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Innovative Monitoring Tools and Early Warning Systems for Risk Management: A Case Study

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  • ASE s.r.l.

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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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... In this study, we chose the Nevissano landslide (Castelnuovo Don Bosco, Piedmont, NW Italy) as a test site to cross-validate the "Moving Sum" empirical method and the instrumental measurements acquired through an innovative monitoring system (Modular Underground Monitoring System (MUMS) technology, produced by ASE S.r.l., [31]). Over recent decades, the Nevissano landslide recorded several re-activations spread over time (i.e., landslide paroxysmal events), the last of which was in 2016. ...
... After the paroxysmal event of 2016, a remotely controlled monitoring system (namely, MUMS system, by ASE S.r.l., [31]) was installed on-site, in correspondence with the SC33 Nevissano Road. The system consists of an array of 24 nodes, installed in a borehole at depths ranging between 0.25 m and 11.75 m and anchored to the ground at a depth of 12 m. ...
... The system records data at time intervals of 1 h, and automatically transmits them to a mainframe server. Additional technical specifications about data acquisition, recording and remote access are available at [31]. ...
Article
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The prediction and prevention of landslide hazard is a challenging topic involving the assessment and quantitative evaluation of several elements: geological and geomorphological setting, rainfalls, and ground motion. This paper presents the multi-approach investigation of the Nevissano landslide (Asti Province, Piedmont, NW Italy). It shows a continuous and slow movement, alongside few paroxysmal events, the last recorded in 2016. The geological and geomorphological models were defined through a field survey. An inventory of the landslide’s movements and rainfall records in the period 2000–2016 was performed, respectively, through archive investigations and the application of “Moving Sum of Daily Rainfall” method, allowing for the definition of rain thresholds for the landslide activation (105 mm and 193 mm, respectively, in 3 and 30 days prior to the event). The displacements over the last 8 years (2016–2023) were monitored through an innovative in-continuum monitoring inclinometric system and Earth Observation (EO) data (i.e., relying on Interferometric Synthetic Aperture Radar, or InSAR data): it gave the opportunity to validate the rainfall thresholds previously defined. This study aims to provide information to public authorities for the appropriate management of the site. Moreover, the proposed workflow could be adopted as a guideline for investigating similar situations.
... Each Array featured a different number of Tilt Link HR 3D V, equipped with 3D MEMS and electrolytic tilt sensors, and customized interspace between nodes, as in Table 7. The event here analyzed, extensively discussed in Segalini et al. (2019), occurred in March 2017, some months after the installation of the Vertical Array DT0014. At that time, DT0014 was the only automatic monitoring device present on site, and the acquisition process was set on a sampling frequency of 1 h. ...
... The time of failure evaluated with this methodology was compared to the date of collapse observed from monitoring data (i.e., the date and time where instrumental data evidenced the damage caused to the Array by soil deformations). As reported by Segalini et al. (2019), both datasets provided a positive prediction of the slope collapse, with a time difference of 3 h for Tilt Link 93, and 1 h for Tilt Link 95. ...
Article
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Over the past years, the growing number of natural hazards all over the world has led to an increasing focus on activities aimed at studying and controlling the occurrence of these phenomena. In this context, monitoring systems have become a fundamental component for Landslide Early Warning Systems, allowing to understand the evolution of these processes and assess the need for dedicated mitigation measures. This result is achieved thanks to several technological advancements that led to the introduction of more accurate and reliable sensors, as well as automatic procedures for data acquisition and elaboration. However, despite these improvements, the data interpretation process is still a challenging task, in particular when it comes to the identification of critical events and failure forecasting operations. This paper presents a methodology developed to assess if a potentially critical event is displaying a significant deviation from previously sampled data, or if it could be classified as a false alarm. The process relies on the definition of a threshold value based on the landslide behavior preceding the event of interest. In particular, the reference value derives from the evaluation of equivalent displacements, defined as the displacements previously observed in a time interval equal to the one showed by the potentially critical event. This paper reports a series of examples referring to different case studies, involving both false alarms and real collapses, underlining the effectiveness of the proposed model as a useful tool to evaluate the landslide behavior with a near-real-time approach.
... The identification of pre-failure conditions in areas presenting instability signs can be performed through in-situ observations and monitoring (Brunner, Hartinger, and Richter 2000;Borgatti et al. 2008;Cascini et al. 2019;Segalini et al. 2019), by exploiting satellitebased technologies such as Interferometric Synthetic Aperture Radar (InSAR) Lacroix et al. 2018;Reyes-Carmona et al. 2020), optical image data (Desrues, Lacroix, and Brenguier 2019), or a combination of different sensors (Clarkson, Williams, and Seppälä 2020). The parameters controlling the landslides effect in term of hazard and landscape change include the landslide occurrence time, size, duration, speed, and total amount of their movement (Schulz et al. 2018). ...
... This theory generated mainly empirical and semi-empirical methodologies, all based on the assumption that the time of slope failure can be forecasted by extrapolating the trend towards zero of the inverse-velocity vs time plot. In particular, collapse predictions obtained through the applications of the Inverse Velocity Method (IVM) firstly introduced by Fukuzono (1985) can be found in literature, displaying generally positive results (Petley 2004;Rose and Hungr 2007;Segalini et al. 2019). ...
Article
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.
... Each Array featured a different number of Links, equipped with 3D MEMS and electrolytic tilt sensors, and customized interspace between nodes: -One 35-meter long Vertical Array was installed in November 2016 -One 35-meter long Vertical Array was installed in September 2017 -Four Vertical Arrays, with length ranging from 66 to 111 meters, were installed in September 2018 -Three 100-meter long Vertical Arrays were installed in November 2020 It should be noted that the first Vertical Array installed on site was irreversibly damaged due to excessive deformation caused by a superficial landslide between February and March 2017. Despite being compromised by the event, the device was still able to identify the occurrence of the event, disseminating a series of alert messages to authorities responsible of the monitoring activity (Segalini et al. 2019). ...
Conference Paper
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The growing frequency and intensity of natural hazards has resulted in increased efforts towards their study and control. As a consequence, monitoring systems have emerged as pivotal components of landslide Early Warning Systems (EWS), facilitating comprehension of process evolution and assessment of mitigation needs. This progress stems from technological advancements, yielding more precise sensors and automated data acquisition procedures. Nevertheless, challenges persist in interpreting data, particularly in identifying critical events and forecasting failures. This paper presents the application of a methodology developed by the authors to identify significant deviations in potentially critical events from previously sampled data, with the objective of separating them from false alarms. The core of this approach relies on establishing a threshold value based on antecedent landslide behavior. Specifically, the reference value is derived from assessing equivalent displacements, defined as displacements observed within a time interval equal to that of the critical event. The paper presents various case studies highlighting the efficacy of the proposed model as a valuable tool for near-real-time assessment of landslide behavior.
... Among the several landslide risk mitigation strategies, early warning (EW) systems are the most cost-effective and allow for better planning of mitigation measures for landslides (Piciullo et al. 2018). For many decades, several conventional and novel technologies have been applied to surface and subsurface slope monitoring, such as remote sensing (Šegina et al. 2020), geographic information systems, acoustic emission and microseismic (Weber et al. 2018), extensometers (Mentes 2015), and inclinometers (Segalini et al. 2019). These techniques have their benefits and drawbacks in measurement range or accuracy. ...
Article
Distributed fibre-optic sensing (DFOS) has developed expeditiously over recent decades in multiple technical fields, including slope engineering, as it furnishes several advantages over conventional landslide monitoring approaches. Fibre-optic (FO) cables can be embedded in a shallow trench or buried in a borehole to detect precursory signs of failure well before collapse. By measuring sent and backscattered light, FO systems detect mass movement from changes on the cable so that early warning measurements can be made. This review paper briefly discusses the fundamentals of optical fibres, followed by a compendious explanation of the sensing principle of various DFOS techniques (Rayleigh, Brillouin, and Raman backscattering). The significant considerations for installing an FO cable in a borehole/shallow trench for deformation sensing and the ground-anchor-cable coupling mechanism are emphasised. The most recent advancements of DFOS applications on slope deformation monitoring from the laboratory model size to the field scale are discussed in great detail, emphasising the progress made within the last ten years. Ultimately, some challenges associated with DFOS sensing and future development prospects are discussed. Engineering geologists and slope hazard mitigation planners are anticipated to benefit from the wide-ranging, in-depth information gathered here.
... Several methods are available to obtain deformation measurements, each with different characteristics, temporal sampling, and spatial coverage. Local techniques include crackmeters, extensometers and inclinometers, that quantify in-situ deformation at the specific location at the landslide or building they are applied to (Logar et al., 2017;Segalini et al., 2019). Slope scale techniques, used to quantify differential deformation within a landslide, include total station measurements, and Global Navigation Satellite System (GNSS) measurement campaigns (Benoit et al., 2015). ...
Article
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Slow-moving landslides move downslope at velocities that range from mm year ⁻¹ to m year ⁻¹ . Such deformations can be measured using satellite-based synthetic aperture radar interferometry (InSAR). We developed a new method to systematically detect and quantify accelerations and decelerations of slowly deforming areas using InSAR displacement time series. The displacement time series are filtered using an outlier detector and subsequently piecewise linear functions are fitted to identify changes in the displacement rate (i.e., accelerations or decelerations). Grouped accelerations and decelerations are inventoried as indicators of potential unstable areas. We tested and refined our new method using a high-quality dataset from the Mud Creek landslide, CA, USA. Our method detects accelerations and decelerations that coincide with those previously detected by manual examination. Second, we tested our method in the region around the Mazar dam and reservoir in Southeast Ecuador, where the time series data were of considerably lower quality. We detected accelerations and decelerations occurring during the entire study period near and upslope of the reservoir. Application of our method results in a wealth of information on the dynamics of the surface displacement of hillslopes and provides an objective way to identify changes in displacement rates. The displacement rates, their spatial variation, and the timing of accelerations and decelerations can be used to study the physical behavior of a slow-moving slope or for regional hazard assessment by linking the timing of changes in displacement rates to landslide causal and triggering factors.
... Several methods are available to obtain deformation measurements, each with different characteristics, temporal sampling, and spatial coverage. Local techniques include crackmeters, extensometers and inclinometers, that quantify in-situ deformation at the specific location at the landslide or building they are applied to (Logar et al., 2017;Segalini et al., 2019). Slope scale techniques, used to quantify differential deformation within a landslide, include total station measurements, and Global Navigation Satellite System (GNSS) measurement campaigns (Benoit et al., 2015). ...
Article
Landslides are a major geohazard in hilly and mountainous environments. In-situ inspection of downslope motion is costly, sometimes dangerous and, requires prior knowledge of the existence of a landslide. Remote sensing from space is a way to detect and characterize landslides systematically at large scale. Interferometric Synthetic Aperture Radar (InSAR) has shown to be a valuable resource of deformation information, but it requires expert knowledge and considerable computational efforts. Moreover, the successful application of InSAR for landslides requires a favorable acquisition geometry relative to the landslide deformation pattern. Consequently, there is a need for a widely applicable tool to assess the potential of InSAR at a particular location a priori. Here we present a novel, generic approach to assess the potential of InSAR-based deformation tracking, providing a standardised and automated method applicable on any slope. We define the detection potential as the sensitivity of InSAR to detect downslope displacement combined with the presence of coherently scattering surfaces. We show that deformation can be detected on at least 91% of the global landslide-prone slopes, and provide an open source Google Earth Engine tool for the quick assessment of the availability of potential coherent scatterers. This tool enables any person interested in applying InSAR to routinely assess the potential for monitoring landslide deformation in their region of interest.
... Each of the physical principles has its advantages and its use depends on the application. Sucesfull innovation of underground displacement monitoring based on MEMS sensors inclinometers were developed in Italy [2,3]. Inertial measurement unit is an essential part of devices used for the Global navigation satellite system, aerial photogrammetry, laser altimetry, remote sensing technologies, unmanned aerial vehicles, but it is also the main component of unmanned ground and marine vehicles. ...
Article
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The inertial measurement unit is an electronic device built-in practically in any controlled or autonomous technology used for land mapping. It is based on a combination of accelerometers and gyroscopes and sometimes magnetometers used for relative orientation and navigation. The paper is focused on functions and trends of an inertial measurement unit, which is a part of inertial navigation indicator of position and velocity of moving devices on the ground, above and below ground in real-time.
... The IVM has been effectively applied to several landslides (e.g. Segalini et al. 2019) and it has also provided satisfactory forecasting results when using InSAR data Carlà et al. 2017;Moretto et al. 2017;Intrieri et al. 2018or Carlà et al. 2019. For the correct implementation of the IVM to identify possible accelerations, the monitoring activity should be constant in time and continued for as long as possible (Valletta et al. 2020). ...
Preprint
When an active landslide is first identified in an artificial reservoir, a comprehensive study has to be quickly conducted to analyse the possible hazard that it may represent to such a critical infrastructure. This paper presents the case of the El Arrecife Landslide, located in a slope of the Rules Reservoir (Southern Spain), as an example of geological and motion data integration for elaborating a preliminary hazard assessment. For this purpose, a field survey was carried out to define the kinematics of the landslide: translational in favour of a specific foliation set, and rotational at the foot of the landslide. A possible failure surface has been proposed, as well as an estimation of the volume of the landslide: 14.7 million m3. At the same time, remote sensing and geophysical techniques were applied to obtain historical displacement rates. A mean subsidence rate of up to 2 cm/yr was obtained by means of Synthetic Aperture Radar Interferometry (InSAR) and Ground Penetrating Radar (GPR) data, during the last 5 and 22 years, respectively. The Structure-from-Motion (SfM) technique provided a higher rate, up to 26 cm/yr during the last 14 years, due to compaction of a slag heap located within the foot of the landslide. All of this collected information will be valuable to optimise the planning of future monitoring surveys (i.e. Differential Global Positioning Systems, inclinometers, ground drilling and InSAR) that should be applied in order to prevent further damage on the reservoir and related infrastructures.
... The IVM has been effectively applied to several landslides (e.g. Segalini et al. 2019) and it has also provided satisfactory forecasting results when using InSAR data Carlà et al. 2017Carlà et al. , 2019Moretto et al. 2017;Intrieri et al. 2018). For the correct implementation of the IVM to identify possible accelerations, the monitoring activity should be constant in time and continued for as long as possible (Valletta et al. 2020). ...
Article
[See the full-text in the following link: https://rdcu.be/cyFI0]. When an active landslide is first identified in an artificial reservoir, a comprehensive study has to be quickly conducted to analyse the possible hazard that it may represent to such a critical infrastructure. This paper presents the case of the El Arrecife Landslide, located in a slope of the Rules Reservoir (Southern Spain), as an example of geological and motion data integration for elaborating a preliminary hazard assessment. For this purpose, a field survey was carried out to define the kinematics of the landslide: translational in favour of a specific foliation set, and rotational at the foot of the landslide. A possible failure surface has been proposed, as well as an estimation of the volume of the landslide: 14.7 million m3. At the same time, remote sensing and geophysical techniques were applied to obtain historical displacement rates. A mean subsidence rate of the landslide around 2 cm/year was obtained by means of synthetic aperture radar interferometry (InSAR) and ground-penetrating radar (GPR) data, during the last 5 and 22 years, respectively. The structure-from-motion (SfM) technique provided a rate up to 26 cm/year during the last 14 years of a slag heap located within the foot of the landslide, due to compaction of the anthropical deposits. All of this collected information will be valuable to optimise the planning of future monitoring surveys (i.e. differential global positioning systems, inclinometers, ground drilling, and InSAR) that should be applied in order to prevent further damage on the reservoir and related infrastructures.
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To manage natural risks, an increasing effort is being put in the development of early warning systems (EWS), namely, approaches facing catastrophic phenomena by timely forecasting and alarm spreading throughout exposed population. Research efforts aimed at the development and implementation of effective EWS should especially concern the definition and calibration of the interpretative model. This paper analyses the main features characterizing predictive models working in EWS by discussing their aims and their features in terms of model accuracy, evolutionary stage of the phenomenon at which the prediction is carried out and model architecture. Original classification criteria based on these features are developed throughout the paper and shown in their practical implementation through examples of flow-like landslides and earth flows, both of which are characterized by rapid evolution and quite representative of many applications of EWS.
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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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The forecast of a landslide's time of failure and the definition of alert thresholds are fundamental aspects in the study of natural hazards. However, these tasks are particularly difficult due to the large number of parameters and factors involved, and are therefore usually performed with a site-specific approach. This work describes an attempt to generalize the behavior of a landslide approaching collapse, with particular attention to the definition of a general criterion to define alert thresholds. The procedure started with the creation of a database of displacement data recorded for historical landslides, then the inverse velocity model was applied to these datasets to evaluate the time of failure under the assumption of linear behavior during the accelerating phase. A model calibration was conducted to best describe the monitored data and highlight any non-linear trend. A curve describing the velocity versus time relationship was then computed for each single slope failure case using the parameter obtained through this operation. In the final step of the study, these curves were processed with a normalization procedure, thus obtaining a dimensionless velocity-related coefficient. This parameter allowed the comparison of different landslide datasets on a single graph, which can be used as a general reference to define alert thresholds for emergency purposes. In order to test the criterion's ability to represent landslide behavior, the procedure was also applied to a different case by simulating progressive data acquisition.
Chapter
The paper illustrates the efficiency of a novel inclinometer device by comparing results obtained from some prototypes installed in three landslides and those derived from classic inclinometers. The new device, called Modular Underground Monitoring System (MUMS) is intended to be applied for natural and artificial slope deformation monitoring and landslides dynamics control, assessment and forecasting. The MUMS instrumentation was developed from the idea of replacing the standard measurement procedure by locating nodes at known distances along a connecting cable placed within a vertical borehole. Each node measures its local orientation (related to the National Elevation Dataset (NED)) by means of a micro electro-mechanical system (MEMS) formed by a 3D digital linear acceleration sensor and a 3D magnetic sensor. This allows us to determine the direction cosines of the borehole axis in each node and calculate its 3D shape and deformation along the whole borehole. This paper compares the classic instruments and the new MUMS device, with evidence of the advantages of measurement automation and economy in the use of the proposed device, which could also be equipped with other electronic instruments that would allow the measurement of other interesting physical quantities (i.e. pore pressure, temperature, stresses etc.) together with displacement components. The comparison is carried out through the examination of few installation in various types of landslides, with particular attention to the accuracy and repeatability of the measurements that are automatically made.
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This paper describes the analysis of the effectiveness and reliability of a new type of inclinometric chain, which is still under development by the authors, and is intended to be applied in the underground slope monitoring field. In the first part, the paper describes the new instrumentation which should allow for a deeper and detailed understanding of the type, location and origin of slope movements that should, in turn, help in understanding the triggering causes and the evolution mechanisms of landslides, and provide an innovative and substantial contribution to their stability analysis and control. The second portion of the paper is dedicated to a comparison between the classic instruments and the new MUMS device, demonstrating the advantages of measurement automation and economy in the use of the proposed device, which could also be equipped with other electronic instruments that would allow the measurement of other interesting physical quantities (such as pore pressure, temperature, stresses, etc.) together with displacement components.