Analysis of precursory seismicity patterns in Zagros (Iran) by CN algorithm

Majid MAYBODIAN; Mehdi ZARE; Hosseyn HAMZEHLOO

Makale detayları

Analysis of precursory seismicity patterns in Zagros (Iran) by CN algorithm

Yazarlar:

Majid MAYBODIAN | Mehdi ZARE | Hosseyn HAMZEHLOO

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Earth Sciences 2014 Vol.23 Issue 1, pp.91-99

Belge Tipi:

Makale

Yayın Tarihi:

5/2014

Belge Dili:

Türkçe

Document ID (Org No.):

2000731665

Sıklık:

İki Aylık

eISSN:

1303-619X

pISSN:

1300-0985

Özet:

 

This study illustrates the application of the CN algorithm for the analysis of precursory seismicity patterns in the Zagros region (Iran), an area characterized by a complex seismotectonic setting and by remarkable seismic activity. CN is a formally defined and widely tested algorithm for intermediate-term middle-range earthquake prediction, based on the analysis of routinely compiled earthquake catalogs. To allow its application, the global and regional catalogs available for the territory of Iran have been analyzed so as to compile a data set sufficiently complete and homogeneous over a time span of about 3 decades, as required for CN application. A number of tests have been performed with respect to changes in the input catalogs, assuming different magnitude completeness levels as well as considering different magnitude thresholds for the selection of target earthquakes. Different variants of the regionalization have been outlined according to the seismotectonic model, and it was concluded that precursory seismicity patterns for the largest events need to be researched in the whole Zagros tectonic domain. Accordingly, an experiment was set up aimed at validation of intermediate-term middle-range prediction of earthquakes with magnitude M >= 6.0 in the Zagros region. Starting in March 2012, CN prediction results have been routinely updated based on the events with M >= Mc = 4.0 as they are reported in the International Seismological Centre catalog.

 

This study illustrates the application of the CN algorithm for the analysis of precursory seismicity patterns in the Zagros region (Iran), an area characterized by a complex seismotectonic setting and by remarkable seismic activity. CN is a formally defined and widely tested algorithm for intermediate-term middle-range earthquake prediction, based on the analysis of routinely compiled earthquake catalogs. To allow its application, the global and regional catalogs available for the territory of Iran have been analyzed so as to compile a data set sufficiently complete and homogeneous over a time span of about 3 decades, as required for CN application. A number of tests have been performed with respect to changes in the input catalogs, assuming different magnitude completeness levels as well as considering different magnitude thresholds for the selection of target earthquakes. Different variants of the regionalization have been outlined according to the seismotectonic model, and it was concluded that precursory seismicity patterns for the largest events need to be researched in the whole Zagros tectonic domain. Accordingly, an experiment was set up aimed at validation of intermediate-term middle-range prediction of earthquakes with magnitude M >= 6.0 in the Zagros region. Starting in March 2012, CN prediction results have been routinely updated based on the events with M >= Mc = 4.0 as they are reported in the International Seismological Centre catalog.

Makale detayları

Analysis of precursory seismicity patterns in Zagros (Iran) by CN algorithm

Yazarlar: Majid MAYBODIAN | Mehdi ZARE | Hosseyn HAMZEHLOO

Yayıncı: TUBITAK

Dergi: Turkish Journal of Earth Sciences 2014 Vol.23 Issue 1, pp.91-99

Belge Tipi: Makale

Yayın Tarihi: 5/2014

Belge Dili: Türkçe

Document ID (Org No.): 2000731665

Sıklık: İki Aylık

eISSN: 1303-619X

pISSN: 1300-0985

Sayı

Yazarlar:

Majid MAYBODIAN | Mehdi ZARE | Hosseyn HAMZEHLOO

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Earth Sciences 2014 Vol.23 Issue 1, pp.91-99

Belge Tipi:

Makale

Yayın Tarihi:

5/2014

Belge Dili:

Türkçe

Document ID (Org No.):

2000731665

Sıklık:

İki Aylık

eISSN:

1303-619X

pISSN:

1300-0985