Low b-value prior to the Indo-Myanmar subduction zone earthquakes and precursory swarm before the May 1995 M 6.3 earthquake

Sharma, Sangeeta; Baruah, Sanjib; Sahu, Omprakash; Bora, P. K.; Duarah, R.

doi:10.1016/j.jseaes.2013.04.019

Cited by 5 publications

(3 citation statements)

References 23 publications

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“…Uncertainty in earthquake magnitude is also taken into account, in that an assumption is made that the observed magnitude is the true magnitude subjected to a random error, which follows a Gaussian distribution, having a zero mean and a known standard deviation (after Kijko and Sellevoll, 1992 [KS-II]). and Kijko, 1994;Sharma et al, 2013;Scholz, 2015). Other theories link the b-value with the homogeneity of the rock, namely the more heterogeneous the rock, the higher the b-value (Wyss et al, 1997;Wesseloo, 2014;Wesseloo et al, 2014).…”

Section: Earthquake-occurrence Modelmentioning

confidence: 99%

Estimation of Earthquake Hazard Parameters from Incomplete Data Files. Part III. Incorporation of Uncertainty of Earthquake‐Occurrence Model

Kijko¹,

Smit²,

Sellevoll³

2016

Bulletin of the Seismological Society of America

104

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Most probabilistic seismic-hazard analysis procedures require that at least three seismic source parameters be known, namely the mean seismic activity rate λ, the Gutenberg-Richter b-value, and the area-characteristic (seismogenic source) maximum possible earthquake magnitude m max . In almost all currently used seismic-hazard assessment procedures that utilize these three parameters, it is explicitly assumed that all three remain constant over time and space. However, closer examination of most earthquake catalogs has indicated that significant spatial and temporal variations existed in the seismic activity rate λ, as well as in the Gutenberg-Richter b-value. In this study, the maximum likelihood estimation of these earthquake hazard parameters considers the incompleteness of the catalogs, the uncertainty in the earthquake magnitude determination, as well as the uncertainty associated with the applied earthquake-occurrence models. The uncertainty in the earthquake-occurrence models is introduced by assuming that both the mean seismic activity rate λ and the Gutenberg-Richter b-value are random variables, each described by the gamma distribution. This approach results in the extension of the classic frequency-magnitude Gutenberg-Richter relation and the

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Section: Earthquake-occurrence Modelmentioning

confidence: 99%

Estimation of Earthquake Hazard Parameters from Incomplete Data Files. Part III. Incorporation of Uncertainty of Earthquake‐Occurrence Model

Kijko¹,

Smit²,

Sellevoll³

2016

Bulletin of the Seismological Society of America

104

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“…Also shown in Fig. 1, the sample sizes larger than 450 are necessary for estimations with standard deviations within ±0.05 of the true value (dotted horizontal lines), and the sample sizes proposed as sufficient by Aki (1965) and Shi and Bolt (1982), *50 and *100 events, respectively, may be too optimistic; we have seen studies with b estimations based on *50 event samples (Sahu and Saikia 1994;Monterroso and Kulhánek 2003;Spada et al 2013;Sharma et al 2013) and can only wonder about the reliability of their results.…”

Section: Introductionmentioning

confidence: 92%

Correcting the Gutenberg–Richter b-value for effects of rounding and noise

Márquez-Ramírez¹,

Nava

Zúñiga³

2015

Earthq Sci

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The effects of magnitude rounding and of the presence of noise in the rounded magnitudes on the estimation of the Gutenberg-Richter b-value are explored, and the ways to correct for these effects are proposed. For typical values, b = 1 and rounding interval DM = 0.1, the rounding error is approximately-10-3 and it can be corrected to a negligible approximately-10-5. For the same typical values, the effect of noise can be larger, depending on the characteristics of the noise distribution; for normally distributed noise with standard deviation r = 0.1, the correct b-value may be underestimated by a factor *0.97. Keywords b-Value Á Noise Á Magnitude 2 Correcting the effects of rounding In what follows, we present our own version of the effects of rounding, in order to introduce the notation that will be used in proposing a correction for them.

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“…The temporal distribution of events (greater than M w » 3.5) ( Figure 2(B-ii)) indicates occurrence of three events greater than M w » 5.5 since 1998 till 2015 and last two events (M w 5.9 and 6.0) merely occurred within a span of 4 years. We have studied the cumulative number of events vs. time for a single magnitude range (M w > 3.5) following Sharma et al 2013 (Figure 2(B-iii)). Negligible changes in the slope of the curve are perceived for the felt events.…”

Section: Study Area and Databasementioning

confidence: 99%

Modelling of the Kopili Fault based on slip rate, moment rate and seismic activity in Mikir Hills Plateau of Northeastern India

Sharma

Baruah

2017

Geomatics, Natural Hazards and Risk

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The recurrence period of maximum magnitude earthquake in a seismogenically active formation along the Kopili Fault has been estimated having adequate dependence on the slip rate, moment rate and its seismicity pattern. Here, the frequency-magnitude cum fault areamaximum magnitude relations play a key role with input parameters pertinent to the Kopili Fault zone. Subsequently, where the fault slip rate estimates are not available, the seismic activity is studied from the seismic moment release. The results of this study show that the return period has a strong relation with the fault length, slip rate, strain drop and rigidity. This study ascertains the activity rate in terms of the return period as »50 § 5 years with the moment release of 2.12E+23 dyne-cm from the most active 80-km fault length considering M w 5.5 as reference magnitude under the Kopili Fault zone that may produce a maximum magnitude of M w » 7.6. Finally, we conclude that these models can be used to study the rate of seismicity of the active faults in Northeast India which will provide us prime inputs for seismic hazard analysis of the region and is especially significant for estimating expected return period for poorly known faults or blind faults that lack surface expression. KEYWORDS Slip rate; moment rate; seismicity pattern; maximum magnitude; recurrence period CONTACT Saurabh Baruah

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Low b-value prior to the Indo-Myanmar subduction zone earthquakes and precursory swarm before the May 1995 M 6.3 earthquake

Cited by 5 publications

References 23 publications

Estimation of Earthquake Hazard Parameters from Incomplete Data Files. Part III. Incorporation of Uncertainty of Earthquake‐Occurrence Model

Estimation of Earthquake Hazard Parameters from Incomplete Data Files. Part III. Incorporation of Uncertainty of Earthquake‐Occurrence Model

Correcting the Gutenberg–Richter b-value for effects of rounding and noise

Modelling of the Kopili Fault based on slip rate, moment rate and seismic activity in Mikir Hills Plateau of Northeastern India

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