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1.
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.  相似文献   

2.
A method for determining medium quality factor is developed on the basis of analyzing the attenuation dispersion of the arrived first period P wave. In order to enhance signal to noise ratio, improve the resolution in measurement and reduce systematic error we applied the data resampling technique. The group velocity delay of P wave was derived by using an improved multi-filtering method. Based on a linear viscoelastic relaxation model we deduced the medium quality factor Q m, and associated error with 95% confidence level. Applying the method to the seismic record of the Xiuyan M=5.4 earthquake sequences we obtained the following result: (1) High Q m started to appear from Nov. 9, 1999. The events giving the deduced high Q m value clustered in a region with their epicenter distances being between 32 and 46 km to the Yingkou station. This Q m versus distance observation obviously deviates from the normal trend of Q m linearly increasing with distance. (2) The average Q m before the 29 Dec. 1999 M=5.4 earthquake is 460, while the average Q m between the M=5.4 event and the 12 Jan. 2000 M=5.1 earthquake is 391, and the average Q m after the M=5.1 event is 204.  相似文献   

3.
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)?=?500f0.9, κ?=?0.04 s, and fmax?=?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.  相似文献   

4.
In the present study, the level of the largest earthquake hazard is assessed in 28 seismic zones of the NW Himalaya and its vicinity, which is a highly seismically active region of the world. Gumbel’s third asymptotic distribution (hereafter as GIII) is adopted for the evaluation of the largest earthquake magnitudes in these seismic zones. Instead of taking in account any type of Mmax, in the present study we consider the ω value which is the largest earthquake magnitude that a region can experience according to the GIII statistics. A function of the form Θ(ω, RP6.0) is providing in this way a relatively largest earthquake hazard scale defined by the letter K (K index). The return periods for the ω values (earthquake magnitudes) 6 or larger (RP6.0) are also calculated. According to this index, the investigated seismic zones are classified into five groups and it is shown that seismic zones 3 (Quetta of Pakistan), 11 (Hindukush), 15 (northern Pamirs), and 23 (Kangra, Himachal Pradesh of India) correspond to a “very high” K index which is 6.  相似文献   

5.
The recent seismicity catalogue of metropolitan France Sismicité Instrumentale de l’Hexagone (SI-Hex) covers the period 1962–2009. It is the outcome of a multipartner project conducted between 2010 and 2013. In this catalogue, moment magnitudes (M w) are mainly determined from short-period velocimetric records, the same records as those used by the Laboratoire de Détection Géophysique (LDG) for issuing local magnitudes (M L) since 1962. Two distinct procedures are used, whether M L-LDG is larger or smaller than 4. For M L-LDG >4, M w is computed by fitting the coda-wave amplitude on the raw records. Station corrections and regional properties of coda-wave attenuation are taken into account in the computations. For M L-LDG ≤4, M w is converted from M L-LDG through linear regression rules. In the smallest magnitude range M L-LDG <3.1, special attention is paid to the non-unity slope of the relation between the local magnitudes and M w. All M w determined during the SI-Hex project is calibrated according to reference M w of recent events. As for some small events, no M L-LDG has been determined; local magnitudes issued by other French networks or LDG duration magnitude (M D) are first converted into M L-LDG before applying the conversion rules. This paper shows how the different sources of information and the different magnitude ranges are combined in order to determine an unbiased set of M w for the whole 38,027 events of the catalogue.  相似文献   

6.
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.  相似文献   

7.
The present study aims at understanding the seismotectonic province of the Shillong Plateau (SP) by identifying the potential seismic source zones within a radius of 500 km from the centre of the SP. From existing literature and earthquake (EQ) data, the seismotectonic region is found to vary in terms of seismicity, tectonic features, geology, thickness of overburden, rupture characteristics and rate of movement. Thus, entire 500-km-radius seismotectonic region is divided into four seismic source zones: namely (1) the Shillong Plateau–Assam Valley Zone (SP-AVZ), (2) the Indo-Burma Ranges Zone (IBRZ), (3) the Bengal Basin Zone (BBZ) and (4) the Eastern Himalaya Zone (EHZ). EQ catalogues for each source zone is analysed for completeness of magnitude and time. Seismic parameter b estimated using a maximum likelihood method is found to be 0.91 ± 0.03, 0.94 ± 0.02, 0.80 ± 0.03 and 0.89 ± 0.03 for the SP-AVZ, IBRZ, BBZ and EHZ, respectively. In addition, the maximum likelihood method is used to estimate the mean annual activity rate, maximum possible magnitude (m max), return period and probability of exceedance for the four zones. The b values estimated suggest that the BBZ is seismically more active; however, the rate of occurrence of EQs is highest in the IBRZ. Findings from this study are an indication of the relative contribution from each of the four seismic source zones towards a seismic hazard of the SP.  相似文献   

8.
The Aki-Utsu method of Gutenberg-Richter (G-R) b value estimation is often misapplied so that estimations not using the G-R histogram are often meaningless because they are not based on adequate samples. We propose a method to estimate the likelihood Pr(b?b m , N, M 1, M 2) that an observed b m estimate, based on a sample of N magnitudes within an [M 1????≤?ΔM/2,?M 2?+?ΔM/2) range, where ΔM?=?0.1 is the usual rounding applied to magnitudes, is due to a “true” source b value, b, and use these likelihoods to estimate source b ranges corresponding to various confidence levels. As an example of application of the method, we estimate the b values before and after the occurrence of a 7.4-magnitude earthquake in the Mexican subduction zone, and find a difference of 0.82 between them with 100% confidence that the b values are different.  相似文献   

9.
An earthquake with the moment magnitude M w ?=?5.8 occurred in the middle part of the Sakhalin Island, Russian Federation, on 14 August 2016, at 11:17 a.m. UTC. The earthquake source was located west of the Central Sakhalin Fault Zone, which is considered to mark the boundary between the Okhotsk and Eurasian (Amurian) plates. Moment tensor solution of the mainshock as well as the configuration of aftershock cloud suggests that the earthquake was caused by slip on a SW-dipping reverse fault. For the first time for Sakhalin, we have got the felt reports unified in accordance with DYFI. We also analyzed observed PGA values and, based on them, produced shaking maps.  相似文献   

10.
An important task in seismic hazard assessment is estimation of the intensity and frequency of extremely strong earthquake effects, in particular, peak ground velocities (PGV). Earlier, a method was proposed to evaluate PGV values based on the magnitude of displacements of rock blocks (Rodkin et al., 2012). In this study, this method is used to analyze field data on the source zones of the August 19, 1992, MS = 7.3 Susamyr earthquake and the January 3, 1911, Mw = 7.9 Kemin earthquake, and estimate maximum ground shaking at the upper construction site of the Upper Naryn series of hydropower plants, Kyrgyz Republic. It is shown that the resulting estimates are consistent with data obtained through other techniques. Therefore, the new approach can be recommended to estimate earthquake effects.  相似文献   

11.
In this study, pre-seismic and post-seismic total electron content (TEC) anomalies of 63 Mw?≥?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 Mw 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 Mw?≤?6.0 earthquakes in Turkey.  相似文献   

12.
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.  相似文献   

13.
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 (Mw≥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 Mw=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 Mw=8.5 on Hokkaido in September 2007, a doublet Simushir earthquake with the magnitudes Mw = 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 (Mw=8.1). The steady changes in the gravity field have also been recorded after the earthquake in the Sichuan region (May 2008, Mw = 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 Mw = 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.  相似文献   

14.
This study is concerned with characteristic frequencies of acceleration spectra as functions of the moment magnitude М w for crustal earthquakes in the 3 ≤ М w ≤ 6.4 range that have occurred in the Baikal Rift Zone (BRZ). The characteristic frequencies were defined as those at which maxima occur in the spectra: fSm, f1, and f2, at the 0.7Sm and 0.5Sm levels, as well as the fc2 and fc3 frequencies, which characterize the transition from the ascending branch of the spectrum (fc2) to the gently sloping branch, and the fc3 frequency, which shows the transition from the gently sloping part to the descending branch. All the characteristic frequencies move toward lower values with increasing earthquake magnitude. The resulting relationships for fc2 and fc3 were used to estimate the scaling, with the result that no similarity is present. As well, we have found no wellpronounced differences in earthquake spectra between different focal mechanism events. It was found that the slope of the low-frequency branch decreases and the high-frequency descending branch becomes flattened with increasing magnitude.  相似文献   

15.
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.  相似文献   

16.
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.  相似文献   

17.
The deep-focus Sea of Okhotsk earthquake that occurred on May 24, 2013 (h = 630 km, M w = 8.3) was accompanied by anomalous effects that were unknown previously. A combined analysis of published data concerning the source rupture evolution and some features of the deep structure provided an explanation of some anomalous effects, such as the large number of aftershocks and the low level of ground shaking in the epicentral area. However, GPS observations revealed high coseismic vertical displacements in the area. The seafloor uplift in the Sea of Okhotsk and the adjacent coasts was 3–12 mm, peaking at the approximate center of the sea, while Kamchatka and the North Kuril Islands subsided by 3–18 mm, peaking at the Apacha station 190 km east of the earthquake epicenter. These maximum estimates are 1.2–1.8 times the analogous values (10 mm) for the Chile mega-earthquake of May 20, 1960 (M w ~ 9.5). It is known that the large distances at which ground shaking is felt during deep-focus earthquakes are due to the fact that the body waves travel through the high-Q lower mantle. However, this does not explain the paradox of the present earthquake in the Sea of Okhotsk, viz., a constant intensity of shaking (two grades) in the range of epicentral distances between 1300 and 9500 km. The explanation requires consideration of the earth’s free oscillations excited by the earthquake.  相似文献   

18.
The Iranian Plateau does not appear to be a single crustal block, but an assemblage of zones comprising the Alborz—Azerbaijan, Zagros, Kopeh—Dagh, Makran, and Central and East Iran. The Gumbel’s III asymptotic distribution method (GIII) and maximum magnitude expected by Kijko—Sellevoll method is applied in order to check the potentiality of the each seismogenic zone in the Iranian Plateau for the future occurrence of maximum magnitude (Mmax). For this purpose, a homogeneous and complete seismicity database of the instrumental period during 1900–2012 is used in 29 seismogenic zones of the examined region. The spatial mapping of hazard parameters (upper bound magnitude (ω), most probable earthquake magnitude in next 100 years (M100) and maximum magnitude expected by maximum magnitude estimated by Kijko—Sellevoll method (max MK ? Smax) reveals that Central and East Iran, Alborz and Azerbaijan, Kopeh—Dagh and SE Zagros are a dangerous place for the next occurrence of a large earthquake.  相似文献   

19.
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.  相似文献   

20.
Temporal distribution of earthquakes with M w > 6 in the Dasht-e-Bayaz region, eastern Iran has been investigated using time-dependent models. Based on these types of models, it is assumed that the times between consecutive large earthquakes follow a certain statistical distribution. For this purpose, four time-dependent inter-event distributions including the Weibull, Gamma, Lognormal, and the Brownian Passage Time (BPT) are used in this study and the associated parameters are estimated using the method of maximum likelihood estimation. The suitable distribution is selected based on logarithm likelihood function and Bayesian Information Criterion. The probability of the occurrence of the next large earthquake during a specified interval of time was calculated for each model. Then, the concept of conditional probability has been applied to forecast the next major (M w > 6) earthquake in the site of our interest. The emphasis is on statistical methods which attempt to quantify the probability of an earthquake occurring within a specified time, space, and magnitude windows. According to obtained results, the probability of occurrence of an earthquake with M w > 6 in the near future is significantly high.  相似文献   

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