Article

# Definition and application of a multi-criteria algorithm to identify landslide acceleration phases

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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.
Presentation
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The identification of potentially critical events involving unstable slopes is a major aspect in the field of natural hazards risk mitigation and management. In this framework, Early Warning Systems (EWS) exploiting advanced technologies represent an efficient approach to decrease the risk generated by landslide phenomena, allowing to reduce the possibility of damages and losses of human lives. EWS effectiveness has increased significantly in recent years, thanks to relevant advances in sensing technologies and data processing. In particular, the introduction of innovative monitoring instrumentation featuring automatic procedures and increased performances in terms of sampling rate and accuracy has permitted to develop EWS characterised by a near-real time approach. Among the several aspects involved in the development of a reliable Early Warning System, one of the most important is the ability to minimize the dissemination of false alarms, which should be avoided or identified in advance. The approach proposed in this study represents a new procedure aimed to assess the hazard level posed by a potentially critical event, previously identified by analysing displacement monitoring data. The process is implemented in a near-real time EWS and defines a total of five different hazard levels, on the basis of the results provided by two different models, namely an accelerating trend identification criterion and a failure forecasting model based on the Inverse Velocity Method (IVM). In particular, the forecasting analysis is performed only if the dataset elaborated by the onset-of-acceleration model highlights a potentially critical behaviour, which represents a first alert level. Following levels are determined by different conditions imposed on three parameters featured by the failure forecasting model, i.e. dataset dimension, coefficient of determination R-squared, and number of sensors displaying an accelerating trend. As these criteria get fulfilled, it is assumed that the monitored phenomenon is gradually evolving towards a more critical condition, thus reaching an increasing alert level depending on the analysis results. According to this classification, it is possible to set up for each single threshold a dedicated warning message, which could be automatically issued to authorities responsible of monitoring activities, in order to provide an adequate dissemination of information concerning the ongoing event. Moreover, the proposed procedure allows to customize the alert approach, giving the possibility to issue warning messages only if a certain Level is reached during the analysis.
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Landslides in reservoir contexts are a well-recognised hazard that may lead to dangerous situations regarding infrastructures and people’s safety. Satellite-based radar interferometry is proving to be a reliable method to monitor the activity of landslides in such contexts. Here, we present a DInSAR (Differential Interferometric Synthetic Aperture Radar) analysis of Sentinel-1 images that exemplifies the usefulness of the technique to recognize and monitor landslides in the Rules Reservoir (Southern Spain). The integration of DInSAR results with a comprehensive geomorphological study allowed us to understand the typology, evolution and triggering factors of three active landslides: Lorenzo-1, Rules Viaduct and El Arrecife. We could distinguish between rotational and translational landslides and, thus, we evaluated the potential hazards related to these typologies, i.e., retrogression (Lorenzo-1 and Rules Viaduct landslides) or catastrophic slope failure (El Arrecife Landslide), respectively. We also observed how changes in the water level of the reservoir influence the landslide’s behaviour. Additionally, we were able to monitor the stability of the Rules Dam as well as detect the deformation of a highway viaduct that crosses a branch of the reservoir. Overall, we consider that other techniques must be applied to continue monitoring the movements, especially in the El Arrecife Landslide, in order to avoid future structural damages and fatalities.
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Recent studies using satellite data have shown a growing interest in detecting and anticipating landslide failures. However, their value for an actual landslide prediction has shown variable results. Therefore, the use of satellite images for that purpose still requires additional attention. Here, we study the landslide of the Tunnel du Chambon in the French Alps that ruptured in July 2015, generating major impacts on economic activity and infrastructures. To evaluate the contribution of very high-resolution optical satellite images to characterize and potentially anticipate the landslide failure, we conduct here a retro analysis of its evolution. Two time periods are analyzed: September 2012 to September 2014, and May to July 2015. We combine Pléiades optical images analysis and geodetic measurements from in situ topographic monitoring. Satellite images were correlated to detect pre-failure motions, showing 1.4-m of displacement between September 2012 and September 2014. In situ geodetic measures were used to analyze motions during the main activity of the landslide in June and July 2015. Topographic measurements highlight different areas of deformations and two periods of strong activity, related to the last stage of the tertiary creep and to anthropic massive purges of unstable masses. The law of acceleration toward the rupture observed in June and July 2015 over the topographic targets also fits well the satellite observation between 2012 and 2014, showing that the landslide probably already entered into tertiary creep 2.5 years before its failure.
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Forecasting the time of failure of landslides at slope-scale is a difficult yet important task that can mitigate the effects of slope failures in terms of both human lives and economic losses. Common applications include public safety situations, where the risk is represented by dwellings built near active landslides or unstable cut slopes that threaten streets and railways, and open-pit mines, for which accurate warnings are fundamental to safeguard workers and simultaneously avoid unnecessary interruptions of the extraction activities. The scientific literature is populated by many methods, guidelines and approaches regarding forecasting the time of failure or defining the conditions of imminent collapse. Thus, obtaining a synoptic view of the advantages and limitations of these different methodologies has become difficult. At the same time, innovations in technology have opened new possibilities to the application of such techniques, which are examined here. This paper discusses and classifies these methods, addressing their respective differences and peculiarities to foster the usage even of less popular methods without overlooking the more scientific aspects and issues of landslide forecasting. Finally, an overview of the future trends and challenges is presented to contribute to the debate around this important topic.
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During recent years, the availability of innovative monitoring instrumentation has been a fundamental component in the development of efficient and reliable early warning systems (EWS). In fact, the potential to achieve high sampling frequencies, together with automatic data transmission and elaboration are key features for a near-real time approach. This paper presents a case study located in Central Italy, where the realization of an important state route required a series of preliminary surveys. The monitoring system installed on site included manual inclinometers, automatic modular underground monitoring system (MUMS) inclinometers, piezometers, and geognostic surveys. In particular, data recorded by innovative instrumentation allowed for the detection of major slope displacements that ultimately led to the landslide collapse. The implementation of advanced tools, featuring remote and automatic procedures for data sampling and elaboration, played a key role in the critical event identification and prediction. In fact, thanks to displacement data recorded by the MUMS inclinometer, it was possible to forecast the slope failure that was later confirmed during the following site inspection. Additionally, a numerical analysis was performed to better understand the mechanical behavior of the slope, back-analyze the monitored event, and to assess the stability conditions of the area of interest.
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The Sentinel-2 optical satellites provide a global coverage of land surfaces with a 5-day revisit time at the Equator. We investigate the ability of these freely available optical images to detect precursory motions before rapid landslides. A 9-month time-series of displacement is derived from Sentinel-2 data over a major landslide in the French Alps, which exhibited a sudden reactivation in June 2016. This analysis reveals a 7-month period of low activity (≤1 m), followed by a sudden acceleration of 3.2 ± 1.2 m in 3 days, before the failure of a mass of about 2 to 3.6 10⁶ m³. The location of this precursory motion is consistent with that of the slow motions occurring since 2001 (about 1 m/year), as revealed by aerial photographs and LiDAR analysis. This change in activity over a very short period of time (days) emphasizes the value of the frequent revisit time of Sentinel-2, despite its medium resolution of 10 m. We finally simulate the ability of Sentinel-2 for detecting these precursory patterns before a rapid landslide occurs, based on typical Voight's laws for creeping materials, characterized by a power law exponent α. Based on this analysis and on global cloud cover maps, we compute the probability to detect pre-failure motions of landslides using the Sentinel-2 constellation. This probability is highly heterogeneous at the global scale, affected by the revisit time of the satellite and the cloud cover. However the main factors controlling this detection ability are the properties of the landslide itself (its size and the α parameter), with almost 100% of detection probability for α = 1.3 and 0% for α = 1.8. Despite all these limitations, probability to detect a motion before a landslide failure often reaches 50% for classical landslide parameters. These results open new perspectives for the early warning of large landslide motion from global and open source remote sensing data.
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The paper 'Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses' by T. Carlà, E. Intrieri, F. Di Traglia, T. Nolesini, G. Gigli and N. Casagli deals with a sensitive topic for landslide risk management. Exploring the pre-failure behaviour of four different case histories, the authors proposed standard procedures for the application of the inverse velocity method (INV, Fukuzono 1985). Specifically, they suggested guidelines for the filtering of velocity data and an original and simple approach to automatically set the first and the second alarm thresholds using the inverse velocity method. The present discussion addresses three different topics: (1) data filter selection according to the features of monitoring instrument; (2) the importance of data sampling frequency for the forecasting analysis and (3) the influence of the starting point (SP in this discussion) for the application of INV analysis. Moreover, based on this matter , a new method is proposed to update the INV analysis on an ongoing basis.
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Largely unknown mechanisms restrain motion of clay-rich, slow-moving landslides that are widespread worldwide and rarely accelerate catastrophically. We studied a clayey, slow-moving landslide typical of thousands in Northern California, USA, to decipher hydrologic-mechanical interactions that modulate landslide dynamics. Similar to some other studies, observed pore-water pressures correlated poorly with landslide reactivation and speed. In situ and laboratory measurements strongly suggested that variable pressure along the landslide's lateral shear boundaries resulting from seasonal soil expansion and contraction modulated its reactivation and speed. Slope-stability modeling suggested that the landslide's observed behavior could be predicted by including transient swell pressure as a resistance term, whereas modeling considering only transient hydrologic conditions predicted movement five to six months prior to when it was observed. All clayey soils swell to some degree; hence, our findings suggest that swell pressure likely modulates motion of many landslides and should be considered to improve forecasts of clayey landslide initiation and mobility.
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Post-event Interferometric Synthetic Aperture Radar (InSAR) analysis on a stack of 45 C-band SAR images acquired by the ESA Sentinel-1 satellites from 9 October 2014 to 19 June 2017 allowed the identification of a clear precursory deformation signal for the Maoxian landslide (Mao County, Sichuan Province, China). The landslide occurred in the early morning of 24 June 2017 and killed more than 100 people in the village of Xinmo. Sentinel-1 images have been processed through an advanced multi-interferogram analysis capable of maximising the density of measurement points, generating ground deformation maps and displacement time series for an area of 460 km2 straddling the Minjiang River and the Songping Gully. InSAR data clearly show the precursors of the slope failure in the source area of the Maoxian landslide, with a maximum displacement rate detected of 27 mm/year along the line of sight of the satellite. Deformation time series of measurement points identified within the main scarp of the landslide exhibit an acceleration starting from April 2017. A detailed time series analysis leads to the classification of different deformation behaviours. The Fukuzono method for forecasting the time of failure appear to be applicable to the displacement data exhibiting progressive acceleration. Results suggest that satellite radar data, systematically acquired over large areas with short revisiting time, could be used not only as a tool for mapping unstable areas, but also for landslide monitoring, at least for some typologies of sliding phenomena.
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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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The management of unstable slopes is one of the most critical issues when dealing with safety in open-pit mines. Suitable notice of impending failure events must be provided, and at the same time the number of false alarms must be kept to a minimum to avoid financial losses deriving from unnecessary outages of the production works. Comprehensive slope monitoring programs and early warning systems are usually implemented to this aim. However, systematic procedures for their tuning are lacking and several key factors are often overlooked. Therefore the mitigation of slope failure risk is still a topic of great concern, especially in open-pit mines excavated through hard rock masses featuring markedly brittle behavior, which supposedly provide little or no measurable precursors to failure. In this paper, 9 instabilities occurred at an undisclosed open-pit mine, and monitored by ground-based radar devices, were reviewed with the goal of characterizing the typical slope deformation behavior and defining the appropriate strategy for the setup of alarms. The estimated mass of the case studies ranged from 1500 t to 750,000 t. 5 instabilities culminated to failure, whereas the other 4, although showing considerable amounts and rates of movement, ultimately did not fail. The analysis provided critical insights into the deformation of hard rock masses of high geomechanical quality, and allowed the identification of “signature” parameters of the failure events. General operative recommendations for effective slope monitoring and early warning were consequently derived.
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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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Major pit slope movements on rock mass discontinuities were initiated by an earthquake in December 1967 and sustained by excavation and blasting operations. Limiting equilibrium analysis suggests that average cohesion mobilized in the slope movements was low (ca. 100 kN/m2) and that friction was also low (Φ = 20–25°). Fluid pressures were apparently absent. The low strength values suggest that failure occurred on smooth joint surfaces coated with sheet silicate minerals. These surfaces are interpreted from analysis and are apparently not reflected in available statistical analyses of rock fabric. The portion of the slope which ultimately collapsed involved three relatively distinct blocks separated by major discontinuities; sliding occurred on planes dipping at perhaps 23–37°W. Displacement and acoustic emission data were collected over a period of a year following initial observations of slope movement. Extrapolation of displacement data was used to predict slope collapse over a month in advance of the date of actual collapse in 1969. Advance prediction permitted modification of mine transportation systems, and mine production was stopped for only 65 hours. No injuries or equipment damage occurred.
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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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A 249 day long record of the accelerating creep of a slope of an open-pit coal mine is analyzed, using linear regression, to test four creep laws. The Saito and Zavodni and Broadbent laws did not lead to a satisfactory estimation of the time of failure as a range of times of failure satisfied the goodness of fit criteria. Using the generalized Saito law, the upper limit for the time of failure was 168 days after the actual failure. Our prediction of a critical slide velocity for the evacuation of pit personnel and equipment, as an indication of impending failure, used two new methods employing the power and exponential laws. Three accelerating creep stages were identified, threshold velocities of 0.02 mm/min and 0.1 mm/min marked the initiation of the second and third stages, respectively.
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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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Forecasting the occurrence of large, catastrophic slope failures remains very problematic. It is clear that in order advance this field a greater understanding is needed of the processes through which failure occurs. In particular, there is a need to comprehend the processes through which a rupture develops and propagates through the slope, and the nature of the inter-relationship between the stress and strain states of the landslide mass. To this end, a detailed analysis has been undertaken of the movement records for the Selborme Cutting slope failure, in which failure was deliberately triggered through pore pressure elevation. The data demonstrate that it is possible to determine the processes occurring in the basal region of the landslide, and thus controlling the movement of the mass, from the surface movement patterns. In particular, it is clear that the process of rupture development and propagation has a unique signature, allowing the development of the rupture to be traced from detailed surface monitoring. For landslides undergoing first time failure through rupture propagation, this allows the prediction of the time of failure as per the 'Saito' approach. It is shown that for such predictions to be reliable, data from a number of points across the landslide mass are needed. Interestingly, due to the complex stress regime in that region, data from the crown may not be appropriate for failure prediction. Based upon these results, the application of new techniques for the detailed assessment of spatial patterns of the development of strain may potentially allow a new insight into the development of rupture surfaces and may ultimately permit forecasting of the temporal occurrence of failure.
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The simple relation OmegaOmega-alpha = 0, where Omega is a measurable quantity such as strain and A and alpha are empirical constants, describes the behavior of materials in terminal stages of failure under conditions of approximately constant stress and temperature. Applicable to metals and alloys, ice, concrete, polymers, rock, and soil, the relation may be extended to conditions of variable and multiaxial stress and may be used to predict time to failure.
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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.
Article
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.
Conference Paper
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.
Article
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.
Article
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.
Article
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.
Opening address to ISL Landslide Workshop
• G S Salt
Time-Deformation Relations in Creep to Failure of Earth Materials
• D J Varnes
Varnes, D. J. 1982. "Time-Deformation Relations in Creep to Failure of Earth Materials." In: Proceedings of the 7th Southeast Asia Geotechnical Conference, Hong Kong (1982), pp. 107-130.
Innovative Monitoring Instrumentations and Methods for Landslide Risk Management and Mitigation
• A Carri
Carri, A. 2019. "Innovative Monitoring Instrumentations and Methods for Landslide Risk Management and Mitigation." PhD Thesis, Università degli Studi di Parma, Dipartimento di Ingegneria e Architettura, http://hdl.handle.net/1889/ 3734.
A new Method for Predicting the Failure Time of a Slope
• T Fukuzono
Fukuzono, T. 1985. "A new Method for Predicting the Failure Time of a Slope." In: Proceedings of the Fourth International Conference and Field Workshop on Landslides (Tokyo; 1985). 1985. Tokyo University Press, pp. 145-150.
Applications of Rock Mass Monitoring for Stability Assessment of Pit Slope Failure
• T M Ryan
• R D Call
Ryan, T. M., and R. D. Call. 1992. "Applications of Rock Mass Monitoring for Stability Assessment of Pit Slope Failure." In: Proceedings of the 33 rd U.S. symposium on rock mechanics (USRMS). Santa Fe, USA, 3-5 June 1992, pp. 221-229. https://doi.org/10.1016/0148-9062(93)90607-F.
In Landslides and Landslide Management in South Wales
• S P Bentley
• H J Siddle
Bentley, S. P., and H. J. Siddle. 2000. "New Tredegar Landslide, Rhymney Valley." In Landslides and Landslide Management in South Wales. Geological Series n°18, edited by H. J. Siddle, E. N. Bromhead, and M. G. Bassett, 71-74. Cardiff: National Museums & Galleries of Wales.
Report on the Analysis of the Deformation Behaviour of Excavated Rock Slopes
• B Glastonbury
• R Fell
Glastonbury, B., and R. Fell. 2002. Report on the Analysis of the Deformation Behaviour of Excavated Rock Slopes. School of Civil & Environmental Engineering. Sydney: University of New South Wales.
Evidential Study on Forecasting Occurrence of Slope Failure
• M Saito
Saito, M. 1979. "Evidential Study on Forecasting Occurrence of Slope Failure." OYO Technical Report 1: 1-23.
Alarm Criteria and Monitoring for Hazardous Landslides. Opening address to ISL Landslide Workshop
• G S Salt
Salt, G. S. 1993. Alarm Criteria and Monitoring for Hazardous Landslides. Opening address to ISL Landslide Workshop, 1988. Updated 1993.