Activation of seismicity in Central and South Asia after the Makran earthquakes: Possible acceleration of preparation of large seismic events in the Tien Shan region

Two zones of seismicity (ten events with M _w = 7.0–7.7) stretching from Makran and the Eastern Himalaya to the Central and EasternTien Shan, respectively, formed over 11 years after the great Makran earthquake of 1945 (M _w = 8.1). Two large earthquakes (M _w = 7.7) hit theMakran area in 2013. In addition, two zones of seismicity (M ≥ 5.0) occurred 1–2 years after theMakran earthquake in September 24, 2013, stretching in the north-northeastern and north-northwestern directions. Two large Nepal earthquakes struck the southern extremity of the “eastern” zone (April 25, 2015, M _w = 7.8 and May 12, 2015, M _w = 7.3), and the Pamir earthquake (December 7, 2015, M _w = 7.2) occurred near Sarez Lake eastw of the “western” zone. The available data indicate an increase in subhorizontal stresses in the region under study, which should accelerate the possible preparation of a series of large earthquakes, primarily in the area of the Central Tien Shan, between 70° and 79° E, where no large earthquakes (M _w ≥ 7.0) have occurred since 1992.     

Temporal and spatial distributions of precursory seismicity rate changes in the Thailand-Laos-Myanmar border region: implication for upcoming hazardous earthquakes

To study the prospective areas of upcoming strong-to-major earthquakes, i.e., M _w  ≥ 6.0, a catalog of seismicity in the vicinity of the Thailand-Laos-Myanmar border region was generated and then investigated statistically. Based on the successful investigations of previous works, the seismicity rate change (Z value) technique was applied in this study. According to the completeness earthquake dataset, eight available case studies of strong-to-major earthquakes were investigated retrospectively. After iterative tests of the characteristic parameters concerning the number of earthquakes (N) and time window (T _w ), the values of 50 and 1.2 years, respectively, were found to reveal an anomalous high Z-value peak (seismic quiescence) prior to the occurrence of six out of the eight major earthquake events studied. In addition, the location of the Z-value anomalies conformed fairly well to the epicenters of those earthquakes. Based on the investigation of correlation coefficient and the stochastic test of the Z values, the parameters used here (N = 50 events and T _w  = 1.2 years) were suitable to determine the precursory Z value and not random phenomena. The Z values of this study and the frequency-magnitude distribution b values of a previous work both highlighted the same prospective areas that might generate an upcoming major earthquake: (i) some areas in the northern part of Laos and (ii) the eastern part of Myanmar.     

An evaluation of earthquake hazard parameters in the Iranian Plateau based on the Gumbel III distribution

The Gumbel’s third asymptotic distribution (GIII) of the extreme value method is employed to evaluate the earthquake hazard parameters in the Iranian Plateau. This research quantifies spatial mapping of earthquake hazard parameters like annual and 100-year mode beside their 90 % probability of not being exceeded (NBE) in the Iranian Plateau. Therefore, we used a homogeneous and complete earthquake catalogue during the period 1900–2013 with magnitude M _w ? ≥?4.0, and the Iranian Plateau is separated into equal area mesh of 1° late?×?1° long. The estimated result of annual mode with 90 % probability of NBE is expected to exceed the values of M _w 6.0 in the Eastern part of Makran, most parts of Central and East Iran, Kopeh Dagh, Alborz, Azerbaijan, and SE Zagros. The 100-year mode with 90 % probability of NBE is expected to overpass the value of M _w 7.0 in the Eastern part of Makran, Central and East Iran, Alborz, Kopeh Dagh, and Azerbaijan. The spatial distribution of 100-year mode with 90 % probability of NBE uncovers the high values of earthquake hazard parameters which are frequently connected with the main tectonic regimes of the studied area. It appears that there is a close communication among the seismicity and the tectonics of the region.     

Ground motion prediction equations for horizontal and vertical components of acceleration in Northern Iran

Recent studies have shown that the vertical component of ground motion can be quite destructive on a variety of structural systems. Development of response spectrum for design of buildings subjected to vertical component of earthquake needs ground motion prediction equations (GMPEs). The existing GMPEs for northern Iranian plateau are proposed for the horizontal component of earthquake, and there is not any specified GMPE for the vertical component of earthquake in this region. Determination of GMPEs is mostly based on regression analyses on earthquake parameters such as magnitude, site class, distance, and spectral amplitudes. In this study, 325 three-component records of 55 earthquakes with magnitude ranging from M _w 4.1 to M _w 7.3 are used for estimation on the regression coefficients. Records with distances less than 300 km are selected for analyses in the database. The regression analyses on earthquake parameters results in determination of GMPEs for peak ground acceleration and spectral acceleration for both horizontal and vertical components of the ground motion. The correlation between the models for vertical and horizontal GMPEs is studied in details. These models are later compared with some other available GMPEs. According to the result of this investigation, the proposed GMPEs are in agreement with the other relationships that were developed based on the local and regional data.     

A study of Guptkashi,Uttarakhand earthquake of 6 February 2017 (<Emphasis Type="Italic">M</Emphasis><Subscript><Emphasis Type="Italic">w</Emphasis></Subscript>5.3) in the Himalayan arc and implications for ground motion estimation

The 2017 Guptkashi earthquake occurred in a segment of the Himalayan arc with high potential for a strong earthquake in the near future. In this context, a careful analysis of the earthquake is important as it may shed light on source and ground motion characteristics during future earthquakes. Using the earthquake recording on a single broadband strong-motion seismograph installed at the epicenter, we estimate the earthquake’s location (30.546° N, 79.063° E), depth (H?=?19 km), the seismic moment (M₀?=?1.12×10¹⁷ Nm, M _w 5.3), the focal mechanism (φ?=?280°, δ?=?14°, λ?=?84°), the source radius (a?=?1.3 km), and the static stress drop (Δσ _s ~22 MPa). The event occurred just above the Main Himalayan Thrust. S-wave spectra of the earthquake at hard sites in the arc are well approximated (assuming ω^?2 source model) by attenuation parameters Q(f)?=?500f^0.9, κ?=?0.04 s, and f_max?=?infinite, and a stress drop of Δσ?=?70 MPa. Observed and computed peak ground motions, using stochastic method along with parameters inferred from spectral analysis, agree well with each other. These attenuation parameters are also reasonable for the observed spectra and/or peak ground motion parameters in the arc at distances ≤?200 km during five other earthquakes in the region (4.6?≤?M _w ?≤?6.9). The estimated stress drop of the six events ranges from 20 to 120 MPa. Our analysis suggests that attenuation parameters given above may be used for ground motion estimation at hard sites in the Himalayan arc via the stochastic method.     

Earthquake recurrence models and occurrence probabilities of strong earthquakes in the North Aegean Trough (Greece)

The determination of strong earthquakes’ recurrence time above a predefined magnitude, associated with specific fault segments, is an important component of seismic hazard assessment. The occurrence of these earthquakes is neither periodic nor completely random but often clustered in time. This fact in connection with their limited number, due to shortage of the available catalogs, inhibits a deterministic approach for recurrence time calculation, and for this reason, application of stochastic processes is required. In this study, recurrence time determination in the area of North Aegean Trough (NAT) is developed by the application of time-dependent stochastic models, introducing an elastic rebound motivated concept for individual fault segments located in the study area. For this purpose, all the available information on strong earthquakes (historical and instrumental) with M_w ≥ 6.5 is compiled and examined for magnitude completeness. Two possible starting dates of the catalog are assumed with the same magnitude threshold, M_w ≥ 6.5 and divided into five data sets, according to a new segmentation model for the study area. Three Brownian Passage Time (BPT) models with different levels of aperiodicity are applied and evaluated with the Anderson–Darling test for each segment in both catalog data where possible. The preferable models are then used in order to estimate the occurrence probabilities of M_w ≥ 6.5 shocks on each segment of NAT for the next 10, 20, and 30 years since 01/01/2016. Uncertainties in probability calculations are also estimated using a Monte Carlo procedure. It must be mentioned that the provided results should be treated carefully because of their dependence to the initial assumptions. Such assumptions exhibit large variability and alternative means of these may return different final results.     

A statistical analysis of seismo-ionospheric TEC anomalies before 63 <Emphasis Type="Italic">M</Emphasis><Subscript>w</Subscript> ≥ 5.0 earthquakes in Turkey during 2003–2016

In this study, pre-seismic and post-seismic total electron content (TEC) anomalies of 63 M_w?≥?5.0 earthquakes in Turkey (36°–42°N, 26°–45°E) were statistically investigated. The largest earthquake that occurred in Turkey during 2003–2016 is the M_w 7.1 Van earthquake on October 23, 2011. The TEC data of epicenters is obtained from CODE-GIM using a simple 4-point bivariate interpolation. The anomalies of TEC variations were determined by using a quartile-based running median process. In order to validate GIM results, we used the GPS-TEC data of available four IGS stations within the size of the Van earthquake preparation area. The anomalies that are detected by GIM and GPS-TEC show a similar pattern. Accordingly, the results obtained with CODE-GIM are reliable. The statistical results show that there are not prominent earthquake precursors for M_w?≤?6.0 earthquakes in Turkey.     

Ground deformation effects from the ~M6 earthquakes (2014–2015) on Cephalonia–Ithaca Islands (Western Greece) deduced by GPS observations

The implications of the earthquakes that took place in the central Ionian Islands in 2014 (Cephalonia, M _w6.1, M _w5.9) and 2015 (Lefkas, M _w6.4) are described based on repeat measurements of the local GPS networks in Cephalonia and Ithaca, and the available continuous GPS stations in the broader area. The Lefkas earthquake occurred on a branch of the Cephalonia Transform Fault, affecting Cephalonia with SE displacements gradually decreasing from north (~100 mm) to south (~10 mm). This earthquake revealed a near N–S dislocation boundary separating Paliki Peninsula in western Cephalonia from the rest of the island, as well as another NW–SE trending fault that separates kinematically the northern and southern parts of Paliki. Strain field calculations during the interseismic period (2014–2015) indicate compression between Ithaca and Cephalonia, while extension appears during the following co-seismic period (2015–2016) including the 2015 Lefkas earthquake. Additional tectonically active zones with differential kinematic characteristics were also identified locally.     

Seismic source zoning and maximum credible earthquake prognosis of the Greater Kashmir Territory,NW Himalaya

We present the seismic source zoning of the tectonically active Greater Kashmir territory of the Northwestern Himalaya and seismicity analysis (Gutenberg-Richter parameters) and maximum credible earthquake (m _max) estimation of each zone. The earthquake catalogue used in the analysis is an extensive one compiled from various sources which spans from 1907 to 2012. Five seismogenic zones were delineated, viz. Hazara-Kashmir Syntaxis, Karakorum Seismic Zone, Kohistan Seismic Zone, Nanga Parbat Syntaxis, and SE-Kashmir Seismic Zone. Then, the seismicity analysis and maximum credible earthquake estimation were carried out for each zone. The low b value (<1.0) indicates a higher stress regime in all the zones except Nanga Parbat Syntaxis Seismic Zone and SE-Kashmir Seismic Zone. The m _max was estimated following three different methodologies, the fault parameter approach, convergence rates using geodetic measurements, and the probabilistic approach using the earthquake catalogue and is estimated to be M _w 7.7, M _w 8.5, and M _w 8.1, respectively. The maximum credible earthquake (m _max) estimated for each zone shows that Hazara Kashmir Syntaxis Seismic Zone has the highest m _max of M _w 8.1 (±0.36), which is espoused by the historical 1555 Kashmir earthquake of M _w 7.6 as well as the recent 8 October 2005 Kashmir earthquake of M _w 7.6. The variation in the estimated m _max by the above discussed methodologies is obvious, as the definition and interpretation of the m _max change with the method. Interestingly, historical archives (～900 years) do not speak of a great earthquake in this region, which is attributed to the complex and unique tectonic and geologic setup of the Kashmir Himalaya. The convergence is this part of the Himalaya is distributed not only along the main boundary faults but also along the various active out-of-sequence faults as compared to the Central Himalaya, where it is mainly adjusted along the main boundary fault.     

Earthquake hazard and risk assessment based on Unified Scaling Law for Earthquakes: Greater Caucasus and Crimea

We continue applying the general concept of seismic risk analysis in a number of seismic regions worldwide by constructing regional seismic hazard maps based on morphostructural analysis, pattern recognition, and the Unified Scaling Law for Earthquakes (USLE), which generalizes the Gutenberg-Richter relationship making use of naturally fractal distribution of earthquake sources of different size in a seismic region. The USLE stands for an empirical relationship log₁₀N(M, L)?=?A?+?B·(5 – M)?+?C·log₁₀L, where N(M, L) is the expected annual number of earthquakes of a certain magnitude M within a seismically prone area of linear dimension L. We use parameters A, B, and C of USLE to estimate, first, the expected maximum magnitude in a time interval at seismically prone nodes of the morphostructural scheme of the region under study, then map the corresponding expected ground shaking parameters (e.g., peak ground acceleration, PGA, or macro-seismic intensity). After a rigorous verification against the available seismic evidences in the past (usually, the observed instrumental PGA or the historically reported macro-seismic intensity), such a seismic hazard map is used to generate maps of specific earthquake risks for population, cities, and infrastructures (e.g., those based on census of population, buildings inventory). The methodology of seismic hazard and risk assessment is illustrated by application to the territory of Greater Caucasus and Crimea.     

Source parameters of the 27th of June 2015 Gulf of Aqaba earthquake

On the 27 June 2015, at 15:34:03 UTC, a moderate-sized earthquake of M _w 5.0 occurred in the Gulf of Aqaba. Using teleseismic P waves, the focal mechanism of the mainshock was investigated by two techniques. The first technique used the polarities of the first P wave onsets, and the second technique was based on the normalized waveform modeling technique. The results showed that the extension stress has a NE orientation with a shallow southward plunge while the compression stress has a NW trend with a nearly shallow westward plunge, obtaining a strike-slip mechanism. This result agrees well with the typical consequence of crustal deformation resulting from the ongoing extensional to shear stress regime in the Gulf of Aqaba (NE-SW extension and NW-SE compression). The grid search method over a range of focal depths indicates an optimum solution at 15 ± 1 km. To identify the causative fault plane, the aftershock hypocenters were relocated using the local waveform data and the double-difference technique. Considering the fault trends, the spatial distribution of relocated aftershocks demarcated a NS-oriented causative fault, in consistence with one of the nodal planes of the focal mechanism solution, emphasizing the dominant stress regime in the region. Following the Brune model, the estimates of source parameters exhibited fault lengths of 0.29 ≤ L ≤ 2.48 km, moment magnitudes of 3.0 ≤ M _w ≤ 5.0, and stress drops of 0.14 ≤ Δσ < 1.14 MPa, indicating a source scaling similar to the tectonic earthquakes related to plate boundaries.     

Probabilistic aftershock hazard analysis,two case studies in West and Northwest Iran

Aftershock hazard maps contain the essential information for search and rescue process, and re-occupation after a main-shock. Accordingly, the main purposes of this article are to study the aftershock decay parameters and to estimate the expected high-frequency ground motions (i.e., Peak Ground Acceleration (PGA)) for recent large earthquakes in the Iranian plateau. For this aim, the Ahar-Varzaghan doublet earthquake (August 11, 2012; M _N =6.5, M _N =6.3), and the Ilam (Murmuri) earthquake (August 18, 2014 ; M _N =6.2) have been selected. The earthquake catalogue has been collected based on the Gardner and Knopoff (Bull Seismol Soc Am 64(5), 1363-1367, 1974) temporal and spatial windowing technique. The magnitude of completeness and the seismicity parameters (a,??b) and the modified Omori law parameters (P,??K,??C) have been determined for these two earthquakes in the 14, 30, and 60 days after the mainshocks. Also, the temporal changes of parameters (a,??b,??P,??K,??C) have been studied. The aftershock hazard maps for the probability of exceedance (33%) have been computed in the time periods of 14, 30, and 60 days after the Ahar-Varzaghan and Ilam (Murmuri) earthquakes. For calculating the expected PGA of aftershocks, the regional and global ground motion prediction equations have been utilized. Amplification factor based on the site classes has also been implied in the calculation of PGA. These aftershock hazard maps show an agreement between the PGAs of large aftershocks and the forecasted PGAs. Also, the significant role of b parameter in the Ilam (Murmuri) probabilistic aftershock hazard maps has been investigated.     

Large-scale aseismic creep in the areas of the strong earthquakes revealed from the GRACE data on the time variations of the Earth’s gravity field

The refinement of the accuracy and resolution of the monthly global gravity field models from the GRACE satellite mission, together with the accumulation of more than a decade-long series of these models, enabled us to reveal the processes that occur in the regions of large (M_w≥8) earthquakes that have not been studied previously. The previous research into the time variations of the gravity field in the regions of the giant earthquakes, such as the seismic catastrophes in Sumatra (2004) and Chile (2010), and the Tohoku mega earthquake in Japan (2011), covered the coseismic gravity jump followed by the long postseismic changes reaching almost the same amplitude. The coseismic gravity jumps resulting from the lower-magnitude events are almost unnoticeable. However, we have established a long steady growth of gravity anomalies after a number of such earthquakes. For instance, in the regions of the subduction earthquakes, the growth of the positive gravity anomaly above the oceanic trench was revealed after two events with magnitudes M_w=8.5 in the Sumatra region (the Nias earthquake of March 2005 and the Bengkulu event of September 2007 near the southern termination of Sumatra Island), after the earthquake with M_w=8.5 on Hokkaido in September 2007, a doublet Simushir earthquake with the magnitudes M_w = 8.3 and 8.1 in the Kuriles in November 2006 and January 2007, and after the earthquake off the Samoa Island in September 2009 (M_w=8.1). The steady changes in the gravity field have also been recorded after the earthquake in the Sichuan region (May 2008, M_w = 8.0) and after the doublet event with magnitudes 8.6 and 8.2, which occurred in the Wharton Basin of the Indian Ocean on April 11, 2012. The detailed analysis of the growth of the positive anomaly in gravity after the Simushir earthquake of November 2006 is presented. The growth started a few months after the event synchronously with the seismic activation on the downdip extension of the coseismically ruptured fault plane zone. The data demonstrating the increasing depth of the aftershocks since March 2007 and the approximately simultaneous change in the direction and average velocity of the horizontal surface displacements at the sites of the regional GPS network indicate that this earthquake induced postseismic displacements in a huge area extending to depths below 100 km. The total displacement since the beginning of the growth of the gravity anomaly up to July 2012 is estimated at 3.0 m in the upper part of the plate’s contact and 1.5 m in the lower part up to a depth of 100 km. With allowance for the size of the region captured by the deformations, the released total energy is equivalent to the earthquake with the magnitude M_w = 8.5. In our opinion, the growth of the gravity anomaly in these regions indicates a large-scale aseismic creep over the areas much more extensive than the source zone of the earthquake. These processes have not been previously revealed by the ground-based techniques. Hence, the time series of the GRACE gravity models are an important source of the new data about the locations and evolution of the locked segments of the subduction zones and their seismic potential.     

A new <Emphasis Type="Italic">M</Emphasis><Subscript><Emphasis Type="Italic">w</Emphasis></Subscript> estimation parameter for use in earthquake early warning systems

We propose a method that employs the squared displacement integral (ID2) to estimate earthquake magnitudes in real time for use in earthquake early warning (EEW) systems. Moreover, using τ _c and P _d for comparison, we establish formulas for estimating the moment magnitudes of these three parameters based on the selected aftershocks (4.0 ≤ M _s  ≤ 6.5) of the 2008 Wenchuan earthquake. In this comparison, the proposed ID2 method displays the highest accuracy. Furthermore, we investigate the applicability of the initial parameters to large earthquakes by estimating the magnitude of the Wenchuan M _s 8.0 mainshock using a 3-s time window. Although these three parameters all display problems with saturation, the proposed ID2 parameter is relatively accurate. The evolutionary estimation of ID2 as a function of the time window shows that the estimation equation established with ID2 ^Ref determined from the first 8-s of P wave data can be directly applicable to predicate the magnitudes of 8.0. Therefore, the proposed ID2 parameter provides a robust estimator of earthquake moment magnitudes and can be used for EEW purposes.     

Probabilistic Assessment of Earthquake Hazard in Gujarat and Adjoining Region of India

The Gujarat and adjoining region falls under all four seismic zones V, IV, III and II of the seismic zoning map of India, and is one of the most seismically prone intracontinental regions of the world. It has experienced two large earthquakes of magnitude M _w 7.8 and 7.7 in 1819 and 2001, respectively and several moderate earthquakes during the past two centuries. In the present study, the probability of occurrence of earthquakes of M ≥ 5.0 has been estimated during a specified time interval for different elapsed times on the basis of observed time intervals between earthquakes using three stochastic models namely, Weibull, Gamma and Lognormal. A complete earthquake catalogue has been used covering the time interval of 1819 to 2006. The whole region has been divided into three major seismic regions (Saurashtra, Mainland Gujarat and Kachchh) on the basis of seismotectonics and geomorphology of the region. The earthquake hazard parameters have been estimated using the method of maximum likelihood. The logarithmic of likelihood function (ln L) is estimated and used to test the suitability of models in three different regions. It was found that the Weibull model fits well with the actual data in Saurashtra and Kachchh regions, whereas Lognormal model fits well in Mainland Gujarat. The mean intervals of occurrence of earthquakes are estimated as 40.455, 20.249 and 13.338 years in the Saurashtra, Mainland Gujarat and Kachchh region, respectively. The estimated cumulative probability (probability that the next earthquake will occur at a time later than some specific time from the last earthquake) for the earthquakes of M ≥ 5.0 reaches 0.9 after about 64 years from the last earthquake (1993) in Saurashtra, about 49 years from the last earthquake (1969) in Mainland Gujarat and about 29 years from the last earthquake (2006) in the Kachchh region. The conditional probability (probability that the next earthquake will occur during some specific time interval after a certain elapsed time from last earthquake) is also estimated and it reaches about 0.8 to 0.9 during the time interval of about 57 to 66 years from the last earthquake (1993) in Saurashtra region, 31 to 51 years from the last earthquake (1969) in Mainland Gujarat and about 21 to 28 years from the last earthquake (2006) in Kachchh region.     

3D <Emphasis Type="Italic">v</Emphasis><Subscript>P</Subscript> and <Emphasis Type="Italic">v</Emphasis><Subscript>S</Subscript> models of southeastern margin of the Tibetan plateau from joint inversion of body-wave arrival times and surface-wave dispersion data

A new 3D velocity model of the crust and upper mantle in the southeastern (SE) margin of the Tibetan plateau was obtained by joint inversion of body- and surface-wave data. For the body-wave data, we used 7190 events recorded by 102 stations in the SE margin of the Tibetan plateau. The surface-wave data consist of Rayleigh wave phase velocity dispersion curves obtained from ambient noise cross-correlation analysis recorded by a dense array in the SE margin of the Tibetan plateau. The joint inversion clearly improves the v _S model because it is constrained by both data types. The results show that at around 10 km depth there are two low-velocity anomalies embedded within three high-velocity bodies along the Longmenshan fault system. These high-velocity bodies correspond well with the Precambrian massifs, and the two located to the northeast of 2013 M _S 7.0 Lushan earthquake are associated with high fault slip areas during the 2008 Wenchuan earthquake. The aftershock gap between 2013 Lushan earthquake and 2008 Wenchuan earthquake is associated with low-velocity anomalies, which also acts as a barrier zone for ruptures of two earthquakes. Generally large earthquakes (M ≥ 5) in the region occurring from 2008 to 2015 are located around the high-velocity zones, indicating that they may act as asperities for these large earthquakes. Joint inversion results also clearly show that there exist low-velocity or weak zones in the mid-lower crust, which are not evenly distributed beneath the SE margin of Tibetan plateau.     

An Evaluation of Coulomb Stress Changes from Earthquake Productivity Variations in the Western Gulf of Corinth,Greece

Spatial and temporal evolution of the stress field in the seismically active and well-monitored area of the western Gulf of Corinth, Greece, is investigated. The highly accurate and vast regional catalogues were used for inverting seismicity rate changes into stress variation using a rate/state-dependent friction model. After explicitly determining the physical quantities incorporated in the model (characteristic relaxation time, fault constitutive parameters, and reference seismicity rates), we looked for stress changes across space and over time and their possible association with earthquake clustering and fault interactions. We focused our attention on the Efpalio doublet of January 2010 (M = 5.5 and M = 5.4), with a high aftershock productivity, and attempted to reproduce and interpret stress changes prior to and after the initiation of this seismicity burst. The spatial distribution of stress changes was evaluated after smoothing the seismological data by means of a probability density function (PDF). The inverted stress calculations were compared with the calculations derived from an independent approach (elastic dislocation model) and this comparison was quantified. The results of the two methods are in good agreement (up to 80 %) in the far field, with the inversion technique providing more robust results in the near field, where they are more sensitive to the uncertainties of coseismic slip distribution. It is worth mentioning that the stress inversion model proved to be a very sensitive stress meter, able to detect even small stress changes correlated with spatio–temporal earthquake clustering. Data analysis was attempted from 1975 onwards to simulate the stress changes associated with stronger earthquakes over a longer time span. This approach revealed that only M > 5.5 events induce considerable stress variations, although in some cases there was no evidence for such stress changes even after an M > 5.5 earthquake.     

Seismicity anomalies before the great earthquake of <Emphasis Type="Italic">M</Emphasis><Subscript>S</Subscript>=8.1 in the Kunlun Pass and its significance to earthquake prediction

A great earthquake of M _S=8.1 took place in the west of Kunlun Pass on November 14, 2001. The epicenter is located at 36.2°N and 90.9°E. The analysis shows that some main precursory seismic patterns appear before the great earthquake, e.g., seismic gap, seismic band, increased activity, seismicity quiet and swarm activity. The evolution of the seismic patterns before the earthquake of M _S=8.1 exhibits a course very similar to that found for earthquake cases with M _S≥7. The difference is that anomalous seismicity before the earthquake of M _S=8.1 involves in the larger area coverage and higher seismic magnitude. This provides an evidence for recognizing precursor and forecasting of very large earthquake. Finally, we review the rough prediction of the great earthquake and discuss some problems related to the prediction of great earthquakes.     

Joint inversion of GNSS and teleseismic data for the rupture process of the 2017 <Emphasis Type="Italic">M</Emphasis><Subscript>w</Subscript>6.5 Jiuzhaigou,China, earthquake

The spatio-temporal slip distribution of the earthquake that occurred on 8 August 2017 in Jiuzhaigou, China, was estimated from the teleseismic body wave and near-field Global Navigation Satellite System (GNSS) data (coseismic displacements and high-rate GPS data) based on a finite fault model. Compared with the inversion results from the teleseismic body waves, the near-field GNSS data can better restrain the rupture area, the maximum slip, the source time function, and the surface rupture. The results show that the maximum slip of the earthquake approaches 1.4 m, the scalar seismic moment is ~ 8.0 × 10¹⁸ N·m (M_w?≈?6.5), and the centroid depth is ~ 15 km. The slip is mainly driven by the left-lateral strike-slip and it is initially inferred that the seismogenic fault occurs in the south branch of the Tazang fault or an undetectable fault, a NW-trending left-lateral strike-slip fault, and belongs to one of the tail structures at the easternmost end of the eastern Kunlun fault zone. The earthquake rupture is mainly concentrated at depths of 5–15 km, which results in the complete rupture of the seismic gap left by the previous four earthquakes with magnitudes >?6.0 in 1973 and 1976. Therefore, the possibility of a strong aftershock on the Huya fault is low. The source duration is ~ 30 s and there are two major ruptures. The main rupture occurs in the first 10 s, 4 s after the earthquake; the second rupture peak arrives in ~ 17 s. In addition, the Coulomb stress study shows that the epicenter of the earthquake is located in the area where the static Coulomb stress change increased because of the 12 May 2017 M_w7.9 Wenchuan, China, earthquake. Therefore, the Wenchuan earthquake promoted the occurrence of the 8 August 2017 Jiuzhaigou earthquake.     

Detailed Study of Time Variations in the Gutenberg–Richter <Emphasis Type="Italic">b</Emphasis>-value Based on Highly Accurate Seismic Observations at the Garm Prognostic Site,Tajikistan

The time variations in the Gutenberg–Richter b-value are minutely studied based on the data of highly accurate seismological observations at the Garm prognostic site, Tajikistan, where a stationary network of seismic stations of the Complex Seismological Expedition (CSE) of Schmidt Institute of Physics of the Earth (IPE) of the USSR (Russian) Academy of Sciences was in operation from 1955 to 1992. A total of 93035 local earthquakes ranging from 0.0 to 6.3 in the Ml magnitudes are considered. The spatiotemporal fluctuations in the minimal magnitude of completeness of the earthquakes, Mc, are analyzed. The study considers a 25-year interval of the observations at the center of the observation system within which Mc = 0.9. It is shown that in most cases, the b-value and log₁₀E^2/3 experience characteristic time variations before the earthquakes with magnitudes higher than the minimal magnitude of the predicted earthquake (MPE). The 6-year anomaly in the parameters’ b-value, log₁₀E^2/3, and log₁₀N associated with the single strongest earthquake with M = 6.3 that occurred in the observation region on October 26, 1984 is revealed. The inversely proportional relationship is established between the time variations in the b-value and the time variations in the velocities of seismic waves Vp and Vp/Vs. It is shown that the exponent p in the power function which links the time variations of the b-value and log₁₀E^2/3 is higher in the zones of crustal compression than in the zones of extension. It is simultaneously confirmed that the average b-value in the zones of compression is lower than in the zones of extension. It is established that in the case of earthquakes with M ≥ 2.6, the time series of seismic activity log₁₀N_i and the time series of the b-value are highly cross correlated with a coefficient of r ≈ 0.75, whereas in the case of earthquakes with M ≥ 0.9, the coefficient of cross correlation between these time series is close to zero (r ≈ 0.06). The law of variations in the slope of the lines approximating the relationship between the log₁₀N_i time series in the different magnitude ranges (M ≥ Mc_i) and b-value time series is obtained. It is hypothesized that the seismic activity of the earthquakes with high magnitudes can be estimated provided that the parameters of the time series of the b-value and time series of the number of earthquakes logN(ΔM_i) in the range of low magnitudes are known. It is concluded that using the parameter log₁₀N for prognostic estimates of the strong earthquakes only makes sense for earthquakes having moderate and large magnitudes. It is inferred that the time variations in the b-value are predominantly contributed by the time variations of the earthquakes with relatively large magnitudes.