S. L. Senyukov

The system of detailed seismological observations in Kamchatka in 2011

This paper presents the main results from the development of the detailed seismological observation system in Kamchatka and the information on the system as of 2011. We describe the networks of seismological stations, the systems for the acquisition, storage, and processing of seismological observations and their technical, methodological, and software support. We discuss the basic characteristics of the recording channels and the system as a whole. We present the information resources of the Kamchatka seismological data bank that provide for basic research in earth sciences. In 2011, the system of seismological observation in Kamchatka was a specialized network for acquisition (recording), storage, transmission, and processing of seismic and geophysical data that provides support for the effective monitoring of seismic and volcanic activities, as well as tsunami warning.

Studies in the activity of Klyuchevskoi volcano by remote sensing techniques between January 1, 2001 and July 31, 2005

The Kamchatka Branch of the Geophysical Service (KB GS) of the Russian Academy of Sciences (RAS) has been observing the activity of Kamchatka volcanoes since 2000 in near real time using three methods: (1) seismicity monitoring (2) visual and video observations, and (3) satellite monitoring of thermal anomalies and ash discharges. The joint use of these data provides objective information on the state of the volcanoes from which to predict possible eruptions. During the period of time investigated, which culminated in the eruptions of March 10, 2003 to February 27, 2004 and January 12, 2005 to April 28, 2005, two active periods of Klyuchevskoi Volcano were identified. The results from our study of the first of these periods helped define an approximate scenario for the activity of the volcano before a summit eruption. The use of this experience in combination with an analysis of the literature enabled us to produce a successful short-term forecast of the January 2005 eruption.

Seismically active subcrustal magma source of the Klyuchevskoy volcano in Kamchatka, Russia

Klyuchevskoy volcano in Kamchatka (Russia) is unique in the island arc systems of Earth in having nearly continuous seismic activity beneath it at depths in excess of 20 km. Seismograms from these deep earthquakes carry an unmistakable signature of their tectonic nature. We use P-to-S (compressional to shear) converted teleseismic waves to constrain the depth of the crust-mantle transition beneath Klyuchevskoy at ~25 km, and to delineate a deeper seismic boundary at ~50 km. Earthquakes directly beneath Klyuchevskoy have hypocentral depths of 25–35 km. S-P delays in records of these earthquakes are always larger than delay times of P-toS converted waves originating at the crust-mantle transition and traversing nearly identical paths. Thus, deep seismic activity under Klyuchevskoy is definitely beneath the crust-mantle transition. Compositions of the Klyuchevskoy parental melts (inferred from melt inclusions and the most primitive lava) interpreted using a barometer based on Si activity in melts saturated with orthopyroxene + olivine show that Klyuchevskoy parental melts form at pressures within the range of 13.9 (±2) kbar (at depths of 46 ± 7 km). Together, the estimates of melting depths, the locations of seismic velocity features, and the occurrence of tectonic earthquakes all point to the existence of a subcrustal volume beneath Klyuchevskoy volcano where processes of magma accumulation are vigorous enough to promote brittle failure in mantle rock.

Monitoring and prediction of volcanic activity in Kamchatka from seismological data: 2000–2010

Seismological Observations in Kamchatka were significantly improved due to the installation of new telemetered seismic stations near active volcanoes and the implementation of modern digital technologies for data transmission, acquisition, and processing in 1996–1998. This qualitative leap forward made it possible, not only to create an effective system for monitoring Kamchatka volcanoes and for timely and reliable assessment of the state of these volcanoes, but also to draw conclusions about volcanic hazard. The experience that was gained allowed us to make successful short-term forecasts for eight moderate explosive eruptions on Bezymyannyi Volcano of the ten that have occurred in 2004–2010, successful intermediate-term forecasts of evolving activity on Klyuchevskoi Volcano in three cases, as well as providing a successful forecast of an explosive eruption on Kizimen Volcano.

Seismic activity at Koryakski volcano in 1994: hybrid seismic events and their implications for forecasting volcanic activity

Abstract A small swarm of 80 earthquakes was observed beneath Koryakski volcano between March 1 and May 31, 1994. These earthquakes ranged from 0 to 8 km in depth and from −2.0 to 1.5 in magnitude (ML). The swarm under Koryakski volcano was primarily of volcano–tectonic character although a special type of event has been identified with a small amplitude signal preceding the P-wave onset. These precursory signals had varying durations ranging between a few seconds and a few tens of seconds. The source of the signal invariably coincided with the hypocenter of the subsequent earthquake. The origin of these signals may be conjectured to be magma emplacement into weakened zones, which generated a rupture giving rise to a normal tectonic earthquake. The existence of this kind of signals may indicate magmatic activity under the volcano and provide a method for estimating futher development of volcanic activity.

The dynamics of the velocity field beneath the North group of volcanoes, Kamchatka, and its relationship to the evolution of volcanic activity

P- and S-wave travel times from local volcanic earthquakes recorded in the North group of volcanoes area during the 2005–2009 period were treated by the “reverse wave” method to calculate the VP velocity field and the TAU parameter, which is an analogue of the P- to S-wave velocity ratio. We constructed 3D velocity distributions along the line traversing the volcanic group along the direction from Ploskii Tolbachik Volcano in the southwest toward Shiveluch Volcano in the northeast. Dynamic changes in the velocity field were identified, both over time and depth. We examine the relationships of these dynamic changes to the evolution of volcanic activity during the period indicated.

ADAP software for automatic detection of ash emission at active volcanoes and calculations of ash plume height using seismological data

ADAP (Automatic Detection of Ash Plume) software intended for automatic detection of the seismic signals accompanying ash emission at the active volcanoes is designed and introduced. This software also calculates the height of the ash plume in real time and automatically sends information on the detected hazardous ash emissions by e-mail and SMS to scientists on duty. The reliability of the program is estimated at 70%. The program has no current analogues.

S -wave velocity model for several regions of the Kamchatka Peninsula from the cross correlations of ambient seismic noise

The data from the seismic networks of the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences are used for calculating the cross correlations of seismic noise for the stationary digital stations over 2013 and for radio telemetric stations (RTS) in the region of the Klyuchevskoy volcano over the period from January 1, 2009 to May 31, 2013. Four hundred and two correlations overall are calculated. The fundamental-mode group velocities of the Rayleigh waves are calculated in the periods ranging from 5 to 50 s. The calculations for the region of the Klyuchevskaya group of volcanoes are based on the RTS data and cover the periods from 2 to 8 s. The two-dimensional (2D) maps of group velocity distributions in different periods are constructed with the use of the algorithm of surface wave tomography (Barmin, 2001). The velocity sections for the selected Kamchatka regions are reconstructed by the dispersion curve inversion technique (Mordret, 2014). For each region, the structure of the Earth’s crust and upper mantle down to a depth of 50 km was obtained.

The development of the system of integrated instrumental monitoring of volcanoes in the Far East Region

This work presents the project of the first stage of implementation of the integrated instrumental system of volcanic activity monitoring in Kamchatka and the Kuril Islands. The system of monitoring was designed for the purpose of ensuring public safety, aviation safety, and reducing economic losses caused by volcanic eruptions. The most active and dangerous volcanoes in Kamchatka (North and Avacha groups of volcanoes) and the Kuril Islands (volcanoes on the islands of Kunashir and Paramushir) are of first priority for monitoring. For this purpose, special observation points are planned to be installed on the volcanoes. The system of monitoring will include a complex of observations (broadband seismic station with a large dynamic range, tiltmeter, devices for gas, acoustic, and electromagnetic observations, and video camera). All the data will be passed to information processing centers in real time. New methods and algorithms of automatic and automated identification of the volcanic activity level and the probabilistic volcano hazard assessment have been developed.

Network-based detection and classification of seismo-volcanic tremors: example from the Klyuchevskoy volcanic group in Kamchatka: NETWORK-BASED CLASSIFICATION OF TREMORS

We develop a network-based method for detecting and classifying seismovolcanic tremors. The proposed approach exploits the coherence of tremor signals across the network that is estimated from the array covariance matrix. The method is applied to four and a half years of continuous seismic data recorded by 19 permanent seismic stations in the vicinity of the Klyuchevskoy volcanic group in Kamchatka (Russia), where five volcanoes were erupting during the considered time period. We compute and analyze daily covariance matrices together with their eigenvalues and eigenvectors. As a first step, most coherent signals corresponding to dominating tremor sources are detected based on the width of the covariance matrix eigenvalues distribution. Thus, volcanic tremors of the two volcanoes known as most active during the considered period, Klyuchevskoy and Tolbachik, are efficiently detected. As a next step, we consider the daily array covariance matrix’s first eigenvector. Our main hypothesis is that these eigenvectors represent the principal components of the daily seismic wavefield and, for days with tremor activity, characterize dominant tremor sources. Those daily first eigenvectors, which can be used as network-based fingerprints of tremor sources, are then grouped into clusters using correlation coefficient as a measure of the vector similarity. As a result, we identify seven clusters associated with different periods of activity of four volcanoes: Tolbachik, Klyuchevskoy, Shiveluch, and Kizimen. The developed method does not require a priori knowledge and is fully automatic; and the database of the network-based tremor fingerprints can be continuously enriched with newly available data.