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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]

Most regional landslide warning systems utilize empirically derived rainfall thresholds that are difficult to improve without recalibration to additional landslide events. To address this limitation, we explored the use of synthetic rainfall to generate thousands of possible storm patterns and coupled them with a physics‐based hydrology and slope stability model for various antecedent soil saturation scenarios to analyze pore water pressure and factor of safety metrics. We used these metrics to generate two‐tiered alert thresholds that can be employed to assess shallow landslide potential for any given combination of storm and antecedent wetness. When applied to the San Francisco Bay region (CA, USA), the results are consistent with events that caused widespread landsliding. Our deterministic modeling approach, which accounts for plausible ranges in soil hydraulic and mechanical properties, can inform the development of the next generation of warning systems for rainfall‐induced landsliding. Plain Language Summary: Providing accurate warning in advance of rainfall‐induced landsliding can help reduce loss of life and property but requires knowledge of hillslope wetness and future rainfall conditions to forecast when widespread landsliding is likely. However, typical landslide warning systems consider only the rainfall characteristics (e.g., rainfall amount, duration, and/or intensity) that were measured during past landslide events. These are used to define a set of rainfall conditions, or a threshold, for which landsliding should be expected within a given area. When a rainfall threshold does not perform well for subsequent landsliding events, it can be difficult to diagnose the problem because hillslope wetness is not considered. We present an approach to develop landslide thresholds that accounts for both rainfall and hillslope wetness. The results are consistent with historical and recent widespread landsliding events in our study region and, more importantly, can be related to measurable properties of hillslopes. This more direct approach could revolutionize the development of the next generation of landslide warning systems. Key Points: Thresholds for rainfall‐induced landsliding of soil‐mantled hillslopes identified with physics‐based hydrologic and slope stability modelingLibrary of modeled infiltration events based on variations in rainfall and antecedent soil saturation facilitates timely hazard assessmentDeterministic modeling approaches that account for parameter variability can inform the next generation of landslide warning systems [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]

Landslides triggered by rainfall are a major multiple geological hazard on Qin-ba Mountain. Debris landslides in the shallow layer make up a large proportion of all landslides. A flume experiment was conducted to successfully initiate shallow debris landslides using artificial rainfall in Zhouzhi County, Qin-ba Mountain. The results confirmed a strong correlation between the deformation of the slope and pore-water pressure and moisture content. Slope deformation and failure were observed, and a possible mechanism was interpreted based on the experimental results. The primary effects of rainfall on shallow debris landslides on Qin-ba Mountain are the generation of a seepage force and a decrease in the effective stress of the sliding surface as a result of increasing pore-water pressure. The effect of rainfall on the shear strength parameters is inconspicuous, which might be attributed to the relatively high saturation of debris soils under natural conditions. The failure type in Test 1 is considered to be a progressive failure, which is a typical failure mode for homogeneous shallow debris slopes on Qin-ba Mountain, particularly for slopes exposed to artificial excavation. The deformation in Test 2 with higher density, merely taking the form of surface erosion, usually occurs in the regions with the least artificial disturbance. The two deformation types can be primarily attributed to differences in the soil density; the higher density reflected the smaller number and size of inside pores and led to lower soil permeability, which further influenced the distribution of the pore-water pressure, direction of seepage force, and slope deformation. Therefore, higher soil density changed by compaction is beneficial for the stability of shallow debris slopes on Qin-ba Mountain, even with high pore-water pressure. In subsequent work, a series of experiments with various densities should be conducted to explore the dividing point between the two deformation modes, and in addition, tests with larger slope gradients should also be considered. [ABSTRACT FROM AUTHOR]

The increase of rainfall and rise of groundwater level can cause frequent failures of unsaturated soil slopes that result in catastrophic landslides. This paper proposes a stochastic method for predicting the risk of failure of an infinite soil slope subjected to unsaturated infiltration flow. Stochastic models for shear stress and strength at an arbitrary plane of an infinite slope are developed. The accuracy of the proposed method is verified with the Monte Carlo simulation method. The merit of the proposed method lies in its analytical form, which can easily facilitate practical applications. Furthermore, a risk-based sensitivity analysis is undertaken in this study to identify the factors that are the most random and that affect the slope failure most significantly. It is found in this study that the developed stochastic models can capture the randomness of all factors that contribute to slope failure. It is also found that the slope inclination angle (θ) soil air entry value (ψb) water table rise from matric suction (yb) dry soil unit weight (γd) and soil-specific constant (aϕ) are important random variables in the accurate prediction of slope failure. The paper concludes that the proposed stochastic method can serve as a tool for geotechnical engineers to predict the risk of slope failure with accuracy and ease. [ABSTRACT FROM AUTHOR]

This paper outlines a framework for risk assessment of landslides triggered by earthquakes and rainfall in urban buildings in the city of Medellín - Colombia, applying a model that uses a geographic information system (GIS). We applied a computer model that includes topographic, geological, geotechnical and hydrological features of the study area to assess landslide hazards using the Newmark's pseudo-static method, together with a probabilistic approach based on the first order and second moment method (FOSM). The physical vulnerability assessment of buildings was conducted using structural fragility indexes, as well as the definition of damage level of buildings via decision trees and using Medellin's cadastral inventory data. The probability of occurrence of a landslide was calculated assuming that an earthquake produces horizontal ground acceleration ( A h ) and considering the uncertainty of the geotechnical parameters and the soil saturation conditions of the ground. The probability of occurrence was multiplied by the structural fragility index values and by the replacement value of structures. The model implemented aims to quantify the risk caused by this kind of disaster in an area of the city of Medellín based on different values of A h and an analysis of the damage costs of this disaster to buildings under different scenarios and structural conditions. Currently, 62% of “Valle de Aburra” where the study area is located is under very low condition of landslide hazard and 38% is under low condition. If all buildings in the study area fulfilled the requirements of the Colombian building code, the costs of a landslide would be reduced 63% compared with the current condition. An earthquake with a return period of 475 years was used in this analysis according to the seismic microzonation study in 2002. [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]

Rainfall induced landslides vary in depth and the deeper the landslide, the greater the damage it causes. This paper investigates, quantitatively, the risk of rainfall induced landslides by assessing the consequence of each failure. The influence of the spatial variability of the saturated hydraulic conductivity and the nature of triggering mechanisms on the risk of rainfall-induced landslides (for an infinite slope) are studied. It is shown that a critical spatial correlation length exists at which the risk is a maximum and the risk is higher when the failure occurs due to a generation of positive pore water pressure. [ABSTRACT FROM AUTHOR]

The 12 May 2008 Wenchuan earthquake in China triggered numerous landslides. Loose landslide materials can easily evolve into deadly debris flows during wet seasons. During the period from 2008 to 2011, three separate large-scale debris flows occurred in the Pubugou Ravine near the epicentre of the earthquake that were among the largest repeated debris flows ever reported. Approximately 1.76 × 106 m3 of sediment was deposited during these three events. This paper aims to ( i) analyze the movements of solid materials during the repeated debris flows, ( ii) discuss the evolution of the initiation mechanisms of these debris flows, and ( iii) evaluate the changing depositional morphology of the debris flow fans and examine the particle sizes of the debris flow materials. To achieve the above research objectives, timely field investigations were undertaken in the past 5 years after each of these debris flow events. Satellite images were used to delineate the boundaries of the initiation areas, the transportation channels, and the deposition zones of these debris flows. With the occurrence of the repeated debris flows, the hill slope deposits gradually evolved into channel deposits and the solid materials in the channels moved toward the gully mouth. Hence, channelized flows gradually became dominant. The debris fan materials of the repeated debris flows became coarser and coarser over time. The three debris flows were all characterized by coarse boulder fronts. [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]