Search

On October 1, 2022, an earthquake with a magnitude (M) of 5.8 occurred in the Tarutung region, Indonesia and was associated with an active fault at a depth of 10 km. The earthquake fault with dextral mechanism is suitable with the pattern of active fault movement in Sumatra in the Northeast - Southwest direction. A total of 170 aftershocks occurred within a week span with magnitude variations of 1.7 – 4.0. In addition, the Tarutung earthquake was felt by the local peoples with an intensity of IV - VI MMI and caused 1 fatality, 25 injuries, and around 900 houses were damaged. Therefore, this study studies the characteristics of seismicity and damage caused by finding an appropriate 1-Dimensional seismic velocity model. The obtained 1-Dimensional speed model has varying values at a depth of 10 km with a speed of ~5.5 km/s and 30 km with a speed of ~7 km/s. The 1-D velocity model obtained has a convergent and unique solution with an RMS value < 1.0. Based on ground motion analysis after relocation, it was found that the high PGA and PGV values were in Tarutung. The PGA results reveal a high percentage value of >10% in Tarutung. This is consistent with the damage data and at the same time confirms that Tarutung is in a seismically active area.

On October 1, 2022, an earthquake with a magnitude of 5.8 shook the Tarutung area which was generated by an active fault at a shallow depth of 10 km. In this study, relocating the hypocenter and determining the mechanism of the earthquake was carried out to understand the active tectonic structure. The distribution of hypocenter relocation figures a pull-apart pattern at shallow depths. The earthquake mechanism shows a dextral pattern in the Southwest – Southeast direction with a strike of 138º – 158º. The aftershocks are more dominantly distributed in the pull-apart system in the southeastern part and show the greater part of the transfer of seismic static stress to the southeastern side of the Toru fault. The pull-apart tectonic system scheme in the Tarutung basin with secondary faults as extensional faults is proposed to be a fault source model that forms a negative-flower structure geological pattern. The results of this study can be used as a reference for the Tarutung tectonic system and applied as a mitigation study.

In this study, a new method was examined that used acoustic emission (AE) monitoring data, in combination with a primary Boundary Element stress analysis, to back-calculate rock mass strength. The presented AE data came from the National Radioactive Waste Repository (NRWR) for low- and intermediate-level waste (LLW/ILW). AE monitoring is able to detect the pre-peak, peak, and post-peak stress changes in rock mass. The presented method used AE monitoring data to back-calculate parameters, such as uniaxial compressive strength and the rock mass deformation modulus. The AE initiation threshold was used to develop an objective function that considered the stress in the rock mass and the rock mass strength. The findings of this research propose that most AE events can be related to the crack initiation threshold, and in space, most of them are located at points away from the excavated walls. In the vicinity of the excavation damage zones around the cavities, the stress conditions beyond the crack damage boundary of the rock mass occur in many areas, leading to significant irreversible deformations. This novel method was demonstrated to aid in the prediction of rock mass strength and is a valuable, non-invasive method for improving the spatial prediction of rock mass parameters, which will lead to safer underground storage facilities. [ABSTRACT FROM AUTHOR]

Parameters of hypocenters and times of 4760 seismic events taken from KNET catalog compiled by the Research Station of the Russian Academy of Sciences for the period since May 2003 till the end of 2020 have been determined by different programs: Hypocenter, HYP, Hypoellipse, HYPO71, Dbloc2. The smallest divergence of epicenters' coordinates is observed for the earthquakes, which have happened within the area of 41°–44.5°N and 73°–77.5°E entirely covering the territory of Bishkek geodynamic test site. Such an analysis can be used to assess the quality of seismic wave arrival times determination. The best agreement is observed between the programs Hypocenter and HYP: for more than 95% of events the epicenter displacement is less than 10 km and the change of time at origin is less than 0.5 sec. This indicates the preservation of the uniformity of the KNET seismological catalog when switching from using Hypocenter to HYP as the main locator program.

This paper proposes a new method to approach earthquake hypocenter studies based on Chaos Game Representation (CGR), a method initially used for making fractal structures and applied for studying DNA sequences. Applying the CGR method, this study aims at checking whether any relation exists between earthquakes occurring in different depth ranges in a seismically active area. For this purpose, the seismically active areas around the Indian tectonic plate were used. The CGR images gave characteristic patterns, implying that the occurrence of earthquakes in some specific depth range combinations showed higher preference. Statistical data on the frequency of different depth range combinations were derived from these plots. We put forward a mathematical value which we call proximity index, to compare the similarity between two different CGR plots. Proximity index values were used to compare the similarity in seismic activity in two different zones by comparing their respective CGR plots. [ABSTRACT FROM AUTHOR]

To solve many geological and geophysical problems, in particular, prediction of strong earthquakes, seismic zoning, and earthquake-resistant construction, it is necessary to have reliable data on the distribution of earthquake hypocenters in the study area. In turn, the completeness of data on the distribution of earthquake hypocenters and accuracy of their determination largely depend on the efficiency of the observation system. We evaluate the efficiency of the actual network of seismological observations in Karelia, which consists of seven seismic stations. The efficiency of the seismological observation network is estimated by the minimum magnitudes of seismic events recorded in the considered region and the minimum errors in determining the main parameters (origin time and hypocentral coordinates) of the recorded events. Calculation of the minimum earthquake magnitudes for the Karelian seismological network shows that a station amplification of 30 000, the network is able to record earthquakes with a magnitude slightly less than 2, with a tendency towards a decrease in this minimum magnitude, provided that the event is recorded by at least three stations. The errors in determining earthquake epicentral coordinates in latitude δφ (km) and longitude δλ (km) do not exceed 1–2 km in the center of the network, and 6 and 11 km on the periphery, respectively. The system's errors in determining the depths of earthquake sources H (km) do not exceed 5 km in the vicinity of the stations and 25 km throughout the territory of Karelia. [ABSTRACT FROM AUTHOR]

Much effort was taken to elucidate how organic precursors appeared in early Earth, and attention was paid to two impact experiments: hypervelocity impacts by a propellant gun which simulated meteorite collides to Earth forming fatty acids and amino acids from inorganics, and micro-impacts by a planetary ball-mill which formed ammonium and acetic acid from inorganics. Our extended study on micro-impacts showed the formation of carboxylic acids, amines, and amino acids from Fe3C/Fe4N, carbon, and carbonates/nitrates by milling up to 30 h at 40 G. Fe(CO2)2·2H2O accelerated the formation a step further. Cu addition caused superior capability to form amines and amino acids. Two reaction fields were disclosed. In the impact field, the hydration of ferrous materials generated hydrogen which hydrogenated inorganic carbons to organics and ferrous transient materials and, in the maturing field, hydrogenated materials were then transformed into complex organics. Iron and CO2 were presumably the key components in the Hadean Ocean. Discussions on the mechano-chemical reaction were extended to serpentinization coupled with diastrophism of oceanic crusts and further led to a depiction that organic precursors were formed by micro-impacts and frictions of rocks and sands (like milling-balls) due to tremors in crusts. It provides a new path on how organic precursors were formed on the aqua-planet Earth.

In this study, a new method was examined that used acoustic emission (AE) monitoring data, in combination with a primary Boundary Element stress analysis, to back-calculate rock mass strength. The presented AE data came from the National Radioactive Waste Repository (NRWR) for low- and intermediate-level waste (LLW/ILW). AE monitoring is able to detect the pre-peak, peak, and post-peak stress changes in rock mass. The presented method used AE monitoring data to back-calculate parameters, such as uniaxial compressive strength and the rock mass deformation modulus. The AE initiation threshold was used to develop an objective function that considered the stress in the rock mass and the rock mass strength. The findings of this research propose that most AE events can be related to the crack initiation threshold, and in space, most of them are located at points away from the excavated walls. In the vicinity of the excavation damage zones around the cavities, the stress conditions beyond the crack damage boundary of the rock mass occur in many areas, leading to significant irreversible deformations. This novel method was demonstrated to aid in the prediction of rock mass strength and is a valuable, non-invasive method for improving the spatial prediction of rock mass parameters, which will lead to safer underground storage facilities.

Some characteristics of the earthquake catalog and seismic process are considered. The catalog is obtained according to the KNET network (KN-code in FSDN, International Federation of Digital Seismograph Networks, that is operated by Research Station of RAS, RS RAS) and contains more than 10000 earthquake parameters from 1994 to 2020. The catalog and seismicity characteristics were determined the whole catalog as well as the catalog that is limited by the coordinates of the Bishkek geodynamic polygon (BGP). Statistical analysis of arrival times of direct P- and S-waves registered at KNET network stations was carried out. The maximum P- and S-waves were registered at AAK station, the minimum – at ULHL station. The territory of the BGP is covered by great P-traces density. We analyzed earthquake localization errors, i.e. the difference between the observed and calculated arrival times of P-and S-wave fronts (RMS), horizontal error (ERH, epicenter) and vertical error (ERZ, depth). Occurred on the BGP territory earthquakes have minimum values of the considered errors. The representative sample is defined: for the whole catalog it includes K≥7.2 earthquakes and for the limited by BGP coordinates catalog – K≥6.7. Statistical characteristics of the representative part of the catalog in terms of time and depth are determined. The temporal distribution of earthquakes by energy classes is constructed and the absence of positive or negative trends in the number of events is noted. Spatial distribution of earthquakes by depth – 0–5, 5–10, 10–15 and more than 15 km is constructed. The smallest errors of earthquake depth determination have the events that occurred on the BGP territory. During the study 46 moderate earthquakes with K≥12 occurred. The most part of these events happened in the North Tien Shan seismgenic zone. 22 events were determined with K≥10 followed by aftershock sequences and give some aftershock characteristics. The most events with aftershocks occurred in the eastern part of the Kyrgyz ridge. The distribution of earthquake numbers and STD intensity is constructed. Zones of seismic activity and maximum intense Earth’s crust deformation are identified. The Gutenberg – Richter law and provisions of nonextensive statistical physics were used to describe the energy distribution function of earthquakes.

Для землетрясений Камчатского региона и землетрясений в районе западной части Алеутско – Командорского желоба рассчитаны невязки между временем пробега волн P исходя из оценки времени в очаге и временем пробега в соответствии с моделью Земли AK135. Выявлено систематическое расхождение значений времен пробега, полученных этими способами, причем величина невязки меняется в зависимости от применяемого метода оценки параметров гипоцентров. Результаты сравнения отражают реальную оценку точности координат гипоцентров в каталогах. Проверка качества привязки сейсмических трасс к точному времени показало наличие сбоев синхронизации на сейсмограммах почти всех комплектов сейсмографов, что может быть одной из причин невязок.

The efficiency of the seismic station network on the territory of the Uda Volcanic Complex (UVC), which consists of 29 irregularly distributed instruments, was assessed. At different points of the UVC, earthquakes of different minimum energy classes were recorded with different accuracies. Calculation of the minimum energy classes for the UVC seismological network of 29 stations shows that, when the number of stations is magnified to ~30 000, such a network throughout the considered territory reliably detects earthquakes of 7.0 minimum energy classes, which corresponds to magnitudes of ~2.5. The errors in determining the earthquake epicentral coordinates in latitude (δφ) and longitude (δλ) within the network do not exceed 0.4 km. The errors in determining the depths of earthquake sources (H) in the center of such a network do not exceed 0.2 km, and within the entire territory of the UVC, 5.0 km. For these calculations, the errors in determining the travel time and propagation velocities of seismic waves were set equal to 0.1 s and 0.1 km/s, respectively, and could be both random and systematic. [ABSTRACT FROM AUTHOR]

According to the available data from the Kamchatka Regional Catalog, in the southwestern part of the Kamchatka region, deep earthquakes systematically occurred away from the main seismic focal zone. The paper shows that these anomalous events in the catalog are an artifact caused by the ambiguity of solutions for the hypocenters of earthquakes, which occur in the region located away from the seismic network. The results can be improved by eliminating the station data with the maximum residuals of the arrival times of the waves. Hypocenters were relocated for 102 deep earthquakes from an extended area covering anomalous events. Most of the new solutions lie within the Kamchatka seismic focal zone. The corresponding changes have been added to the Kamchatka regional catalog.

The paper discusses the results of the detection of seismic and infrasonic waves generated by a major earthquake and its aftershock (the moment magnitude MW=4.9 and MW=4.2 respectively), which occurred in northern Mongolia under Lake Hovsgool on December 5, 2014. The joint analysis of waveforms of seismic and infrasonic oscillations has shown that the signal recorded by the infrasound station of the Geophysical Observatory of the Institute of Solar-Terrestrial Physics SB RAS (ISTP SB RAS) is formed from sources of three generation types: local, secondary, and epicentral. This analysis enables us to propose a hypothesis of generation of epicentral infrasonic signal by flexural waves in an elastic ice membrane on the surface of Lake Hovsgool, which appear during the passage of seismic wave packets. This hypothesis explains the similarity between seismic and epicentral infrasonic signals, negative initial phase of epicentral infrasonic waves, and detection of a weak signal after a small-magnitude aftershock.

Magma intrusion usually causes seismicity and deformation in the surrounding rock and often leads to eruptions. A swarm of volcano-tectonic (VT) earthquakes associated with rapid dike intrusion in hours occurred beneath Sakurajima volcano on August 15, 2015. We determined the hypocenters and focal mechanisms of the VT earthquake swarm. The distributions of pressure (P)- and tension (T)-axes of the azimuths of the mechanisms are also obtained. The results indicate spatiotemporal changes of the distributions of the hypocenters and P- and T-axes. The hypocenters are distributed at depths of 0.3–1 km and 7:00–10:30 JST, and are located at depths of 0.3–3 km and 10:30–12:00 during which the seismic activity is the largest. At 12:00–24:00, the hypocenters are distributed in shallow and deep clusters at depths of 0.2–1 km and 1.5–3.5 km, respectively. The dike induced rapid ground deformation and is located between the shallow and deep clusters. The strike and opening directions of the dike are parallel to the NE–SW and NW–SE directions, respectively, corresponding to the regional maximum and minimum compression stress. The T-axes of the shallow cluster are distributed parallel to the opening direction of the dike. The P-axes of the deep cluster exhibit a pattern corresponding to the NE–SW direction and the T-axes are distributed in the NW–SE direction. In contrast, a 90° rotated pattern of strike-slip faulting is also observed at the deep cluster at 12:00–24:00, where the P-axes are distributed in the NW–SE direction and the T-axes are distributed in the NE–SW direction. This reflects the change in the stress field due to the dike inflation during the earthquake generation, and indicates that the alteration of stress in the vicinity of the dike due to the dike inflation and VT earthquakes are induced by the differential stress exceeding the brittle fracture strength of the rock. Future seismic and deformation observations in volcanoes will verify whether the spatiotemporal changes of the hypocenters and focal mechanism shown by this study are unique features of rapid dike intrusion.

From 26 April to 8 May 2020, an earthquake sequence occurred in the Haenam region in southwestern Korea. The main shock with a moment magnitude of 3.2 occurred on 3 May. It was preceded by 38 foreshocks that occurred over a week, with magnitudes ranging from 0.8 to 2.7, and was followed for another week by 35 aftershocks with magnitudes ranging from 0.5 to 2.4. The P-wave first-motion indicates that the focal mechanism of the mainshock was a strike of 193° or 102°, a dip of 83° or 78°, and a rake of –168° or –7°. The stress orientation of the focal mechanism is consistent with the regional tectonic stress field. Spectral analysis of the mainshock indicates that it occurred on a fault with a radius of 216 ± 4.58 m and a stress drop of 31.4 ± 2.35 bar. The hypocenters of the sequence, determined using the double-difference method, were shown to cluster along a trend striking 100° and dipping 65° to the south at a depth of 20.1 ± 0.05 km, which indicates that the earthquakes in the sequence occurred within a rupture radius of the mainshock. Detailed seismic analysis of the sequence indicates that closely located subfaults or small weak zones were related to the mainshock. [ABSTRACT FROM AUTHOR]

Abstrac—: The existing network of seismic stations in the North Caucasus consists of 37 instruments, but they are not evenly distributed on the territory. In this paper, we evaluated the effectiveness of this network, calculated and constructed maps of the distribution over the territory of the completeness of the energy class of recorded seismic events, and the error in determining the coordinates of their hypocenters. In general, the North Caucasian seismological network is quite effective. At different points in the region, earthquakes of different minimum energy classes and with different accuracy are recorded. In order for the observing system to record events occurring in different parts of the North Caucasus with the same accuracy and one minimum energy class, it is necessary that the seismic stations of the system be located more evenly throughout the territory; i.e., the observing system must have an optimal configuration. This optimal configuration was calculated, and the characteristics of the real and optimal networks were compared. Calculation of the minimum energy classes for the optimal magnification seismological network of the North Caucasus consisting of 32 seismic stations shows that with an increase of stations to 30 000, such a network throughout the territory of the North Caucasus confidently detects earthquakes of energy class 8.5 or greater, which corresponds to a magnitude of 2.5. At the same time, the position of seismic stations of the optimal network in the North Caucasus is determined accurate to a parallel shift and arbitrary rotation of the entire monitoring system. The error in determining the coordinates of earthquake epicenters in latitude and in longitude within the optimal network does not exceed 0.5 km. The error in determining the depths of earthquake sources in the center of such a network does not exceed 0.6 km, and throughout the territory of the North Caucasus it does not exceed 1.0 km. [ABSTRACT FROM AUTHOR]

It is necessary to have reliable data on the distributions of earthquake hypocenters in the study area to solve many geological and geophysical problems, in particular, the forecast of strong earthquakes, seismic zoning and earthquake-proof construction. In turn, the completeness of the data on the distribution of earthquake hypocenters and the accuracy of their determination largely depends on the effectiveness of the observing system. The efficiency of the modern Ukrainian network of seismological observations that consists of 28 stations is estimated in this article. By the effectiveness of the seismological observation network we mean the ability of the network to record events with minimal magnitudes at certain epicentral distances and allowing us to determine its main parameters (time in the focus and coordinates of hypocenters) with minimal errors depending on the position of the earthquake hypocenter. Calculation of the minimum magnitude of earthquakes for the Ukrainian seismological network shows if each seismic station increase of susceptibility to 50,000 units then the seismological the network confidently registers earthquakes with a magnitude of 3 or more throughout the Ukraine. The errors in the determination of the coordinates of epicenters of earthquakes in latitude (δφ) (km) and in longitude (δλ) (km) do not exceed 1.0 km in the center of the network and 5.0 km on the periphery of the network. The values of errors in determining the depths of the earthquake (H) (km) centers in the center of the network does not exceed 5.0 km but on the whole territory of Ukraine does not exceed 20 km. The optimal configuration of the network of Ukrainian seismic stations based on the C-criterion of optimality, introduced earlier to the theory design of optimal experiments by one of the authors of the article, is proposed. [ABSTRACT FROM AUTHOR]

Analysis was conducted of the seismic state of Dagestan and the safety of the Chirkey HPP for the effects of the activated earthquakes of 2013 – 2018 in the zone of the Chirkey reservoir. [ABSTRACT FROM AUTHOR]

Modelling of earthquake source locations and parameters infers seismogenesis of earthquakes. In this study, we modelled the earthquake source locations through hypocenter location algorithm using the difference in arrival time of P and S waves and source parameters through the Levenberg–Marquardt non-linear inversion method using S-wave spectra. A total of 340 aftershocks of 2001 Bhuj mainshock ( 1.8 ≤ M w < 4.3 ), which have occurred in Kachchh, Gujarat, India from January 2014 to January 2015, are located in this study. Out of 340 aftershocks, digital waveforms of 78 aftershocks ( 2.2 ≤ M w < 3.9 ) are used for estimation of the earthquake source parameters. The results obtained from earthquake locations show two clusters of seismicity along the Kachchh Mainland Fault (KMF) and North Wagad Fault (NWF) and three felt events ( M w ≥ 3.0 ); one along the Katrol Hill Fault (KHF) ( M w = 3.3 ), two along the Banni Fault (BF) ( M w = 3.0 , 3.2 ). The generation of these three felt events is attributed to the triggering mechanisms caused by the migration of fluids or the stress pulse generated by the 20 MPa stress drop of the Mw 7.7 Bhuj earthquake. A marked concentration of events is noticed in 15–30 km depth range, which could be attributed to the presence of a mafic intrusive body, resulting in stress build-up for earthquake generation in this region. The results of source parameters; seismic moment (M0), source radius (r) and stress drop (Δσ) vary from 1.86 × 1012 to 3.2 × 1015 N m, 146–262 m and 0.04–5.73 MPa, respectively. The maximum stress drop value is estimated to be 5.73 MPa at 24 km depth for the largest studied event of M w 3.9. Large stress drops are confined to the 8–33 km depth range, which indicates the probable existence of the base of the seismogenic layer in this depth range. This observed large stress drops could be attributed to stresses induced by crustal mafic intrusive bodies and the presence of aqueous fluids in the lower crust below the region. [ABSTRACT FROM AUTHOR]

For successful prediction of strong earthquakes, seismic risk zoning, and earthquake-resistant construction, it is necessary above all to have a sufficiently clear understanding of the hypocentral distribution of earthquakes in the area in question. In order to determine the position of earthquake foci with high accuracy, it is necessary to have an observation system capable of this. The modern seismological network in the Republic of Armenia (RA) essentially consists of two independent networks that barely interact with each other. Moreover, each network uses its own data processing methods (for determining hypocenters and travel-time curves). One network belongs to the National Seismic Protection Service under the Ministry of Emergencies of the Republic of Armenia (NSPS RA) and consists of 16 stations; the other is subordinate to the Institute of Geology of RA National Academy of Sciences (IG NAS RA) and hosts 14 seismic stations. Both networks are set up unevenly in the territory of Armenia, and each has its own disadvantages. The IG NAS RA network is sparser (with only 14 stations), and its stations are located only in northwestern Armenia. Therefore, it cannot accurately localize the hypocenters of earthquakes throughout the republic. The NSPS RA network consists of 16 stations. They are also located unevenly across Armenia, but at the same time, they encompass the southeastern part of the country. Calculations have been performed and maps compiled of the distribution of minimum energy classes and maximum errors in determining hypocentral coordinates of earthquakes recorded both separately by the IGN NAS RA and NSPS RA networks and by the integrated seismic network. It is shown that when the networks are combined, localization of earthquake hypocenters improves somewhat, but the territory between northwestern and southeastern Armenia remains virtually uncovered. This is because, at present, the stations of both existing networks, on the one hand, duplicate each other in some cases, while on the other, they are located unevenly across the territory. To obtain more accurate and reliable information, it is better to have a single network with be uniformly placed throughout the republic. [ABSTRACT FROM AUTHOR]

The total length of the seismic profiles in the northeastern regions ofRussiaand, accordingly, the area of the territories covered by the seismic data interpretations, remains insignificant in comparison with the total area of these regions. At the same time, the geological objects in the northeastern regions attract much attention in view of their prospects, including potential mineral resources. The challenge is to construct the regional models of the crust structure without deep seismic survey data, and to analyze the regional seismicity that depends on the features of the deep crust structure. We develop a density model of the crust structure using the new interpretational gravimetry method. The density modeling results show that the density changes in the crust can be used to estimate the position of a surface separating the lower (quasi-homogeneous) and upper (heterogeneous) parts of the crust, i.e. to assess the density boundary of stratification. This boundary is formed due to a complex of physical and chemical processes that facilitate the transition of the material in the lower part of the crust into the quasi-uniform (homogeneous) state. The study area is the junction zone of the Ayan-Yuryakh anticlinorium and Inyali-Debin synclinorium (62‒63°N, 148‒152° E). The initial interpretation of the deep seismic survey data on the reference geological-geophysical profile 3-DV was available, so the ambiguity of the density modeling was reduced. In turn, the density modeling results can provide additional information for geological-geophysical interpretation of the DSS results on the sites wherein the seismic profiles go along the fault zones. The relationship between seismic events and the relief of the density boundary of stratification in the crust was studied quantitatively on the basis of the data from the regional catalog of seismic events and the results of the earlier analysis of seismicity in the study area. The analysis shows that 74 % hypocenters are located above the density boundary of stratification. The earthquake hypocenters located at depths ranging from 20 to35 kmare usually confined to the systems of long-living regional crustal faults and occur below the density boundary of stratification. The energy class of such earthquakes does not exceed9. Inthe study area, the seismically active zones are mainly confined to the areas of subduction of the density boundary of stratification. Most of the earthquake epicenters (80 %) occur in the zones where the gradient of the relief change of the density boundary does not exceed 1. The number of recorded seismic events practically reduces to zero in the regions where the dip angle of the density boundary exceeds 65°.

A significant increase in the number of volcano-tectonic (VT) and VB earthquakes preceded the 2007 and 2014 eruptions of Kelud volcano, Indonesia. The background seismicity rates at the volcano is generally <5 of VTs per month and other types of volcanic earthquakes are rarely recorded. After 17 years of quiescence, the 2007 eruption was preceded by an increase in VTs starting in September 2007, two months prior to the eruption. An intense VT swarm began in October 2007 and led to occurrence of VB, sometimes presenting as repetitive self-similar events. The final precursory seismicity included spasmodic bursts of VTs, repetitive self-similar VBs and low frequency tremor, prior to lava dome formation in the crater lake, on November 3, 2007. After just ~6 years, VTs began to increase again in December 2013. The number significantly intensified in mid January 2014, ~1 month before the eruption. Seismicity continued to intensify including VTs, VBs, and LFs into February 2014, with the final precursory seismicity consisting of a burst of over scale tremor, followed by a short burst of repetitive self-similar events that merged into harmonic, gliding tremor a couple hours prior to the explosive eruption on February 13, 2014. We examine the locations of VTs, the energy release rate, and the precursory seismic pattern prior to both eruptions to understand the differences in the eruptions' style and size. We found that epicentral locations of VTs are similar for both eruptions, but the depths were slightly deeper prior to the 2014 eruption. We also find that the cumulative energy released prior to 2014 is twice that of 2007 and in half the time. The migration of VTs in Kelud volcano may indicate magma intrusion from a deeper storage region in 2014 and at a faster rate, leading to a much more explosive eruption. • A significant increase on VT earthquake leads to effusive eruption and explosion eruptions of Kelud volcano, Indonesia. • Magnitudes of the VTs were larger in 2014 than in 2007. • The cumulative seismic energy released by VTs in 2014 is twice that of 2007, and occurred in half the time. • The rate of cumulative seismic energy release is greater in 2014 and the resulting explosion was greater (VEI 4 vs VEI 2). [ABSTRACT FROM AUTHOR]

Most of the world's explosive volcanoes are located in volcanic arcs, formed by fluid-fluxed melting of upper mantle rocks. The fluids that facilitate melting are released from subducted tectonic plates as they sink into the mantle. Yet, we have sparse knowledge of the migration pathways of melts through the upper mantle (i.e., between the surface of the subducted plate and arc volcanoes). We are also uncertain of the time required for this migration to occur. Here, we show evidence of two earthquake swarms that occur in the upper mantle beneath the Mariana and Izu-Bonin arc systems. The best-resolved swarm occurs beneath the Mariana arc, where the earthquakes define a sub-vertical pipe-like structure with a diameter of ∼50 km and occurs between depths of ∼10–250 km. To test the robustness of depth locations, we used a fully non-linear grid search algorithm, double-difference relocation, as well as an analysis of pP-P arrival times and depth sensitive phases. In addition, we calculated centroid moment tensor solutions using a 3D Earth model to understand the mechanism of failure within the swarms. These data demonstrate that the sub-vertical earthquake swarm occurs within the upper mantle between the subducted slab and the overriding volcanic arc, with seismicity concentrated within discrete day- to month-long swarms of activity over a single two-year period. The Izu-Bonin example shares a similar sub-vertical pipe-like geometry with seismic activity bracketed within a two-year period. We infer that these rare earthquake swarms record the ascent of hydrous melt and/or fluid, from dehydration of the subducting plate. This implies that hydrous minerals within subducted slabs continue to dehydrate to depths of at least 200–250 km. Also, the short duration of earthquake swarms implies that fluids/melts can be rapidly transported through the sub-arc mantle at rates in the order of km/hr. This is consistent with rapid melt ascent rates inferred from geospeedometry and experimental petrology and is reminiscent of patterns seen during episodic tremor and slip events. • Definitive evidence of earthquakes occurring within sub-arc mantle ('mantle wedge'). • The earthquakes delineate the path of fluid/melt ascent above the subducted slab. • Earthquakes occur as day- to month long swarms, but all within a two-year period. • These earthquakes may provide insight into the rate of sub-arc fluid/melt transport. [ABSTRACT FROM AUTHOR]

Analysis was conducted of the seismic state of Dagestan and the safety of the Chirkey HPP for the effects of the activated earthquakes of 2013 – 2018 in the zone of the Chirkey reservoir. [ABSTRACT FROM AUTHOR]

A new approach is proposed for determining earthquake hypocenters aimed at a more comprehensive characterization of its uncertainty and ambiguity. Application of the new approach to study the seismic focal subduction zones and volcanic seismicity is discussed by the example of the data of the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences. [ABSTRACT FROM AUTHOR]

The modern seismological network of the Caucasus contains a little more than 300 seismic stations. Despite the fact that the number of stations is rather large, they are not uniformly distributed over the territory of Caucasus. Therefore, although the Caucasian seismological network is quite effective in general, earthquakes with different minimum energy classes and different accuracy are recorded at different points. To ensure that the observation system records seismic events occurring at different points of the Caucasus region with the same accuracy and with one minimum energy class, it is necessary that the system's seismic stations be located more uniformly over the territory; i.e., the observation system should have an optimal configuration. Calculation of the minimum energy classes for the optimal seismic network of Caucasus, which included 55 seismic stations, shows that at 50 000 magnification of all stations, the system will reliably record all earthquakes of the energy class K = 9 (which corresponds to a magnitude of M = 2.6) of more in the entire territory of the Caucasus. The errors in determining the epicentral coordinates of earthquakes in latitude and longitude within the limits of the network will not exceed 1.0 km. The errors in determining the depths of earthquake will not exceed 1.0 km in the central part of the network and 10 km in the entire Caucasus. [ABSTRACT FROM AUTHOR]

Copyright of Diyala Journal for Pure Science is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To solve multiple geological and geophysical problems, in particular, the forecast of strong earthquakes, seismic zoning, and earthquake-resistant engineering, it is necessary to have reliable data on the distribution of earthquake hypocenters in the study area. In turn, the completeness of data on distribution of earthquake hypocenters and the accuracy of their determination largely depends on effectiveness of the observational system. This article assesses the effectiveness of the Caucasian seismological network consisting of 258 stations. The effectiveness of the seismological network means network ability to record seismic events with minimal magnitudes at certain epicentral distances and to provide, depending on hypocentral location of an earthquake, determination of the main earthquake parameters (time in the source and coordinates of hypocenters) with minimal errors. Calculation of the minimum energy classes (threshold) for the seismological network shows that if all Caucasus stations would have magnification of 30 000, the network would confidently record earthquakes of the 9th energy class and higher, which corresponds to a magnitude of 2.8. The errors in determination of epicentral coordinates of earthquakes on latitude and longitude do not exceed 0.4 km in the center of the network, and 1.0 km in the network periphery. The values of errors in determining depths of earthquake sources by the seismological network do not exceed 1.0 km in its center, and 10 km in the entire Caucasus region. [ABSTRACT FROM AUTHOR]

Previous results on the location of crustal earthquake foci in the Caucasus clearly show that the methods used in seismic service practice to determine the hypocenters of earthquakes do not allow accurate localization of events and can hardly be used to forecast earthquakes or study the structure of the Earth's crust and upper mantle in detail. The arrival times of seismic waves often have large errors that prevent qualitative processing of observations and, therefore, is is difficult to obtain reliable results. In addition, the use of only one velocity curve or one set of travel-time curves for all stations of the network hinders accurate determination of the location of earthquake hypocenters. In order to localize earthquake foci with high precision, it is also necessary to have a sufficiently detailed representation of the structure of the Earth's crust and upper mantle in the studied region. It is also desirable to take information about the structure of the region not from earthquake data, but based on other observations, e.g., deep seismic sounding (DSS) data. Using seismological bulletins for 1970–2015, we have redetermined the hypocentral coordinates of crustal earthquakes in the Caucasus. The new distribution of crustal earthquake hypocenters in the Caucasus differs significantly from the old distribution obtained from the catalog. This may become the basis for refining ideas about the regional geodynamics. [ABSTRACT FROM AUTHOR]