Variability in the Statistical Properties of Continuous Seismic Records on a Network of Stations and Strong Earthquakes: A Case Study from the Kamchatka Peninsula, 2011–2021

A study of spatiotemporal variability and synchronization effects in continuous seismic records (seismic noise) on a network of 21 broadband seismic stations on the Kamchatka Peninsula was carried out in connection with the occurrence of strong earthquakes, М = 7.2–8.3. Data of 1‐min registrations of the vertical movements velocity Earth’s surface were used for constructing time series of daily values of the generalized Hurst exponent α*, singularity spectrum support width Δα, wavelet‐based spectral exponent β, and minimum normalized entropy of squared orthogonal wavelet coefficients En for all stations during the observation period 2011–2021. Averaged maps and time‐frequency diagrams of the spectral measure of four noise parameters’ coherent behavior were constructed using data from the entire network of stations and by groups of stations taking into account network configuration, volcanic activity and coastal sea waves. Based on the distribution maps of noise parameters, it was found that strong earthquakes arose near extensive areas of the minimum values of α*, Δα, β, and the En maximum values advance manifestation during several years. The time‐frequency diagrams revealed increased amplitudes of the spectral measure of the coherent behavior of the 4‐dimensional time series (synchronization effects) before three earthquakes with Мw = 7.5–8.3 over months to about one year according to observations from the entire network of stations, as well as according to data obtained at groups of continental and non‐volcanic stations. A less‐pronounced manifestation of coherence effects diagrams plotted from data obtained at coastal and volcanic groups of stations and is apparently associated with the noisiness in seismic records caused by coastal waves and signals of modern volcanic activity. The considered synchronization effects correspond to the author’s conceptual model of seismic noise behavior in preparation of strong earthquakes and data from other regions and can also be useful for medium‐term estimates of the place and time of seismic events with Mw ≥ 7.5 in the Kamchatka

Cross-Correlation Earthquake Precursors in the Hydrogeochemical and Geoacoustic Signals for the Kamchatka Peninsula

We propose a new type of earthquake precursor based on the analysis of correlation dynamics between geophysical signals of different nature. The precursor is found using a two-parameter cross-correlation function introduced within the framework of flicker-noise spectroscopy, a general statistical physics approach to the analysis of time series. We consider an example of cross-correlation analysis for water salinity time series, an integral characteristic of the chemical composition of groundwater, and geoacoustic emissions recorded at the G-1 borehole on the Kamchatka peninsula in the time frame from 2001 to 2003, which is characterized by a sequence of three groups of significant seismic events. We found that cross-correlation precursors took place 27, 31, and 35 days ahead of the strongest earthquakes for each group of seismic events, respectively. At the same time, precursory anomalies in the signals themselves were observed only in the geoacoustic emissions for one group of earthquakes.Comment: 21 pages, 5 figures, 1 table; to be published in "Acta Geophysica". arXiv admin note: substantial text overlap with arXiv:1101.147

Multidimensional Wavelet Analysis of Time Series of Electrotelluric Observations in Kamchatka

The paper presents results of joint multidimensional wavelet analysis of three series of variations in the electrotelluric potential observed at the Verkhnyaya Paratunka station in the Kamchatka Peninsula from October 1, 1996, to June 23, 2001. The analysis was made in order to identify common components in the signals analyzed and compare them with the seismic regime and variations in meteorological parameters. The analysis was based on the method of robust wavelet-aggregated signals, developed by one of the authors for monitoring problems. The average prognostic efficiency of the inferred anomalies is estimated. The analysis revealed the effect of frequency migration of the collectiveness measure peak in the behavior of the study series toward higher frequencies; this effect took place throughout the observation interval. Recently, specific features of this type in the behavior of geophysical characteristics have more often been regarded as a basically new class of strong earthquake precursors

Statistical Analysis of Precision Water Level Data from Observations in a Seismoactive Region: Case Study of the YuZ-5 Well, Kamchatka

A new method is presented for statistical analysis of long-term time series of water level observations aimed at distinguishing short-term disturbances; observation data from the YuZ-5 well, located in the Petropavlovsk Geodynamic Test Area, eastern Kamchatka, are considered. These data (from July 27, 2012, to February 1, 2018) are remarkable for their degree of detail: the sampling rate of the water level and atmospheric pressure measurements was 5 min and the sensitivity (accuracy) was ±0.1 cm for water level recording and ±0.1 hPa for atmospheric pressure. Also, five strong earthquakes with Mw = 6.5–8.3 occurred at epicentral distances of de = 80–700 km during the observation period. A thorough analysis of the hydrodynamic regime of the observation well over a long period and the high quality of observation data, together with the data on strong seismic events, allow us to consider the possibility of using formalized statistical methods of water level data processing for diagnostics of anomalous conditions. As a result of factor and cluster analysis applied to the sequence of multidimensional vectors of the statistical properties of water level time series in successive one-day-long time windows, after adaptive compensation for atmospheric pressure, four different statistically significant states of time series, replacing each other in time, are distinguished. Geophysical interpretation of the anomalous conditions of the water level time series (with a probability of 0.013) is carried out in comparison to strong earthquakes, technical conditions of observations, and seasonal features of the hydrodynamic regime in the observation well. It is shown that this method of water level data processing can detect short-term anomalies in the hydrogeodynamic regime of a well, significantly supplementing traditional processing of water level data aimed mostly at finding low-frequency trends in water level changes. This method can be applied in geophysical monitoring and prediction of earthquakes from online processing of water level data in wells