Empirical Global Relations Converting M S and m b to Moment Magnitude

Scordilis, E. M.

doi:10.1007/s10950-006-9012-4

Cited by 519 publications

(245 citation statements)

References 36 publications

Supporting

Mentioning

194

Contrasting

Unclassified

Order By: Relevance

“…Hence these data were converted to a common scale of moment magnitude (M w ). The local magnitudes were converted Heaton et al (1986), the body wave and surface wave magnitude were converted using the relations suggested by Scordilis (2006) and the intensity values were converted using the empirical relation (M=(2/3) I +1), where I is the earthquake intensity value. A declustering algorithm was used to remove the dependent events from this catalogue.…”

Section: Seismicity Characteristicsmentioning

confidence: 99%

Estimation of peak ground acceleration and spectral acceleration for South India with local site effects: probabilistic approach

Vipin

Anbazhagan

Sitharam

2009

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. In this work an attempt has been made to evaluate the seismic hazard of South India (8.0 • N-20 • N; 72 • E-88 • E) based on the probabilistic seismic hazard analysis (PSHA). The earthquake data obtained from different sources were declustered to remove the dependent events. A total of 598 earthquakes of moment magnitude 4 and above were obtained from the study area after declustering, and were considered for further hazard analysis. The seismotectonic map of the study area was prepared by considering the faults, lineaments and the shear zones in the study area which are associated with earthquakes of magnitude 4 and above. For assessing the seismic hazard, the study area was divided into small grids of size 0.1 • ×0.1 • , and the hazard parameters were calculated at the centre of each of these grid cells by considering all the seismic sources with in a radius of 300 km. Rock level peak horizontal acceleration (PHA) and spectral acceleration (SA) values at 1 s corresponding to 10% and 2% probability of exceedance in 50 years have been calculated for all the grid points. The contour maps showing the spatial variation of these values are presented here. Uniform hazard response spectrum (UHRS) at rock level for 5% damping and 10% and 2% probability of exceedance in 50 years were also developed for all the grid points. The peak ground acceleration (PGA) at surface level was calculated for the entire South India for four different site classes. These values can be used to find the PGA values at any site in South India based on site class at that location. Thus, this method can be viewed as a simplified method to evaluate the PGA values at any site in the study area.

show abstract

Section: Seismicity Characteristicsmentioning

confidence: 99%

Estimation of peak ground acceleration and spectral acceleration for South India with local site effects: probabilistic approach

Vipin

Anbazhagan

Sitharam

2009

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…In the relations of M L ∼ mM w , the scale factor m varies between 0.97 and 2.25, depending on magnitude range, geographical region, and algorithm for the calculation of M w . Moreover, an attempt to define a global relationship failed due to varying magnification of different WoodAnderson (WA) instruments (Scordilis, 2006) and different calibration of local magnitude scales.…”

Section: Introductionmentioning

confidence: 99%

Scaling Relations of Local Magnitude versus Moment Magnitude for Sequences of Similar Earthquakes in Switzerland

Bethmann

Deichmann

Martin

2011

Bulletin of the Seismological Society of America

View full text Add to dashboard Cite

Theoretical considerations and empirical regressions show that, in the magnitude range between 3 and 5, local magnitude, M L , and moment magnitude, M w , scale 1∶1. Previous studies suggest that for smaller magnitudes this 1∶1 scaling breaks down. However, the scatter between M L and M w at small magnitudes is usually large and the resulting scaling relations are therefore uncertain. In an attempt to reduce these uncertainties, we first analyze the M L versus M w relation based on 195 events, induced by the stimulation of a geothermal reservoir below the city of Basel, Switzerland. Values of M L range from 0.7 to 3.4. From these data we derive a scaling of M L ∼ 1:5M w over the given magnitude range. We then compare peak Wood-Anderson amplitudes to the low-frequency plateau of the displacement spectra for six sequences of similar earthquakes in Switzerland in the range of 0:5 ≤ M L ≤ 4:1. Because effects due to the radiation pattern and to the propagation path between source and receiver are nearly identical at a particular station for all events in a given sequence, the scatter in the data is substantially reduced. Again we obtain a scaling equivalent to M L ∼ 1:5M w . Based on simulations using synthetic source time functions for different magnitudes and Q values estimated from spectral ratios between downhole and surface recordings, we conclude that the observed scaling can be explained by attenuation and scattering along the path. Other effects that could explain the observed magnitude scaling, such as a possible systematic increase of stress drop or rupture velocity with moment magnitude, are masked by attenuation along the path.

show abstract

“…The final catalog contains 3293 earthquakes within the period January 1973-April 2013 for events greater than M w 3.0, and this seismicity is illustrated in Figure 1. The data were homogenized to the moment magnitude (M w ) scale using equations E Q -T A R G E T ; t e m p : i n t r a l i n k -; ; 5 5 ; 1 2 5 Scordilis, 2006). The K-means data-partitioning method of Hartigan (1975) has made it possible to partition such a regional seismicity into clusters of earthquakes and even into seismic zones (e.g., Greece; Weatherill and Burton, 2009).…”

Section: Methodsmentioning

confidence: 99%

Earthquake Clustering and Energy Release of the African–Arabian Rift System

Hall¹,

Nixon

Keir

et al. 2018

Bulletin of the Seismological Society of America

View full text Add to dashboard Cite

The earthquakes associated with continental deformation are spatially and temporally variable and are fundamental in understanding fault activity and seismogenic hazards. We conduct K-means cluster analysis on seismicity in the AfricanArabian rift systems to create the first computationally objective analysis of the pattern of earthquakes. We use seismic moment to compute spatial variations in maximum credible earthquake (Mcred) and likely time to the next major release of seismic energy. Our best-fit model has 32 clusters of ∼100-400 km in length, with cluster size decreasing northward along the rift and cluster boundaries correlating with major structural segmentation of the rift. Mcred varies between M w 5.2 and 7.4 across the whole dataset, with the highest values estimated in portions of the rift where the majority of extension is accommodated by seismogenic failure.

show abstract

Empirical Global Relations Converting M S and m b to Moment Magnitude

Cited by 519 publications

References 36 publications

Estimation of peak ground acceleration and spectral acceleration for South India with local site effects: probabilistic approach

Estimation of peak ground acceleration and spectral acceleration for South India with local site effects: probabilistic approach

Scaling Relations of Local Magnitude versus Moment Magnitude for Sequences of Similar Earthquakes in Switzerland

Earthquake Clustering and Energy Release of the African–Arabian Rift System

Contact Info

Product

Resources

About