Short-term Precursors Research Articles

Critical analysis of the ULF power depression as a possible Tohoku earthquake precursor

Among electromagnetic methods of short-term earthquake prediction, an approach is being actively developed based on the phenomenon of magnetic ultra-low-frequency (ULF) power depression occurring a few days before an earthquake. In particular, a nighttime geomagnetic power depression in the band 0.03–0.05 Hz was observed approximately 5 days before the catastrophic Tohoku 2011 earthquake. To verify the reliability of this method, we performed an extended analysis using data from magnetometer arrays JMA, MAGDAS, PWING, and INTERMAGNET. The selected stations included sites close to the epicenter (<300 km) and remote points (∼10000 km). The band-integrated spectral power of nighttime magnetic noise decreased significantly from March 6–9, several days before the earthquake. However, such variations occur simultaneously not only at nearby stations but also at distant stations. During this event, the ULF power depression was caused by low global geomagnetic activity, as evidenced by the planetary index SME. Thus, the depression of geomagnetic ULF noise cannot be considered a reliable short-term precursor.

Inversion of short-term precursor of acoustic emission in uniaxial compression based on SOM neural network

Inversion of short-term precursor of acoustic emission in uniaxial compression based on SOM neural network

Analysis of cracks development and damage evolution in red sandstone under dry-wet cycles based on temporal and frequency characteristics of acoustic emission

Utilizing the goafs of underground reservoirs (underground buildings) in western coal mines as storage spaces plays a crucial role in ecological environment protection and energy transition in mining areas. Hence, it is crucial to recognize the repeated erosion of reservoir water levels on the deformation and damage mechanisms of the roof and floor rock masses in the underground building dams. This paper intends to study the instability failure mechanisms and precursor responses of red sandstone samples with 0–3 dry-wet cycles during uniaxial loading-unloading under acoustic emission (AE) monitoring. The AE time-frequency features were analyzed, and the crack three-dimensional spatial extension and tensile-shear crack evolution were explored. The b-value and entropy value of AE events were presented for evaluating crack expansion damage status during loading-unloading. The findings suggest that the peak strength, elastic modulus, and crack thresholds of red sandstone exhibit a positive exponential decline with growing dry-wet cycles. Conversely, the peak strain and strain-softening modulus exhibit an opposite trend. With growing dry-wet cycles, AE signals from low-frequency, high-amplitude, and large-scale cracks decline, exhibiting a multi-frequency simultaneous response effect before sample instability. Meanwhile, the proportion and concentration of localization events with energy exceeding 104 aJ rise, and the failure instability gradually shifts from tensile-shear failure to tensile cracks. The sudden decline in b-value and the significant fluctuation in entropy value serve as short-term precursors to imminent rock instability failure, with the system energy following an ordered-disordered-ordered pattern. The research findings offer certain experimental foundation and novel judgment indicators for rock structure safety warning, including the stability of underground building dams, support for water-rich roadways, water hazard prevention, and utilization of abandoned mine spaces.

Research on thermal infrared anomaly characteristics of moderate strong earthquakes in northeast China

In this article, the daily brightness temperature data from January 2006 to May 2020 of China’s geostationary meteorological satellite FY-2E/G were used to identify the brightness temperature differences before deep and shallow earthquakes in the study area using wavelet transform and the relative wavelet power spectrum (RWPS) methods. The objective was to explore the characteristics of thermal infrared (TIR) radiation anomaly changes before deep and shallow earthquakes in Northeast China by carrying out anomaly extraction and data analysis. The research has shown that five significant earthquakes experienced TIR radiation anomalies in the vicinity of the epicenter approximately 1–2 months before the event. The amplitude of the anomaly ranged from seven to twenty times higher than average, and the anomaly lasted about 3 months. The infrared radiation anomaly characteristics before the earthquake were especially significant in the case of two earthquakes in the Songyuan area. From the research, it was concluded that the TIR radiation anomaly could act as a short-term precursor for earthquake prediction. The method employed in this study would provide great support for predicting deep and shallow earthquakes in Northeast China using satellite thermal infrared technology.

Spatial and Temporal Analysis of Climatic Precursors before Major Earthquakes in Iran (2011–2021)

The present study provides a systematic assessment of the relationships between climatic variables and major earthquakes (M &gt; 6) in Iran (2011–2021). These variables include total cloud cover (tcc), low cloud cover (lcc), total precipitation (tp), surface latent heat flux (slhf), and total column rainwater (tcrw). Based on a wider set of variables provided by a multidimensional global dataset (ERA5), the combination of a cross-correlation function (CCF) and receiver operating characteristic (ROC) was used to develop the spatial and temporal analytic relations. Covering maximal values from 0.42 to 0.92, the CCF plots revealed that an increase in climatic parameters could provide valuable information about impending earthquake activity within 8 to 20 days. The mean values of tcc, lcc, tp, slhf, and tcrw were found to increase by 95%, 60%, 80.0 mm, 105 W/m2, and 95 kg−3/m2, respectively. In fact, with the mean AUC (area under the curve) indices ranging from 0.677 (tcc) to 0.810 (tcrw) prior to major earthquakes, the ROC plots allowed for discrimination between seismic and climatic variables ranging from “acceptable” to “excellent”. The changes in the climatic variables under study were due to anomalous air ionization and water condensation in the atmosphere, which can be regarded as short-term precursors to major earthquakes.

Results of Geomagnetic Studies on the Problem of Forecasting Strong Earthquakes in Uzbekistan

The article is devoted to the problem of forecasting strong earthquakes by the geomagnetic method. The geomagnetic method is widely used on this problem in seismically active regions of the world as one of the promising, informative and operational geophysical methods. The results of long-term geomagnetic studies on the problem of forecasting strong earthquakes in Uzbekistan are presented. Geomagnetic studies were carried out on the territories of the Tashkent, Ferghana, and Kyzylkum geodynamic polygons in the epicentral zones of strong earthquakes that occurred. Long-term, medium- and short-term precursors of earthquakes have been identified. Anomalous changes in the geomagnetic field associated with the decline in aftershock activity were also revealed. The dependence between the duration of the manifestation of long-term magnetic precursors and the magnitude of earthquakes is determined. Absolute proton magnetometers MMP-1, MV-01 (Russia), and G-856 (USA) were used to measure the geomagnetic field.

Этапы подготовки к прерывистому скольжению на предварительно вырезанных разломах в лабораторных моделях и проверка этапов в природе

This study is focused on analog modeling of the stick-slip process along an existing large fault in an elastic-viscoplastic model subjected to loading at a constant strain rate. Based on our model results and data from (Ma et al., 2012, 2014), we distinguish stable, meta-stable, and meta-instable stages of the stick-slip process (the latter includes the early and late sub-stages). Our experiments show that the fault is periodically reactivated by segmentation. We analysed this mechanism from one fault reactivation to another, and identified regressive and progressive trends of segmentation. The regressive segmentation takes place during the stable and meta-stable stages of the stick-slip process. Under regressive segmentation the number of active segments and their lengths are reduced. The progressive segmentation is initiated at the early meta-instable sub-stage of the stick-slip process. Its activity is desplayed by an increase in the number of active segments to a certain critical density, while their pattern becomes more chaotic. In the late sub-stage, number of segments decreases as they rapidly grow and join with each other to form larger active segments, up to full reactivation of the entire fault. For comparison with the model results, we interpret rock deformation monitoring records before the Bystroe earthquake. Our analysis confirms specific features of the anomalous rock deformation that are similar to the strain features observed along the model fault during the meta-instable stage. There are evidence to suggest that meta-instability of a fault is a potential candidate to short-term precursor of earthquakes.

Adaptive Approach to Time-Frequency Analysis of AE Signals of Rocks

The paper describes a new adaptive approach to the investigation of acoustic emission of rocks, the anomalies of which may serve as short-term precursors of strong earthquakes. The basis of the approach is complex methods for monitoring acoustic emission and for analysis of its time-frequency content. Piezoceramic hydrophones and vector receivers, installed at the bottom of natural and artificial water bodies, as well as in boreholes with water, are used as acoustic emission sensors. To perform a time-frequency analysis of geoacoustic signals, we use a sparse approximation based on the developed Adaptive Matching Pursuit algorithm. The application of this algorithm in the analysis makes it possible to adapt to the concrete characteristics of each geoacoustic pulse. Results of the application of the developed approach for the investigation of acoustic emission anomalies, occurring before earthquakes, are presented. We analyzed the earthquakes, that occurred from 2011 to 2016 in the seismically active region of the Kamchatka peninsula, which is a part of the circum-Pacific orogenic belt also known as the "Ring of Fire". It was discovered that geoacoustic pulse frequency content changes before a seismic event and returns to the initial state after an earthquake. That allows us to make a conclusion on the transformation of acoustic emission source scales before earthquakes. The obtained results may be useful for the development of the systems for environmental monitoring and detection of earthquake occurrences.

Lineament analysis as a seismic precursor: The El Mayor Cucapah earthquake of April 4, 2010 (MW7.2), Baja California, Mexico

An earthquake called the MW7.2 “El Mayor Cucapah” earthquake on April 4, 2010 has been analyzed for seismic precursor. The changes in the lineament system concerning its pattern and time intervals were analyzed during the earthquake preparation period and occurrence using the automated lineament detection method. The Landsat 5 TM images were processed using LESSA and ADALGEO software obtaining similar results. The statistical analysis revealed the stress accumulation due to plate interaction during earthquake formation. The study shows that the number of extracted lineaments changes rapidly about 23 months before the earthquake, and the systems return to the initial stage after 23 months. Most lineaments coincide with the extension of the San Andreas Fault as NW direction is the dominant trend. Thus, it can be concluded that the featural changes within the Rose diagram corresponding to the different strokes direction along with oriented elongation lines as disclosed in the present study using satellite images could be identified as a mid-term and/or short-term precursors of the earthquake. However, even though the dynamism of the El Mayor Cucapah earthquake is found in the extracted lineaments, it is possible to isolate more significant earthquakes even if new ones appear near the zone. Moreover, using two algorithms for lineament detection allows for the tectonics to corroborate the obtained lineaments and dynamism.

AMBIENT SEISMIC NOISE VARIATIONS BEFORE EARTHQUAKES IN THE BAIKAL RIFT SYSTEM

This paper proposes a method to observe the pre-earthquake features based on the variations in ambient noises using local moderate and strong seismic events as an example. Eight earthquakes in the Baikal rift system with energy classes K=10.1–15.9 were associated to a significant decrease in the level of ambient noises at epicentral distances from 3 to 81 km a few hours before the shock. The observed decrease in the ambient noise level can be classified as a short-term precursor of the medium consolidation 4–5 hours before the earthquake.

Evaluation of Thermal anomaly Preceding Northern Red Sea Earthquake, the 16th June 2020

On the 16th June, 2020, a moderate earthquake (Mw = 5.2) hit the Northern Red Sea region, Egypt, that was felt throughout the Hurghada and Sharm El-Sheikh cities and the surrounding areas without any damages. The thermal anomaly before the earthquakes was widely studied with satellite data, such as NOAA/AVHRR and MODIS. The case study aims to monitor and demonstrate the possibility of any variation of the thermal anomaly of sea surface temperature (SST) before and after the 16th June 2020 earthquake and to correlate the results with the previous heat flow study (deep thermal action). The Daytime/Nighttime (SST) data are retrieved from the OBPG serves as a Distributed Active Archive Center (OB. DAAC). The outputs indicated a thermal anomaly on the June 12th, 2020 a few days before the earthquake, covered a large area around the epicenter 60 km impact area, and reached a high value on the 15th June 2020, one day before the earthquake. For the deep thermal action of the entire crust, the earthquake frequency distributions presumed from the reviewed catalogue indicated that the peak of the seismicity is concentrated close to the center of the rift axis in the Northern Red Sea. The heat flow measurements are increased toward the center of the Red Sea rift and decreased toward both sides, generating some partial melt of the rocks and producing crustal subsidence at the center of the Red Sea rift. These results are compatible with the pattern of the seismic activity and heat flow effect around the epicenter. It could be considered as a short-term precursor of the earthquake.

Spatio-temporal features of the manifestation of long-term, medium-term and short-term earthquake precursors

Spatio-temporal features of the manifestation of long-term, medium-term and short-term earthquake precursors

LSTM-Autoencoder Network for the Detection of Seismic Electric Signals

Seismic electric signals (SESs) are essential short-term precursors of earthquakes. Accurate and efficient detection of SESs is significant to short-term predictions of earthquakes. However, SESs are usually disturbed by various noises and are thus difficult to recognize. Although conventional techniques have made substantial efforts in improving the SES detection accuracy, the success rates of SES detection at certain stations are still less satisfactory due to the complexity and diversity of noises. In this study, we apply deep learning to extract SESs and develop a novel deep learning network based on geoelectric field characteristics by combining the long short-term memory (LSTM) blocks with an autoencoder structure and a time-step attention module. The detection results of both synthetic and real data demonstrate that our proposed network yields superior performance in detecting embedded SESs in the presence of severe noise interference compared with traditional methods and several well-known networks. Moreover, our novel network shows the excellent ability of massive data processing, generalization and migration, which can process one-day&#x2019;s worth of data in only milliseconds, adapt to SESs whose durations and amplitudes are different from those of the training set and be easily transferred to newly acquired data. The proposed novel method can provide more efficient and accurate detection results, which will broaden the data availability of hazard mitigation based on SESs.

Control of variations in the stress-strain state based on monitoring the apparent resistivity in the well

The article gives an example of the application of a new approach to the search for short-term earthquake precursors based on the analysis of the data of three-year monitoring of the apparent resistivity in a water-saturated well on board a reservoir near a hydroelectric power station. The analysis also involved data on atmospheric pressure, water level and temperature in the well. The effects were estimated in a linear approximation, neglecting transients. The method of principal components was used for data processing. The results obtained in the time and frequency domains indicate that a new method for controlling localization variations and searching for short-term precursors of earthquakes is promising.

A Lithosphere–Atmosphere–Ionosphere Coupling Phenomenon Observed Before M 7.7 Jamaica Earthquake

The satellite-based earth observations have become an appropriate instrumental approach in monitoring the natural hazards among modern-day researchers. This study presents a multi-parameter approach using precursors of different physical nature defining the states of atmosphere and the ionosphere in terms of temporal and spatial variations about 5 days before the impending M 7.7 Jamaican earthquake (EQ). We performed a comprehensive analysis from the surface to the ionosphere at different altitude levels by analyzing the different datasets comprising, surface air temperature, relative humidity, total column water vapor, air pressure, Outgoing Longwave Radiations (OLR), and the total electron content of the global ionosphere maps (GIM-TEC). We observed a sharp increment in the atmospheric chemical potential (ACP) due to the increased radon activity that led to an abrupt decrement in the atmospheric relative humidity and, consequently, increased OLR that provides strong evidence of the air ionization production around the epicenter of M 7.7 EQ. Moreover, to check the periodicity of these atmospheric parameters, we performed a confutation analysis by meticulously analyzing these parameters in the same month and region for the previous 5 years during the non-existence of any major seismicity. This technique confirmed that the simultaneous atmospheric variations observed before the Jamaica EQ are not cyclic in the absence of significant seismic activities. The ionospheric conditions have also shown consistency with atmospheric disturbances, as depletions in GIM-TECs, having an amplitude of 4 TECU, are observed over the epicenter for 6 h (LT = 13–19 (-– UT)) on January 23, 2020. Additionally, the vertical ionospheric and atmospheric profiles from FORMOSAT-7/COSMIC-2 (F7/C2), at different altitudes (75–225 km) over the EQ epicenter, showed significant depletions on January 23, 2020. These TEC variations are observed to be an effect of the vertical seismogenic electric field due to the production of the air ionization at the atmospheric boundary layer by increased radon activity around the seismic preparation zone. The existence of these co-located synchronized atmospheric and ionospheric anomalies is explicitly and persistently local over a small region of the epicenter of Jamaican EQ that could be considered as potential short-term precursors. Also, these multi-observed anomalies will contribute to the physical explanation of the Lithosphere-Atmosphere–Ionosphere Coupling (LAIC) model.

Early Manifestations of Short-Term Precursors in Stress-Strain State Dynamics of Southern California

—The stress-strain state before the М = 7.1 Ridgecrest earthquake in Southern California is analyzed based on spatiotemporal distribution of shear strains calculated in the geomechanical model within local ~100 × 100 km crustal segments at a depth of 3–7 km. In the epicentral zone of the earthquake, starting from three years before the event, a successive series of the time intervals, up to the occurrence of the earthquake, when shear deformations are completely absent and rocks are farthest from ultimate strength—the so-called quiescence zones—are established. The spatial distribution of shear strains in the vicinity of the epicentral zone is analyzed during the quiescence intervals and subsequent bursts of maximum amplitude in the epicentral zone itself. The time intervals of the bursts are called excursions. The successive emergence of maxima in shear strain amplitudes in the epicentral zone and surrounding medium during the excursions corresponds to the situation of a swing when the entire preparation region of a future earthquake is rocking up to the moment of event. Consistency of the obtained results with the existing theoretical models of earthquake preparation is discussed.

Artificial Neural Network based thermal anomalies associated with earthquakes in Pakistan from MODIS LST

There are several reports about thermal anomalies associated with the impending earthquakes (EQs); among which the underlying mechanism is linked with the main shock with long, intermediate and short-term precursors. In this paper, we analyzed thermal anomalies from Moderate Resolution Imaging Spectroradiometer (MODIS) based Land Surface Temperature (LST) of three different magnitudes and shallow depth EQs in Pakistan. Our focus is to investigate the thermal anomalies by the statistical approach and Artificial Neural Network (ANN) in spatial and temporal LST values within 10 days before and after the main shock as short-term precursors. After implementing statistical and the ANN approach, LST revealed that thermal anomalies occurred within 1–10 days before the main shock of Mw > 6.0 EQs. However, a low intensity LST anomaly is also recorded within 20–25 days before the main shock of Mw 5.2 EQ. We study that LST anomalies are magnitude and depth dependent and it is more likely to occur before EQ of Mw > 6.0 and shallow depth within 10 days before/after the main shock day. The results depict that Mw 5.2 EQ anomaly is not clearly associated to the main shock, as it locates outside the window of 1–10 days before/after the main shock. Similarly, two out of three events caused post-seismic thermal anomalies of less magnitude as compared to the pre-seismic thermal anomalies. The pre-seismic LST anomalies occur with high intensity before shallow depth and large magnitude EQs than post seismic LST anomalies. The LST anomalies occurred before all the EQs suggesting it to be a reliable precursor of short to intermediate interval associated with an impending EQ.

Atmospheric and ionospheric coupling phenomena associated with large earthquakes

This paper explores multi-instrument space-borne observations in order to validate physical concepts of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) in relation to a selection of major seismic events. In this study we apply some validated techniques to observations in order to identify atmospheric and ionospheric precursors associated with some of recent most destructive earthquakes: M8.6 of March 28, 2005 and M8.5 of Sept. 12, 2007 in Sumatra, and M7.9 of May 12, 2008 in Wenchuan, China. New investigations are also presented concerning these three earthquakes and for the M7.2 of March 2008 in the Xinjiang-Xizang border region, China (the Yutian earthquake). It concerns the ionospheric density, the Global Ionospheric Maps (GIM) of the Total Electron Content (TEC), the Thermal Infra-Red (TIR) anomalies, and the Outgoing Longwave Radiation (OLR) data. It is shown that all these anomalies are identified as short-term precursors, which can be explained by the LAIC concept proposed in [S. Pulinets, D. Ouzounov, J. Asian Earth Sci. 41, 371 (2011)].

Методология деформационного мониторинга в Южном Прибайкалье и концептуальный подход к прогнозу землетрясений

The Southern Baikal region is located within the limits of the actively developing Baikal rift zone (BRZ). Its seismic potential is significant, and M&gt;7 earthquakes occur periodically with intensive shaking in the epicenters (up to 10 points). The problem of prediction and forecasting of strong earthquakes has always been critical for this region, considering its increasing urbanization, industrial clusters and transport systems. The article describes the methodology based on rock deformation monitoring data, which aims at developing a technology capable of efficient prediction and forecasting of strong earthquakes. The technology is based on the stick-slip model developed by of W. Brace and J. Byerlee and its synergetic interpretation proposed by Ma J. et al. This model shows the preparation of the earthquake source in stages, which is reflected in deformation monitoring data. An integral property of the deformation process is its self-organization right before an earthquake. The self-organization, that always takes place before a seismic event, is considered by the authors as an inevitable shortterm precursor. All other indicators that occur randomly are considered occasional precursors. The article is focused on the methodology aspects and describes the technical details of measuring the rock deformation. It presents the proven methods of data processing with the major goal of detecting the inevitable precursor. Described in detail are the structural-geodynamic conditions of the locations of rock deformation monitoring points in the study area. The main results are based on the rock deformation records taken before three strong earthquakes in the study area – Kultuk (August 27, 2008), Bystrinskoe (September 21, 2020), and Kudara (December 10, 2020) earthquakes. The study shows that, in contrast to the inevitable precursor, the occasional precursors are manifested depending on the geodynamic conditions of the earthquake source preparation, the position of the monitoring point relative to the source, and the structural conditions of the monitoring point location.

Joint Analysis of Anomalies of Different Geophysical Fields, Recorded from Space before Strong Earthquakes in California

Results are presented from using satellite data to study anomalies of different geophysical fields due to the interaction of the lithosphere, atmosphere, and ionosphere. The anomalies are mid- and short-term precursors of strong earthquakes in California that occurred on July 4 and 5, 2019 (M = 6.4 and M = 7.1). Precursory changes in the lithosphere are analyzed using lineament system characteristics obtained by processing satellite imagery (Terra/Aqua satellites and MODIS instrument), along with variations in the Earth’s surface temperature (the Aqua satellite and the AIRS instrument). Fluctuations in the temperature of the near-surface atmospheric layer are studied to detect atmospheric anomalies during preparation of seismic events, as are fluctuations in the air temperature now at an altitude of 1000 hPa and changes in outgoing longwave radiation recorded by the AIRS instrument on the Aqua satellite. Variations in the ionospheric electron density in the F2-layer maximum are studied with GPS data to reveal ionospheric anomalies during the precursors and occurrence of earthquakes. Joint analysis of anomalies in different geophysical fields, identified via satellite monitoring, allow precursory changes in the lithosphere to be detected a month before strong earthquakes. Precursory changes in the atmosphere and ionosphere can be detected 3–6 days and 3–5 or 10 days before earthquakes, respectively.