The Effect of Seismic Sequences in Probabilistic Seismic Hazard Analysis

Šipčić, Nevena; Kohrangi, Mohsen; Παπαδόπουλος, Αθανάσιος; Marzocchi, Warner; Bazzurro, Paolo

doi:10.1785/0120210208

Cited by 11 publications

(3 citation statements)

References 63 publications

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“…For this reason, the stochastic event sets in this study are considered acceptable. It is worth noting that other studies based on classical ETAS approaches also seem to provide a good description of the Italian seismicity, especially in the 5 < M W < 5.5 range (e.g., Šipčić et al., 2022).…”

Section: Case Studymentioning

confidence: 88%

Integrating Long and Short‐Term Time Dependencies in Simulation‐Based Seismic Hazard Assessments

Iacoletti

Cremen

Galasso

2022

Earth and Space Science

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Conventional probabilistic seismic hazard analysis (PSHA) only considers mainshock events and uses a time‐independent earthquake rupture forecast to describe the occurrence of mainshocks. This approach neglects the long‐term time‐dependency of mainshocks on specific fault segments, the interaction of adjacent faults, and the spatial and temporal clustering of aftershocks. This study integrates a recently proposed advanced fault‐based PSHA framework with an aftershock simulator based on the Epidemic‐Type Aftershock Sequence (ETAS) model, to overcome the aforementioned limitations. Central Italy is used as a case study to illustrate the proposed framework. The case‐study hazard curves show that including state‐of‐the‐art advances in fault‐based PSHA may increase the ground‐motion amplitudes for low return periods, and decrease the ground‐motion amplitudes for high return periods, relative to a conventional PSHA approach. The magnitude of ground‐motion estimate increases due to aftershock inclusion is dependent on the selected site and return period. Sensitivity analyses of the results demonstrate that: (a) close to modeled faults, high‐return‐period hazard estimates are more affected by fault‐related inputs than the aftershock inclusion; (b) close to modeled faults, the influence of aftershock inclusion is higher for low return periods than high ones; (c) away from modeled faults, aftershocks inclusion greatly affects the variance of the hazard results; and (d) fault interaction has a limited effect on the variance of the hazard estimates compared to other analysis inputs. This study could help with the future implementation of complex fault modeling approaches and aftershock hazard in seismic risk models.

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Section: Case Studymentioning

confidence: 88%

Integrating Long and Short‐Term Time Dependencies in Simulation‐Based Seismic Hazard Assessments

Iacoletti

Cremen

Galasso

2022

Earth and Space Science

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“…In addition, the Epidemic Type Aftershock Sequence (ETAS) model has also been used to study the spatio-temporal distribution of earthquakes in recent years (Ogata, 1988;Ogata, 1998;Zhuang et al, 2005;Ogata and Zhuang, 2006), and has been proposed or used by scientists as a means for probabilistic seismic hazard analysis (e.g., Xu et Wu, 2017;Pei et al, 2021;Šipčić et al, 2022). However, for seismic hazard analysis, more attention is paid to the temporal distribution of main shocks (Michael, 2011;Daub et al, 2012;Shearer and Stark, 2012;Beroza, 2012).…”

Section: Introductionmentioning

confidence: 99%

Temporal distribution model and occurrence probability of M ≥ 6.5 earthquakes in North China Seismic Zone

Gao

2023

Nat Hazards

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The temporal distribution of earthquakes provides important basis for earthquake prediction and seismic hazard analysis. The relatively limited records of strong earthquakes have often made it di cult to study the temporal distribution models of regional strong earthquakes. However, there are hundreds of years of complete strong earthquake records in North China Seismic Zone, providing abundant basic data for studying temporal distribution models. Using the data of M ≥ 6.5 earthquakes in North China as inputs, this paper estimates the model parameters using the maximum likelihood method with exponential, Gamma, Weibull, Lognormal and Brownian passage time (BPT) distributions as target models. The optimal model for describing the temporal distribution of earthquakes is determined according to Akaike information criterion (AIC), determination coe cient R 2 and Kolmogorov-Smirnov test (K-S test). The results show that Lognormal and BPT models perform better in describing the temporal distribution of strong earthquakes in North China. The mean recurrence periods of strong earthquakes (M ≥ 6.5) calculated based on these two models are 8.1 years and 13.2 years, respectively. In addition, we used the likelihood pro le method to estimate the uncertainty of model parameters. For the BPT model, the mean and 95% con dence interval of recurrence interval µ is 13.2 (8.9-19.1) years, and the mean and 95% con dence interval of α is 1.29 (1.0-1.78). For the Lognormal model, the mean value and 95% con dence interval of v is 2.09 (1.68-2.49), the mean value exp (v) corresponding to earthquake recurrence interval is 8.1 (5.4-12.1) years. In this study, we also calculated the occurrence probability of M ≥ 6.5 earthquakes in North China Seismic Zone in the future, and found that the probability and 95% con dence interval in the next 10 years based on the BPT model is 35.3% (26.8%-44.9%); the mean value and 95% con dence interval of earthquake occurrence probability based on the Lognormal distribution is 35.4% (22.9%-49.7%); the mean probability and 95% con dence interval based on the Poisson model is 53.1% (41.1%-64%). The results of this study may provide important reference for temporal distribution model selection and earthquake recurrence period calculation in future seismic hazard analysis in North China.

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Section: Introductionmentioning

confidence: 99%

Temporal Distribution Model and Occurrence Probability of M≥6.5 Earthquakes in North China Seismic Zone

Gao

2022

Preprint

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The temporal distribution of earthquakes provides important basis for earthquake prediction and seismic hazard analysis. The relatively limited records of strong earthquakes have often made it difficult to study the temporal distribution models of regional strong earthquakes. However, there are hundreds of years of complete strong earthquake records in North China Seismic Zone, providing abundant basic data for studying temporal distribution models. Using the data of M ≥ 6.5 earthquakes in North China as inputs, this paper estimates the model parameters using the maximum likelihood method with exponential, Gamma, Weibull, Lognormal and Brownian passage time (BPT) distributions as target models. The optimal model for describing the temporal distribution of earthquakes is determined according to Akaike information criterion (AIC), determination coefficient R2 and Kolmogorov-Smirnov test (K-S test). The results show that Lognormal and BPT models perform better in describing the temporal distribution of strong earthquakes in North China. The mean recurrence periods of strong earthquakes (M ≥ 6.5) calculated based on these two models are 8.1 years and 13.2 years, respectively. In addition, we used the likelihood profile method to estimate the uncertainty of model parameters. For the BPT model, the mean and 95% confidence interval of recurrence interval µ is 13.2 (8.9–19.1) years, and the mean and 95% confidence interval of α is 1.29 (1.0-1.78). For the Lognormal model, the mean value and 95% confidence interval of v is 2.09 (1.68–2.49), the mean value exp (v) corresponding to earthquake recurrence interval is 8.1 (5.4–12.1) years. In this study, we also calculated the occurrence probability of M ≥ 6.5 earthquakes in North China Seismic Zone in the future, and found that the probability and 95% confidence interval in the next 10 years based on the BPT model is 35.3% (26.8%-44.9%); the mean value and 95% confidence interval of earthquake occurrence probability based on the Lognormal distribution is 35.4% (22.9%-49.7%); the mean probability and 95% confidence interval based on the Poisson model is 53.1% (41.1%-64%). The results of this study may provide important reference for temporal distribution model selection and earthquake recurrence period calculation in future seismic hazard analysis in North China.

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The Effect of Seismic Sequences in Probabilistic Seismic Hazard Analysis

Cited by 11 publications

References 63 publications

Integrating Long and Short‐Term Time Dependencies in Simulation‐Based Seismic Hazard Assessments

Integrating Long and Short‐Term Time Dependencies in Simulation‐Based Seismic Hazard Assessments

Temporal distribution model and occurrence probability of M ≥ 6.5 earthquakes in North China Seismic Zone

Temporal Distribution Model and Occurrence Probability of M≥6.5 Earthquakes in North China Seismic Zone

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