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Landslide dams are a common phenomenon. They form when a landslide reaches the bottom of a river valley causing a blockage. The first effect of such a dam is the infilling of a lake that inundates the areas upstream, while the possibility of a sudden dam collapse, with a rapid release of the impounded waters, poses a higher flood risk to the downstream areas.The results of the main inventories carried out to date on landslide dams, have been examined to determine criteria for forecasting landslide dam evolution with particular emphasis on the assessment of dam stability. Not all landslides result in the blockage of a river channel. This only occurs with ones that can move a large amount of material with moderate or high-velocities. In most cases, these landslides are triggered by rainfall events or high magnitude earthquakes. A relationship also exists between the volume of the displaced material and the landslide dam stability.Several authors have proposed that landslide dam behaviour can be forecast by defining various geomorphological indexes, that result from the combination of variables identifying both the dam and the dammed river channel. Further developments of this geomorphological approach are presented in this paper by the definition of a dimensionless blockage index. Starting with an analysis of 84 episodes selected worldwide, it proved to be a useful tool for making accurate predictions concerning the fate of a landslide dam.

We present the methodologies adopted and the outcomes obtained in the analysis of landslide risk in the basin of the Arno River (Central Italy) in the framework of a project sponsored by the Basin Authority of the Arno River, started in the year 2002 and completed at the beginning of 2005. In particular, a complete set of methods and applications for the assessment of landslide susceptibility and risk are described and discussed.A new landslide inventory of the whole area was realized, using conventional (aerial-photo interpretation and field surveys) and nonconventional methods (e.g. remote sensing techniques such as DIn-SAR and PS-InSAR).The great majority of the mapped mass movements are rotational slides (75%), solifluctions and other shallow slow movements (17%) and flows (5%), while soil slips, and other rapid landslides, seem less frequent everywhere within the basin. The relationships between landslide characteristics and environmental factors have been assessed through statistical analysis. As expected, the results show a strong control of land cover, lithology and morphology on landslide occurrence. The landslide frequency-size distribution shows a typical scaling behaviour already underlined in other landslide inventories worldwide. The assessment of landslide hazard in terms of probability of occurrence in a given time, based for mapped landslides on direct and indirect observations of the state of activity and recurrence time, has been extended to landslide-free areas through the application of statistical methods implemented in an artificial neural network (ANN). Unique conditions units (UCU) were defined by the map overlay of landslide preparatory factors (lithology, land cover, slope gradient, slope curvature and upslope contributing area) and afterwards used to construct a series of model vectors for the training and test of the ANN. Various different ANNs were selected throughout the basin, until each UCU was assigned a degree of membership to a susceptibility and a hazard class. Model validation confirms that prediction results are very good, with an average percentage of correctly recognized mass movements of about 85%. The analysis also revealed the existence of a large number of unmapped mass movements, thus contributing to the completeness of the final inventory. Temporal hazard was estimated via the translation of state of activity in recurrence time and hence probability of occurrence. The following intersection of hazard values with vulnerability and exposure figures, obtained by reclassification of digital vector mapping at 1:10,000 scale, lead to the definition of risk values for each terrain unit for different periods of time into the future. The final results of the research are now undergoing a process of integration and implementation within land planning and risk prevention policies and practices at local and national level.

We present the continuous monitoring of ground deformation at regional scale using ESA (European Space Agency) Sentinel-1constellation of satellites. We discuss this operational monitoring service through the case study of the Tuscany Region (Central Italy), selected due to its peculiar geological setting prone to ground instability phenomena. We set up a systematic processing chain of Sentinel-1 acquisitions to create continuously updated ground deformation data to mark the transition from static satellite analysis, based on the analysis of archive images, to dynamic monitoring of ground displacement. Displacement time series, systematically updated with the most recent available Sentinel-1 acquisition, are analysed to identify anomalous points (i.e., points where a change in the dynamic of motion is occurring). The presence of a cluster of persistent anomalies affecting elements at risk determines a significant level of risk, with the necessity of further analysis. Here, we show that the Sentinel-1 constellation can be used for continuous and systematic tracking of ground deformation phenomena at the regional scale. Our results demonstrate how satellite data, acquired with short revisiting times and promptly processed, can contribute to the detection of changes in ground deformation patterns and can act as a key information layer for risk mitigation.

Pore water pressures (positive and negative) were monitored for four years (1996-1999) using a series of tensiometer-piezometers at increasing depths in a riverbank of the Sieve River, Tuscany (central Italy), with the overall objective of investigating pore pressure changes in response to flow events and their effects on bank stability. \ud The saturated/unsaturated flow was modelled using a finite element seepage analysis, for the main flow events occurring during the four-year monitoring period. Modelling results were validated by comparing measured with computed pore water pressure values for a series of representative events. Riverbank stability analysis was conducted by applying the limit equilibrium method (Morgenstern-Price), using pore water pressure distributions obtained by the seepage analysis. \ud The simulation of the 14 December 1996 event, during which a bank failure occurred, is reported in detail to illustrate the relations between the water table and river stage during the various phases of the hydrograph and their effects on bank stability. The simulation, according to monitored data, shows that the failure occurred three hours after the peak stage, during the inversion of flow (from the bank towards the river). A relatively limited development of positive pore pressures, reducing the effective stress and annulling the shear strength term due to the matric suction, and the sudden loss of the confining pressure of the river during the initial drawdown were responsible for triggering the mass failure. \ud Results deriving from the seepage and stability analysis of nine selected flow events were then used to investigate the role of the flow event characteristics (in terms of peak stages and hydrograph characteristics) and of changes in bank geometry. Besides the peak river stage, which mainly controls the occurrence of conditions of instability, an important role is played by the hydrograph characteristics, in particular by the presence of one or more minor peaks in the river stage preceding the main on