Earthquake research at Parkfield, California, 1993 and beyond; report of the NEPEC working group to evaluate the Parkfield earthquake prediction experiment

Abstract. The local "when" for earthquake prediction is based on the connection between geomagnetic "quakes" and the next incoming minimum or maximum of tidal gravitational potential. The probability time window for the predicted earthquake is for the tidal minimum approximately ±1 day and for the maximum ±2 days. The preliminary statistic estimation on the basis of distribution of the time difference between occurred and predicted earthquakes for the period 2002-2003 for the Sofia region is given. The possibility for creating a local "when, where" earthquake research and prediction NETWORK is based on the accurate monitoring of the electromagnetic field with special space and time scales under, on and over the Earth's surface. The periodically upgraded information from seismic hazard maps and other standard geodetic information, as well as other precursory information, is essential.

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Seismicity alert probabilities at Parkfield, California, revisited

Bulletin of the Seismological Society of America ◽

10.1785/bssa0880010117 ◽

1998 ◽

Vol 88 (1) ◽

pp. 117-130

Author(s):

Andrew J. Michael ◽

Lucile M. Jones

Keyword(s):

Uniform Distribution ◽

Earthquake Prediction ◽

Confidence Level ◽

San Andreas Fault ◽

Strike Slip ◽

San Andreas ◽

Background Seismicity ◽

Parkfield Earthquake ◽

The U.S

Abstract For a decade, the U.S. Geological Survey has used the Parkfield Earthquake Prediction Experiment scenario document to estimate the probability that earthquakes observed on the San Andreas fault near Parkfield will turn out to be foreshocks followed by the expected magnitude 6 mainshocks. During this time, we have learned much about the seismogenic process at Parkfield, about the long-term probability of the Parkfield mainshock, and about the estimation of these types of probabilities. The probabilities for potential foreshocks at Parkfield are reexamined and revised in light of these advances. As part of this process, we have confirmed both the rate of foreshocks before strike-slip earthquakes in the San Andreas physiographic province and the uniform distribution of foreshocks with magnitude proposed by earlier studies. Compared to the earlier assessment, these new estimates of the long-term probability of the Parkfield mainshock are lower, our estimate of the rate of background seismicity is higher, and we find that the assumption that foreshocks at Parkfield occur in a unique way is not statistically significant at the 95% confidence level. While the exact numbers vary depending on the assumptions that are made, the new alert probabilities are lower than previously estimated. Considering the various assumptions and the statistical uncertainties in the input parameters, we also compute a plausible range for the probabilities. The range is large, partly due to the extra knowledge that exists for the Parkfield segment, making us question the usefulness of these numbers.

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Introduction to Professor Usami's Review in 1974

Journal of Disaster Research ◽

10.20965/jdr.2006.p0415 ◽

2006 ◽

Vol 1 (3) ◽

pp. 415-415

Author(s):

Kazuki Koketsu ◽

Keyword(s):

Earthquake Prediction ◽

Early Stage ◽

Strong Motion ◽

Earthquake Forecasting ◽

Professor Emeritus ◽

Suruga Bay ◽

Kanto Earthquake ◽

Earthquake Prediction Research ◽

Earthquake Research ◽

Short Term Prediction

Tatsuo Usami, now professor emeritus at the University of Tokyo, published a paper entitled “Earthquake Studies and the Earthquake Prediction System in Japan” in the March 1974 issue of Technocrat. I was impressed by Professor Usami’s comprehensive review and healthy criticism of earthquake prediction in Japan, which appears fresh even today. He gave an overview of the 1923 Kanto earthquake and Program 1 to 2 of the earthquake prediction project in Japan. The motivation and research for the project in its early stage are well summarized in the paper. The Tokai earthquake hypothesis [1] was proposed during Program 3, so the budget for the project at national universities was approximately tripled in Program 4 and increased to about 12 billion yen in Program 7 (Table 1). The 1995 Kobe (Hyogo-ken Nanbu) earthquake occurred during Program 7 killing 6,434 people and completely destroying 104,906 houses [2]. Since this unexpected earthquake was as destructive as the 1923 Kanto earthquake, the earthquake prediction project was reformed in New Program 1 (Table 1). The Headquarters for Earthquake Research Promotion was established, moving emphasis from empirical short-term prediction to long-term earthquake forecasting and prediction of strong ground motion [3]. Dr. Hiroe Miyake and I reviewed this situation in a preceding article [4], taking over the mission of writing a recent history of Japanese seismology from Professor Usami's paper. References: [1] K. Ishibashi, “Did the rupture zone of the 1707 Hoei earthquake not extend to deep Suruga Bay?,” Rep. Subcomm. Tokai Distr., Coord. Comm. Earthq. Predict., Geogr. Surv. Inst., pp. 69-78, 1977 (in Japanese). [2] K. Koketsu, “Chronological table of damaging earthquakes in Japan,” in Chronological Scientific Tables 2007, Maruzen, pp.698-729, 2006 (in Japanese). [3] N. Hirata, “Past, current and future of Japanese national program for earthquake prediction research,” Earth Planets and Space, 56, pp. xliii-l, 2004. [4] K. Koketsu and H. Miyake, “Earthquake Observation and Strong Motion Seismology in Japan from 1975 to 2005,” Journal of Disaster Research, Vol.1, No.3, pp. 407-414, 2006. Kazuki Koketsu Professor, University of Tokyo

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Exploring the knowledge domain of earthquake prediction based on bibliometric analysis and text mining

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-212442 ◽

2021 ◽

pp. 1-17

Author(s):

Xiaorong He

Keyword(s):

Text Mining ◽

Bibliometric Analysis ◽

Earthquake Prediction ◽

Citation Index ◽

Knowledge Domain ◽

Scientific Publications ◽

Main Research ◽

Detection Techniques ◽

Subject Categories ◽

Earthquake Research

Earthquake prediction is one of the important themes of earthquake research, and it is also a very difficult scientific problem in the world. In this study, a bibliometric analysis is conducted on the scientific publications about earthquake prediction indexed in SCIE (Science Citation Index Expanded) and SSCI (Social Sciences Citation Index) databases during the past two decades (1998–2017). The subject categories, annual and journal distributions, leading countries/regions and institutions are investigated in this field. The main research topics are identified through text mining method. The research trends are explored by keyword co-occurrence analysis and bursting keywords detection techniques. The results of this study are helpful for scholars in this field to find the knowledge structure and important participants. It is also helpful for scholars to seize the current research hotspots and future development trends in this field.

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