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The M(w) 6.3, 2009 earthquake (L'Aquila, central Italy) was characterized by discontinuous surface rupture along the 19-km long NW-SE trending Paganica-San Demetrio fault system. The earthquake nucleated just below the town of L'Aquila at a depth of ca. 9 km, rupturing mainly toward SE. Due to the high urbanization of the area and to centuries-long agricultural works, the surficial traces of this fault system are not clear everywhere. In order to provide more detailed and accurate information concerning the Paganica fault segment, four Electrical Resistivity Tomographies (ERT) were carried out around the Paganica village area. ERT results were supported by interpretation of aerial photos, morphotectonic investigation, geological field survey, borehole data and a paleoseismological trench. The electrical images showed the cumulated offset of the fault at depth and the existence of other splays parallel to the main strand which depict a staircase geometry of the fault in the Paganica area.

The Normalized Wavelet Cross-Correlation Function (NWCCF) was used to study correlations between the series of extreme events in self-potential data and earthquakes, both modelled as stochastic point processes. This method gives objective results, robust to the presence of nonstationarities that often affect observational time series. Furthermore, the NWCCF identifies the timescales involved in the cross-correlated behaviour between two point processes. In particular, we analyzed the cross-correlation between the sequence of extreme events in self-potential data measured at the monitoring station Tito, located in a seismic area of Southern Italy, and the series of earthquakes which occurred in the same area during 2001. To evaluate the influence of rain on the dynamics of geoelectrical variations, we applied the same approach between the selected extreme values and the rain data. We find that the anomalous geoelectrical values seem to cross-correlate with the rain at short and intermediate timescales (tau < 500 h), while they significantly cross-correlate only with earthquakes (M greater than or equal to 2.5) at long timescales (tau > 500 h).

In recent years there has been deep development in the use of techniques to analyse the statistical properties of point process time series. Furthermore many efforts have been made to establish robust methods to identify time clustering structures in the temporal distribution of seismic events. In this paper we intend to give a systematic review of some common used techniques to characterise the temporal properties of an earthquake sequence; we also present new methods, commonly used in other scientific fields, to reveal time clustering structures in a seismic sequence and to clearly identify non-poissonian behaviours at different time scales. An application of these methods has been performed on the seismicity of Irpinia-Basilicata area (Southern Italy).

We investigate the time dynamics of sequences of earthquakes occurred in three different seismic zones in Italy. All the series analyzed present 1/f(alpha) temporal fluctuations, shown by the power-law behaviour of several statistics (Fano Factor, Allan Factor and Count-based Periodogram), that allow to detect correlation properties in point processes.