Retrospective Study on the Predictability of Pattern Informatics to the Wenchuan M8.0 and Yutian M7.3 Earthquakes

Two large earthquakes occurred in the western part of China in 2008, one of them being the Yutian (35.6°N, 81.6°E) M7.3 earthquake that occurred on March 21 (BJT) and the other the Wenchuan (31.0°N, 103.4°E) M8.0 earthquake that occurred on May 12 (BJT). In this paper, the West Continental China (included in 20.0°–50.0°N, 70.0°–110.0°E region) was the study region for verifyong the predictability of the pattern informatics (PI) method using the receiver-operating characteristic curve (ROC) test and R score test. Different forecasting maps with different calculating parameters were obtained. The calculating parameters were the grid size Δx, base time t _b, reference interval t _b to t ₁, change interval t ₁ to t ₂, and forecasting interval t ₂ to t ₃. In this paper, the base time t _b fixed to June 1, 1971, the ending forecast time t ₃ fixed to June 1, 2008, and the forecasting interval t ₂ to t ₃ changed from 1 to 10 years, and the grid sizes were chosen as 1° × 1° and 2° × 2°, respectively. The results show that the PI method could forecast the Yutian M7.3 and Wenchuan M8.0 earthquakes only using suitable parameters. Comparing the forecast results of grid sizes 1° × 1° and 2° × 2°, the models with 2° × 2° grids were better. Comparing the forecast results with different forecasting windows from 1 to 10 years, the models with forecasting windows of 4–8 years were better using the ROC test, and the models with forecasting windows of 7–10 years were better using the R score test. The forecast efficiency of the model with a grid size of 2° × 2° and forecast window of 8 years was the best one using either the ROC test or the R score test.     

Short- and Long-Term Earthquake Forecasts for California and Nevada

We present estimates of future earthquake rate density (probability per unit area, time, and magnitude) on a 0.1-degree grid for a region including California and Nevada, based only on data from past earthquakes. Our long-term forecast is not explicitly time-dependent, but it can be updated at any time to incorporate information from recent earthquakes. The present version, founded on several decades worth of data, is suitable for testing without updating over a five-year period as part of the experiment conducted by the Collaboratory for Study of Earthquake Predictability  (CSEP). The short-term forecast is meant to be updated daily and tested against similar models by CSEP. The short-term forecast includes a fraction of our long-term one plus time-dependent contributions from all previous earthquakes. Those contributions decrease with time according to the Omori law: proportional to the reciprocal of the elapsed time. Both forecasts estimate rate density using a radially symmetric spatial smoothing kernel decreasing approximately as the reciprocal of the square of epicentral distance, weighted according to the magnitude of each past earthquake. We made two versions of both the long- and short-term forecasts, based on the Advanced National Seismic System  (ANSS) and Preliminary Determinations of Epicenters (PDE) catalogs, respectively. The two versions are quite consistent, but for testing purposes we prefer those based on the ANSS catalog since it covers a longer time interval, is complete to a lower magnitude threshold and has more precise locations. Both forecasts apply to shallow earthquakes only (depth 25 km or less) and assume a tapered Gutenberg-Richter magnitude distribution extending to a lower threshold of 4.0.     

On the reality of the 56-year cycle and the increased probability of large earthquakes for Petropavlovsk-Kamchatskii during the period 2008–2011 according to lunar cyclicity

A 56-year cyclicity in the occurrence of large Kamchatka earthquakes has been previously detected. This is another manifestation of the tendency for the timing of large Kamchatka earthquakes to be synchronized to the cycles related to the period T _o of rotation of the lunar nodes found by V.A. Shirokov in 1974. He identified cycles of 18.6 years = T _o and 6.2 years = T _o/3, while the period of the 56-year cycle is 3T _o. The genuineness of that phenomenon had to be revised in connection with the occurrence of a large (M _w = 7.8) earthquake in Kamchatka at the end of 1997, in violation of the 56-year cyclicity. It turned out that, even though the 56-year cycle has become less distinct after the 1997 event, the cyclicity itself has remained statistically significant. A byproduct is an updated forecast of earthquake hazard for Kamchatka. The update is necessary in view of the approaching hazardous period of 2008–2011. It is found that, assuming the validity of these empirical tendencies, the expected rate of large earthquakes off Kamchatka for the period of August 2008 to October 2011 will be four times as high as the long-term mean. We derive the first-ever estimate of future hazard in terms of felt intensity for specified soil conditions (the so-called average soil) at a specified site (the town of Petropavlovsk-Kamchatskii). For these soil conditions, the estimated probability of at least one shock of intensity VII or greater during the period specified above is equal to 0.39 ± 0.15. The expected rate of single events or sets of events with M _w ≥ 7.6 in Kamchatka during this period is 0.76 ± 0.25.     

The caustic and other properties of SKP

The caustic of SKP is found at an epicentral distance Δ_C = 129.5° for surface foci and at Δ_C = 128.9° for foci at 400 km depth, by means of amplitude-distance graphs based upon short-period time-domain measurements. These results are essentially confirmed by long-period time-domain measurements of SKP as well as by frequency-domain studies, even though the spectra are less accurate for such determinations. The average period of SKP is $\text{T}\text{= 1.45 ± 0.45}\text{sec}$ from short-period records, significantly different from the corresponding PKP-period of 1.00 ± 0.31 sec. Likewise, the long-period averages of SKP = 10.8 ± 4.5 sec and of PKP = 7.7 ± 3.0 sec are significantly different from each other. A travel-time table of SKP1 is deduced, covering the epicentral distance range of 130–143° and the focal depth range of 100–700 km. All results are based on measurements on seismograms of the Swedish network of stations, deriving almost exclusively from earthquakes in the southwest Pacific area.     

Evaluation of the damping modification factor for structures subjected to near-fault ground motions

The damping modification factor (DMF) has been extensively used in earthquake engineering to describe the variation of structural responses due to varied damping ratios. It is known that DMFs are dependent not only on structural dynamic properties but also on characteristics of ground motions. DMFs regulated in current seismic codes are generally developed based on far-fault ground motions and are inappropriately used in structural design where pulse-like near-fault ground motions are involved. In this paper, statistical investigation of the DMF is performed based on 50 carefully selected pulse-like near-fault ground motions. It is observed that DMFs for pulse-like ground motions exhibit significant dependence on the pulse period T _p in a specific period range. If the period of the structure in response is close to the pulse period, the DMF attains the same level as that derived from far-fault ground motions; as the period of the structure is considerably larger or smaller than the pulse period T _p , the response reduction effect by the increased damping ratio is generally small, except for large earthquakes with long pulse periods, which exhibit significant reduction of response for structures with periods smaller than T _p . Based on the statistical results of DMFs, the empirical formulas for estimating DMFs for displacement, velocity and acceleration spectra are proposed, the effect of structural period, pulse period and damping ratio are considered in the formulas, and the formulas are designed to satisfy the specific reliability requirement in the period range of 0.1 < T/T _p  < 1, which is of engineering interest.     

A New Insight into Probabilistic Seismic Hazard Analysis for Central India

The Son-Narmada-Tapti lineament and its surroundings of Central India (CI) is the second most important tectonic regime following the converging margin along Himalayas-Myanmar-Andaman of the Indian sub-continent, which attracted several geoscientists to assess its seismic hazard potential. Our study area, a part of CI, is bounded between latitudes 18°–26°N and longitudes 73°–83°E, representing a stable part of Peninsular India. Past damaging moderate magnitude earthquakes as well as continuing microseismicity in the area provided enough data for seismological study. Our estimates based on regional Gutenberg–Richter relationship showed lower b values (i.e., between 0.68 and 0.76) from the average for the study area. The Probabilistic Seismic Hazard Analysis carried out over the area with a radius of ~300 km encircling Bhopal yielded a conspicuous relationship between earthquake return period (T) and peak ground acceleration (PGA). Analyses of T and PGA shows that PGA value at bedrock varies from 0.08 to 0.15 g for 10 % (T = 475 years) and 2 % (T = 2,475 years) probabilities exceeding 50 years, respectively. We establish the empirical relationships $ {\text{ZPA}}_{(T = 475)} = 0.1146\;[V_{\text{s}} (30)]^{ - 0.2924}, $ and $ {\text{ZPA}}_{(T = 2475)} = 0.2053\;[V_{\text{s}} (30)]^{ - 0.2426} $ between zero period acceleration (ZPA) and shear wave velocity up to a depth of 30 m [V _s (30)] for the two different return periods. These demonstrate that the ZPA values decrease with increasing shear wave velocity, suggesting a diagnostic indicator for designing the structures at a specific site of interest. The predictive designed response spectra generated at a site for periods up to 4.0 s at 10 and 2 % probability of exceedance of ground motion for 50 years can be used for designing duration dependent structures of variable vertical dimension. We infer that this concept of assimilating uniform hazard response spectra and predictive design at 10 and 2 % probability of exceedance in 50 years at 5 % damping at bedrocks of different categories may offer potential inputs for designing earthquake resistant structures of variable dimensions for the CI region under the National Earthquake Hazard Reduction Program for India.     

Melting of the silica isotypes SiO 2, BeF 2 and GeO 2 at elevated pressures

The melting curves of the structural analogues SiO ₂, BeF ₂ and GeO ₂ have been studied at pressures ?40 kbar in a piston-cylinder apparatus. The initial slopes dT_m/dP of the β-quartz-liquid boundaries for SiO ₂ and BeF ₂ are ～35° while the slope of the rutile-liquid boundary for GeO ₂ is approximately 32°C/kbar. These large values of dT/dP reflect the unusually low entropies of fusion for these compounds in which strong structural similarities exist between the crystalline phases and the melt. Implications for the extended phase diagram of silica are discussed and it is concluded that either: (1) a maximum exists on the coesite melting curve, or (2) estimates of the melting temperature of stishovite need to be revised upwards.     

Tsunami Early Warning Within Five Minutes

Tsunamis are most destructive at near to regional distances, arriving within 20–30 min after a causative earthquake; effective early warning at these distances requires notification within 15 min or less. The size and impact of a tsunami also depend on sea floor displacement, which is related to the length, L, width, W, mean slip, D, and depth, z, of the earthquake rupture. Currently, the primary seismic discriminant for tsunami potential is the centroid-moment tensor magnitude, M _w ^CMT , representing the product LWD and estimated via an indirect inversion procedure. However, the obtained M _w ^CMT and the implied LWD value vary with rupture depth, earth model, and other factors, and are only available 20–30 min or more after an earthquake. The use of more direct discriminants for tsunami potential could avoid these problems and aid in effective early warning, especially for near to regional distances. Previously, we presented a direct procedure for rapid assessment of earthquake tsunami potential using two, simple measurements on P-wave seismograms—the predominant period on velocity records, T _d , and the likelihood, T ₅₀ ^Ex , that the high-frequency, apparent rupture-duration, T ₀, exceeds 50–55 s. We have shown that T _d and T ₀ are related to the critical rupture parameters L, W, D, and z, and that either of the period–duration products T _d T ₀ or T _d T ₅₀ ^Ex gives more information on tsunami impact and size than M _w ^CMT , M _wp, and other currently used discriminants. These results imply that tsunami potential is not directly related to the product LWD from the “seismic” faulting model, as is assumed with the use of the M _w ^CMT discriminant. Instead, information on rupture length, L, and depth, z, as provided by T _d T ₀ or T _d T ₅₀ ^Ex , can constrain well the tsunami potential of an earthquake. We introduce here special treatment of the signal around the S arrival at close stations, a modified, real-time, M _wpd(RT) magnitude, and other procedures to enable early estimation of event parameters and tsunami discriminants. We show that with real-time data currently available in most regions of tsunami hazard, event locations, m _b and M _wp magnitudes, and the direct, period–duration discriminant, T _d T ₅₀ ^Ex can be determined within 5 min after an earthquake occurs, and T ₀, T _d T ₀, and M _wpd(RT) within approximately 10 min. This processing is implemented and running continuously in real-time within the Early-est earthquake monitor at INGV-Rome (http://early-est.rm.ingv.it). We also show that the difference m _b  ? log₁₀(T _d T ₀) forms a rapid discriminant for slow, tsunami earthquakes. The rapid availability of these measurements can aid in faster and more reliable tsunami early warning for near to regional distances.     

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.     

Correlation of Geoelectric Data with Aquifer Parameters to Delineate the Groundwater Potential of Hard rock Terrain in Central Uganda

Knowledge of aquifer parameters is essential for management of groundwater resources. Conventionally, these parameters are estimated through pumping tests carried out on water wells. This paper presents a study that was conducted in three villages (Tumba, Kabazi, and Ndaiga) of Nakasongola District, central Uganda to investigate the hydrogeological characteristics of the basement aquifers. Our objective was to correlate surface resistivity data with aquifer properties in order to reveal the groundwater potential in the district. Existing electrical resistivity and borehole data from 20 villages in Nakasongola District were used to correlate the aquifer apparent resistivity (ρ _e) with its hydraulic conductivity (K _e), and aquifer transverse resistance (TR) with its transmissivity (T _e). K _e was found to be related to ρ _e by; $ {\text{Log }}(K_{\text{e}} ) = - 0.002\rho_{\text{e}} + 2.692 $ . Similarly, TR was found to be related to T by; $ {\text{TR}} = - 0.07T_{\text{e}} + 2260 $ . Using these expressions, aquifer parameters (T _c and K _c) were extrapolated from measurements obtained from surface resistivity surveys. Our results show very low resistivities for the presumed water-bearing aquifer zones, possibly because of deteriorating quality of the groundwater and their packing and grain size. Drilling at the preferred VES spots was conducted before the pumping tests to reveal the aquifer characteristics. Aquifer parameters (T _o and K _o) as obtained from pumping tests gave values (29,424.7 m²/day, 374.3 m/day), (9,801.1 m²/day, 437.0 m/day), (31,852.4 m²/day, 392.9 m/day). The estimated aquifer parameter (T _c and K _c) when extrapolated from surface geoelectrical data gave (7,142.9 m²/day, 381.9 m/day), (28,200.0 m²/day, 463.4 m/day), (19,428.6 m²/day, 459.2 m/day) for Tumba, Kabazi, and Ndaiga villages, respectively. Interestingly, the similarity between the K _c and K _o pairs was not significantly different. We observed no significant relationships between the T _c and T _o pairs_. The root mean square errors were estimated to be 18,159 m²/day and 41.4 m/day.     

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.     

PI Forecast for the Sichuan-Yunnan Region: Retrospective Test after the May 12, 2008, Wenchuan Earthquake

The May 12, 2008, Wenchuan M _S 8.0/M _w 7.9 earthquake occurred in the middle part of the north–south seismic zone in central west China, being one of the greatest thrust events on land in recent years. To explore whether there were some indications of the increase of strong earthquake probabilities before the Wenchuan earthquake, we conducted a retrospective forecast test applying the Pattern Informatics (PI) algorithm to the earthquakes in the Sichuan-Yunnan region since 1992. A regional earthquake catalogue complete to M _L 3.0 from 01/01/1977 to 15/06/2008 was used. A 15-year long ‘sliding time window’ was used in the PI calculation, with ‘anomaly training time window’ and ‘forecast time window’ both set to 5 years. With a forecast target magnitude of M _S 5.5, the ROC test shows that the PI forecast outperforms not only random guess but also the simple number-counting approach based on the clustering hypothesis of earthquakes (the RI forecast). ‘Hotspots’ can be seen in the region of the northern Longmenshan fault which is responsible for the Wenchuan earthquake. However, when considering bigger grid size and higher cutoff magnitude, such ‘hotspots’ disappear and there is very little indication of an impending great earthquake.     

Three-dimensional admittance analysis of lithospheric elastic thickness over the Louisville Ridge

Using bathymetry and altimetric gravity anomalies, a 1° 9 1° lithospheric effective elastic thickness(Te) model over the Louisville Ridge and its adjacent regions is calculated using the moving window admittance technique. For comparison, three bathymetry models are used: general bathymetric charts of the oceans, SIO V15.1,and BAT_VGG. The results show that BAT_VGG is more suitable for calculating T e than the other two models. T e along the Louisville Ridge was re-evaluated. The southeast of the ridge has a medium Te of 10–20 km, while Te increases dramatically seaward of the Tonga-Kermadec trench as a result of the collision of the Pacific and IndoAustralian plates.     

Pattern Informatics and its Application for Optimal Forecasting of Large Earthquakes in Japan

Pattern Informatics (PI) technique can be used to detect precursory seismic activation or quiescence and make an earthquake forecast. Here we apply the PI method for optimal forecasting of large earthquakes in Japan, using the data catalogue maintained by the Japan Meteorological Agency. The PI method is tested to forecast large (magnitude m ≥ 5) earthquakes spanning the time period 1995–2004 in the Kobe region. Visual inspection and statistical testing show that the optimized PI method has forecasting skill, relative to the seismic intensity data often used as a standard null hypothesis. Moreover, we find in a retrospective forecast that the 1995 Kobe earthquake (m = 7.2) falls in a seismically anomalous area. Another approach to test the forecasting algorithm is to create a future potential map for large (m ≥ 5) earthquake events. This is illustrated using the Kobe and Tokyo regions for the forecast period 2000–2009. Based on the resulting Kobe map we point out several forecasted areas: The epicentral area of the 1995 Kobe earthquake, the Wakayama area, the Mie area, and the Aichi area. The Tokyo forecast map was created prior to the occurrence of the Oct. 23, 2004 Niigata earthquake (m = 6.8) and the principal aftershocks with 5.0 ≤ m. We find that these events were close to in a forecasted area on the Tokyo map. The PI technique for regional seismicity observation substantiates an example showing considerable promise as an intermediate-term earthquake forecasting in Japan.     

Space- and Time-Dependent Probabilities for Earthquake Fault Systems from Numerical Simulations: Feasibility Study and First Results

In weather forecasting, current and past observational data are routinely assimilated into numerical simulations to produce ensemble forecasts of future events in a process termed “model steering”. Here we describe a similar approach that is motivated by analyses of previous forecasts of the Working Group on California Earthquake Probabilities (WGCEP). Our approach is adapted to the problem of earthquake forecasting using topologically realistic numerical simulations for the strike-slip fault system in California. By systematically comparing simulation data to observed paleoseismic data, a series of spatial probability density functions (PDFs) can be computed that describe the probable locations of future large earthquakes. We develop this approach and show examples of PDFs associated with magnitude M > 6.5 and M > 7.0 earthquakes in California.     

Earthquakes Along the Passive Margin of Greenland: Evidence for Postglacial Rebound Control

—?An intriguing observation in Greenland is a clear spatial correlation between seismicity and deglaciated areas along passive continental margins, a piece of evidence for earthquake triggering due to postglacial rebound. Another piece of evidence for induced seismicity due to deglaciation derives from earthquake source mechanisms. Sparse, low magnitude seismicity has made it difficult to determine focal mechanisms from Greenland earthquakes. On the basis of two normal faulting events along deglaciated margins and from the spatial distribution of epicenters, earlier investigators suggested that the earthquakes of Greenland are due to postglacial rebound. This interpretation is tested here by using more recent data. Broadband waveforms of teleseismic P waves from the August 10, 1993 (m _b = 5.4) and October 14, 1998 (m _b = 5.1) earthquakes have been inverted for moment tensors and source parameters. Both mechanisms indicate normal faulting with small strike-slip components: the 1993 event, strike = 348.9°, dip = 41.0°, rake =?56.3°, focal depth = 11?km, seismic moment = 1.03?×?10²⁴ dyne-cm, and M _w = 5.3; the 1998 event, strike = 61.6°, dip = 58.0°, rake =?95.5°, focal depth = 5?km, seismic moment = 5.72?×?10²³ dyne-cm, and M _w = 5.1. These and the two prior events support the theory that the shallow part of the lithosphere beneath the deglaciated margins is under horizontal extension. The observed stress field can be explained as flexural stresses due to removal of ice loads and surface loads by glacial erosion. These local extensional stresses are further enhanced by the spreading stress of continental crust and reactivate preexisting faults. Earthquake characteristics observed from Greenland suggest that the dominant seismogenic stresses are from postglacial rebound and spreading of the continental lithosphere.     

The 2014–2015 earthquake series in the northern Upper Rhine Graben,Central Europe

Since March 2014, an unusually large amount of earthquakes occur southeast of the city of Darmstadt in the northern Upper Rhine Graben. During the period, until April 2015, we have recorded 356 earthquakes with magnitudes ranging from M_L?=??0.6 to 4.2. We identified two source clusters separated laterally by about 5 km. The hypocentres within these clusters are aligned vertically extending over a depth range from 1 to 8 km with a lateral extent of about 1 to 2 km. Focal mechanisms show left-lateral strike-slip movements; b values are changing with time between b?=?0.6 and b?=?0.9. This is the first time in almost 150 years that such high earthquake rates have been observed in the region. Historical accounts dating back to the nineteenth century report of over 2000 felt earthquakes over a time span from 1869 to 1871. From these, maximum intensities of VII have been estimated. Other seismic activities in the region were reported in the 1970s. The observations of the 2014–2015 earthquake series do not completely match a typical main shock–aftershock sequence or a typical earthquake swarm. Especially the activity at the beginning of the earthquake series may be considered as a mixture of a main shock–aftershock sequence and a short-lasting swarm event. Whether or not the time gap between the current seismic activity, which actually takes place at the same locations as parts of the seismic swarm in 1869–1871, and the seismic activity in the nineteenth century or the seismic activity in the 1970s can be interpreted as a seismic cycle remains unclear.     

Temporal evolution of the focal mechanism consistency of the 2021 Yangbi MS 6.4 earthquake sequence in Yunnan

Using the Cut And Paste (CAP) method, we invert the focal mechanism of 38 moderate earthquakes (M_S ≥ 3.0) recorded by Yunnan seismic network and analyze the corresponding focal mechanism consistency based on the minimum spatial rotation angle. Our results indicate that the M_S 6.4 mainshock is induced by a lateral strike slip fault (with a rake angle of ～ ?165°) and a little normal-faulting component event along a nearly vertical plane (dipping angle～ 79° and strike ～138°). Combining our results with high resolution catalog, we argue that the seismogenic fault of this earthquake sequence is a secondary fault western to the major Weixi-Qiaohou-Weishan fault. The focal mechanism evolution can be divided into three periods. During the first period, the foreshock sequence, the focal mechanism consistency is the highest (KA<36°); during the second period which is shortly after the mainshock, the focal mechanism shows strong variation with KA ranging from 8° to 110°; during the third period, the seismicity becomes weak and the focal mechanism of the earthquakes becomes more consistent than the second period (18°<KA<73°). We suggest that the KA, to some extent, represents the coherence between local tectonic stress regime and the stress state of each individual earthquake. Furthermore, high focal mechanism consistency and high linearity of seismic distribution may serve as indicators for the identification of foreshock sequence.     

Stress field change around the Mount Fuji volcano magma system caused by the Tohoku megathrust earthquake, Japan

Crustal deformation by the M _w 9.0 megathrust Tohoku earthquake causes the extension over a wide region of the Japanese mainland. In addition, a triggered M _w 5.9 East Shizuoka earthquake on March 15 occurred beneath the south flank, just above the magma system of Mount Fuji. To access whether these earthquakes might trigger the eruption, we calculated the stress and pressure changes below Mount Fuji. Among the three plausible mechanisms of earthquake–volcano interactions, we calculate the static stress change around volcano using finite element method, based on the seismic fault models of Tohoku and East Shizuoka earthquakes. Both Japanese mainland and Mount Fuji region are modeled by seismic tomography result, and the topographic effect is also included. The differential stress given to Mount Fuji magma reservoir, which is assumed to be located to be in the hypocentral area of deep long period earthquakes at the depth of 15 km, is estimated to be the order of about 0.001–0.01 and 0.1–1 MPa at the boundary region between magma reservoir and surrounding medium. This pressure change is about 0.2 % of the lithostatic pressure (367.5 MPa at 15 km depth), but is enough to trigger an eruptions in case the magma is ready to erupt. For Mount Fuji, there is no evidence so far that these earthquakes and crustal deformations did reactivate the volcano, considering the seismicity of deep long period earthquakes.