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Abstract

Landslides represent a serious hazard in many areas around the world, potentially leading to human losses and significant damages to structures and buildings. For this reason, over the years a consistent number of studies and researches have been carried out to analyse these natural phenomena and their evolution. This study presents the application of an automatic procedure specifically developed to identify the onset of landslide acceleration by analysing monitoring displacement data with a multi-criteria approach. The proposed procedure aims to identify this point by applying a four-level validation process on a pre-determined dataset. Once the analysis returns a positive result for a certain number of monitoring data, it is possible to state that the landslide reached the accelerating phase of its evolution, thus allowing to define a specific point representing the onset of acceleration. The method was applied to several historical case studies taken from scientific literature, in order to test its practicability and effectiveness. This procedure could be especially useful in Early Warning Systems where time of failure forecasting models are implemented, allowing to improve their performances by providing an automated and reliable procedure to define the beginning of potentially critical landslide events.

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... Many studies are also based on this idea. Ref. [12] presented the application of an automatic procedure specifically developed to identify the onset of landslide acceleration by analyzing displacement monitoring data with a multi-criteria approach. Refs. ...
... where t i is the collection time of the i − th datapoint, and S i is the cumulative deformation of the i − th datapoint. In conventional early warning, the velocity and acceleration of the landslide displacement must be calculated, which is usually done using the differential calculation method of the following equation [12]: ...
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The data collection in the automated monitoring of landslides is often characterized by large amounts of data, periodic fluctuations, many outliers, and different collection intervals. The traditional method of calculating velocity and acceleration using the differential algorithm for landslide acceleration relies on experience to select thresholds and produces a large number of false early warnings. A hybrid early warning method for the landslide acceleration process based on automated monitoring data is proposed to solve this problem. The method combines the conventional warning method, based on cumulative displacement, velocity, and acceleration, and the critical sliding warning method based on normalized tangent angle according to different strategies. On the one hand, the least-squares fitting of monitoring data inside a given time window is used to calculate various early warning parameters, improving data usage and lowering calculation error. On the other hand, a dynamic semi-quantitative and semi-empirical method is provided for the determination of the thresholds, which is more reliable than the purely empirical method. The validation experiments at the Lishanyuan landslide in southern China show that the hybrid method can accurately identify the accelerating deformation of the landslide and gives very few false warnings. The proposed method is practical and effective for systems that require automated monitoring and warnings for a large number of landslides.
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The 10-mile Slide is contained within an ancient earthflow located in British Columbia, Canada. The landslide has been moving slowly for over 40 years, requiring regular maintenance work along where a highway and a railway track cross the sliding mass. Since 2013, the landslide has shown signs of retrogression. Monitoring prisms were installed on a retaining wall immediately downslope from the railway alignment to monitor the evolution of the retrogression. As of September 2016, cumulative displacements in the horizontal direction approached 4.5 m in the central section of the railway retaining wall. After an initial phase of acceleration, horizontal velocities showed a steadier trend between 3 and 9 mm/day, which was then followed by a second acceleration phase. This paper presents an analysis of the characteristics of the surface displacement vectors measured at the monitoring prisms. Critical insight on the behavior and kinematics of the 10-mile Slide retrogression was gained. An advanced analysis of the trends of inverse velocity plots was also performed to assess the potential for a slope collapse at the 10-mile Slide and to obtain further knowledge on the nature of the sliding surface.
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In this work, the ability of advanced satellite interferometry to monitor pre-failure landslide behaviours and the potential application of this technique to Failure Forecasting Methods (FFMs) are analysed. Several limits affect the ability of the technique to monitor a landslide process, especially during the pre-failure phase (tertiary creep). In this study, two of the major limitations affecting the technique have been explored: (1) the low data sampling frequency and (2) the phase ambiguity constraints. We explored the time series of displacements for 56 monitored landslides inferred from the scientific literature and from different in situ and remote monitoring instruments (i.e., extensometers, inclinometers, distometers, Ground Base InSAR, and total station). Furthermore, four different forecasting techniques have been applied to the monitoring data of the selected landslides. To analyse the reliability of the FFMs based on the InSAR satellite data, the 56 time series have been sampled based on different satellite features, simulating the satellite revisit time and the phase ambiguity constraints. Our analysis shows that the satellite InSAR technique could be successful in monitoring the landslide’s tertiary creep phase and, in some cases, for forecasting the corresponding time of failure using FFMs. However, the low data sampling frequency of the present satellite systems do not capture the necessary detail for the application of FFMs in actual risk management problems or for early warning purposes.
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Predicting the time of failure is a topic of major concern in the field of geological risk management. Several approaches, based on the analysis of displacement monitoring data, have been proposed in recent years to deal with the issue. Among these, the inverse velocity method surely demonstrated its effectiveness in anticipating the time of collapse of rock slopes displaying accelerating trends of deformation rate. However, inferring suitable linear trend lines and deducing reliable failure predictions from inverse velocity plots are processes that may be hampered by the noise present in the measurements; data smoothing is therefore a very important phase of inverse velocity analyses. In this study, different filters are tested on velocity time series from four case studies of geomechanical failure in order to improve, in retrospect, the reliability of failure predictions: Specifically, three major landslides and the collapse of an historical city wall in Italy have been examined. The effects of noise on the interpretation of inverse velocity graphs are also assessed. General guidelines to conveniently perform data smoothing, in relation to the specific characteristics of the acceleration phase, are deduced. Finally, with the aim of improving the practical use of the method and supporting the definition of emergency response plans, some standard procedures to automatically setup failure alarm levels are proposed. The thresholds which separate the alarm levels would be established without needing a long period of neither reference historical data nor calibration on past failure events.
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Forecasting the failure of large rock slides is difficult because of nonlinear time dependency and seasonal effects, which affect the displacements. Starting from the accelerating creep theory proposed by Voight, a method is suggested to forecast slope failures and to assess alert velocity thresholds using monitoring data. The 20 Mm3 Ruinon rock slide (Valfurva, Central Alps, Italy), susceptible to evolve into a rock avalanche, is studied. Three different evolutionary patterns of displacements have been recognized through the analysis of the monitoring data for a 5 year period. Data representing the surface-based large-scale behaviour of the rock mass were fitted by power-law curves, according to the "accelerating creep" model. Voight's equation has been expressed in terms of displacement and used to fit the data by nonlinear estimation techniques. Values for the controlling parameters (A, α, tf), representative of the mechanical behaviour of the rock mass approaching failure, have been determined both for single and multiple accelerating phases. "Characteristic velocity curves" have been computed by assuming these parameters are representative of the rock mass behaviour. Velocity threshold values for pre-alert, alert, and emergency phases have been computed. The method has been validated by collecting and analysing literature data for historical rock slope failures.Key words: slope stability, rock slide, accelerating creep, monitoring, failure forecasting, velocity thresholds.
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Landslides interacting with large infrastructures represent a major problem for the economy, society as a whole, and the safety of workers. Continuous monitoring for 23months using an integrated platform with a ground-based SAR interferometer (GB-InSAR), a weather station, and an automatic camera gave us the opportunity to analyze the response of an unstable slope to the different phases of work. The deformational behavior of both the natural slope and the man-made structures was recorded and interpreted in relation to the working stages and the rainfall conditions during the whole monitoring period. A typical pattern of displacement was identified for shallow landslides, debris produced by the excavation and gabions, metallic walls, and anchored bulkheads. Furthermore, insights into the dynamics and behavior of the slope and the man-made structures that interact with the landslide were obtained. Extreme rainfall is the main trigger of shallow landslides and gabion deformations, while anchored bulkheads are less influenced by rainfalls. Movement of debris that is produced by excavations and temporary metallic barrier deformation are closely related to each other. The herein proposed monitoring platform is very efficient in monitoring unstable slopes that are affected by human activities. Moreover, the recorded patterns of displacement in the slope and the man-made structures can be used as reference data for similar studies and engineering designs. KeywordsGB-InSAR–Interferometry–Landslide–Monitoring–Displacement–Infrastructure
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Accelerating displacements preceding some catastrophic landslides have been found empirically to follow a time-to-failure power law, corresponding to a finite-time singularity of the velocity $v \sim 1/(t_c-t)$ [{\it Voight}, 1988]. Here, we provide a physical basis for this phenomenological law based on a slider-block model using a state and velocity dependent friction law established in the laboratory and used to model earthquake friction. This physical model accounts for and generalizes Voight's observation: depending on the ratio $B/A$ of two parameters of the rate and state friction law and on the initial frictional state of the sliding surfaces characterized by a reduced parameter $x_i$, four possible regimes are found. Two regimes can account for an acceleration of the displacement. We use the slider-block friction model to analyze quantitatively the displacement and velocity data preceding two landslides, Vaiont and La Clapi\`ere. The Vaiont landslide was the catastrophic culmination of an accelerated slope velocity. La Clapi\`ere landslide was characterized by a peak of slope acceleration that followed decades of ongoing accelerating displacements, succeeded by a restabilizing phase. Our inversion of the slider-block model on these data sets shows good fits and suggest to classify the Vaiont (respectively La Clapi\`ere) landslide as belonging to the velocity weakening unstable (respectively strengthening stable) sliding regime.
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Real-time monitoring can improve the performance assessment of tailings dams by reducing the laborious component of data collection while streamlining the analysis process. When planning and installing instrumentation, the challenge exists where if nothing goes wrong, the question is asked whether too much instrumentation is installed, where on the other hand if a failure occurs, the question is asked as to why more investment was not made to prevent it from occurring. This paper identifies the monitoring system requirements, assesses the cost of historical tailings dam failures (Mt Polley and Fundão), assesses the cost of a real-time monitoring system to suit the instrumentation that was in place at time of failure of those dams (including standpipe and vibrating wire piezometers, digital inclinometers, and flow meters), and suggests ways to extract more value from individual instruments to full monitoring system integration.
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Rainfall can trigger flow-like mass movements characterised by different percentages of solid and water (debris flows, hyperconcentrated flows, and flash floods). They exhibit different magnitude (volume), run-out distance and consequence, due to both distinct triggering mechanisms and kinematic features. Indeed, discriminating among these phenomena for appropriate risk analysis and zoning is a relevant issue also considering that the volume of the flow may sudden increase along the propagation path. The paper deals with September 2010 combined types of flows occurred at Atrani village (Amalfi coast, southern Italy), and originated by heavy rainstorm in the catchment located upslope to the urban centre. The events were reconstructed by using multi-source information. Field surveys, geological analysis, elaboration of videos recorded during the events and numerical modelling were combined. A 40 minutes lasting water flood abruptly combined to a relatively small-sized high-discharge hyperconcentrated flow, with the consequence of an abnormal flow that invaded the narrow main street of the urban area in few minutes. The peak discharge at the catchment outlet was increased by erosion and/or other rainfall-induced slope instabilities occurred in the whole catchment. As main conclusion, the multidisciplinary analysis has resulted effective to enhance the understanding of the complex flow-like mass movements.
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The concept of pre-failure behaviour within a landslide mass was first established by Terzaghi (1950) who noted that, for landslide failure to occur, a progressive reduction in shear strength was required at the shear surface. Similarly, observations by Varnes (1978) noted that deforming materials undergo pre-failure creep as a result of deformation of the material. These observations have been developed by others into methods for predicting slope failures and landslides. Despite these prediction methods, the mechanisms by which prefailure creep occurs remains poorly understood. This paper develops a predictive pre-failure model through detailed analysis of surface movement patterns of first-time and pre-existing landslides. The analysis includes specialist pore-pressure re-inflation tests where elevated pore pressures are simulated under a constant deviatoric stress. The results demonstrate how subtle variations in pre-failure creep are related to material deformation and local porewater pressure conditions at the shear zone. This new research contributes to the development of site-specific ground behaviour and failure prediction models for complex landslides undergoing first-time and reactivation failures.
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The time of failure of a slope is forecasted using the basic equation regarding the time process in tertiary creep. First, the equation to forecast the time of slide (tr) is derived. This equation is the same type as Saito's equation with respect to exp (at). Here, a is the constant, and t is time. Then, if the value of coefficient a is assumed, the time of failure (tr) can be forecasted using time (t) with respect to three equal intervals Δl in continuous displacement (l). This method of slide forecasting is called the a-tr method and slide forecasting is made for some field v-t data. The error for this method is not much better than Saito's graphical analysis.
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A slope 120 m wide and 100 m high collapsed including the roadbed of a national highway of Route 168 at Ohto, Nara, Japan on August 10, 2004. The precursory phenomena of abnormal features were found as cracks growing on the road-side slope 7 months before the catastrophe. The movements of the slope were monitored by extensometers. The data of the extensometers showed that creep mode turned from the secondary into the tertiary due to the heavy rainstorm of Typhoon Namtheun. The slide claimed no victims because the highway was closed 43 h before the catastrophe, anticipating a possible hazard when the creep velocity reached 4 mm/2 h. Comparison of rupture time predictions suggested that precision of the prediction using the reciprocal of creep velocity is higher than that by tertiary creep analysis, although leaving a problem that the prediction of the time zone of failure erred on the dangerous side. The slide generated ground vibration which was observed by seismometers deployed around the slide. Duration of the seismic signals corresponded well with the slide motion deciphered from video records. We found the fact that the seismic energy radiation from a landslide consisted of four stages. This had not been reported in any previous study, and may be important in understanding the dynamics of a rock-slide avalanche.
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Late in January 2004 slope instability evidence such as cracks and subsidence appeared on a retaining wall along National Highway 168, near Otomura (Nara Prefecture, Japan). This road plays a strategic role as a long distance route for passenger vehicles and trucks, therefore detailed investigations and constant surveillance have to be carried out in order to manage the induced risk situations. Six months later, on August 10th, a large landslide occurred due to heavy rainfalls related to typhoons #10 and #11 that hit Japan on the first week of August. Field and aerial surveys of the site were carried out soon after the appearance of the first geomorphologic evidence of landslide movements, and a monitoring system was immediately set up. Landslide displacements have been measured since the early stage of movement and road traffic was strictly controlled in order to minimize possible damage. This paper illustrates the effects of landslide activation and the investigations carried out in order to assess landslide hazard and predict the time of failure. Suitable methods for risk management oriented to increase the public safety and including risk control and crisis mitigation acts are also discussed.
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