Time-Independent and Time-Dependent Seismic Hazard in Greece Based on Seismogenic Sources

2000 ◽  
Vol 90 (1) ◽  
pp. 22-33 ◽  
Author(s):  
Ch. A. Papaioannou
Keyword(s):  
Seismic Hazard ◽  
Time Dependent ◽  
Seismogenic Sources

A Hybrid Time‐Dependent Probabilistic Seismic‐Hazard Model for Canterbury, New Zealand

2016 ◽  
Vol 87 (6) ◽  
pp. 1311-1318 ◽  
Author(s):  
Matthew C. Gerstenberger ◽  
David A. Rhoades ◽  
Graeme H. McVerry
Keyword(s):  
New Zealand ◽  
Seismic Hazard ◽  
Hazard Model ◽  
Time Dependent ◽  
Probabilistic Seismic Hazard

scholarly journals Bayesian probabilities for occurrence of large earthquakes in the seismogenic sources of Japan and Phillipine during the period 1998-2017

2001 ◽  
Vol 34 (4) ◽  
pp. 1619
Author(s):  
T. M. TSAPANOS ◽  
O. CH. GALANIS ◽  
S. D. MAVRIDOU ◽  
M. P. HELMl
Keyword(s):  
Seismic Hazard ◽  
Bayesian Statistics ◽  
Poisson Distribution ◽  
Bayesian Approach ◽  
Seismic Sources ◽  
Time Interval ◽  
Seismogenic Sources ◽  
The One ◽  
Large Earthquakes ◽  
The Bayesian Approach

The Bayesian statistics is adopted in 11 seismic sources of Japan and 14 of Philippine in order to estimate the probabilities of occurrence of large future earthquakes, assuming that earthquakes occurrence follows the Poisson distribution. The Bayesian approach applied represents the probability that a certain cut-off magnitude (or larger) will exceed in a given time interval of 20 years, that is 1998-2017. This cut-off magnitude is chosen the one with M=7.0 or greater. In this case we can consider these obtained probabilities as a seismic hazard presentation. More over curves are produced which present the fluctuation of the seismic hazard between these seismic sources. These graphs of varying probability are useful either for engineering or other practical purposes

The Seismic Hazard Implications of Declustering and Poisson Assumptions Inferred from a Fully Time-Dependent Model

2021 ◽  
Author(s):  
Edward H. Field ◽  
Kevin R. Milner ◽  
Nicolas Luco
Keyword(s):  
Seismic Hazard ◽  
Poisson Process ◽  
Seismic Hazard Assessment ◽  
Aftershock Sequence ◽  
Time Dependent ◽  
Probabilistic Seismic Hazard Assessment ◽  
Full Time ◽  
Quiet Time ◽  
Epidemic Type Aftershock Sequence ◽  
True Time

ABSTRACT We use the Third Uniform California Earthquake Rupture Forecast (UCERF3) epidemic-type aftershock sequence (ETAS) model (UCERF3-ETAS) to evaluate the effects of declustering and Poisson assumptions on seismic hazard estimates. Although declustering is necessary to infer the long-term spatial distribution of earthquake rates, the question is whether it is also necessary to honor the Poisson assumption in classic probabilistic seismic hazard assessment. We use 500,000 yr, M ≥ 2.5 synthetic catalogs to address this question, for which UCERF3-ETAS exhibits realistic spatiotemporal clustering effects (e.g., aftershocks). We find that Gardner and Knopoff (1974) declustering, used in the U.S. Geological Survey seismic hazard models, lowers 2% in 50 yr and risk-targeted ground-motion hazard metrics by about 4% on average (compared with the full time-dependent [TD] model), with the reduction being 5% at 40% in 50 yr ground motions. Keeping all earthquakes and treating them as a Poisson process increases these same hazard metrics by about 3%–12%, on average, due to the removal of relatively quiet time periods in the full TD model. In the interest of model simplification, bias minimization, and consideration of the probabilities of multiple exceedances, we agree with others (Marzocchi and Taroni, 2014) that we are better off keeping aftershocks and treating them as a Poisson process rather than removing them from hazard consideration via declustering. Honoring the true time dependence, however, will likely be important for other hazard and risk metrics, and this study further exemplifies how this can now be evaluated more extensively.

scholarly journals Time independent seismic hazard analysis of Greece deduced from Bayesian statistics

2003 ◽  
Vol 3 (1/2) ◽  
pp. 129-134 ◽  
Author(s):  
T. M. Tsapanos ◽  
G. A. Papadopoulos ◽  
O. Ch. Galanis
Keyword(s):  
Seismic Hazard ◽  
Bayesian Statistics ◽  
Hazard Analysis ◽  
Earthquake Occurrence ◽  
Time Intervals ◽  
Seismogenic Sources ◽  
Earthquake Resistant Design ◽  
Seismogenic Source ◽  
Earthquake Resistant ◽  
Of Greece

Abstract. A Bayesian statistics approach is applied in the seismogenic sources of Greece and the surrounding area in order to assess seismic hazard, assuming that the earthquake occurrence follows the Poisson process. The Bayesian approach applied supplies the probability that a certain cut-off magnitude of Ms = 6.0 will be exceeded in time intervals of 10, 20 and 75 years. We also produced graphs which present the different seismic hazard in the seismogenic sources examined in terms of varying probability which is useful for engineering and civil protection purposes, allowing the designation of priority sources for earthquake-resistant design. It is shown that within the above time intervals the seismogenic source (4) called Igoumenitsa (in NW Greece and west Albania) has the highest probability to experience an earthquake with magnitude M > 6.0. High probabilities are found also for Ochrida (source 22), Samos (source 53) and Chios (source 56).

scholarly journals Probabilistic Space- and Time-Interaction Modeling of Mainshock Earthquake Rupture Occurrence

2020 ◽  
Author(s):  
Luis Ceferino ◽  
Anne Kiremidjian ◽  
Gregory Deierlein
Keyword(s):  
Seismic Hazard ◽  
Probabilistic Models ◽  
Spatial Interaction ◽  
Information Criterion ◽  
Passage Time ◽  
Time Dependent ◽  
Attractive Alternative ◽  
Earthquake Rupture ◽  
Time Interaction ◽  
Seismic Moment Release

ABSTRACT This article presents a probabilistic formulation for modeling earthquake rupture processes of mainshocks. A correlated multivariate Bernoulli distribution is used to model rupture occurrence. The model captures time interaction through the use of Brownian passage-time distributions to assess rupture interarrival in multiple sections of the fault, and it also considers spatial interaction through the use of spatial correlograms. The correlograms represents the effect of rupture nucleation and propagation. This model is proposed as an attractive alternative to existing probabilistic models because it (1) incorporates time and space interactions of mainshocks, (2) preserves the marginal distributions of interarrival times after including spatial rupture interactions, that is, model consistency, and (3) has an implicit physical interpretation aligned with rupture behavior observations. The proposed model is applied to assess the occurrence of large interface earthquakes in the subduction fault along the coast of Lima, Peru. The model matches well both the annual magnitude exceedance rates and the average seismic moment release in the tectonic region. The Akaike information criterion (AIC) test confirms that our model performs statistically better than models that do not capture earthquake space interactions. AIC also shows that the spherical correlogram outperforms the exponential correlogram at reproducing earthquake data. Finally, time-dependent seismic hazard in the region is calculated, and the results demonstrate that by accounting for recent earthquake occurrences, the inclusion of time-dependent effects can reduce the 30 yr seismic hazard by a factor of 4.

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