Characteristics of earthquake clustering in and around Japan revealed by single-link cluster analysis

In this study,we apply the single-link cluster(SLC)method to analyze the characteristics of earth-quake clustering in Japan.Among the clustering algorithms,the SLC method is effpctive in characterizing earthquake clusters or isolated events at both global and local scales.The results indicate that link lengths for the whole investigated area in and around Japan follow negative exponential functi-onal or Gamma distribution functional increase.Besides,some difference is revealed among different areas,e.g.,link lengths in the area of the Japan Trench and the Kuril Trench are shorter than those in other areas;the densest spatial distribution of the SLC framework is also in the area of the Japan Trench and the Kuril Trench.The close investigations indicate that the a and 1/θvalues estimated respectively from the exponential function and Gamma distribution may relate to spatial clustering,which is supported by the results of the distribution of link lengths and the spatial distribution of the SLC framework in the investigated areas.

The algorithm of decomposing superimposed 2-D Poisson processes and its application to the extracting earthquake clustering pattern

Aiming at the complexity of seismic gestation mechanism and spatial distribution, we hypothesize that the seismic data are composed of background earthquakes and anomaly earthquakes in a certain temporal-spatial scope. Also the background earthquakes and anomaly earthquakes both satisfy the 2-D Poisson process of different parameters respectively. In the paper, the concept of N-th order distance is introduced in order to transform 2-D superimposed Poisson process into 1-D mixture density function. On the basis of choosing the distance, mixture density function is decomposed to recognize the anomaly earthquakes through genetic algorithm. Combined with the temporal scanning of C value, the algorithm is applied to the recognition on spatial pattern of foreshock anomalies by exam-ples of Songpan and Longling sequences in the southwest of China.

Strong earthquake clustering around the eastern Tibetan Plateau after the 2008 MW7.9 Wenchuan earthquake

After the 2008 M_W7.9 Wenchuan earthquake,the eastern Tibetan Plateau experienced a series of M_W>6.0 earthquakes,including the 2013 M_W6.6 Lushan,2014 M_W6.1 Kangding and 2017 M_W6.5 Jiuzhaigou events.Based on available constraints,we build a three-dimensional viscoelastic finite element model to calculate Coulomb failure stress caused by these strong earthquakes.In this model,the geometry and slip vector of the initial rupture zone of each earthquake are used to better evaluate the earthquake-related stress projection.Considering reasonable ranges of viscosities for the crust and upper mantle in different tectonic units,numerical results show that after the Wenchuan earthquake,the coseismic Coulomb failure stress change at the hypocenters of the subsequent earthquakes increased to approximately+0.012–+0.040,+0.01–+0.03,and+0.008–+0.015 MPa,respectively.With viscoelastic relaxation of the lower crust and upper mantle,the Coulomb failure stress change at the hypocenters of these earthquakes accumulated to about+0.014–+0.042,+0.016–+0.036,and+0.003–+0.007 MPa just before their occurrence.This suggests that the Wenchuan earthquake indeed triggered or hastened the occurrence of the Lushan,Kangding and Jiuzhaigou events,supporting that strong earthquake clustering around the eastern Tibetan Plateau could be related to stress interaction between the seismogenic faults.Besides,~94%and^6%of the stress increase around(and before the occurrence of)the Kangding earthquake were contributed by the Wenchuan event and the Lushan event,respectively;the positive Coulomb failure stress change at the Jiuzhaigou earthquake hypocenter was related to coseismic slip partitioning of the Wenchuan earthquake.This means that stress interaction among the earthquakes could be controlled by the combined effect of stress of the previous events and by the complexity of earthquake ruptures.Thus,in researches on the earthquake-triggering mechanism,special attentions should be paid on both details of the rupture model and multiple factors of previous earthquakes.

Application of fuzzy clustering method to determining sub-fault planes of earthquake from aftershocks sequence

Earthquake rupture process generally involves several faults activities instead of a single fault A new method using both fuzzy clustering and principal component analysis makes it possible to reconstruct three dimensional structure of involved faults in earthquake if the aftershocks around the active fault planes distribute uniformly. When seismic events are given, the optimal faults structures can be determined by our new method. Each of sub-fault planes is fully characterized by its central location, length, width, strike and dip. The resolution determines the number of fault segments needed to describe the earthquake catalog. The higher the resolution, the finer the structure of the reconstructed fault segments. The new method successfully reconstructs the fault segments using synthetic earthquake catalogs. By taking the 28 June 1992 Landers earthquake oceured in southern California as an example, the reconstructed fault segments are consistent with the faults already known on geological maps or blind faults that appeared quite frequently in longer-term catalogs.

Spatio-temporal distribution of earthquake occurrence in Eastern Himalaya and vicinity(26°N-31°N and 87°E-98°E)based on b-value and fractal dimension

This study investigates the spatial and temporal variation of fractal dimension and b-value for the eastern part of the Himalaya and adjoining area(26°N–31°N and 87°E–98°E).The analysis is carried out on the earthquake dataset of 1373 events(Mc=4.0)by sliding window technique for the period 1964 to 2020.The region is divided into three sub regions A(87°E–92°E),B(92°E–94°E)and C(94°E–98°E).The b-value computed for the region A comprising eastern Nepal is smaller compared to other two regions which infers the possible high stress and asperities in the region.High spatial fractal dimension(Dc>1.5)and low temporal fractal dimension(Dt<0.31)are computed for the regions.High spatial fractal dimension may indicate that fractures generating earthquakes are approaching a 2D structure and low temporal fractal dimension implies high clustering of earthquake’s epicenters.The b value shows a weak negative correlation with Dc for regions A and C while a weak positive correlation is observed for the region B.Based on b-value and fractal dimension,this study explains the frequency of earthquakes and heterogeneity of the seismogenic structure in this part of the Himalaya.

Research on the Application of Time Structure Variation Analysis to the Jiashi-Bachu Earthquake Swarm Sequence

In 1997 - 2003, 27 earthquakes with M≥ 5.0 occurred in the Jiashi-Bachu area of Xinjiang. It was a rare strong earthquake swarm activity. The earthquake swarm has three time segments of activity with different magnitudes in the years 1997, 1998 and 2003. In different time segments, the seismic activity showed strengthenin-qguiet changes in various degrees before earthquakes with M ≥ 5.0. In order to delimitate effectively the precursory meaning of the clustering （strengthening） quiet change in sequence and to seek the time criterion for impending prediction, the nonlinear characteristics of seismic activity have been used to analyze the time structure characteristics of the earthquake swarm sequence, and further to forecast the development tendency of earthquake sequences in the future. Using the sequence catalogue recorded by the Kashi Station, and taking the earthquakes with Ms≥ 5.0 in the sequence as the starting point and the next earthquake with Ms = 5.0 as the end, statistical analysis has been performed on the time structure relations of the earthquake sequence in different stages. The main results are as follows： （1） Before the major earthquakes with M ≥ 5.0 in the swarm sequence, the time variation coefficient （δ-value） has abnormal demonstrations to different degrees. （2） Within 10 days after δ= 1, occurrence of earthquakes with M ≥ 5.0 in the swarm is very possible. （3） The time variation coefficient has three types of change. （4） The change process before earthquakes with M5.0 is similar to that before earthquakes with M6.0, with little difference in the threshold value. In the earthquake swarm sequence, it is difficult to delimitate accurately the attribute of the current sequences （foreshock or aftershock sequence） and to judge the magnitude of the follow-up earthquake by δ-value. We can only make the judgment that earthquakes with M5.0 are likely to occur in the sequence. （5） The critical clustering characteristics of the sequence are hierarchical. Only corresponding to a certain magnitude can the sequence have the variation state of critical clustering. （6） The coefficient of the time variation has a clear meaning in physics. After the clustering-quiet state of earthquake activity has appeared, it can describe clearly the randomness of the seismogenic system. Furthermore, it can efficiently clarify whether or not the clustering quiescence variation is of some prognostic meaning. In the case that the earthquake frequency attenuation is essentially normal （h 〉 1 ） and there is no remarkable clustering-quiescence state, it is still possible to discover the abnormal change of the sequence from the time variation coefficient. On the contrary, in the later period of swarm activity, after the appearance of many seismic quiescence phenomena, this coefficient did not appear abnormally, even when h 〈 1, suggesting that the δ-value diagnosis is more universal.

One feature of the activated southern Ordos block:the Ziwuling small earthquake cluster

Small earthquakes （Ms〉2.0） have been recorded from 1970 to the present day and reveal a significant diffrence in seismicity between the stable Ordos block and its active surrounding area. The southern Ordos block is a conspicuous small earthquake belt clustered and isolated along the NNW direction and extends to the inner stable Ordos block; no active fault can match this small earthquake cluster. In this paper, we analyze the dynamic mechanism of this small earthquake cluster based on the GPS velocity field （from 1999 to 2007） , which are mainly from Crustal Movement Observation Network of China （CMONOC） with respect to the north and south China blocks. The principal direction of strain rate field, the expansion ratefield, the maximum shear strain rate, and the rotation rate were constrained using the GPS velocity field. The results show that the velocity field, which is bounded by the small earthquake cluster from Tongchuan to Weinan, differs from the strain rate field, and the crustal deformation is left-lateral shear. This left-lateral shear belt not only spatially coincides with the Neo-tectonic belt in the Weihe Basin but also with the NNW small earthquake cluster （the Ziwuling small earthquake cluster）. Based on these studies, we speculate that the NNW small earthquake cluster is caused by left-lateral shear slip, which is prone to strain accumulation. When the strain releases along the weak zone of structure, small earthquakes diffuse within its upper crust. The maximum principal compression stress direction changed from NE-SW to NEE-SWW, and the former reverse faults in the southwestern margin of the Ordos block became a left-lateral strike slip due to readjustment of the tectonic stress field after the middle Pleistocene. The NNW Neo-tectonie belt in the Weihe Basin, the different movement character of the inner Weihe Basin （which was demonstrated through GPS measurements） anti the small earthquake cluster belt reflect the activated southern margin of the Ordos block, which was generated through readjustment of the tectonic stress field after the middle Pleistocene.

Variation of shearwave splitting in earthquake clusters with very similar waveforms

Among the records of aftershock observation of the 1991 Datong, China ML=5.8 earthquake, very similar waveforms from clusters of small earthquakes were found. Cross-correlation of the waveforms of each pair in the cluster confirmed the similarities. Re-sample technology is used to improve the sampling rate, which is helpful to distinguish the small variation of shear wave splitting. The variation of shear wave splitting could be found directly from seismograms of each pair in a cluster.

Paterns and regularity of ring distribution of seismic activity before great earthquakes in China

A systematic study on ″ring phenomena″ frequently occurring before great earthquakes has made in this paper, which has analyzed the features of ring distributions before 16 great earthquakes and part of large earthquakes in China and its boundary areas, and discussed their features of generality, regularity and predictive meaning. The results have showed that moderate earthquakes or larger earthquakes distribute around the epicenter like a ring from decades to hundred years before the great earthquakes of magnitude more than 7, which is a general phenomenon of great earthquakes without an exception. The active ring generally occurs in the areas from hundreds to thousands of kilometers from the epicenter(according to the magnitude). The seismicity in the ring has three basic stages with different features. in the first stage, seismicity remains at low level and the earthquakes distribute scatteredly, while the source area of the future great earthquake remains quiet; in the second stage, the seismicity strengthens, whose frequency, intensity, concentrated degree, released rate of strain and ratio of distributed area etc. increase, while the quiet area decreases or disappears; in the third stage, the seismicity is weaker than in the former stage, and the quiet area appears again. The source area surrounded by the active ring might have three periods of activity(called as early term, medium term and late term foreshocks activity). The length of the quiet area undergoes the process from large to small, then to large. Therefore, we can estimate the occurring place, magnitude and seismogenic stage of great earthquake according to the area,length and the seismicity in the active ring, which is valuable to make a long term prediction of great earthquakes. At last, we had a preliminary discussion on the mechanism of active ring formation.

On the Occurrence Time of an Earthquake Cluster in the Shanxi Reservoir

An earthquake cluster occurred in the Shanxi reservoir, located around Wenzhou city in Zbejiang Province. From February 4 to February 11, 2006, 9 earthquakes with ML ≥ 4.0 occurred, and the greatest magnitude was ML4.6. The correlations of earthquake occurrence time with reservoir level changes and tides are discussed, and the possible factors that induced the reservoir earthquakes and the trend of seismic activity are analyzed based on the characteristics of earthquake occurrence time. Finally, we suggest that it is necessary to slow down the speed of storing water and to maintain a level below the highest historical level to avoid greater earthquakes in the reservoir.

Cluster of Strong Earthquakes and Aftershocks in Ahar-Varzeghan Area on August 11, 2012

Seismic events are very complex spatial-temporal phenomena. Seismic catalogues, reporting information about spatial-temporal distribution of the main shocks, are nowadays available for many seismic areas in the world, very often major events mark the beginning of a series of earthquakes （aflershocks） whose frequency and energy are meanly decreasing in time down to the background level of activity. Azerbaijan is one of the most active segments of the Alpine-Himalayan seismic belt and marks the junction between the African-Arabian and Indian plate to the south, and Eurasian plate to the north. The cluster of earthquakes that struck near Varzeghan-Ahar was centered near the Gosha-Dagh fault, but preliminary data suggested that the fault was not responsible for the temblor. On the late afternoon of Saturday, August 11, 2012, the northwest of Iran was shaken by two of the strong earthquakes in Iranian history. First was hit by Mw （moment magnitude scale） = 6.4 Richter at local time 16：54 （12：23 GMT （Greenwich Mean Time））, and about 11 min later, an Mw = 6.3 struck 10 km to the west. The spatial-temporal clustering of micro earthquakes （aftershocks） near Varzeghan, is parameterized by means of a generalized passion model. The region has known faults but numerous smaller or deeply buried faults remain undated, according to the Geological Survey of Iran.

An Evaluation of Reverse-Time Imaging of Clustering Earthquakes

Clustering earthquakes refer to the seismic events that occur closely with each other in time and space. Because their overlapping waveform records make it difficult to pick the first arrivals, the hypocenters of clustering earthquakes cannot be determined accurately by traveltime location methods. Here we apply a reverse-time imaging （RTI） method to map clustering earthquakes. Taking the advantage of directly using waveforms, the RTI method is capable to map either a single small earthquake or some densely distributed clustering earthquakes beneath a 2-D seismic array. In 3-D case the RTI method is successfully applied to locate the long-offset doublet earthquakes using the data from a set of sparsely distributed surface stations. However, for the same acquisition geometry, the RTI encounters challenges in mapping densely distributed clustering earthquakes. While it is obvious that improving the mapping of clustering earthquakes requires a denser receiver network with wider range of illumination angles, it is necessary to verify the actual resolution of the RTI method with synthetic data. In our study area in the Three Gorges region, our tests in 3-D case suggest that some events beneath the linear aligned sub-arrays have reasonable resolution.

Pattern recognition of seismogenic nodes using Kohonen selforganizing map: example in west and south west of Alborz region in Iran

Pattern recognition of seismic and mor- phostructural nodes plays an important role in seismic hazard assessment. This is a known fact in seismology that tectonic nodes are prone areas to large earthquake and have this potential. They are identified by morphostructural analysis. In this study, the Alborz region has considered as studied case and locations of future events are forecast based on Kohonen Self-Organized Neural Network. It has been shown how it can predict the location of earthquake, and identifies seismogenic nodes which are prone to earthquake of M5.5＋ at the West of Alborz in Iran by using International Institute Earthquake Engineering and Seismology earthquake catalogs data. First, the main faults and tectonic lineaments have been identified based on MZ （land zoning method） method. After that, by using pattern recognition, we generalized past recorded events to future in order to show the region of probable future earthquakes. In other word, hazardous nodes have determined among all nodes by new catalog generated Self-organizing feature maps （SOFM）. Our input data are extracted from catalog, consists longitude and latitude of past event between 1980-2015 with magnitude larger or equal to 4.5. It has concluded node D1 is candidate for big earthquakes in comparison with other nodes and other nodes are in lower levels of this potential.