In this work we analyse the hourly geoelectrical time series recorded by means of three stations located in a seismically active area of Southern Apennine Chain (Italy): Tito station (January 1992 - December 1997), Tramutola station (January 1995 - December 1995) and Giuliano station (January 1996 - December 1997). The time dynamics of the geoelectrical time series was investigated to obtain information regarding: i) the stochastic or chaotic behaviour of the time series; ii) the presence of scaling laws in their power spectral density and the estimation of the power-law index; iii) the possible correlation between the temporal variation of the power-law index and the local seismic activity. Autoregressive models and the Lomb Periodogram method have been applied to get the most quantitative information about the time dynamics from geoelectrical signals. Firstly, the predictability of geoelectrical measurements has been investigated using autoregressive models. The procedure is based on two forecasting approaches: the global and the local autoregressive approximation. The comparison of the predictive skill of the two techniques is a strong test to discriminate between low-dimensional chaos and stochastic dynamics. Our findings suggest that the physical system governing the electrical phenomena in active seismic areas is characterized by a stochastic dynamics. In a second step we investigated the stochastic properties of the geoelectrical signals searching for scaling laws in the power spectral density, identifying for it a power-law P(f)proportional to 1/f(alpha), with the scaling exponent alpha being a typical fingerprint of fractional brownian processes. In this analysis we apply the Lomb Periodogram method, which allows to calculate the power spectral density for time series with missing data. Finally the possible correlation between the time fluctuations of power-law index and the local seismic sequences has been investigated. An interesting coseismic variation of the scaling exponent in power spectra of geoelectrical time series recorded at Tito station has been identified on April 3, 1996. During the same period significant anomalous patterns are indentified in geoelectrical time series measured at Giuliano and Tramutola stations.

On the time dynamics of geoelectrical signals recorded in a seismic area of Southern Apennine Chain (Italy)

Cuomo V;Lapenna V;Telesca L
2000

Abstract

In this work we analyse the hourly geoelectrical time series recorded by means of three stations located in a seismically active area of Southern Apennine Chain (Italy): Tito station (January 1992 - December 1997), Tramutola station (January 1995 - December 1995) and Giuliano station (January 1996 - December 1997). The time dynamics of the geoelectrical time series was investigated to obtain information regarding: i) the stochastic or chaotic behaviour of the time series; ii) the presence of scaling laws in their power spectral density and the estimation of the power-law index; iii) the possible correlation between the temporal variation of the power-law index and the local seismic activity. Autoregressive models and the Lomb Periodogram method have been applied to get the most quantitative information about the time dynamics from geoelectrical signals. Firstly, the predictability of geoelectrical measurements has been investigated using autoregressive models. The procedure is based on two forecasting approaches: the global and the local autoregressive approximation. The comparison of the predictive skill of the two techniques is a strong test to discriminate between low-dimensional chaos and stochastic dynamics. Our findings suggest that the physical system governing the electrical phenomena in active seismic areas is characterized by a stochastic dynamics. In a second step we investigated the stochastic properties of the geoelectrical signals searching for scaling laws in the power spectral density, identifying for it a power-law P(f)proportional to 1/f(alpha), with the scaling exponent alpha being a typical fingerprint of fractional brownian processes. In this analysis we apply the Lomb Periodogram method, which allows to calculate the power spectral density for time series with missing data. Finally the possible correlation between the time fluctuations of power-law index and the local seismic sequences has been investigated. An interesting coseismic variation of the scaling exponent in power spectra of geoelectrical time series recorded at Tito station has been identified on April 3, 1996. During the same period significant anomalous patterns are indentified in geoelectrical time series measured at Giuliano and Tramutola stations.
2000
EARTHQUAKE PREDICTION; SERIES; CHAOS; RANDOMNESS
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/2762
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