Strategies in strong earthquake prediction

Molchan, G.

doi:10.1016/0031-9201(90)90097-h

Cited by 152 publications

(102 citation statements)

References 7 publications

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“…As a result, the question of which statistics correspond to the recurrent behavior of earthquakes remains controversial. In addition, while the recurrent time-interval statistics have been investigated by many authors (Abaimov et al, 2007a, b;Matthews et al, 2002;Molchan, 1990Molchan, , 1991Nishenko and Buland, 1987;Rikitake, 1982;Utsu, 1984), only a few attempts have been made to investigate the recurrent frequency-size statistics (e.g., Abaimov et al, 2007a;Bakun et al, 2005). This paper focuses on investigating the recurrent frequency-size statistics of characteristic earthquakes on a fault or at a given point on a fault.…”

Section: Introductionmentioning

confidence: 99%

Recurrent frequency-size distribution of characteristic events

Abaimov

Tiampo

Turcotte

et al. 2009

Nonlin. Processes Geophys.

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Abstract. Statistical frequency-size (frequency-magnitude) properties of earthquake occurrence play an important role in seismic hazard assessments. The behavior of earthquakes is represented by two different statistics: interoccurrent behavior in a region and recurrent behavior at a given point on a fault (or at a given fault). The interoccurrent frequencysize behavior has been investigated by many authors and generally obeys the power-law Gutenberg-Richter distribution to a good approximation. It is expected that the recurrent frequency-size behavior should obey different statistics. However, this problem has received little attention because historic earthquake sequences do not contain enough events to reconstruct the necessary statistics. To overcome this lack of data, this paper investigates the recurrent frequencysize behavior for several problems. First, the sequences of creep events on a creeping section of the San Andreas fault are investigated. The applicability of the Brownian passage-time, lognormal, and Weibull distributions to the recurrent frequency-size statistics of slip events is tested and the Weibull distribution is found to be the best-fit distribution. To verify this result the behaviors of numerical sliderblock and sand-pile models are investigated and the Weibull distribution is confirmed as the applicable distribution for these models as well. Exponents β of the best-fit Weibull distributions for the observed creep event sequences and for the slider-block model are found to have similar values ranging from 1.6 to 2.2 with the corresponding aperiodicities C V of the applied distribution ranging from 0.47 to 0.64. We also note similarities between recurrent time-interval statistics and recurrent frequency-size statistics.

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Section: Introductionmentioning

confidence: 99%

Recurrent frequency-size distribution of characteristic events

Abaimov

Tiampo

Turcotte

et al. 2009

Nonlin. Processes Geophys.

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“…Molchan (1990) modi ed this method as an error diagram to predict random point processes. Molchan and Kagan (1992) and Molchan (1997;2003) also review the error diagram method and its applications.…”

Section: Introductionmentioning

confidence: 99%

On Earthquake Predictability Measurement: Information Score and Error Diagram

Kagan

2007

Pure appl. geophys.

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We discuss two methods for measuring the e ectiveness of earthquake prediction algorithms: the information score based on the likelihood ratio and error diagrams. For both of these methods, closed form expressions are obtained for the renewal process based on the gamma and lognormal distributions. The error diagram is more informative than the likelihood ratio and uniquely speci es the information score.We derive an expression connecting the information score and error diagrams. We then obtain the estimate of the region bounds in the error diagram for any value of the information score. We discuss how these preliminary results can be extended for more realistic models of earthquake occurrence.

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“…Accordingly, it uses the nomenclature of statistical estimation. The second one applies the results by Molchan (1990Molchan ( , 1997; see also Molchan & Keilis-Borok 2008) who proposed error diagrams for measuring prediction efficiency. The EDs plot the normalized rate of failures-to-predict (ν) versus the normalized time of alarms (τ ).…”

Section: Introductionmentioning

confidence: 99%

“…proposed by Molchan (1990Molchan ( , 2003 and Molchan & Kagan (1992). But in this case we use the normalized spatial area, not time, as the horizontal axis.…”

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confidence: 99%

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Testing long‐term earthquake forecasts: Likelihood methods and error diagrams

2013

Earthquakes

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Strategies in strong earthquake prediction

Cited by 152 publications

References 7 publications

Recurrent frequency-size distribution of characteristic events

Recurrent frequency-size distribution of characteristic events

On Earthquake Predictability Measurement: Information Score and Error Diagram

Testing long‐term earthquake forecasts: Likelihood methods and error diagrams

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