Regularities in the time variations of seismic parameters and their implications for prediction of strong earthquakes in Greece (original) (raw)
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Statistical Prediction of the Sequence of Large Earthquakes in Iran
International Journal of Engineering-Transactions B: …, 2011
The use of different probability distributions as described by the Exponential, Pareto, Lognormal, Rayleigh, and Gama probability functions applied to estimation the time of the next large earthquake (Ms≥6.0) in different seismotectonic provinces of Iran. This prediction is based on the information about past earthquake occurrences in the given region and the basic assumption that future seismic activity will follow the pattern of past activity by maximizing the conditional probability of earthquake occurrence. The estimated recurrence times and the error of estimation for different distributions have been computed for different provinces. Results indicated Exponential model seem to be better than other models in prediction of occurrence time of the next earthquake in different seismotectonic provinces.
Study of the Possibility of Predicting Earthquakes
International Journal of Geosciences, 9, 688-706., 2018
It is already well known that the "when, where and how strong" earthquake prediction problem cannot be solved by only analyzing the database from former earthquakes. A possible solution to this problem is proposed herein based on the analysis of the physicochemical processes as participants in earthquake preparation and on the characteristic rate of reflection of these processes on the Earth's surface. The proposed procedure includes monitoring of correlation of electromagnetic fields variations with tidal waves. This solution provides a way of selecting a complex of reliable earthquake precursors using the Inverse Problem Method for earthquakes which will occur in the region around the monitoring point (radial distance ≈ 700 km) in the next seven-day period [1].
EARTHQUAKE PREDICTION: A GLOBAL REVIEW AND LOCAL RESEARCH
2009
This article reviews natural pre-earthquake phenomena such as gravity variations, radon emanation, anomalous electric field and changes in meteorological parameters like temperature and relative humidity. The concept of Earthquake Preparation Zone which is the first sign of an imminent earthquake is described. According to this concept all the ground based pre-earthquake signals are generated all over this zone. The size of this zone is dependent upon the size of the earthquake under preparation and may have a radius of more than 300 km for an earthquake of magnitude 6. Furthermore, use of dedicated satellites to monitor earthquake precursors from space has been presented. In addition to ground based research, the countries involved in space based research on earthquake prediction include France, Russia, Italy, Mexico, Japan, the UK, Ukraine and the USA. A plan is also presented for co-locating a tele-metered network of continuous monitoring some ground based earthquake precursors with existing seismic stations in earthquake prone areas of northern Pakistan. The present global trends in this field are a source of effusive optimism for successful earthquake prediction to become a reality in the near future. As a matter of fact, recent results of global earthquake prediction research promise successful prediction in the near future of hitherto difficult parameters about earthquake prediction such as Where?, When? and How Strong? Section 6 of the paper also describes some research work in Earthquake Prediction/Forecasting carried out locally at the Center for Earthquake Studies. A sample result from the Statistical Method which gives intermediate term forecasting of earthquakes is given. A novel technique of recording gravity variations from distant earthquakes was started with the assistance of Azerbaijan. The results obtained thereof are also given.
Prediction of the occurrence of Related Strong Earthquakes in Italy
Pure and Applied Geophysics PAGEOPH, 1993
In the seismic flow it is often observed lhat a Strong Earthquake (SE), is 1'ullowed by Related Strong Earthquakes (RSEs), which occur near ihc epicentre of (he SE wilh origin time rather close to the origin time of the SE. The algorithm for the prediction of the occurrence of a RSE has been developed and applied for the first lime to the seismicity data of the California-Nevada region and has been successfully tested in several regions of the World, the statistical significance of the result being 97%. So far it has been possible to make five successful forward predictions, with no false alarms or failures to predict.
Short Term and Short Range Seismicity Patterns in Different Seismic Areas of the World
1999
The aim of this work is to quantitatively set up a simple hypothesis for occurrence of earthquakes conditioned by prior events, on the basis of a previously existing model and the use of recent instrumental observations. A simple procedure is presented in order to determine the conditional probability of pairs of events (foreshock-mainshock, mainshock-aftershock) with short time and space separation. The first event of a pair should not be an aftershock, i.e., it must not be related to a stronger previous event. The Italian earthquake catalog of the Istituto Nazionale di Geofisica (ING) (1975-1995, M 3.4), the earthquake catalog of the Japan Meteorological Agency (JMA) (1983-1994, M 3.0) and that of the National Observatory of Athens (NOA) (1982-1994, M 3.8) were analyzed. The number of observed pairs depends on several parameters: the size of the space-time quiescence volume defining nonaftershocks, the inter event time, the minimum magnitude of the two events, and the spatial dimension of the alarm volume after the first event. The Akaike information criterion has been adopted to assess the optimum set of space-time parameters used in the definition of the pairs, assuming that the occurrence rate of subsequent events may be modeled by two Poisson processes with different rates: the higher rate refers to the space-time volume defined by the alarms and the lower one simulates earthquakes that occur in the nonalarm space-time volume. On the basis of the tests carried out on the seismic catalog of Italy, the occurrence rate of M 3.8 earthquakes followed by a M 3.8 mainshock within 10 km and 10 days (validity) is 0.459. We have observed, for all three catalogs, that the occurrence rate density λ for the second event of a couple (mainshock or aftershock) of magnitude M 2 subsequent to a nonaftershock of magnitude M 1 in the time range T can be modeled by the following relationship: λ(T , M 2) = 10 a +b(M 1 −M 2) with b varying from 0.74 (Japan) to 1.09 (Greece). The decrease of the occurrence rate in time for a mainshock after a foreshock or for large aftershocks after a mainshock, for all three databases, obeys the Omori's law with p changing from 0.94 (Italy) to 2.0 (Greece).
2021
A large earthquake is still considered to be a natural catastrophic event that not only causes immeasurably great material damage to seismically active regions and countries but also takes the lives of thousands of people.That is why the assessment of seismic risk is one of the most important issues, and research in this area is now in one of the first places in all countries. However, despite the high level of research, the practical results of the seismic risk do not provide great protection guarantees from disaster. Based on recent studies of earthquake prediction possibility, the offered article presents a completely different view on the possibilities of seismic risk assessing and reducing the accumulated tectonic stress in the large earthquake focus. Discussion Since, on the base of modern satellite and terrestrial observations, it has become possible to create a model of the generation of electromagnetic emissions detected prior to earthquakes and accordingly, analytically to...
Intermediate term earthquake prediction in the area of Greece: Application of the algorithm M8
Pure and Applied Geophysics PAGEOPH, 1990
The 3 strongest earthquakes, M -> 7.0, which have occurred since 1973 in the area of Greece were preceded by a specific increase of the earthquake activity in the lower magnitude range. This activation is depicted by algorithm M8. This algorithm of intermediate term earthquake prediction was originally designed for diagnosis by Times of Increased Probability (TIPs) of the strongest earthquake, M -> 8.0 worldwide . At present the algorithm is retrospectively tested for smaller magnitudes in different seismic regions KOSSOBOKOV, 1986, 1988). A TIP refers to a time period of 5 years and an area whose linear size is proportional and several times larger than that of the incipient earthquake source. Altogether the TIPs diagnosed by the algorithm M8 in the area of Greece occupy less than 20% and the Times of Expectation (TEs) about 10% of the total space-time domain considered. Also there is a current TIP for the southeastern Aegean sea and 1988-1992. It may specify the long-term prediction given in WYss and BAER (1981a, b).
Statistical and Non-linear Dynamics Methods of Earthquake Forecast: Application in the Caucasus
2020
In 20th century, more than 10 strong earthquakes (EQs) of magnitudes 6,7 hit South Caucasus, causing thousands of casualties and gross economic losses. Thus, strong-EQ forecast is an actual problem for the region. In this direction, we developed a physical percolation model of fracture, which considers the final failure of solid as a termination of the prolonged process of destruction: generation and clustering of micro-cracks, till appearance-at some critical concentration-of the infinite cluster, marking the final failure. Percolation provides a model of preparation of an individual strong event (slip or EQ). The natural seismic process contains many such events: the appropriate model is a non-linear stick-slip model, which is a particular case of the general theory of the integrate-and-fire process. Non-linearity of the seismic process is in contradiction with a memoryless Poissonian approach to seismic hazard. The complexity theory offers a chance to improve strong EQs' forecast using analysis of hidden (non-linear) patterns in seismic time series, such as attractors in the phase space plot. For a regional forecast, we applied the Bayesian approach to assess the conditional probability expected in the next 5 years of strong EQs of magnitudes five and more. Later on, in addition to Bayesian probability assessment, we applied to seismic time series the pattern recognition technique, based on the assessment of the empirical risk function [generalized portrait (GP) method]: nowadays, this approach is known as the support vector machine (SVM) technique. The preliminary analysis shows that application of the GP technique allows predicting retrospectively 80% of M5 events in Caucasus. Besides long-and middle-term forecast studies, intensive work is under way on the short-term (next-day) EQ prediction also. Here, we present the results of multiparametrical (hydrodynamic and magnetic) monitoring carried out on the territory of Georgia. In order to assess the reliability of the precursors, we used the machine learning approach, namely, the algorithm of deep learning ADAM, which optimizes target function by a combination of optimization algorithm designed for neural networks and a method of stochastic gradient descent with momentum. Finally, we used the method of receiver operating characteristics (ROC) to assess the forecast quality of this binary classifier system. We show that the true positive rate statistical measure is preferable for the EQ forecast.
2011
Introduction of new sensitive broadband seismographs, new dense seismic networks and new methods of signal processing lead to the breakthrough in triggering and synchronization studies and formation of a new important domain of earthquake seismology, related to dynamic triggering of local seismicity by wave trains from remote strong earthquakes. In the paper are considered the peculiarities of triggered seismicity in Georgia on the example of 11.03.2011great Tohoku earthquake in Japan. (M=9,) and moderated earthquake in East Greece (09. 03.2011).
Testing the Earthquake Early-Warning Parameter Correlations in the Southern Iberian Peninsula
Pure and Applied Geophysics, 2015
The south of the Iberian Peninsula is of especial interest for the application of Earthquake Early Warning System (EEWS) technologies due to the past occurrence of damaging earthquakes such as the 1755 Lisbon earthquake. However, there are several critical issues that need to be addressed in order to develop an EEWS in this area. The first is the magnitude scale inhomogeneity of the available catalogues. A second is that most of the available broad-band seismograms for this area correspond to earthquakes with magnitudes less than 6.0, recorded at distances greater than 100 km, and sometimes with a low signal-to-noise ratio. And third, the occurrence of large earthquakes in this area means that the standard EEWS time window normally used needs to be tested in order to check whether it is long enough. Our paper describes the results of homogenizing the catalogue magnitudes by using empirical relationships to obtain the moment magnitude M w. A criterion based on a threshold value for the signal-to-noise ratio is applied in order to avoid noise-contaminated seismogram data. An important part of the study is a check of whether the correlations previously obtained for south Iberia are valid for other neighbouring areas such as Algeria, and for larger earthquakes. Finally, since recent studies have shown that the larger the earthquake the longer the time window needed to properly estimate the magnitude, the window was increased progressively from 0 to 20 s in order to study the behaviour of the EEWS parameters for the largest earthquakes in the database.