Table 2
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This research proposes a conceptual approach for analysis and numerical modelling of the hydromechanical behaviour of large landslides, applied to one of the source areas of the Corvara earthflow (Dolomites, Italy). The approach consists of two steps: forward calculation and inverse analysis. For the forward calculations, the geological model of th...
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This research proposes a conceptual approach for analysis and numerical modelling of the hydromechanical behaviour of large landslides, applied to one of the source areas of the Corvara earthflow (Dolomites, Italy). The approach consists of two steps: forward calculation and inverse analysis. For the forward calculations, the geological model of th...
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... And in fact, measurement is point wise and instruments can only acquire measurements within a small area around the measurement point, usually displacement-based. Inverse analysis, based on engineering-measured information to invert the physical and mechanical parameters or measured loads of materials under the assumption of known material ontological relationships, has been applied in several fields [14][15][16][17][18]. Therefore, to improve the accuracy of the values of the dam material parameters, thus laying the foundation for the accurate analysis of the deformation state of the dam, attention should be paid to the inverse analysis of the mechanical parameters of the dam foundation based on the measured data. ...
A original strategy for optimizing the inversion of concrete dam parameters based on the multi-strategy improved Sooty Tern Optimization algorithm (MSSTOA) is proposed to address the issues of low efficiency, low accuracy, and poor optimizing performance. First, computational strategies to improve the traditional Sooty tern algorithm, such as chaos mapping to improve the initial position of the population, a new nonlinear convergence factor, the LIMIT threshold method, and Gaussian perturbation to update the optimal individual position, are adopted to enhance its algorithmic optimization seeking ability. Then, the measured and finite element data are combined to create the optimization inversion fitness function. Based on the MSSTOA, the intelligent optimization inversion model is constructed, the inversion efficiency is improved by parallel strategy, and the optimal parameter inversion is searched. The inversion strategy is validated through test functions, hypothetical arithmetic examples, and concrete dam engineering examples and compared with the inversion results of the traditional STOA and other optimization algorithms. The results show that the MSSTOA is feasible and practical, the test function optimization results and computational time are better than the STOA and other algorithms, the example inversion of the elastic modulus is more accurate than the traditional STOA calculation, and the results of the MSSSTOA inversion are reasonable in the engineering example. Compared with other algorithms, the local extremes are skipped, and the time consumption is reduced by at least 48%. The finite element hydrostatic components calculated from the inversion results are well-fitted to the statistical model with minor errors. The intelligent inversion strategy has good application in concrete dam inverse analysis.
... Generally, numerical simulations have always been popular among researchers [11,12,19,[43][44][45][46][47][48]. Therefore, to compare with the monitored data more directly and observe the slope deformation and instability at the same time, numerical experiments were also conducted. ...
... Therefore, to compare with the monitored data more directly and observe the slope deformation and instability at the same time, numerical experiments were also conducted. At present, the commonly used numerical method is still the finite element method (FEM) [11,12,19,43,44,47,48]. However, the FEM is well-known to easily suffer from mesh distortion. ...
The purpose of this article is to provide an effective approach to evaluate slope stability in real-time in a reservoir area, which is significant for carrying out risk management for landslide disaster prevention in various engineering practices. A comprehensive idea for stability estimation of bank slope under the influence of rainfall or the reservoir water level is presented in this work. Slope stability analysis and back analysis of soil parameters are both included based on numerical simulation. The mechanical parameters of the bank slope were first back-analyzed using particle swarm optimization (PSO), and real-time stability analysis with high accuracy and efficiency was then established based on multiple continuously monitored displacements. Two case studies were carried out in this study. The results show that (1) based on the real-time monitored displacement and numerical simulation, the mechanical parameters of the slope can be reasonably retrieved through PSO; and (2) based on the inverse mechanical parameters, the safety factors of the slope can be numerically obtained, so that the real-time estimation of slope stability can be realized.
... Landslides often also interfere with human activities, impacting on urban areas, infrastructures such as roads, tunnels, bridges, pipelines and areas related to other socioeconomic activities causing significant economic losses (Crosta et al. 2004;Evans and Bent 2004;Pankow et al. 2014;Bozzano et al. 2017;Marinos et al. 2019). In this framework, sometimes structures or infrastructures are faced with complex arrangements of landslides rather than a single movement (Barredo et al. 2000;Schädler et al. 2015;Uzielli et al. 2015;Bozzano et al. 2016). Such complexity can be related to different spatiotemporal arrangements of landslides: there can be a frequent occurrence of phenomena in a relatively small area (Corbi et al. 1996;Crozier 2010;Berti et al. 2013), or the spatial overlap of successive landslide occurrences, like converging flow-like movements (Cascini et al. 2008;Schädler et al. 2015), or relatively shallower phenomena developed over deep-seated movements (Guida et al. 1987;Guerricchio et al. 2000;Murillo-García et al. 2015), or partial mobilizations of previous landslides in nested structures (Lee et al. 2001), or various superimpositions of different landslide types (Stefanini 2004;Guida et al. 2006;Valiante et al. 2016). ...
... In this framework, sometimes structures or infrastructures are faced with complex arrangements of landslides rather than a single movement (Barredo et al. 2000;Schädler et al. 2015;Uzielli et al. 2015;Bozzano et al. 2016). Such complexity can be related to different spatiotemporal arrangements of landslides: there can be a frequent occurrence of phenomena in a relatively small area (Corbi et al. 1996;Crozier 2010;Berti et al. 2013), or the spatial overlap of successive landslide occurrences, like converging flow-like movements (Cascini et al. 2008;Schädler et al. 2015), or relatively shallower phenomena developed over deep-seated movements (Guida et al. 1987;Guerricchio et al. 2000;Murillo-García et al. 2015), or partial mobilizations of previous landslides in nested structures (Lee et al. 2001), or various superimpositions of different landslide types (Stefanini 2004;Guida et al. 2006;Valiante et al. 2016). Overlapping landslides derive from the temporal sequence of events and some authors also suggested the concept of path dependency for landslide susceptibility analysis, stating that preexisting landslides could be a predisposing factor for future phenomena (Samia et al. 2017a, b). ...
LOOM (landslide object-oriented model) is here presented as a data structure for landslide inventories based on the object-oriented paradigm. It aims at the effective storage, in a single dataset, of the complex spatial and temporal relations between landslides recorded and mapped in an area and at their manipulation. Spatial relations are handled through a hierarchical classification based on topological rules and two levels of aggregation are defined: (i) landslide complexes, grouping spatially connected landslides of the same type, and (ii) landslide systems, merging landslides of any type sharing a spatial connection. For the aggregation procedure, a minimal functional interaction between landslide objects has been defined as a spatial overlap between objects. Temporal characterization of landslides is achieved by assigning to each object an exact date or a time range for its occurrence, integrating both the time frame and the event-based approaches. The sum of spatial integrity and temporal characterization ensures the storage of vertical relations between landslides so that the superimposition of events can be easily retrieved by querying the temporal dataset. The here proposed methodology for landslides inventorying has been tested on selected case studies in the Cilento UNESCO Global Geopark (Italy). We demonstrate that the proposed LOOM model avoids data fragmentation or redundancy and topological inconsistency between the digital data and the real-world features. This application revealed to be powerful for the reconstruction of the gravity-induced deformation history of hillslopes, thus for the prediction of their evolution.
... The landslide involves clayey silt or silty clay material, with mixed gravels and blocks made up of arenites, marly limestone and dolostone [54]. The landslide has been investigated extensively over the past years, including studies on landslide characterization and field-based monitoring [55], dating [56], and modeling [57]. The aforementioned studies concluded that the Corvara landslide has an estimated total volume of more than 30 million m 3 , a depth of up to 100 m and has been active for more than 10,000 years. ...
From the wide range of methods available to landslide researchers and practitioners for monitoring ground displacements, remote sensing techniques have increased in popularity. Radar interferometry methods with their ability to record movements in the order of millimeters have been more frequently applied in recent years. Multi-temporal interferometry can assist in monitoring landslides on the regional and slope scale and thereby assist in assessing related hazards and risks. Our study focuses on the Corvara landslides in the Italian Alps, a complex earthflow with spatially varying displacement patterns. We used radar imagery provided by the COSMO-SkyMed constellation and carried out a validation of the derived time-series data with differential GPS data. Movement rates were assessed using the Permanent Scatterers based Multi-Temporal Interferometry applied to 16 artificial Corner Reflectors installed on the source, track and accumulation zones of the landslide. The overall movement trends were well covered by Permanent Scatterers based Multi-Temporal Interferometry, however, fast acceleration phases and movements along the satellite track could not be assessed with adequate accuracy due to intrinsic limitations of the technique. Overall, despite the intrinsic limitations, Multi-Temporal Interferometry proved to be a promising method to monitor landslides characterized by a linear and relatively slow movement rates.
... Laws exist for a rigid perfectly plastic slope behaviour (Iverson 2000) as well as for a viscous behaviour (Vulliet and Hutter 1988;Bracegirdle et al. 1991;Butterfield 2000;Leroueil 2000). Physical models can also make use of numerical codes that couple groundwater recharge models to slope stability models in order to deterministically forecast displacement rates (Corominas et al. 2005;Herrera et al. 2009;Belle et al. 2014;Bernardie et al. 2014;Abellán et al. 2015;Bernardie et al. 2015;Schädler et al. 2015). Nonlinear models are based upon computational approaches that aim to represent the posterior distribution of displacement using functions based on training data and prior distribution. ...
Active landslides are generally characterized by variations in displacement rate in response to cumulated precipitation. Velocities that are only exceeded in a limited number of days during the year might be considered as critical events, since they might determine, or prelude to, a significant evolution of the landslide. The purpose of this paper is to present a novel approach based on the use of receiver operating characteristic (ROC) curves for assessing cumulated precipitation thresholds that can provide early warning for the occurrence of critical events such as the exceedance of rare displacement rates. The approach has been developed and tested in the Piagneto landslide, an active complex rock slide—debris slide in the Northern Apennines of Italy, for which a 5-year continuous surveying monitoring dataset is available. On the basis of the first 4 years of monitoring data (training dataset), threshold curves relating cumulative precipitation (mm) to precipitation moving windows (days) have been generated by using different benchmarks that, in literature, are used to estimate the maximum predictive performance of ROC curves. These threshold curves have been successfully validated using the last 1 year of monitoring data (validation dataset). They have then been used to simulate how they might help defining different early warning levels in due advance. The proposed methodology can be replicated in any landslide for which a monitoring dataset that includes recurrent acceleration events in response to precipitation is available.
... In addition, the understanding of the landslides kinematics is also crucial in defining efficient prevention and mitigation strategies and can be effectively pursued only if multidisciplinary data, both in terms of temporal and spatial coverage of the area is available. The kinematics of the landslide phenomena has been analyzed in a large number of scientific studies; the approaches range from the analytical one-dimensional (1D) infinite slope models, suitable for landslides bodies with sliding surface depth about constant and significantly lower than the landslide length [1][2][3][4][5], to more sophisticated two-(2D) and three-dimensional (3D) Finite Element (FE) models aimed at detecting the different kinematical sectors along the slope area [6][7][8][9]. In particular, the recent development of three-dimensional numerical codes allows us to carry out simulations of the displacement rate field of a landslide process in a more realistic and accurate way. ...
... The reliability of the performed numerical models significantly improves when the same models are calibrated and validated by using the measurements collected by means of the available monitoring networks. To this purpose, the inverse analysis carried out via optimization procedures aimed at searching for the model best-fitting solution against the monitoring dataset, represents a very efficient tool in identifying the physical process that governs the observed phenomenon [8,9]. To accomplish an effective inverse analysis of a 3D landslide model, spatially distributed surface measurements are needed. ...
In this paper, we propose an advanced methodology to perform three-dimensional (3D)
Finite Element (FE) modeling to investigate the kinematical evolution of a slow landslide phenomenon.
Our approach benefits from the effective integration of the available geological, geotechnical and
satellite datasets to perform an accurate simulation of the landslide process. More specifically, we fully
exploit the capability of the advanced Differential Synthetic Aperture Radar Interferometry (DInSAR)
technique referred to as the Small BAseline Subset (SBAS) approach to provide spatially dense
surface displacement information. Subsequently, we analyze the physical behavior characterizing
the observed landslide phenomenon by means of an inverse analysis based on an optimization
procedure. We focus on the Ivancich landslide phenomenon, which affects a residential area outside
the historical center of the town of Assisi (Central Italy). Thanks to the large amount of available
information, we have selected this area as a representative case study highlighting the capability of
advanced 3D FE modeling to perform effective risk analyses of slow landslide processes and accurate
urban development planning. In particular, the FE modeling is constrained by using the data from
7 litho-stratigraphic cross-sections and 62 stratigraphic boreholes; and the optimization procedure is
carried out using the SBAS-DInSAR retrieved results by processing 39 SAR images collected by the
Cosmo-SkyMed (CSK) constellation in the 2009–2012 time span. The achieved results allow us to
explore the spatial and temporal evolution of the slow-moving phenomenon and via comparison
with the geomorphological data, to derive a synoptic view of the kinematical activity of the urban
area affected by the Ivancich landslide.
... Corvara landslide is a complex earth slide-earth flow located above the tourist town of Corvara in Badia, Italy ( Figure 1A). The landslide has been investigated extensively over the past years, including studies on landslide characterisation and field-based monitoring (Corsini et al., 2005), event dating (Borgatti and Soldati, 2010), scenario modelling (Schädler et al., 2014), and satellite-based multitemporal interferometry monitoring . The current monitoring set-up ( Figure 1B) includes regular and permanent GPS measurements, as well as several corner reflectors for satellite-based radar monitoring. ...
... The Corvara landslide is an active, complex earth slide-earthflow with spatially varying displacement patterns located above the tourist centre of Corvara in Badia valley, Dolomites, Autonomous Province of Bolzano, Italy ( Figure 1). The landslide has been investigated extensively over the past years, including studies involving landslide characterisation and field-based monitoring (Corsini et al., 2005), dating (Borgatti and Soldati, 2010), modelling (Schädler et al., 2014), and satellite-based MTI monitoring (e.g. . Corvara landslide has a total volume of more than 30 million m³, a length of 3.5 km, a depth of up to 100 m and has been active for more than 10,000 years. ...
... Robinson & Wastald, 1987;Eckhardt & Arnold, 2001;). Some attempts have likewise already been made to use automatic procedures for parameter calibrations for landslide analysis: Schädler et al. (2014), for example, proposed an inverse identification approach associated with a back analysis procedure to establish the constitutive parameters of a viscous-elasto-plastic finite element model used to reproduce displacement evolution over time with regard to the Corvara landslide in Italy. To the authors' knowledge, similar attempts have not yet been made for debris flows phenomena. ...
Parameter calibration is one of the most problematic phases of numerical modeling since the choice of parameters affects the model’s reliability as far as the physical problems being studied are concerned. In some cases, laboratory tests or physical models evaluating model parameters cannot be completed and other strategies must be adopted; numerical models reproducing debris flow propagation are one of these. Since scale problems affect the reproduction of real debris flows in the laboratory or specific tests used to determine rheological parameters, calibration is usually carried out by comparing in a subjective way only a few parameters, such as the heights of soil deposits calculated for some sections of the debris flows or the distance traveled by the debris flows using the values detected in situ after an event has occurred. Since no automatic or objective procedure has as yet been produced, this paper presents a numerical procedure based on the application of a statistical algorithm, which makes it possible to define, without ambiguities, the best parameter set. The procedure has been applied to a study case for which digital elevation models of both before and after an important event exist, implicating that a good database for applying the method was available. Its application has uncovered insights to better understand debris flows and related phenomena.
Large-scale slow-moving deep-seated landslides are complex and potentially highly damaging phenomena. The detection of their dynamics in terms of displacement rate distribution is therefore a key point to achieve a better understanding of their behavior and support risk management. Due to their large dimensions, ranging from 1.5 to almost 4 km2, in situ monitoring is generally integrated using satellite and airborne remote sensing techniques. In the framework of the EFRE-FESR SoLoMon project, three test-sites located in the Autonomous Province of Bolzano (Italy) were selected for testing the possibility of retrieving significant slope displacement data from the analysis of multi-temporal airborne optic and light detection and ranging (LiDAR) surveys with digital image correlation (DIC) algorithms such as normalized cross-correlation (NCC) and phase correlation (PC). The test-sites were selected for a number of reasons: they are relevant in terms of hazard and risk; they are representative of different type of slope movements (earth-slides, deep seated gravitational slope Deformation and rockslides), and different rates of displacement (from few cm/years to some m/years); and they have been mapped and monitored with ground-based systems for many years (DIC results can be validated both qualitatively and quantitatively). Specifically, NCC and PC algorithms were applied to high-resolution (5 to 25 cm/px) airborne optic and LiDAR-derived datasets (such as hillshade and slope maps computed from digital terrain models) acquired during the 2019–2021 period. Qualitative and quantitative validation was performed based on periodic GNSS surveys as well as on manual homologous point tracking. The displacement maps highlight that both DIC algorithms succeed in identifying and quantifying slope movements of multi-pixel magnitude in non-densely vegetated areas, while they struggle to quantify displacement patterns in areas characterized by movements of sub-pixel magnitude, especially if densely vegetated. Nonetheless, in all three landslides, they proved to be able to differentiate stable and active parts at the slope scale, thus representing a useful integration of punctual ground-based monitoring systems.
