Vol 55, No 3 (2019)

Often, a sharp increase or decrease in seismic wave level cannot be explained by existing seismic microzoning methods, especially since at magnitudes of 8–9, the amplitude does not increase on loose soils; on the contrary, they are somewhat lower than on rocky soils. At high amplitudes, seismic wave attenuation is no longer determined by the properties of the medium, but by the vibration level. The absorption decrement sharply increases, and the resonance properties of soils subside until they disappear completely. Moreover, the near zone is located above the focal zone, where not only absorption but also energy release takes place. The article discusses three processes that can explain anomalous variations in seismic wave amplitudes. First, the amplitude may increase with distance from the fault, since the fault may occur not in the area of maximum deformation, but at the area of minimum strength of the medium, i.e., in the area of a previously formed fault. However, such a model poorly agrees with the fact that zones of anomalous amplitudes are often arranged symmetrically with respect to the fault. The second reason is that, naturally, the fault plane can contain no energy; the fault only allows the release of accumulated deformation energy in the surrounding medium. Consequently, the energy of seismic waves propagating from the fault surface will increase until elements of the medium release more energy than they absorb. This model is confirmed by empirical data. Acceleration amplitudes during earthquakes of different magnitudes scale well with a shift along the distance axis and not along the amplitude axis, as is commonly believed. Many researchers have shown that, based on empirical data, the maximum level of acceleration in the focal region does not depend on magnitude, but is determined by the type of movement along the fault. It has been shown empirically that the level of acceleration at magnitudes of 9–11 is the same. Seismic intensity above 9 is no longer determined by the acceleration amplitude, but by residual deformations, i.e., changes in the relief. The two described processes do not explain the phenomenon of alternating zones of increasing and decreasing amplitude under the same soil conditions observed in earthquake focal areas. The authors propose an idea for discussion that explains all of the above phenomena: the occurrence of standing waves in the focal region. The article presents information on the occurrence of anomalous amplitude variations, which can be explained by the theory of standing waves. Zones of anomalous increase and decrease in amplitudes can be interpreted as zones of nodes and antinodes of standing waves. Empirical equations are proposed for distances at which zones of nodes and antinodes may appear.

When compiling historical earthquake catalogs, the main problem is to validate the reliability of information to exclude false reports. Detailed descriptions from reliable sources contribute to more precise intensity assessment. Additionally, in low-active territories, very important problem of identifying the nature of the event has to be solved. Earthquakes generated by tectonic or other activity (such as landslides or karst collapses) may have similar descriptions. Recently, cryoseisms have also been considered a possible source of the ground surface shaking. Seismic events in Belarus reported based on noninstrumental data and having fundamentally different interpretations in different publications are studied. The analysis is based on original information from primary sources. It is shown that two out of four seismic events are cryoseisms, while the other two are not related to the territory of Belorussia.

The study focuses on improving the methodology and technology of detailed seismic zoning of the Sakhalin region and adjacent areas. A new regional GMPE (ground motion prediction equation) model derived from instrumental data of accelerometer and seismometer networks are considered, as well as imported new-generation advanced (NGA 2) models. The results of probabilistic seismic hazard analysis (PSHA) for Yuzhno-Sakhalinsk has made it possible to compare the hazard curves of physical parameters produced by different attenuation models. The advantages and disadvantages of the regional GMPE model are discussed based on this comparison. Practical recommendations are given.

To predict the effects of strong earthquakes, it is important to know the soil characteristics. The accepted methods for such assessment ignore the fact that soils properties can vary greatly throughout the year. This is apparently due to the lack of data required for such consideration. In this paper, based on an analysis of long-term monitoring data by vertical electric sounding (VES) in a stationary array with a large number of spacing, we analyze seasonal variations in specific resistivity at different near-surface depths of a section in the area of the Peter the Great Range in Tajikistan. Based on long-term precision daily measurement data, a horizontally four-layered model of the geoelectric section was constructed. The amplitude of seasonal variations in the specific resistivity in each layer was estimated as the ratio of the standard deviation of the seasonal variation to the mean interannual specific resistivity. In the upper part of the section (depth 0–1.5 m), the amplitude of the seasonal variation reaches 20%, and its shape agrees well with the seasonal variation of the apparent resistivity at small spacings. In the second (depth 1.5–10 m) and third (depth 10–66 m) layers, the amplitude of the seasonal wave decreases rapidly, being less than 1% in the third layer. In the fourth layer (depth from 66 m or more), this amplitude again increases, reaching 2%. The difference between the maximum and minimum values of the seasonal wave (i.e., its range) reaches 7%. One possible explanation for such a high amplitude of seasonal variations in specific resistivity at depths of hundreds of meters is the presence of a deep aeration zone with annual regulation of the level and salinity of groundwater. The results should be taken into account in exploration geophysics, in engineering surveys, and in accounting for soil properties when predicting the possible consequences of strong seismic impacts.

The paper describes the operating principle of piezoelectric accelerometers and methods for determining their conversion factor in the time and frequency domains; the methods involve comparing simultaneous recordings of an accelerometer, a displacement sensor, a velocimeter, and a calibration shaker table. The frequency band and conversion factor of the accelerometer are determined. It is shown that the experimental and theoretical frequency responses of accelerometers agree well with each other within the frequency range from 1 to 10 Hz. It is found that accelerometers are of little use for quickly and accurately measuring seismic vibrations. It is found that velocimeter records can be efficiently used to simulate accelerograms.

The low-frequency deconvolution method makes it possible to convert digital records of electrodynamic seismometers to records of virtual sensors of a similar type, but with a lower natural frequency. The procedure requires only knowledge of the sensor parameters, which can be found from its technical description or obtained by calibration. Deconvolution in the time domain requires attention in choosing a numerical integration method, since use of the simplest methods leads to signal distortion. This is especially noticeable when the sampling rate of the original record is close to a geophone’s natural frequency. A universal approach is presented: realization of a low-frequency deconvolution algorithm in the frequency domain. Testing has shown good accuracy both in synthetic tests and for real seismological records, which were used to demonstrate reconstruction of the low-frequency component of a seismic geophone signal. The results are mainly relevant for problems that use a low sampling rate of recording, and they place high demands on the metrological characteristics of the recording equipment (e.g., local and regional seismicity monitoring).