A stochastic methodology for risk assessment of a large earthquake when a long time has elapsed

Fierro, Raúl; Leiva, Víctor

doi:10.1007/s00477-016-1288-5

Cited by 4 publications

(3 citation statements)

References 28 publications

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“…New insights from the state-of-the-art statistical methods for predicting the occurrence of large earthquakes (e.g. Fierro and Leiva 2017) are useful for investigating the impact of uncertainties of earthquake occurrence to the overall assessment of earthquake-tsunami hazard and risk.…”

Section: Discussionmentioning

confidence: 99%

Stochastic coupled simulation of strong motion and tsunami for the 2011 Tohoku, Japan earthquake

Goda

Petrone

Risi

et al. 2016

Stoch Environ Res Risk Assess

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This study conducts coupled simulation of strong motion and tsunami using stochastically generated earthquake source models. It is focused upon the 2011 Tohoku, Japan earthquake. The ground motion time-histories are simulated using the multiple-event stochastic finite-fault method, which takes into account multiple local rupture processes in strong motion generation areas. For tsunami simulation, multiple realizations of wave profiles are generated by evaluating nonlinear shallow water equations with run-up. Key objectives of this research are: (i) to investigate the sensitivity of strong motion and tsunami hazard parameters to asperities and strong motion generation areas, and (ii) to quantify the spatial variability and dependency of strong motion and tsunami predictions due to common earthquake sources. The investigations provide valuable insights in understanding the temporal and spatial impact of cascading earthquake hazards. Importantly, the study also develops an integrated strong motion and tsunami simulator, which is capable of capturing earthquake source uncertainty. Such an advanced numerical tool is necessary for assessing the performance of buildings and infrastructure that are subjected to cascading earthquake-tsunami hazards.

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Section: Discussionmentioning

confidence: 99%

Stochastic coupled simulation of strong motion and tsunami for the 2011 Tohoku, Japan earthquake

Goda

Petrone

Risi

et al. 2016

Stoch Environ Res Risk Assess

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“…When modelling annual maximum earthquake magnitudes, the Gumbel (GU) distribution is analogous to the EXP distribution [45], whereas the generalized extreme value (GEV) distribution extends the GU distribu-tion in the setting of maximum magnitudes [45]. Recent work on statistical distributions proposed for modelling earthquake is attributed to [10]. Note that no applications of BS distributions in seismology have yet been considered.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, fatigue is created from vibrations and an earthquake can be thought of similarly. It is accepted that earthquakes are produced by the accumulation of energy, beginning with the deformation of rocks induced by the movement of tectonic plates, where the geological fault is located; see [10] and references therein for more details about the physical laws describing the generation of earthquakes. This deformation grows due to the energy accumulated by stress, provoking the rupture of rocks, when this energy exceeds a critical threshold, which releases the energy.…”

Section: Introductionmentioning

confidence: 99%

L-moments of the Birnbaum–Saunders distribution and its extreme value version: estimation, goodness of fit and application to earthquake data

Lillo

Leiva

Nicolis

et al. 2016

Journal of Applied Statistics

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Understanding patterns in the frequency of extreme natural events, such as earthquakes, is important as it helps in the prediction of their future occurrence and hence provides better civil protection. Distributions describing these events are known to be heavy tailed and positive skew making standard distributions unsuitable for such a situation. The Birnbaum-Saunders distribution and its extreme value version have been widely studied and applied due to their attractive properties. We derive L-moment equations for these distributions and propose novel methods for parameter estimation, goodness-of-fit assessment and model selection. A simulation study is conducted to evaluate the performance of the L-moment estimators, which is compared to that of the maximum likelihood estimators, demonstrating the superiority of the proposed methods. To illustrate these methods in a practical application, a data analysis of real-world earthquake magnitudes, obtained from the global centroid moment tensor catalogue during 1962-2015, is carried out. This application identifies the extreme value Birnbaum-Saunders distribution as a better model than classic extreme value distributions for describing seismic events.

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A hidden Markov model for earthquake prediction

Yip

Yau

2017

Stoch Environ Res Risk Assess

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A stochastic methodology for risk assessment of a large earthquake when a long time has elapsed

Cited by 4 publications

References 28 publications

Stochastic coupled simulation of strong motion and tsunami for the 2011 Tohoku, Japan earthquake

Stochastic coupled simulation of strong motion and tsunami for the 2011 Tohoku, Japan earthquake

L-moments of the Birnbaum–Saunders distribution and its extreme value version: estimation, goodness of fit and application to earthquake data

A hidden Markov model for earthquake prediction

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