scholarly journals The Correlation of B-Value in the Earthquake Frequency-Magnitude Distribution, Heat Flow and Gravity Data in the Sivas Basin, Central Eastern Turkey

2019 ◽  
Vol 9 (1) ◽  
pp. 11-15 ◽  
Author(s):  
Funda Bilim
Keyword(s):  
Heat Flow ◽  
Gravity Data ◽  
B Value ◽  
Magnitude Distribution ◽  
Eastern Turkey ◽  
Sivas Basin ◽  
Earthquake Frequency ◽  
Central Eastern ◽  
Frequency Magnitude Distribution ◽  
Frequency Magnitude

Mapping b-Value Anomalies Along the Indonesian Island Chain: Implications for Upcoming Earthquakes

2014 ◽  
Vol 08 (04) ◽  
pp. 1450010 ◽  
Author(s):  
Santi Pailoplee
Keyword(s):  
Spatial Relationship ◽  
B Value ◽  
Fixed Number ◽  
Earthquake Catalogue ◽  
Suitable Assumption ◽  
B Values ◽  
Magnitude Distribution ◽  
Risk Areas ◽  
Frequency Magnitude Distribution ◽  
Frequency Magnitude

In this study, the geospatial frequency–magnitude distribution (FMD) b-value images of the prospect sources of upcoming earthquakes were investigated along the Indonesian Sunda Margin (ISM) that strikes parallel to and near the Indonesian Island chain. After enhancing the completeness and stability of the earthquake catalogue, the seismicity data were separated according to their seismotectonic setting into shallow crustal and Intraslab earthquakes. In order to verify the spatial relationship between the b-values and the occurrence of subsequent major earthquakes, the complete shallow crustal seismicity dataset (1980–2005) was truncated into the 1980–2000 sub-dataset. Utilizing the suitable assumption of fixed-number of earthquakes, retrospective tests of both the complete and truncated datasets supported that areas of comparatively low b-values could reasonably be expected to predict likely hypocenters of future earthquakes. As a result, the present-day distributions of b-values derived from the complete (1980–2005) shallow crustal and Intraslab seismicity datasets revealed eight and six earthquake-prone areas, respectively, along the ISM. Since most of these high risk areas proposed here are quite close to the major cities of Indonesia, attention should be paid and mitigation plans should be developed for both seismic and tsunami hazards.

A grid-based b-value approximation through Southern and Northern Norway: preliminary results 

2021 ◽  
Author(s):  
Rodrigo Estay ◽  
Claudia Pavez
Keyword(s):  
B Value ◽  
Seismic Events ◽  
Online Database ◽  
Magnitude Of Completeness ◽  
Stress Regime ◽  
Magnitude Distribution ◽  
The Mean ◽  
Frequency Magnitude Distribution ◽  
Frequency Magnitude ◽  
Grid Based

<p>The Gutenberg – Richter’s b-value is commonly used to analyze the frequency-magnitude distribution of earthquakes, describing the proportion of small and large seismic events as the first estimation of seismic hazard. Additionally, the b-value has been used as a stress meter, giving some insights into the stress regime in different regions around the world. In this research, a grid-based spatial distribution for the b – value was estimated in three different areas of Norway: northern (74°-81° N/ 12°-26° E), southern (57°-64°N/3°-12° E), and the ridge zones of Mohns and Knipovich. For this, we used a complete catalog from the years 2000 to 2019, which was obtained from the Norwegian National Seismic Network online database. The magnitude of completeness was estimated separately for each zone both in time and space, covering a total area of ~425,000 km<sup>2</sup>. Our results show a regional variation of the mean b-value for northern (b<sub>north</sub> = 0.79) and southern (b<sub>south</sub> = 1.03) Norway, and the Ridge (b<sub>ridge</sub> = 0.73), which can be interpreted in terms of the predominant stress regime in the different zones. So far, a few calculations regarding the b-value were previously done in Norway to analyze local intraplate sequences. Then, according to our knowledge, this research corresponds to the first estimation of a regional spatial variation of the b – value in the country.</p>

scholarly journals Generalized earthquake frequency–magnitude distribution described by asymmetric Laplace mixture modelling

2019 ◽  
Vol 219 (2) ◽  
pp. 1348-1364 ◽  
Author(s):  
A Mignan
Keyword(s):  
Homogeneous Space ◽  
Mixture Model ◽  
Space Time ◽  
Seismic Network ◽  
Earthquake Catalogues ◽  
Magnitude Distribution ◽  
Mixture Modelling ◽  
Earthquake Frequency ◽  
Frequency Magnitude Distribution ◽  
Frequency Magnitude

SUMMARY The complete part of the earthquake frequency–magnitude distribution, above the completeness magnitude mc, is well described by the Gutenberg–Richter law. On the other hand, incomplete data does not follow any specific law, since the shape of the frequency–magnitude distribution below max(mc) is function of mc heterogeneities that depend on the seismic network spatiotemporal configuration. This paper attempts to solve this problem by presenting an asymmetric Laplace mixture model, defined as the weighted sum of Laplace (or double exponential) distribution components of constant mc, where the inverse scale parameter of the exponential function is the detection parameter κ below mc, and the Gutenberg–Richter β-value above mc. Using a variant of the Expectation-Maximization algorithm, the mixture model confirms the ontology proposed by Mignan [2012, https://doi.org/10.1029/2012JB009347], which states that the shape of the earthquake frequency–magnitude distribution shifts from angular (in log-linear space) in a homogeneous space–time volume of constant mc to rounded in a heterogeneous volume corresponding to the union of smaller homogeneous volumes. The performance of the proposed mixture model is analysed, with encouraging results obtained in simulations and in eight real earthquake catalogues that represent different seismic network spatial configurations. We find that k = κ/ln(10) ≈ 3 in most earthquake catalogues (compared to b = β/ln(10) ≈ 1), suggesting a common detection capability of different seismic networks. Although simpler algorithms may be preferred on pragmatic grounds to estimate mc and the b-value, other methods so far fail to model the angular distributions observed in homogeneous space-time volumes. Mixture modelling is a promising strategy to model the full earthquake magnitude range, hence potentially increasing seismicity data availability tenfold, since ca. 90 per cent of earthquake catalogue events are below max(mc).

scholarly journals The Effect of Declustering on the Size Distribution of Mainshocks

2021 ◽  
Author(s):  
Leila Mizrahi ◽  
Shyam Nandan ◽  
Stefan Wiemer
Keyword(s):  
Seismic Hazard Assessment ◽  
B Value ◽  
Aftershock Sequence ◽  
Earthquake Catalogs ◽  
Magnitude Distribution ◽  
Independent Events ◽  
Potential Source ◽  
Epidemic Type Aftershock Sequence ◽  
Frequency Magnitude Distribution ◽  
Frequency Magnitude

Abstract Declustering aims to divide earthquake catalogs into independent events (mainshocks), and dependent (clustered) events, and is an integral component of many seismicity studies, including seismic hazard assessment. We assess the effect of declustering on the frequency–magnitude distribution of mainshocks. In particular, we examine the dependence of the b-value of declustered catalogs on the choice of declustering approach and algorithm-specific parameters. Using the catalog of earthquakes in California since 1980, we show that the b-value decreases by up to 30% due to declustering with respect to the undeclustered catalog. The extent of the reduction is highly dependent on the declustering method and parameters applied. We then reproduce a similar effect by declustering synthetic earthquake catalogs with known b-value, which have been generated using an epidemic-type aftershock sequence model. Our analysis suggests that the observed decrease in b-value must, at least partially, arise from the application of the declustering algorithm on the catalog, rather than from differences in the nature of mainshocks versus fore- or aftershocks. We conclude that declustering should be considered as a potential source of bias in seismicity and hazard studies.

The Gutenberg-Richter law based on rupture dynamics

2020 ◽  
Author(s):  
Zhenguo Zhang ◽  
Wenqiang Zhang ◽  
Jiankuan Xu ◽  
Xiaofei Chen
Keyword(s):  
Power Law Distribution ◽  
Magnitude Distribution ◽  
Rupture Dynamics ◽  
Earthquake Sources ◽  
Rupture Area ◽  
Earthquake Frequency ◽  
Frequency Magnitude Distribution ◽  
First Time ◽  
The Relationship ◽  
Frequency Magnitude

<p>Earthquakes recorded by instruments obey the Gutenberg-Richter law, which expresses the dependence of earthquake frequency on magnitude. The Gutenberg-Richter law reveals the physics of earthquake sources and is important for analyzing the seismicity of active fault systems and vulnerable areas. Based on rupture dynamics, for the first time, we obtain a power-law distribution for the relationship between earthquake frequency and magnitude. The weight of an earthquake relies on its rupture area and recurrence interval. Our derived frequency-magnitude distribution agrees with the Gutenberg-Richter law, which is summarized from global and regional earthquake catalogs. This work provides a new way to understand the Gutenberg-Richter law and the physics of earthquake sources.</p>

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