Probabilistic tsunami hazard analysis for Tuzla test site using Monte Carlo simulations

Bayraktar, Hafize Başak; Sözdinler, Ceren Özer

doi:10.5194/nhess-20-1741-2020

Cited by 5 publications

(1 citation statement)

References 82 publications

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“…The application of the time-dependent model is based on a characteristic earthquake model. In the field of PTHA, some case studies have modeled the occurrence probability of characteristic earthquakes using the BPT distribution, a time-dependent model, instead of the Poisson distribution, a time-independent model (e.g., Bayraktar & Ozer Sozdinler, 2020;Goda, 2019). By using a time-dependent occurrence model, it is possible to generate hazard curves or probabilistic tsunami inundation depth distributions that focus on a medium-to long-term period, such as the next 30 or 50 years, instead of hazard curves averaged over the long term.…”

Section: Accepted Articlementioning

confidence: 99%

Time‐Dependent Probabilistic Tsunami Inundation Assessment Using Mode Decomposition to Assess Uncertainty for an Earthquake Scenario

et al. 2021

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 The singular value decomposition method is used to evaluate the eigenmodes of the tsunami inundation depth distribution and reduce the computational cost.  The variations in three variables are considered earthquake fault uncertainties: the fault depth, slip amount, and slip distribution.  A time-dependent probabilistic tsunami inundation assessment is performed with the BPT distribution to account for seismic imminence.

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Section: Accepted Articlementioning

confidence: 99%

Time‐Dependent Probabilistic Tsunami Inundation Assessment Using Mode Decomposition to Assess Uncertainty for an Earthquake Scenario

et al. 2021

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Probabilistic Tsunami Risk Assessment from Incomplete and Uncertain Historical Impact Records: Mediterranean and Connected Seas

Triantafyllou

Papadopoulos

Kijko

2023

Pure Appl. Geophys.

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Tsunami risk is considered as the probability of a particular coastline being struck by a tsunami that may cause a certain level of impact (destructiveness). The impact metric of a tsunami is expressed in terms of tsunami intensity values, K, assigned on a 12-degree scale. To calculate tsunami risk we are based on the tsunami history of the region codified in tsunami catalogues. The probabilistic model adopted was used successfully for hazard assessment of earthquakes (Kijko et al. in Bull Seismol Soc Am 79:645–654, 2016) and of tsunamis (Smit et al. in Environmetrics 30:e2566, 2019) by considering seismic magnitude and tsunami height as metrics of the respective hazards. In this model, instead of hazard metrics we inserted risk metric, i.e. wave impact in terms of intensity values. The procedure allows utilization of the entire data set consisting not only from the complete (recent) part of tsunami catalogue but also from the highly incomplete and uncertain historical part of the catalogue. Risk is assessed in terms of probabilities of exceedance and return periods of certain intensity values in specific time frames. We applied the model using catalogues for the Mediterranean and connected seas. Sensitivity analysis showed that using complete data sets generally provided more realistic results than using entire data sets. Results indicated that the risk level depends on the seismicity level and not on the size of individual ocean basin. The highest tsunami risk level was found in the eastern Mediterranean (EM), with a significantly lower risk in the western Mediterranean (WM). In the Marmara Sea (MS), the tsunami risk was low, and the lowest was in the Black Sea (BS). The risk in the small Corinth Gulf (CG, Central Greece) was comparable to that of WM. The return period of damaging tsunamis (i.e. K ≥ 7) was 22 years in the entire Mediterranean basin and 31, 118, 135, 424, and 1660 years in the EM, WM, CG, MS, and BS basins, respectively.

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Effect of permanent stress on the time-dependent earthquake probability: implication for seismic hazard assessment in the African continent

Bantidi

2023

Geophysical Journal International

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Summary Earthquake hazard assessment is the first step towards implementing prevention, preparedness, and response or faster recovery actions to reduce the risk of seismic disasters. In this paper, we present a comprehensive study on present-day seismicity in terms of the estimated waiting time and conditional probability in Africa by 2022 – 2072 using four competing distribution models (Brownian passage time (BPT), gamma, lognormal, and Weibull). We also investigate how much Coulomb stress change ($\Delta CFF$) induced by previous earthquakes that occurred in neighboring active sources should revise the probability of occurrence at the location of the next events. We analyze large earthquakes with moment magnitude, ${M}_w \ge 6.0$, collating data from the Global Centroid Moment Tensor and from several published literature that list fault plane solutions of large African earthquakes since 1900. We assume that the dataset is stationary and consists of independent events. First, the model's parameters are estimated and the results of the statistical analysis of the interevent times show clear evidence of quasi-periodic recurrence behavior for large earthquakes ${M}_w \ge $ 6.0 in different seismotectonic regions in Africa. Next, a comparison among the distribution models is performed with the aim of selecting the most suitable one. The results in terms of the maximum likelihood criterion and its extension (Akaike Information Criterion) indicate that, in general, the BPT and Weibull models had similar fits to each other, and performed slightly better than gamma and lognormal models. Then, we use Gaussian random distributions to treat parameter uncertainties (e.g., aperiodicity, maximum expected magnitude, slip rate, and mean recurrence time) of the distribution models associated with each seismotectonic region. From repeated Monte Carlo draws, we assess uncertainties of the 50-year conditional probability values for the next earthquake obtained from two distribution models (BPT and BPT + $\Delta CFF$) related to the 50th percentile. The results of the BPT distribution indicate very high chances of future earthquakes in the study region where the conditional probability of a large earthquake reaches 99.5%, 95.6%, 83.1%, and 82.2% for the western branch of the East African Rift System (EARS), northwest Africa, the Afar region, and the eastern branch of EARS, respectively. Taking into account the effect of stress change from interacting sources (BPT + $\Delta CFF$), these probabilities are slightly modified to 99.8%, 98.4%, 89.9%, and 87.3% for the western branch of EARS, northwest Africa, the Afar region, and the eastern branch of EARS, respectively. These marginal increases suggest that the estimated effect of the earthquake interaction introduced by the coseismic slip of previous earthquakes on neighboring active sources is minor if compared with the uncertainties affecting the renewal models used for the basic time-dependent conditional probability assessment.

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Probabilistic tsunami hazard analysis for Tuzla test site using Monte Carlo simulations

Cited by 5 publications

References 82 publications

Time‐Dependent Probabilistic Tsunami Inundation Assessment Using Mode Decomposition to Assess Uncertainty for an Earthquake Scenario

Time‐Dependent Probabilistic Tsunami Inundation Assessment Using Mode Decomposition to Assess Uncertainty for an Earthquake Scenario

Probabilistic Tsunami Risk Assessment from Incomplete and Uncertain Historical Impact Records: Mediterranean and Connected Seas

Effect of permanent stress on the time-dependent earthquake probability: implication for seismic hazard assessment in the African continent

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