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Our observations indicate a characteristic pattern in the long-term variation of soil radon concentrations, which seems to be consistent with the expected variation of regional stress in relation to seismicity. However, it seems that the major changes in radon level begin before the rock rapture, i.e. before the earthquake occurs. These conclusions have emerged after long-term observations with continuous and thorough real-time gamma-radiation monitoring in the seismically active area of the Gulf of Corinth, Greece. The recordings acquired close to a hot spring were of very high quality, implying that the deep hydraulic flow can possibly play a key role in the pre-earthquake variation of radon level. We were able to observe outstanding examples of radon level variations before significant seismic events in the Gulf of Corinth that cannot be attributed to other external factors such as atmospheric phenomena.

We propose a new strategy to reveal the spatial‐temporal evolution of the earthquake rupture process from near‐regional data, without assuming a constant rupture velocity. The approach is based on a conjugate gradient method, for which we express analytically the required waveform‐misfit derivative with respect to slip on the fault. The derivative is given by back‐propagation of residual seismograms towards the source. A good initial source approximation is necessary, being obtained from hypocenter location and centroid‐moment tensor solution. The iterative approach then gradually reveals major characteristics of the source process. As an application, we investigate a line source model of a damaging Mw6.3 earthquake in Greece, revealing predominantly unilateral rupture propagation and two or three main slip patches, one of which being significantly delayed, indicating a temporary rupture arrest. The region of largest slip coincides with the region of least abundant aftershocks between hypocenter and centroid. The method has application potential for shakemaps, emergency response, and/or aftershock hazard assessment.

Patras is the third largest city in Greece and an ideal candidate for earthquake early warning (EEW) applications due to its high seismic hazard, its existing research infrastructure and the presence of critical structures such as the Rion-Antirion bridge. Patras is located a few hundred kilometres from the Hellenic Arc, where very strong and potentially damaging earthquakes occur. This distance is large enough to allow a few tens of seconds of warning time prior to significant shaking, provided earthquakes are timely detected by a dense seismic network. Within the framework of the EC-funded project REAKT, the Virtual Seismologist (VS) EEW software was installed at Patras Seismological Laboratory. Its initial performance evaluation is presented here. In general VS provides magnitudes similar to the official, manually revised ones. Given the current station density and network telemetry, the average time that VS needs to deliver the first magnitude estimate is rather large, of the order of tens of seconds and not yet satisfactory for routine operational use of EEW. Even so, the system is able to provide up to 10 s of warning time prior to S-wave arrivals for events occurring on the Hellenic Arc. Our results indicate that the seismic networks in Greece need enhancements for regional EEW, either by adding stations or by upgrading the hardware to reduce delays. The application of an EEW system in the area is promising and, once operational, capable of mitigating earthquake risk.

This second part of the study, deals with the evaluation of the earthquake hazard in Greece in terms of the response spectral acceleration and the elastic input energy equivalent velocity. Four sets of predictive equations were selected, two for each type of spectra. Probabilistic hazard maps were created by determining the seismic hazard at grid points covering the region of interest. The maps are presented for the dominant periods of 0.2 s and 1.0 s for each spectrum. Uniform hazard response spectra (UHRS) for six cities located in the regions of highest estimated hazard are also presented. The comparison with elastic design spectra proposed by the latest national building code, has shown that the UHRS values exceed the design values at almost all periods.

Seismic hazard assessment represents a basic tool for rational planning and designing in seismic prone areas. In the present study, a probabilistic seismic hazard assessment in terms of peak ground acceleration, peak ground velocity, Arias intensity and cumulative absolute velocity computed with a 0.05 g acceleration threshold, has been carried out for Greece. The output of the hazard computation produced probabilistic hazard maps for all the above parameters estimated for a fixed return period of 475 years. From these maps the estimated values are reported for 52 Greek municipalities. Additionally, we have obtained a set of probabilistic maps of engineering significance: a probabilistic macroseismic intensity map, depicting the Modified Mercalli Intensity scale obtained from the estimated peak ground velocity and a probabilistic seismic-landslide map based on a simplified conversion of the estimated Arias intensity and peak ground acceleration into Newmark's displacement.

This paper presents the development of a non-parametric forecast model based on artificial neural networks for the direct assessment of Arias Intensity corresponding to a historic earthquake using seismic intensity data. The neural models allow complex and nonlinear behaviour to be tracked. Application of this methodology on earthquakes with known instrumental data from Greece, showed that the artificial neural network forecast model have excellent data synthesis capability.

In this paper we suggest the use of diffusion-neural-networks, (neural networks with intrinsic fuzzy logic abilities) to assess the relationship between isoseismal area and earthquake magnitude for the region of Greece. It is of particular importance to study historical earthquakes for which we often have macroseismic information in the form of isoseisms but it is statistically incomplete to assess magnitudes from an isoseismal area or to train conventional artificial neural networks for magnitude estimation. Fuzzy relationships are developed and used to train a feed forward neural network with a back propagation algorithm to obtain the final relationships. Seismic intensity data from 24 earthquakes in Greece have been used. Special attention is being paid to the incompleteness and contradictory patterns in scanty historical earthquake records. The results show that the proposed processing model is very effective, better than applying classical artificial neural networks since the magnitude macroseismic intensity target function has a strong nonlinearity and in most cases the macroseismic datasets are very small.

Complex application domains involve difficult pattern classification problems. This paper introduces a model of MMI attenuation and its dependence on engineering ground motion parameters based on artificial neural networks (ANNs) and genetic algorithms (GAs). The ultimate goal of this investigation is to evaluate the target-region applicability of ground-motion attenuation relations developed for a host region based on training an ANN using the seismic patterns of the host region. This ANN learning is based on supervised learning using existing data from past earthquakes. The combination of these two learning procedures (that is, GA and ANN) allows us to introduce a new method for pattern recognition in the context of seismological applications. The performance of this new GA-ANN regression method has been evaluated using a Greek seismological database with satisfactory results.

In spite of the fact that the great majority of seismic tsunami is generated in ocean domains, smaller basins like the Ionian Sea sometimes experience this phenomenon. In this investigation, we study the tsunami hazard associated with the Ionian Sea fault system. A scenario-based method is used to provide an estimation of the tsunami hazard in this region for the first time. Realistic faulting parameters related to four probable seismic sources, with tsunami potential, are used to model expected coseismic deformation, which is translated directly to the water surface and used as an initial condition for the tsunami propagation. We calculate tsunami propagation snapshots and mareograms for the four seismic sources in order to estimate the expected values of tsunami maximum amplitudes and arrival times at eleven tourist resorts along the Ionian shorelines. The results indicate that, from the four examined sources, only one possesses a seismic threat causing wave amplitudes up to 4 m at some tourist resorts along the Ionian shoreline.

The present third part of the study, concerning the evaluation of earthquake hazard in Greece in terms of various ground motion parameters, deals with the deaggregation of the obtained results The seismic hazard maps presented for peak ground acceleration and spectral acceleration at 0.2 s and 1.0 s, with 10% probability of exceedance in 50 years, were deaggregated in order to quantify the dominant scenario. There are three basic components of each dominant scenario: earthquake magnitude (M), source-to-site distance (R) and epsilon (ε). We present deaggregation maps of mean and mode values of M-R-ε triplet showing the contribution to hazard over a dense grid.