New tool for the spatio-temporal variation analysis of seismic parameters

Papadopoulos, G. A.; Baskoutas, I.

doi:10.5194/nhess-9-859-2009

Cited by 19 publications

(4 citation statements)

References 14 publications

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“…Papadopoulos and Baskoutas 12 have introduced the new FastBEE algorithm for the seismic hazard assessment, based on the hypothesis that temporal changes of the seismicity reflects the influence of the previously mentioned factors on the strong earthquakes preparatory process, therefore the analysis of the temporal variation of the seismicity can reveal such influence. In this sense the respective FastBEE analysis tool was designed to obtain temporal variation curves of some basic seismicity parameters, which acts as seismic precursors, by the elaboration of common earthquake catalogue data.…”

Section: Introductionmentioning

confidence: 99%

Precursory seismicity pattern before strong earthquakes in Greece

Baskoutas

Papadopoulos

2014

Res Geophys

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The temporal variation of seismicity, based on the retrospective analyses of three seismic parameters i.e., number of earthquakes, bvalue and energy released, have shown significant changes. Their remarkable relation with strong earthquakes occurrence was formulated as a qualitative character precursory seismicity pattern, which were interpreted in terms of a strong earthquakes occurrence preparation phases. The main characteristic of this pattern is that permits the identification of two period of low and high probability for an earthquake occurrence, suggesting its utility in the current seismic hazard assessment, by the continuous monitoring of the temporal variation of the seismic parameters in a given area. This paper investigates the qualitative and quantitative characteristics of the proposed precursory seismicity pattern, before al strong earthquakes occurrence in Greece the time period

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Section: Introductionmentioning

confidence: 99%

Precursory seismicity pattern before strong earthquakes in Greece

Baskoutas

Papadopoulos

2014

Res Geophys

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“…The number of studies devoted to time and space variations of the b-value regularly increases (e.g. Zöller et al 2002;Zhao and Wu 2008;Papadopoulos and Baskoutas 2009;Telesca et al 2009) while a debate remains on the reality and on the physical significance of these variations (e.g. Frohlich 2004).…”

Section: Introductionmentioning

confidence: 99%

Bootstrap determination of the reliability of b-values: an assessment of statistical estimators with synthetic magnitude series

Bengoubou-Valerius

Gibert

2012

Nat Hazards

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International audienceWe consider some practical issues of the determination of the b-value of sequences of magnitudes with the bootstrap method for short series of length L and various quantization levels Dm of the magnitude. Preliminary Monte Carlo tests performed with Dm ¼ 0 demonstrate the superiority of the maximum likelihood estimator bMLE, and the inconsistency of the, yet often used, bLR estimator defined as the least-squares slope of the experimental Gutenberg-Richter curve. The Monte Carlo tests are also applied to an estimator, bKS, which minimizes the Kolmogorov-Smirnov distance between the cumulative distribution of magnitudes and a power-law model. Monte Carlo tests of discrete versions of the bMLE and bKS estimators are done for Dm ¼ f0:1; 0:2; 0:3g and used as reference to evaluate the performance of the bootstrap determination of b. We show that all estimators provide b estimates within 10 % error for L C 100 and if a large number, n = 2 9 105, of bootstrapped sample series is used. A resolution test done with Dm ¼ 0:1 reveals that a clear distinction between b = 0.8, 1.0, and 1.2 is obtained if L= 200

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“…These changes, although their qualitative characters are believed to reflect the changes in stress in the broader area. The positive relation of the observed significant fluctuations with strong earthquakes occurrence were considered by Papadopoulos and Baskoutas (2009; as prognostic anomalies. The regularity of temporal prognostic anomalies appearance, over a long time variation profiles can be formulated, in the ambit of the FastBEE algorithm, as a qualitative precursor seismicity pattern.…”

Section: Qualitative Temporal Variation Precursory Seismicity Patternmentioning

confidence: 99%

“…Alternatively, such precursors may result from systematic spatio-temporal seismicity fluctuations in areas of spatially varying rock properties. In this direction, Papadopoulos and Baskoutas (2003;2009; have introduced the FastBEE algorithm for the seismic hazard assessment, base on the hypothesis that temporal changes of the seismicity reflects the influence of the physical process. The analysis tool, in this algorithm, was designed to obtain temporal variation profiles of some basic seismicity parameters, by the elaboration of common earthquake catalogue data.…”

Section: Introductionmentioning

confidence: 99%