Towards landslide predictions: two case studies

Sornette, Didier; Helmstetter, Agnès; Andersen, Jørgen Vitting; Gluzman, S.; Grasso, J. R.; Писаренко, В. Ф.

doi:10.1016/j.physa.2004.02.065

Cited by 66 publications

(73 citation statements)

References 23 publications

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“…[50] Sornette et al [2004] verified the proposition of Voight [1988] that using the (L-t) model one could make a 10-day forecast for the Vaiont collapse. Also, these authors extended their study by using a Dieterich-Ruina friction model to obtain a hyperbolic relationship between the velocity of the slide and the collapse time.…”

Section: Comparison Of the Blowup Time Estimate With Other Studiesmentioning

confidence: 85%

“…This means in turn that the formula for the slide velocity proposed by Sornette et al [2004] is a good approximation of the theoretical one, equation (33) (Figure 6), and should be used for a first estimate of the relevant model parameters, as this was done in Appendix D.…”

Section: Veveakis Et Al: Thermoporomechanics Of Creeping Slidesmentioning

confidence: 99%

“…The slide velocity computed from equations (D4), (D5) and (D6) yields the estimate of Sornette et al [2004] V ¼ U 1…”

Section: Appendix A: Generalization Of Bagnold's Modelmentioning

confidence: 99%

“…Indeed the best fit for Müller's [1964] data, using the formula of Sornette et al [2004], equation (D7), provides the following estimates ( Figure 6):…”

Section: Appendix A: Generalization Of Bagnold's Modelmentioning

confidence: 99%

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Thermoporomechanics of creeping landslides: The 1963 Vaiont slide, northern Italy

2007

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[1] The catastrophic Vaiont landslide (Southern Alps, Italy) of 9 October 1963 moved 2.7 Â 10 8 m 3 of rock that collapsed in an artificial lake, causing a giant wave that killed 1917 people. The landslide was preceded by 2-3 years of creep that ended with the final collapse of the rock mass slipping at about 30 m s À1 . Assuming that creep was localized in a clay-rich water-saturated layer, in this study we propose shear heating as the primary mechanism for the long-term phase of accelerating creep. We study only the creeping phase of the slide, and we model this phase using a rigid block moving over a thin zone of high shear strain rates. Introducing a thermal softening and velocity strengthening law for the basal material, we reformulate the governing equations of a water-saturated porous material, obtaining an estimate for the collapse time of the slide. Our model is calibrated upon real velocity measurements from the Vaiont landslide and provides an estimation of the critical time of failure up to 169 days before the collapse. We also show that the slide became critical $21 days before the collapse, when shear heating started localizing in the clay-rich layer, inducing a tendency for slip localization and thermal runaway instability in a plane. The total loss of strength in the slipping zone during the last minutes prior to the slide is explained by the onset of thermal pressurization, triggered by the temperature rise within the clay-rich layer.

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Section: Comparison Of the Blowup Time Estimate With Other Studiesmentioning

confidence: 85%

Section: Veveakis Et Al: Thermoporomechanics Of Creeping Slidesmentioning

confidence: 99%

“…The slide velocity computed from equations (D4), (D5) and (D6) yields the estimate of Sornette et al [2004] V ¼ U 1…”

Section: Appendix A: Generalization Of Bagnold's Modelmentioning

confidence: 99%

“…Indeed the best fit for Müller's [1964] data, using the formula of Sornette et al [2004], equation (D7), provides the following estimates ( Figure 6):…”

Section: Appendix A: Generalization Of Bagnold's Modelmentioning

confidence: 99%

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Thermoporomechanics of creeping landslides: The 1963 Vaiont slide, northern Italy

2007

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“…So far, many models have been put forward (Saito, 1965;Voight, 1989;Crosta and Agliardi, 2002;Lu and Rosenbaum, 2003;Feng et al, 2004;Helmstetter et al, 2004;Neaupane and Achet, 2004;Sornette et al, 2004;Randall, 2007;Mufundirwa et al, 2010). They can be roughly classified into four categories: deterministic physical models, statistics models, nonlinear models and numerical simulation models (Li et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Application of GA–SVM method with parameter optimization for landslide development prediction

Jiming

2014

Nat. Hazards Earth Syst. Sci.

109

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Abstract. Prediction of the landslide development process is always a hot issue in landslide research. So far, many methods for landslide displacement series prediction have been proposed. The support vector machine (SVM) has been proved to be a novel algorithm with good performance. However, the performance strongly depends on the right selection of the parameters (C and γ ) of the SVM model. In this study, we present an application of genetic algorithm and support vector machine (GA-SVM) method with parameter optimization in landslide displacement rate prediction. We selected a typical large-scale landslide in a hydro-electrical engineering area of southwest China as a case. On the basis of analyzing the basic characteristics and monitoring data of the landslide, a single-factor GA-SVM model and a multifactor GA-SVM model of the landslide were built. Moreover, the models were compared with single-factor and multifactor SVM models of the landslide. The results show that the four models have high prediction accuracies, but the accuracies of GA-SVM models are slightly higher than those of SVM models, and the accuracies of multi-factor models are slightly higher than those of single-factor models for the landslide prediction. The accuracy of the multi-factor GA-SVM models is the highest, with the smallest root mean square error (RMSE) of 0.0009 and the highest relation index (RI) of 0.9992.

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Avalanching glacier instabilities: Review on processes and early warning perspectives

Faillettaz

Funk

Vincent

2015

Reviews of Geophysics

103

102

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Avalanching glacier instabilities are gravity-driven rupture phenomena that might cause major disasters, especially when they are at the origin of a chain of processes. Reliably forecasting such events combined with a timely evacuation of endangered inhabited areas often constitute the most efficient action. Recently, considerable efforts in monitoring, analyzing, and modeling such phenomena have led to significant advances in destabilization process understanding, improving early warning perspectives. The purpose of this paper is to review the recent progress in this domain. Three different types of instabilities can be identified depending on the thermal properties of the ice/bed interface. If cold (1), the maturation of the rupture is associated with a typical time evolution of surface velocities and passive seismic activity. A prediction of the final break off is possible using these precursory signs. For the two other types, water plays a key role in the development of the instability. If the ice/bed interface is partly temperate (2), the presence of meltwater may reduce the basal resistance, which promotes the instability. No clear and easily detectable precursory signs are known in this case, and the only way to infer any potential instability is to monitor the temporal evolution of the thermal regime. The last type of instability (3) concerns steep temperate glacier tongues switching for several days/weeks during the melting season into a so-called "active phase" followed in rare cases by a major break-off event. Although the prediction of such events is still far from being achievable, critical conditions promoting the final instability can be identified.

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Towards landslide predictions: two case studies

Cited by 66 publications

References 23 publications

Thermoporomechanics of creeping landslides: The 1963 Vaiont slide, northern Italy

Thermoporomechanics of creeping landslides: The 1963 Vaiont slide, northern Italy

Application of GA–SVM method with parameter optimization for landslide development prediction

Avalanching glacier instabilities: Review on processes and early warning perspectives

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