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Pattern recognition technique for prediction of strong earthquakes in the North Anatolian fault zone, Turkey

Başlık çevirisi mevcut değil.

  1. Tez No: 364434
  2. Yazar: ŞERİF BARIŞ
  3. Danışmanlar: PROF. DR. CEMİL GÜRBÜZ
  4. Tez Türü: Doktora
  5. Konular: Deprem Mühendisliği, Earthquake Engineering
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 1995
  8. Dil: İngilizce
  9. Üniversite: Boğaziçi Üniversitesi
  10. Enstitü: Kandilli Rasathanesi ve Deprem Araştırma Enstitüsü
  11. Ana Bilim Dalı: Deprem Mühendisliği Ana Bilim Dalı
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: 175

Özet

Bu

Özet (Çeviri)

A pattern recognition algorithm called the CN (California-Nevada) for intermediate- term earthquake prediction in three areas situated in the westernmost, the central, and easternmost portions of the NAFZ. One of them is the Marmara region and its vicinity (Region 1), which contain the western Anatolian graben complex and part of the Anatolian Trough. The NAFZ splays into three strands and extends to mainland Greece. The Marmara region and its vicinity are the most important area of Turkey from economical and sociological points of view. Existence ofa seismic gap in a densely populated region of Turkey, attempts have been made to collect data for predicting future earthquakes in this region. The second one (Region 2) is the central section of the NAFZ. Also, there is a probable seismic gap in this area (specifically between the longitudes of 33 °E and 35 °E). The third area is the Karliova triple junction and surrounding area (Region 3), where three active fault zones intersect and have produced many destructive earthquakes in the past. There are two unbroken segments of the NAFZ, (proposed as seismic gaps) located in the regions 1 and 3. Recently, a destructive earthquake occurred on March 13, 1992, causing about 650 deaths and at least 2000 injures. The epicenter of this earthquake and its aftershocks are located around the western boundary of the proposed seismic gap in Region 3. The 13.3.1992 earthquake is not considered as the potentially greatest earthquake that can take place in Erzincan according to data from strain accumulation of the segment of the NAFZ to the east of Erzincan, and the OvacIk Fault has not ruptured for more than 1000 years. These regions were selected because many destructive earthquakes have occurred in these areas, which have high seismotectonic activity relative to their surroundings according to information from tectonical and seismological studies. In the present work we investigate the possibility of the application of CN algorithm for intermediate-term prediction of earthquakes with magnitude Mo=6.8 in region 1 and 3; Mo=5.2 in Region 2 for the period of 1934-64 and 1964-1994. The first period used only for testing and learning the seismicity patterns of the NAFZ. The CN algorithm has diagnosed the Time of Increased Probability of a strong earthquake (TIP) which preceded 5 out of 6 earthquakes with Mo=6.8 in Region 1, lout of 5 strong earthquakes with 110=5.2 in Region 2 and 4 out of 6 strong earthquakes with 110=6.8 in Region 3. The TIPs occupied 40% of the total time for Region 1, 27% for Region 2 and 36% for Region 3 for the second period. The eN algorithm shows current alarms for regions 1 and 3. The stability of the results depends on using different catalogues and time periods of the algorithm considered. I believe that all experiments demonstrate that the results of the TIP's diagnosis are stable for Region 1 and Region 3. The retrospective analysis of seismic data in the Marmara region and the Karliova triple junction show that the eN algorithm can be applied without any readaptation for these regions of Turkey. The results of TIP diagnosis by the eN algorithm for both regions coincide well with the result of a worldwide test of the eN algorithm. The total diagnosis time of TIPs is slightly higher than the actual ones. This algorithm has given unsuccessful results for the prediction of earthquakes with magnitude 5 or higher in the middle part ofthe NAFZ and Marmara region. These results can be explained by incompleteness of the earthquakes recorded in the region and existence of the different seismicity patterns in the central part ofthe NAFZ. Application of the algorithm with standard parameters is not possible for this region and given magnitude range. Therefore, the eN algorithm must be reconsidered for adaptation and adjustment and database must be also updated. The reliability of TIP diagnostics needs further monitoring of earthquake flow, i.e. by forward prediction. The analysis carried out in this work should be considered only as the basis for such testing. The results of eN were stable when I changed the threshold value for the definition of strong earthquakes and made a slight change in the regionalization. I recommend that the algorithm should be applied continuously with monthly catalogues for the purpose of monitoring existing current alarms in the regions and for short-term prediction of strong shocks in Turkey compared with the observation results obtained from multidisciplinary earthquake prediction studies in iznik -Mekece area.

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