Magnitude Conversion of Earthquake Rate Forecasts

2017 ◽  
Vol 107 (6) ◽  
pp. 3037-3043
Author(s):  
David A. Rhoades ◽  
Annemarie Christophersen
Keyword(s):  
Magnitude Conversion

scholarly journals An updated and unified earthquake catalog from 1787 to 2018 for seismic hazard assessment studies in Mexico

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Rashad Sawires ◽  
Miguel A. Santoyo ◽  
José A. Peláez ◽  
Raúl Daniel Corona Fernández
Keyword(s):  
Seismic Hazard ◽  
Hazard Assessment ◽  
Seismic Hazard Assessment ◽  
Large Earthquake ◽  
Seismic Source ◽  
Earthquake Catalog ◽  
Magnitude Conversion ◽  
Seismic Source Models ◽  
Source Models ◽  
Definition Of

Abstract Here we present a new updated and unified Poissonian earthquake catalog for Mexico. The details about the catalog compilation, the removal of duplicate events, unifying the magnitude scales, removal of dependent events through the declustering process and its completeness analysis are presented. Earthquake and focal mechanism data have been compiled from various local, regional and international sources. Large earthquake events (MW ≥ 6.5) have been carefully revised for their epicentral locations and magnitudes from trusted publications. Different magnitude-conversion relationships, compatible with available local and regional ones, has been established to obtain unified moment magnitude estimates for the whole catalog. Completeness periods for the declustered catalog were estimated for the definition of appropriate seismic source models for the whole territory. The final unified Poissonian earthquake catalog spans from 1787 to 2018, covering a spatial extent of 13° to 33°N and 91° to 117°W. This catalog is compatible with other published catalogs providing basis for new analysis related to seismicity, seismotectonics and seismic hazard assessment in Mexico.

Seismic magnitude conversion and its effect on seismic hazard analysis

2019 ◽  
Vol 23 (4) ◽  
pp. 623-647 ◽  
Author(s):  
P. Anbazhagan ◽  
A. Balakumar
Keyword(s):  
Seismic Hazard ◽  
Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Magnitude Conversion ◽  
Seismic Magnitude

Regional Earthquake Magnitude Conversion Relations for the Himalayan Seismic Belt

2020 ◽  
Vol 91 (6) ◽  
pp. 3195-3207
Author(s):  
Rajiv Kumar ◽  
Ram Bichar Singh Yadav ◽  
Silvia Castellaro
Keyword(s):  
Moment Tensor ◽  
Earthquake Magnitude ◽  
Seismic Belt ◽  
Centroid Moment Tensor ◽  
Moment Tensor Solution ◽  
Magnitude Conversion ◽  
Magnitude Scales ◽  
Regression Relations ◽  
Regional Earthquake ◽  
Earthquake Magnitude Conversion

Abstract We present regional earthquake magnitude conversion relations among different magnitude scales (Mw, Ms, mb, ML, and MD) for the Himalayan seismic belt developed from data of local, regional, and international seismological agencies (International Seismological Centre [ISC], National Earthquake Information Centre [NEIC], Global Centroid Moment Tensor Solution [CMT], International Data Centre [IDC], China Earthquake Administration [BJI], and National Centre for Seismology [NDI]). The intra- (within the same magnitude scale) and inter- (with different magnitude scales) magnitude regression relations have been established using the general orthogonal regression and orthogonal distance regression techniques. Results show that the intra-magnitude relations for Mw, Ms, and mb reported by the Global CMT, ISC, and NEIC exhibit 1:1 relationships, whereas ML reported by the IDC, BJI, and NDI deviates from this relationship. The IDC underestimates Ms and mb compared with the ISC, NEIC, and Global CMT; this may be due to different measurement procedures adopted by the IDC agency. The inter-magnitude relations are established between Mw,Global CMT and Ms, mb, and ML reported by the ISC, NEIC, IDC, and NDI, and compared with the previously developed regional and global regression relations. The duration (MD) and local (ML) magnitudes reported by NDI exhibit a 1:1 relationship. The derived magnitude regression relations are expected to support the homogenization of the earthquake catalogs and to improve seismic hazard assessment in this region.

The Magnitude Conversion Problem: Further Insights

2011 ◽  
Vol 101 (1) ◽  
pp. 379-384 ◽  
Author(s):  
R. Gutdeutsch ◽  
S. Castellaro ◽  
D. Kaiser
Keyword(s):  
Magnitude Conversion

Magnitude conversion to unified moment magnitude using orthogonal regression relation

2012 ◽  
Vol 50 ◽  
pp. 44-51 ◽  
Author(s):  
Ranjit Das ◽  
H.R. Wason ◽  
M.L. Sharma
Keyword(s):  
Moment Magnitude ◽  
Orthogonal Regression ◽  
Regression Relation ◽  
Magnitude Conversion

scholarly journals Magnitude conversion relations for very short distances: The Charlevoix, Quebec, Seismic Zone

2016 ◽  
Author(s):  
A L Bent ◽  
F Vadnais
Keyword(s):  
Seismic Zone ◽  
Magnitude Conversion

scholarly journals Production of a homogeneous seismic catalog based on machine learning for northeast Egypt

2021 ◽  
Vol 13 (1) ◽  
pp. 1084-1104
Author(s):  
Sayed S. R. Moustafa ◽  
Gad-Elkareem A. Mohamed ◽  
Mohamed Metwaly
Keyword(s):  
Machine Learning ◽  
Regression Analysis ◽  
Linear Regression ◽  
Hybrid Approach ◽  
Vertical Component ◽  
P Wave ◽  
Supervised Machine Learning ◽  
Magnitude Conversion ◽  
The Moment ◽  
Lower Magnitude

Abstract This research presents a new approach which addresses the conversion of earthquake magnitude as a supervised machine-learning problem through a multistage approach. First, the moment magnitude (M w) calculations were extended to lower magnitude earthquakes using the spectral P-wave analyses of the vertical component seismograms to improve the scaling relation of M w and the local magnitude (M L) of 138 earthquakes in northeastern Egypt. Second, using unsupervised clustering and regression analysis, we applied the k-means clustering technique to subdivide the mapped area into multiple seismic activity zones. This clustering phase created five spatially close seismic areas for training regression algorithms. Supervised regression analysis of each seismic area was simpler and more accurate. Conversion relations between M w and M L were calculated by linear regression, general orthogonal regression (GOR), and random sample consensus (RANSAC) regression techniques. RANSAC and GOR produced better results than linear regression, which provides evidence for the effects of outliers on regression accuracy. Moreover, the overall multistage hybrid approach produced substantial improvements in the measured-predicted dataset residuals when individual seismic zones rather than all datasets were considered. In 90% of the analyzed cases, M w values could be regarded as M L values within 0.2 magnitude units. Moreover, predicted magnitude conversion relations in the current study corresponded well to magnitude conversion relations in other seismogenic areas of Egypt.

Performance of Different Regression Procedures on the Magnitude Conversion Problem

2007 ◽  
Vol 97 (4) ◽  
pp. 1167-1175 ◽  
Author(s):  
S. Castellaro ◽  
P. Bormann
Keyword(s):  
Magnitude Conversion

Magnitude conversion problem for the Turkish earthquake data

2010 ◽  
Vol 55 (2) ◽  
pp. 333-352 ◽  
Author(s):  
Aykut Deniz ◽  
M. Semih Yucemen
Keyword(s):  
Magnitude Conversion ◽  
Earthquake Data
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