Historical Seismograms - Evidence from the AD 2000 Izu Islands ...

138 A. D. Gvishiani and Wilbur A. RinehartThe pattern recognition methods used for this problem and the results of its applicationswere described in many papers (see, for example, Gelfand, et al., 1976).The regions of strong earthquakes which were investigated by these methods are:Pacific Belt (M 2 8.0); Andes (M 2 7:); Kamchatka (M 2 7;); Pamir-Tienshen(M 2 6.5, M 2 7.0); Anatolia and Balkans (M 2 6.5, M 2 7.0); California(M 2 6.5); Apennines (M 2 6.0); Alps (M 2 5.0); and Pyrenees (M 2 5.0).Noninstrumental historical epicenters are not used in this process of patternrecognition. Thus, the catalogs of historical seismicity data represent independentinformation, which gives an opportunity to evaluate the reliability of the patternrecognition results. It is clear that if an object is recognized as a high seismicdanger, then the existence of an epicenter of a strong historical earthquake supportsthe reliability of the pattern recognition results. For example, on the Pacific coastof South America, as shown in Figure 7, the locations of the historical epicentersagree well with the result of the pattern recognition procedures. After the paperwith these results was published (Gabrielov, et al., 1982), two strong earthquakesoccurred in the Aades region. The first one, on December 12, 1979, on the border ofEcuador and Colombia, had a magnitude of 7.9 and a depth of 62 km. The secondone, the recent earthquake of March 4, 1985, which killed more than 100 people andcaused extensive damage, had its epicenter near Santiago, Chile, and a magnitudeof 7.75. In Figure 7, the locations of both earthquakes predicted by the patternrecognition results are shown.4. ConclusionThe recognition of zones of high seismicity is one of the many applications of theearthquake catalog data bases. For these applications, the advantages of comprehensivecollections of seismicity data in two major world centers is obvious. Thecreation of such collections is the goal of the joint NGDC-IPE project. We appealto the participants of this symposium to support this effort.REFERENCESGabrielov, A. M., A. D. Gvishiani, and M. P. Zhidkov (1982). Normalized morphostructuralzoning of the mountainous zones of the Andes, mathematical model of theearth’s structure, and forecasting of earthquakes (in Russian), Comput. Seism.(Moscow), 14, 38-56.Gelfand, I. M., Sh. I. Guberman, V. I. Keilis-Borok, L. KnopoR, F. Press, E. Ya. Ranzman,I. M. Rotwain, and A. M. Sadovsky (1976). Pattern recognition applied to earthquakeepicenters in California. J. Phys. Earth Planet. Interiors, 11, 227-283.Gvishiani, A. D., and V. A. Zheligovsky (in press). Logical scheme of the analyticalapproach to error control of geophysical data files, Solid Earth Series Rept., WorldData Center A (Boulder, CO).Rinehart, W. A., K. D. Woerner, and S. Godeaux (in press). Quality control in the NOAAdatabase, Solid Earth Series Rept., World Data Center A (Boulder, CO).Shebalin, P. (in press). Methods of computer integration of different earthquake catalogs,Solid Earth Series Rept., World Data Center A (Boulder, CO).