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Landslides are the most dangerous and common natural phenomena causing higher number of victims and damages in Piemonte (north-western Italy). An integrated statistical approach to identify the main predisposing and triggering factor causing shallow landslides occurrence based on a large dataset of historical rainfall-induced shallow landslides and a long-time series of rainfall data is presented. Historical shallow landslide events were compared with territorial and rainfall characteristics. Exploratory Spatial Data Analysis (ESDA) has been performed in order to explore the spatial distributions of landslides with the environmental quantitative variables (morphometry and rainfall) to identify possible patterns of spatial autocorrelation. ESDA showed strong autocorrelation of landslide locations with rainfall variables, while resulting in low values for morphometric parameters at the investigated scale. Moreover, by intersecting landslides distribution with categorical land thematic parameters (land thematic maps) allowed to identify areas with different landslide density occurrence. Resulting susceptibility-related areas were used to improve the landslides regional Early Warning System of Piemonte based on refined empirical intensity vs duration (I-D) rainfall thresholds. [ABSTRACT FROM AUTHOR]

Many landslides were triggered by heavy rainfall from 29 June to 1 July 2017 in Ningxiang County, Hunan Province, China. A field investigation into one of the landslides, known as the Wangjiawan landslide, was undertaken on July 3, 2017, to understand the landslide mechanisms and the factors that triggered the event. The landslide is a translational and rotational slide that degraded downslope to an earth flow. It occurred on a steeply dipping mud-rich slate intercalation. Field investigation shows that the landslide had a movement rate of more than 25 m/s and had been triggered by up to 338 mm of continuous rainfall over 2 days. The landslide was fast-moving because it occurred on a steep slope and showed a rapid reduction in shear strength. The landslide resulted in nine fatalities and 19 injuries, most during initial rescue efforts. To mitigate a possible secondary landslide disaster, later emergency measures including evacuation of the survivors, setting up warning signs, and covering landslide cracks with plastic sheeting were adopted. [ABSTRACT FROM AUTHOR]

This work focuses on the development of a combined statistical-mechanical approach to predict changes in landslide displacement rates from observed changes in rainfall amounts. The forecasting tool FLAME (Forecasting Landslides Accelerations induced by Meteorological Events) associates (1) a statistical impulse response (IR) model to simulate the changes in landslide rates by computing a transfer function between the input signal (e.g. rainfall) and the output signal (e.g. displacement) and (2) a simple 1D mechanical (MA) model (e.g. viscoplastic rheology) to take into account changes in pore water pressure. The models have been applied to forecast the displacement rates at the Super-Sauze landslide (South East France). The performance of different combinations of models (IR model alone, MA model alone and a combination of the IR and MA models) is evaluated against observed changes in pore water pressures and displacement rates at the study site. Results indicate that the three models are able to reproduce the displacement pattern in the general kinematic regime (succession of acceleration and deceleration phases); conversely, extreme kinematic regimes such as fluidization of part of the landslide mass are not being reproduced. The approach constitutes however a robust tool to predict changes in displacement rates from rainfall or groundwater time series. [ABSTRACT FROM AUTHOR]

In Italy, rainfall-induced landslides are recurrent phenomena that cause societal and economic damage. Thus, assessing the rainfall conditions responsible for landslides is important and may contribute to reducing risk. The prediction of rainfall-induced landslides relies primarily on empirical rainfall thresholds. However, the thresholds are affected by uncertainties that limit their use in operational warning systems. A source of uncertainty lies in the characterization of the rainfall events responsible for landslides. Objective criteria for the definition of rainfall events are lacking. To overcome the problem, we propose an algorithm that reconstructs the rainfall events, identifies the rainfall conditions that have resulted in landslides, and measures the duration and the cumulated rainfall for the events. The algorithm is independent from the local settings and uses a reduced set of parameters to account for different physical settings and operational conditions. We tested the algorithm in Sicily, Italy, with rainfall and landslide information between January 2002 and December 2012. The rainfall conditions responsible for landslides identified by the algorithm were compared against results obtained manually. The algorithm was proven capable of accurately reconstructing most (87.7 %) of the rainfall events. For each landslide, the algorithm identified a variable number of rainfall conditions responsible for the failures, which are equally likely triggers of the landslide. This opens the possibility of evaluating the uncertainty introduced by different criteria to determine the rainfall events responsible for landslides. Use of the algorithm shall contribute to reducing the uncertainty in the definition of landslide-triggering rainfall events, to compiling large catalogues of rainfall events with landslides and to determining reliable rainfall thresholds for possible landslide occurrence. [ABSTRACT FROM AUTHOR]

On October 25, 2011, an extreme rainfall event affected a wide area along the coasts of Cinque Terre (eastern Liguria, northern Italy). Particularly, in the Vernazza catchment, the event triggered hundreds of shallow landslides and a debris flood that caused three casualties. Investigation of the slope stability after the event was carried out aiming at defining the most effective mitigation measures which may be adopted in future land use planning. To this objective, a susceptibility model was produced and a series of scenarios were simulated using probabilistic methods. The susceptibility model has provided information about landslide conditioning factors on which to act for reducing landslide occurrence and therefore the associated risk. The simulations have taken into consideration the following alternative types of mitigation measures: (1) restoration of abandoned terraces, (2) reforestation of abandoned terraces, (3) use of local structural measures over stretches of potentially unstable hillsides and (4) avoidance of any intervention. The advantages and the disadvantages of the proposed mitigation measures for shallow landslide risk are discussed considering the results of the simulations and taking into account their complex interaction with environmental, historical, cultural and socio-economic aspects. The results show that the most effective mitigation strategy for reducing landslide risk at short term consists of applying structural measures over potentially unstable slopes. However, a long-term programme promoting the development of agricultural or forestry practices on terraced slopes is necessary. In fact, the simulations indicate that if no measures are applied to avoid the degradation of the terraced areas, landslide areal frequency would inevitably increase. [ABSTRACT FROM AUTHOR]

The wired and wireless monitoring system installed in the Rebaixader catchment detected six debris flows and 11 debris floods between 2009 and 2012. Apart from results directly related to the processes, many experiences associated with monitoring were collected. Debris flows and debris floods showed clear differences in both the recorded data and field observations. The distinction was especially visible in the stage measurements and the ground vibration registered by the most downstream geophone. At this geophone, a positive relation between the maximum ground vibration and the volume was also observed. The triggering of most events was associated with short, high-intensity rainstorms in summer, but some were also generated in spring, when the melting of snow cover and frozen soil played an additional role. A positive correlation between the volume and both the amount and the intensity of the triggering rainfall was observed. Regarding technical aspects, a switch between a 'no-event' mode with a low sample rate and an 'event' mode with a fast sampling was particularly useful at the station that register the passing of a flow. In addition, the stations, which most recently were installed at Rebaixader, apply wireless devices because wireless techniques include multiple advantages against standard wired systems. Although recorded data or even video images provide detailed information on the debris-flow behavior, we strongly recommend periodic field surveys along the entire torrent to verify and improve the interpretation obtained from the monitoring system. [ABSTRACT FROM AUTHOR]

This paper concerns a regional scale warning system for landslides that relies on a decisional algorithm based on the comparison between rainfall recordings and statistically defined thresholds. The latter were based on the total amount of rainfall, which was cumulated considering different time intervals: 1-, 2- and 3-day cumulates took into account the critical rainfall influencing shallow movements, whilst a variable time interval cumulate (up to 240 days) was used to consider the triggering of deep-seated landslides in low permeability terrains. A prototypal version of the model was initially set up to define statistical thresholds. Then, thresholds were calibrated using a database of past georegistered and dated landslides. A validation procedure showed that the calibration highly improves the results and therefore the model was integrated in the regional warning system of Emilia Romagna (Italy) for civil protection purposes. The proposed methodology could be easily implemented in other similar regions and countries where a sufficiently organised meteorological network is present. [ABSTRACT FROM AUTHOR]