume is well fitted by a power law. Based on this relation, a new method is presented which allows estimating the fall frequency and probability for a wall section in a homogenous cliff, considering all possible rock fall volumes. The hazard for an element located at the foot of the cliff, with a minimal energy, is also estimated. The method has been applied to an itinerary, for which the human risk has also been estimated. Rock fall inventories featuring the location, date, and volume of the falls and the dimensions of the fallen compartments (width, length, and thickness) are needed for better estimating of hazard and risk

Rockfall hazard and risk assessments along roads at a regional scale: example in Swiss Alps

Unlike fragmental rockfall runout assessments, there are only few robust methods to quantify rock-mass-failure susceptibilities at regional scale. A detailed slope angle analysis of recent Digital Elevation Models (DEM) can be used to detect potential rockfall source areas, thanks to the Slope Angle Distribution procedure. However, this method does not provide any information on block-release frequencies inside identified areas. The present paper adds to the Slope Angle Distribution of cliffs unit its normalized cumulative distribution function. This improvement is assimilated to a quantitative weighting of slope angles, introducing rock-mass-failure susceptibilities inside rockfall source areas previously detected. Then rockfall runout assessment is performed using the GIS- and process-based software Flow-R, providing relative frequencies for runout. Thus, taking into consideration both susceptibility results, this approach can be used to establish, after calibration, hazard and risk maps at regional scale. As an example, a risk analysis of vehicle traffic exposed to rockfalls is performed along the main roads of the Swiss alpine valley of Bagnes

Rock Slopes from Mechanics to Decision Making

http://lmrwww.epfl.ch/Eurock/Eurock2010/files/papers%20grouped.pdfRock slope instabilities are discussed in the context of decision making for risk assessment and management. Hence, the state of the slope and possible failure mechanism need to be defined first. This is done with geometrical and mechanical models for which recent developments are presented. This leads with appropriate consideration of uncertainties to risk determination and to the description of tools for risk management through active and passive countermeasures, including warning systems. The need for sensitivity analysis is then demonstrated, and final comments address updating through information collection.National Science Foundation (U.S.)MIT-Portugal ProgramPortuguese Science and Technology FoundationNorwegian Geotechnical Institute (International Centre for Geohazards)United States. Dept. of Energ

Brief communication: On direct impact probability of landslides on vehicles

Abstract. When calculating the risk of railway or road users of being killed by a natural hazard, one has to calculate a temporal spatial probability, i.e. the probability of a vehicle being in the path of the falling mass when the mass falls, or the expected number of affected vehicles in case such of an event. To calculate this, different methods are used in the literature, and, most of the time, they consider only the dimensions of the falling mass or the dimensions of the vehicles. Some authors do however consider both dimensions at the same time, and the use of their approach is recommended. Finally, a method considering an impact on the front of the vehicle is discussed

Sydney Basin Landslide Susceptibility, NSW, Australia

University of Wollongong GIS-based Landslide Inventory has been expanded to facilitate reliable modeling of landslide susceptibility and hazard zonation over the wider Sydney Basin area. Landslide inventory development is underway after designing a state of the art inventory structure following a comprehensive international literature review. The alphanumerical as well as spatial data bases of landslides have been updated after field verification of landslides in Sydney and Newcastle as the stepping stone for the wider Sydney Basin area landslide susceptibility model development. In the lead up to this, landslide susceptibility modeling in two smaller sub-regions of Sydney (Wollongong Local Government Area and the Picton area) has been undertaken by the Landslide Research Team at the University of Wollongong. In tandem with the development of the landslide inventory, new tools and methods have been developed to aid application of Data Mining techniques within a GIS framework to obtain more reliable modeling, analysis and synthesis. The main aim of this paper is to report the latest advances in landslide inventory development, preparation and compilation of data for the modeling work

The combination of DInSAR and facility damage data for the updating of slow-moving landslide inventory maps at medium scale

Abstract. Testing innovative procedures and techniques to update landslide inventory maps is a timely topic widely discussed in the scientific literature. In this regard remote sensing techniques – such as the Synthetic Aperture Radar Differential Interferometry (DInSAR) – can provide a valuable contribution to studies concerning slow-moving landslides in different geological contexts all over the world. In this paper, DInSAR data are firstly analysed via an innovative approach aimed at enhancing both the exploitation and the interpretation of remote sensing information; then, they are complemented with the results of an accurate analysis of survey-recorded damage to facilities due to slow-moving landslides. In particular, after being separately analysed to provide independent landslide movement indicators, the two datasets are combined in a DInSAR-Damage matrix which can be used to update the state of activity of slow-moving landslides. Moreover, together with the information provided by geomorphological maps, the two datasets are proven to be useful in detecting unmapped phenomena. The potentialities of the adopted procedure are tested in an area of southern Italy where slow-moving landslides are widespread and accurately mapped by using geomorphological criteria

Definition of environmental indicators for a fast estimation of landslide risk at national scale

The purpose of this paper is to propose a new set of environmental indicators for the fast estimation of landslide risk over very wide areas. Using Italy (301,340 km2) as a test case, landslide susceptibility maps and soil sealing/land consumption maps were combined to derive a spatially distributed indicator (LRI—landslide risk index), then an aggregation was performed using Italian municipalities as basic spatial units. Two indicators were defined, namely ALR (averaged landslide risk) and TLR (total landslide risk). All data were processed using GIS programs. Conceptually, landslide susceptibility maps account for landslide hazard while soil sealing maps account for the spatial distribution of anthropic elements exposed to risk (including buildings, infrastructure, and services). The indexes quantify how much the two issues overlap, producing a relevant risk and can be used to evaluate how each municipality has been prudent in planning sustainable urban growth to cope with landslide risk. The proposed indexes are indicators that are simple to understand, can be adapted to various contexts and at various scales, and could be periodically updated, with very low effort, making use of the products of ongoing governmental monitoring programs of Italian environment. Of course, the indicators represent an oversimplification of the complexity of landslide risk, but this is the first time that a landslide risk indicator has been defined in Italy at the national scale, starting from landslide susceptibility maps (although Italy is one of the European countries most affected by hydro-geological hazards) and, more in general, the first time that land consumption maps are integrated into a landslide risk assessment