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Since 1966, China has been using apparent resistivity observation to forecast strong aftershocks of the Xingtai earthquake. Retrospective studies of subsequent strong earthquakes have shown that anomalies in apparent resistivity observation before earthquakes usually exhibit anisotropic characteristics. In addition to the anisotropic changes in apparent resistivity before earthquakes, factors such as subway operation near the observation area, metal pipeline networks, and changes in water levels have also been found to cause anisotropic changes. These factors are called environmental interference factors. Therefore, distinguishing between anisotropic changes before earthquakes and anisotropic changes caused by interference and eliminating the effects of interference is crucial for using apparent resistivity observations for forecasting. Taking the observation of Hefei seismic station in Anhui Province as an example, a model is constructed using the finite element method to try to establish a method for analyzing anisotropy in apparent resistivity before earthquakes, and the data from other provincial stations are used for verification. In the modeling process, the influence coefficient is a measure of the relationship between the variation in apparent resistivity and the changes in the medium of the measurement area. The following results are obtained by calculating the influence coefficient using the finite element method: the influence coefficient between the power supply electrode and the measuring electrode of the apparent resistivity observation is negative, and the rest are positive, and the distribution of the influence coefficient shows obvious symmetry, with the axis of symmetry being the line connecting the electrodes and its midline, and the absolute value of the influence coefficient is inversely proportional to the distance from the electrodes. In addition, according to the constructed finite element model, the amplitude of anisotropic changes caused by interference can be quantitatively calculated. Given that interference is ubiquitous in various regions of the world, this study can provide a reference for international earthquake forecasters to quantitatively remove environmental interference in anisotropy. Moreover, when building apparent resistivity stations in seismic areas for earthquake prediction, it is best to avoid areas with larger local influence coefficients to ensure that the anomalous data before the earthquake is true and reliable. [ABSTRACT FROM AUTHOR]

The Load/Unload Response Ratio (LURR) is a seismic prediction method based on the dynamic evolution of the stress-strain relationship of rocks. By adopting Benioff strain as the response indicator, an in-depth analysis was conducted on the LURR anomalies within 400 km of the epicenter and its surrounding areas before the Ms7.4 earthquake in Madoi, Qinghai Province, on 22 May 2021. The analysis revealed that the LURR value peaked 1 month before the earthquake and then declined within half a month, indicating that the rock medium in the seismic gestation area was approaching the end of its yielding phase. Further investigation using the Outgoing Longwave Radiation (OLR) data from the National Oceanic and Atmospheric Administration (NOAA) satellite was conducted to study the short-term and imminent anomalous evolution of ground longwave radiation values after the high values declined (from May 14 to 25). The results showed that, spatially, significant and continuous OLR anomalies were observed only in the northern area of the epicenter before the earthquake, and these anomalies exhibited a trend of expanding towards the epicenter. Temporally, the entire anomalous evolution process can be divided into six phases: initial warming, anomaly expansion, peak intensity, anomaly weakening, earthquake occurrence, and anomaly disappearance. To validate this finding, the spatiotemporal evolution characteristics of LURR and OLR within 300 km of the epicenter and its surrounding areas before the Ms6.4 earthquake in Yangbi, Yunnan Province, on 21 May 2021, were analyzed, and similar patterns were found. These results suggest that the high LURR value before its decline may mark the end of the rock medium's yielding phase, and OLR data can reflect, to some extent, the state of tectonic stress accumulation along active faults in a critical condition. A comprehensive study of the anomalous evolution characteristics of these two physical parameters before the earthquake is not only conducive to the continuity from long-term to short-term forecasts but also of great significance for more accurately assessing the trend of seismic activity. [ABSTRACT FROM AUTHOR]

Abstract: The magnetotelluric method (MT) consists in the observation of the surface natural variations of the electromagnetic field in a broad range of periods. The apparent resistivity is proportional to the modulus of the surface impedance, which is the tensorial relation between the horizontal components of the electric with the magnetic field. The subsurface resistivity distribution is obtained by inverting the apparent resistivity. The method of the detrended fluctuation analysis (DFA) has been applied to investigate the dynamics of apparent resistivity, which represents one of the most important scientific challenges in the studies devoted to the geophysical monitoring. Our results show that during July 2003 the time series representing variations of the apparent resistivity in the seismic area of Val d’Agri (southern Italy) are persistent at all the periods considered, tending to pure randomness with the increase of the period. Due to the relationship between the period and the depth, the observed variations are compatible with resistivity changes in the shallow layers. [Copyright &y& Elsevier]

The multiple segmenting method (MSM) has been applied to investigate the scaling behaviour in the Earth's apparent resistivity time series, measured in a seismic area of southern Italy. The study of apparent resistivity represents one of the most important scientific challenges in the studies devoted to the geophysical monitoring. Our results show that apparent resistivity is characterized by a persistent scaling behaviour at all the periods considered, with the scaling exponent tending approximately to 0.5. [ABSTRACT FROM AUTHOR]

Abstract: We analyzed the time fluctuations in the dynamics of geoelectrical data, recorded in a seismic area of southern Italy, by means of Fisher information measure, which is a powerful tool to investigate complex and nonstationary signals. The time evolution of the Fisher information measure calculated for our signal reveals some links with the earthquakes which occurred in the investigated area. [Copyright &y& Elsevier]

Abstract: We performed the Allan factor analysis on the 1986–2001 seismicity of the 80 seismogenetic zones in which the Italian territory has been subdivided by the Gruppo Nazionale Difesa dai Terremoti (GNDT), in order to investigate the presence of time-correlated behaviour. Power-law time-correlated areas have been identified analyzing the aftershock-depleted seismicity. Strong variability in the scaling properties has been found, suggesting that different dynamical mechanisms govern the seismic activity of the Italian seismogenetic zones. [Copyright &y& Elsevier]

The Flicker-Noise Spectroscopy (FNS) is an innovative method of extracting quantitative dynamical information from time series. The method represents the signal as sequences of irregularities (spikes, jumps, discontinuities of derivatives), derived on the basis of power spectra and structural functions of different orders. By means of this method we investigated one-year hourly geoelectrical data measured during 2002 in the station Giuliano, southern Italy, one of the most seismically active areas of Mediterranean region. The analysis performed seems to reveal the potential of the FNS to identify seismic precursors. [Copyright &y& Elsevier]

Presents a study that investigated the time dynamics of sequences of earthquakes that occurred ion different seismic zones in Italy. Methodology; Analysis of the temporal fluctuations of the seismic sequences; Comparison of the seismicity of the seismic zones.

We analyzed fluctuations in the time dynamics of nonstationary geoelectrical data, recorded in a seismic area of southern Italy, by means of the multifractal detrended fluctuation analysis (MF-DFA). The multifractal character of the signal depends mostly on the different long-range properties for small and large fluctuations. The time variation of indices, denoting the departure from monofractal behaviour, reveals an enhancement of the multifractality of the signal prior seismic occurrences. [Copyright &y& Elsevier]

In past and recent years geoelectrical fluctuations measured in seismic areas have been attributed to stress and strain changes, associated with earthquakes. The complex nature of this problem has suggested the development of monitoring networks based on multi-parametric remote stations, in order to perform geophysical monitoring for a long time period and with a high spatial resolution. In this work we present the geophysical monitoring network built up with remote stations able to jointly detect geoelectrical and seismometric parameters in the Basilicata region, a seismically active area of southern Apennine Chain (Italy), struck by strong earthquakes in the past (1857) and recently (1980). The seismological settings and a very low level of anthropic noise allow us to consider the investigated area as well suited to study possible correlations between tectonic activity and anomalous patterns in geoelectrical data. [Copyright &y& Elsevier]

Since many years a geophysical monitoring network has been operating in the Basilicata region (Italy) to measure jointly geoelectric (self-potential) and seismometric parameters. Recently, some tests have been performed to evaluate the best site to install a new continuous magnetotelluric station in this region. By means of a robust signal processing, we estimated the apparent resistivity and phase at the monitoring station Villa d''Agri, located in a seismic area of Southern Italy. The geological and seismological settings of this area suggest to study temporal fluctuations of the apparent resistivity in order to find correlations with the seismic activity of the area. [Copyright &y& Elsevier]

Correlations between geoelectrical extreme events and earthquakes have been investigated by means of the normalized wavelet cross-correlation function (NWCCF) and the cross-periodogram (CP). These methods allow to detect subtle forms of interdependence between sequences of events. In particular, we analyzed the correlation between the sequence of extreme events in geoelectrical signals, measured by the monitoring station Tito, located in a seismic area of southern Italy, and the series of earthquakes occurred in the same area during the 2001–2002. The NWCCF analysis highlights the presence of non-random cross-correlation between the series of geoelectrical anomalous values and the seismicity; the CP analysis reveals a co-fractal behavior between the self-potential extreme events and earthquakes, indicating that both sequences are subject to a common fractal modulation. [Copyright &y& Elsevier]

Multifractal investigation of the time fluctuations in the hourly time variability of geoelectrical signals, measured from January 2001 to September 2002 by four stations installed in Basilicata region (southern Italy) has been performed. Three stations (Giuliano, Marsico and Tito) are located in a seismic area and one (Laterza) in an aseismic area. The set of the multifractal parameters reveals the larger “complexity” of data measured in seismic areas respect to those recorded in aseismic areas, suggesting their potential in discriminating the two types of signals. [Copyright &y& Elsevier]