Distribution of maximum earthquake magnitudes in future time intervals: application to the seismicity of Japan (1923–2007)

Писаренко, В. Ф.; Sornette, Didier; Родкин, М. В.

doi:10.5047/eps.2010.06.003

Cited by 30 publications

(12 citation statements)

References 15 publications

(18 reference statements)

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“…The distribution function generalized extreme value is defined as follows (Pisarenko, 2007(Pisarenko, , 2008(Pisarenko, , 2010:…”

Section: Methodsmentioning

confidence: 99%

“…The methodology of the Generalized Extreme Value Distribution (GEV) can solve this problem. This probabilistic method has been developed by Pisarenko and his colleagues to evaluate the maximum earthquake magnitude for many catalogs such as the Harvard earthquake list (Pisarenko et al, 2008(Pisarenko et al, , 2014, the Japanese earthquake catalog (Pisarenko et al, 2010),… Thus, in general, it has been shown that the East Sea area has the potentially high seismic risk. However, historical earthquake data and machine data were used and the magnitudes have not been unified.…”

Section: Introductionmentioning

confidence: 99%

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Seismic activity characteristics in the East Sea area

Hoan

Lu²,

Родкин

et al. 2018

TCCKHVTD

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In this paper, seismic activity characteristics in the East Sea area was analyzed by authors on the base of the unified earthquake catalog , including 131505 events with magnitude 3 ≤ Mw ≤ 8.4. The seismic intensity in the East Sea during the period 1900 -2017 is characterized by the earthquake representative level Mw = 4.7. The strong earthquake activity in the East Sea area clearly shows the regularity in each stage. In the period from 1900 to 2017, the East Sea area has four periods of strong earthquake activity, each stage is nearly 30 years with particular characteristics. The distribution of the maximum earthquake quantities by years has a cyclicity in all four periods. In each stage there are 1-2 strong earthquakes with M max ≥ 8.0. The strong earthquakes with M max ≥ 7.5 have occurred by a repeatable rule of 3-5 years in all four stages. This allows the prediction of the maximum earthquake repeat cycle of M max ≥ 7.5 in the study area is 3-5 years. In other hand, the maximum magnitude values for the East Sea region has assessed by GEV method with several different predict periods (20, 40, 60, 80, 100 years), with predicted probability 80%. We concluded that it is possible that earthquake have M max = 8.7 will occur in next 100 years.

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“…The distribution function generalized extreme value is defined as follows (Pisarenko, 2007(Pisarenko, , 2008(Pisarenko, , 2010:…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Seismic activity characteristics in the East Sea area

Hoan

Lu²,

Родкин

et al. 2018

TCCKHVTD

View full text Add to dashboard Cite

show abstract

“…It is also possible to use a magnitude-frequency distribution with no a priori prescribed analytical shape (e.g., Kijko, 2004). Other methods use the theory of extreme values of random variables (Pisarenko et al, 2008(Pisarenko et al, , 2010. These various methods are based only on the observed seismicity data.…”

Section: Usual Methodsmentioning

confidence: 99%

“…Previous estimates for M max varied from 9 (McCaffrey, 2008, using scaling relations and fault segment lengths) to 10 (if confidence limits are high) (Zöller et al, 2014, using the tapered GR distribution, but not conservation of moment). Using the theory of extreme values, Pisarenko et al (2010) found the absolute M max to be 9:57 0:86 for Japan. With the model and assumptions here, there is a 30% chance that M w ≤ 9 could be M max , but almost zero chance that it would be as large as M w 10.…”

Section: Japan Trenchmentioning

confidence: 99%

Determination of Mmax from Background Seismicity and Moment Conservation

Stevens

Avouac

2017

Bulletin of the Seismological Society of America

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We describe a simple method to determine the probability distribution function of the magnitude M max and return period T R of the maximum plausible earthquake on crustal faults. The method requires the background seismicity rate (estimated from instrumental data) and the rate of interseismic moment buildup. The method assumes that the moment released by the seismic slip is in balance with the moment deficit accumulated in between earthquakes. It also assumes that the seismicity obeys the Gutenberg-Richter (GR) law up to M max . We took into account the aftershocks of large infrequent events that were not represented in the instrumental record, so that we could estimate the average seismicity rate over the entire fault history. We extrapolated the instrumental record, using the GR law to model the frequency of larger events and their aftershocks. This increased the frequencies of smaller events on average; when these smaller events were newly extrapolated, they predicted a higher frequency of larger events. We iterated this process until stability was reached, and then we assumed moment balance when we found the maximum magnitude; we have found this method to be appropriate in applications involving examples of fault with good historical catalogs. We then showed examples of applications to faults with no historical catalogs. We present results from nine cases. For the San Andreas fault system, we find

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“…In the study of earthquakes, the EVT is a relevant tool, providing important information, such as the estimation of the probability of occurring a large earthquake over a long period of time or high quantiles (see e.g. Pisarenko et al (2010)). …”

Section: Introductionmentioning

confidence: 99%

Modeling of Extremal Earthquakes

Brito

Cavalcante

Freitas

2015

CIM Series in Mathematical Sciences

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Natural hazards, such as big earthquakes, affect the lives of thousands of people at all levels. Extreme-value analysis is an area of statistical analysis particularly concerned with the systematic study of extremes, providing an useful insight to fields where extreme values are probable to occur. The characterization of the extreme seismic activity is a fundamental basis for risk investigation and safety evaluation. Here we study large earthquakes in the scope of the Extreme Value Theory. We focus on the tails of the seismic moment distributions and we propose to estimate relevant parameters, like the tail index and high order quantiles using the geometric-type estimators.In this work we combine two approaches, namely an exploratory oriented analysis and an inferential study. The validity of the assumptions required are verified, and both geometric-type and Hill estimators are applied for the tail index and quantile estimation. A comparison between the estimators is performed, and their application to the considered problem is illustrated and discussed in the corresponding context.

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Distribution of maximum earthquake magnitudes in future time intervals: application to the seismicity of Japan (1923–2007)

Cited by 30 publications

References 15 publications

Seismic activity characteristics in the East Sea area

Seismic activity characteristics in the East Sea area

Determination of Mmax from Background Seismicity and Moment Conservation

Modeling of Extremal Earthquakes

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