The role of near-field interaction between seismic waves and slope on the triggering of a rockslide at Lorca (SE Spain)

Alfaro, P.; Delgado, José; García-Tortosa, Francisco J.; Giner, J. J.; Lenti, Luca; López-Casado, C.; Martino, Salvatore; Mugnozza, Gabriele Scarascia

doi:10.5194/nhess-12-3631-2012

Cited by 24 publications

(6 citation statements)

References 50 publications

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“…Several studies have been conducted worldwide during the last few decades that report on ground failures triggered by earthquakes (Bommer and Rodriguez, 2002;Sepulveda et al, 2005;Porfido et al, 2007;Tosatti et al, 2008;Gorum et al, 2011;Tang et al, 2011;Alfaro et al, 2012; among many others) and that forecast, using predictive models, the distribution scenarios of earthquake-induced ground effects (Sassa et al, 1996;Jibson et al, 2000;Prestininzi and Romeo, 2000;Romeo, 2000;Jibson, 2007;Hsieh and Lee, 2011;among others). These studies provide inventory maps of the effects that have occurred or susceptibility maps of expected ground failures.…”

Section: Introductionmentioning

confidence: 99%

Earthquake-induced ground failures in Italy from a reviewed database

Martino

Prestininzi

Romeo

2014

Nat. Hazards Earth Syst. Sci.

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Abstract.A database (Italian acronym CEDIT) of earthquake-induced ground failures in Italy is presented, and the related content is analysed. The catalogue collects data regarding landslides, liquefaction, ground cracks, surface faulting and ground changes triggered by earthquakes of Mercalli epicentral intensity 8 or greater that occurred in the last millennium in Italy. As of January 2013, the CEDIT database has been available online for public use (http://www.ceri.uniroma1.it/cn/gis.jsp) and is presently hosted by the website of the Research Centre for Geological Risks (CERI) of the Sapienza University of Rome.Summary statistics of the database content indicate that 14 % of the Italian municipalities have experienced at least one earthquake-induced ground failure and that landslides are the most common ground effects (approximately 45 %), followed by ground cracks (32 %) and liquefaction (18 %). The relationships between ground effects and earthquake parameters such as seismic source energy (earthquake magnitude and epicentral intensity), local conditions (site intensity) and source-to-site distances are also analysed. The analysis indicates that liquefaction, surface faulting and ground changes are much more dependent on the earthquake source energy (i.e. magnitude) than landslides and ground cracks. In contrast, the latter effects are triggered at lower site intensities and greater epicentral distances than the other environmental effects.

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Section: Introductionmentioning

confidence: 99%

Earthquake-induced ground failures in Italy from a reviewed database

Martino

Prestininzi

Romeo

2014

Nat. Hazards Earth Syst. Sci.

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“…These can involve localities distant up to tens or hundreds of kilometres from the earthquake epicentre (Keefer, 1984;Rodrıguez et al, 1999;Delgado et al, 2011;Jibson and Harp, 2012). During the last decades, they have been confirmed by several authors reporting on ground failures triggered by earthquakes (Bommer and Rodriguez, 2002;Sepúlveda et al, 2005;Porfido et al, 2007;Tosatti et al, 2008;Gorum et al, 2011;Tang et al, 2011;Alfaro et al, 2012;Martino et al, 2020a, among others). To preemptively reduce the risk associated with these processes, predictive models have been proposed to estimate the distribution of earthquake-triggered ground effects scenarios (Sassa, 1996;Jibson et al, 2000;Prestininzi and Romeo, 2000;Romeo, 2000;Jibson, 2007;Hsieh and Lee, 2011, among others) representative of a uniform hazard distribution or seismic shaking scenarios.…”

Section: Introductionmentioning

confidence: 76%

Earthquake-triggered landslide susceptibility in Italy by means of Artificial Neural Network

Amato¹,

Fiorucci²,

Martino³

et al. 2021

Preprint

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The use of Artificial Neural Network (ANN) approaches has gained a significant role over the last decade in the field of predicting the distribution of effects triggered by natural forcing, this being particularly relevant for the development of adequate risk mitigation strategies. Among the most critical features of these approaches, there are the accurate geolocation of the available data as well as their numerosity and spatial distribution. The use of an ANN has never been tested at a national scale in Italy, especially in estimating earthquake-triggered landslides susceptibility. Based on the statistics deductible from the most up-to-date national inventory of earthquake-induced ground effects, i.e. the CEDIT catalogue, it results that over 56% of the ground effects triggered by earthquakes in Italy are represented by landslides. Therefore, a landslide dataset with such high geolocation precision was suitable to evaluate the efficiency of an ANN to explain the distribution of landslides over the Italian territory. An ex-post evaluation of the ANN-based susceptibility model was also performed, using a sub-dataset of historical data with lower geolocation precision. The ANN training highly performed in terms of spatial prediction, by partitioning the Italian landscape into slope units. The obtained results returned a distribution of potentially unstable slope units with maximum concentrations primarily distributed in the central-northern Apennines and secondarily in the southern Apennines. Moreover, the Alpine sector clearly appeared to be divided into two areas, a western one with relatively low susceptibility to earthquake-triggered landslides and the eastern sector with a higher susceptibility. However, the scale of the analysis carried out to train the ANN does not allow it to be applied for planning purposes or for seismic microzonation studies, for which training on a smaller spatial scale will be required.

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“…where b is the length of potential slip surface lock-up segment, m; and ρ is the curvature radius at the end of the failure surface, m. Under the cyclic shear loadings, seismic waves result in the fragmentation of the rock-soil body and reduce the rock-soil mass integrity and strength parameters (Alfaro et al, 2012). Moreover, in the process of progressive slope damage, the failure surface still has residual strength, which can provide part of the anti-slide force.…”

Section: Mechanism Of Dynamic Slope Failurementioning

confidence: 99%

Study on the slope dynamic stability considering the progressive failure of the slip surface under earthquake

Zhang

et al. 2022

Front. Earth Sci.

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The strength of a rock-soil mass shows complex and obvious weakening characteristics under seismic dynamic load. The previous stability analysis methods of a seismic slope do not fully depict the attenuation law of geotechnical materials and cannot truly reflect the stable state of a slope under earthquake action. Based on the theoretical analysis of the progressive failure mechanism and the evolution law of a seismic slope, the adverse effect of progressive failure on slope stability is clarified. According to the progressive failure process of a slope under dynamic load, the strain-softening model and vibration deterioration model are introduced to represent the attenuation law of rock strength parameters, and a calculation method of seismic slope stability coupled with vibration disturbance and progressive failure is proposed. The method considers the strength parameter characteristics of a rock-soil mass in different stages and is combined with the vector sum method to obtain the time-history curve of the slope safety factor under earthquake action, which makes the evaluation result of slope stability more accurate and reliable. The numerical examples show that this method can effectively reflect the dynamic stability of seismic slopes, and solve the problem that the traditional calculation methods are difficult to characterize the strength attenuation characteristics of rock and soil mass. If these characteristics are not considered, the calculation results will be unsafe.

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The role of near-field interaction between seismic waves and slope on the triggering of a rockslide at Lorca (SE Spain)

Cited by 24 publications

References 50 publications

Earthquake-induced ground failures in Italy from a reviewed database

Earthquake-induced ground failures in Italy from a reviewed database

Earthquake-triggered landslide susceptibility in Italy by means of Artificial Neural Network

Study on the slope dynamic stability considering the progressive failure of the slip surface under earthquake

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