Continuous long-term array analysis of seismic records observed during the 2011 Shinmoedake eruption activity of Kirishima volcano, southwest Japan
© The Society of Geomagnetism and Earth, Planetary and Space Sciences (SGEPSS); The Seismological Society of Japan; The Volcanological Society of Japan; The Geodetic Society of Japan; The Japanese Society for Planetary Sciences; TERRAPUB 2013
Received: 30 October 2012
Accepted: 4 March 2013
Published: 8 July 2013
We deployed a seismic array at a site 5 km east of Shinmoedake volcano, in the Kirishima volcanic complex of southwest Japan, five days after the sub-Plinian eruption on 26 January, 2011. The array record between February and September 2011 included explosion earthquakes and episodes of weak continuous tremor during eruption periods. We estimated slownesses and back azimuths of seismic waves on a sliding 1-min window using the semblance method. The slownesses of the weak continuous tremor clustered within the range 0.2–0.8 s/km, consistent with a mix of body and surface waves. A probabilistic approach based on a grid search was used to estimate the source locations of the explosion earthquakes and weak continuous tremor. The sources of the explosion earthquakes were beneath the crater at depths of −0.5–1 km above sea level, while the source of the weak continuous tremor was beneath the northern part of Shinmoedake at depths between 1 km below sea level and 1 km above sea level. This latter region corresponds to a shallow low-resistivity layer, suggesting that hydrothermal processes are more plausible than magmatic processes as the generating mechanism of the weak continuous tremor.
Volcanic tremor is a seismic signal commonly observed at active volcanoes during quiescent and eruptive stages (e.g., Chouet, 1996; Konstantinou and Schlindwein, 2002). Various models have been invoked to explain its source mechanisms (e.g., Chouet, 1986; Julian, 1994; Jellinek and Bercovici, 2011), all involving interaction between hydrothermal or magmatic fluids and their host rocks. Explosion earthquakes are seismic signals excited by explosive-type (e.g., Vulcanian or Plinian) eruptions (e.g., Kanamori et al., 1984; Nishimura and Hamaguchi, 1993; Tameguri et al., 2002). Therefore, the quantitative analysis of seismicity is a fundamental step toward a better understanding of the dynamics of volcanic processes.
The first step is to locate the origin of seismic signals from volcanoes. Because of the lack of clear body-wave phase arrivals and the rapid loss of signal coherence with distance, tremor and explosion earthquakes cannot be precisely located using conventional hypocenter determination methods based on phase arrivals. However, seismic arrays have been used successfully to locate tremor and explosion earthquake sources at a number of volcanoes, such as Colima (Palo et al., 2009), Etna (Di Lieto et al., 2007), Hawaii (Goldstein and Chouet, 1994; Almendros et al., 2001b), Izu-Ohshima (Furumoto et al., 1990), and Stromboli (Chouet et al., 1997; Saccorotti et al., 1998; La Rocca et al., 2004). We deployed a seismic array to observe and locate tremor episodes and explosion earthquakes of Shinmoedake volcano, beginning after the sub-Plinian eruption of 26 January, 2011, and continuing to the present.
In this paper, we report our array analysis of continuous waveform data from the period February to September 2011 to detect coherent waves from the volcano. Using a probabilistic method to locate explosion earthquakes and tremor, we offer some insight into the probable source process of tremor. Given that explosion earthquakes can be assumed to originate in the shallow part of the erupting crater, we also evaluate the location of tremor by comparison with the location of explosion earthquakes.
2. Seismic Array Observation and Data
We deployed a small-aperture seismic array, consisting of 16 stations, on the east flank of the Kirishima cluster on 30–31 January, 2011, at a site 5 km east of the active crater of Shinmoedake (Fig. 1). The site has a relatively smooth topography with gentle slopes, allowing the array to be set up on a roughly planar ground surface. The elevations of seismometers are between 660 m and 700 m above sea level. The aperture of the array is 400 m. The 40 m difference in sensor elevation is not significant for seismic array analysis as it is an order of magnitude smaller than the aperture. The relative positions of all array components were determined by GPS with an accuracy on the order of 10−2 m, and the precision of their absolute locations was 0.5 m. Each station has a three-component Sercel L-22D seismometer with a natural frequency of 2 Hz and a sensitivity of 60 V/m/s. Signals from the seismometers were recorded by Keisokugiken HKS-9550 data loggers, which are 24-bit recorders storing data at 200 samples per second per channel. We used data from 15 of the 16 seismic stations, discarding data from the station (gray circle in Fig. 1(b)) that had timing problems (M. Nakamoto, personal communication on 22 July, 2012). The directional sensitivity and resolution power of the array are described by the beam-forming array response at 2.5 Hz in Fig. 1(c). There was no distinct side lobe in the array response.
3. Array Analysis of Continuous and Explosion Earthquake Records
We used the semblance technique (Neidell and Taner, 1971) to measure apparent slownesses and back azimuths of the coherent wave phases that crossed the array. We calculated the semblance values for the selected array data at all the apparent slowness and back azimuth grid nodes. The position of the nodes with the maximum semblance value provides an estimate of the apparent slowness and back azimuth of the incoming wavefronts. The method works in the time domain, giving an advantage over techniques based on Fourier transforms in that the results are less sensitive to the length of the signal time window selected for the analysis (Almendros et al., 1999). This method requires much more computer time than frequency domain techniques, but less than the zero-lag cross-correlation technique (Frankel et al., 1991).
The semblance analysis was performed on the vertical component of the seismograms. After the waveform data were filtered using a bandpass filter of 2–3 Hz, the semblance coefficient was calculated for a time window of 0.5 s. This window length, determined after trying several values and observing the dependence of the results, was chosen because it guaranteed stable results and was greater than the one-cycle period at the middle of the dominant frequency band. We performed a continuous long-term array analysis, in which the time window started from the beginning of a continuous waveform 1 h long and was moved successively by the length of 0.125 s until the end of the waveform, repeated for each 1 h continuous record in the observation period from 1 February to 30 September, 2011. We adopt the time shift length to reduce necessary computation time and to obtain enough time resolution for the wave propagation parameters.
The range of apparent slowness was searched from 0.05 to 3.00 s/km in steps of 0.05 s/km, and the range of back azimuth was searched from 0° to 355° (measured clockwise from north) in 5° steps over this continuous long-term analysis. We extracted the waveforms of nine explosion earthquakes that occurred during the observation period. For the analysis of these earthquakes, we adopted the same time window and time increment but finer step intervals: 0.01 s/km steps for apparent slowness and 1° steps for back azimuth.
4. Seismic Signatures and Results of Array Analysis of Explosion Earthquakes
5. Results of Continuous Long-Term Array Analyses andDetectionofWeakContinuousTremor
6. Source Locations of Explosion Earthquakes and Weak Continuous Tremor
The standard deviation σ includes the uncertainties in the estimate of observed and predicted slowness vector components. Although the predicted uncertainty depends on the velocity structure (Saccorotti and Del Pezzo, 2000), we only consider here the standard deviation for the observed slowness. We calculate the standard deviations for the observed slownesses in the P and S time windows of the explosion earthquake, as shown in Fig. 3, to be 0.025 and 0.04 s/km, respectively. For safety’s sake, we adopt twice the standard deviations as σ P = 0.05 s/km and σ S = 0.08 s/km, which are slightly larger than those used for locating explosion earthquake sources at Stromboli (Saccorotti et al., 1998; Saccorotti and Del Pezzo, 2000; La Rocca et al., 2004).
As described in Section 4, the means of the apparent slownesses and back azimuths for P waves of the explosion earthquakes were 0.3 s/km and 260°, respectively, which we used to locate their sources. As shown in Section 5, the apparent slownesses and back azimuths of tremor corresponded to a mix of body and surface waves. It is difficult to discriminate phases of tremor for assigning wave types to the estimated apparent slowness. We assumed an apparent slowness of 0.4 s/km, corresponding to S waves, which is comparable to the slowness of 0.35–0.39 s/km for S waves from the explosion earthquakes (Fig. 3). We adopted the back azimuth of 265° for locating the source of the tremor.
As seen in Figs. 7–9, the propagation parameters of the tremor were somewhat scattered. The causes of the scatter may include the action of multiple nonisotropic sources, measurement errors associated with departure from the plane-wave assumption, severe ray bending associated with medium heterogeneities, and focusing effects resulting from free-surface interactions related to the volcano topography (e.g., Ripperger et al., 2003). Assessing all these effects would require inverting the estimated propagation parameters using theoretical slowness fields obtained from wavefield simulations in three-dimensional, heterogeneous media, and including the free-surface effect of topography (e.g., Almendros et al., 2001a). However, that task is unfeasible without information on the velocity structure at a scale comparable to the wavelengths analyzed in this study.
7. Discussion and Conclusions
As shown in Section 6, a high-likelihood region for the tremor source is shallower than 1.5 km below the northern part of Shinmoedake (Fig. 11). This region corresponds to the low-resistivity layer, suggesting that hydrothermal processes are more plausible than magmatic processes as the generating mechanism of the tremor. The magma transport path would be between the estimated pressure source region and the summit of Shinmoedake, because that is where the significant deflation of the volcano associated with the 26
January sub-Plinian eruption occurred (Japan Meteorological Agency, 2012b). The volatiles that exsolved from the magma would enter the water-saturated porous layer. Furthermore, the magma may encounter groundwater and supply some of its heat to the hydrothermal system. Several models for the tremor source involve fluids-water, magma, exsolved volatiles, or all three (e.g., Kumagai and Chouet, 2000; Fujita et al., 2004; Iwamura and Kaneshima, 2005). Tremor caused by boiling of water is generally weaker than tremor involving magma movement (McNutt, 1996). Therefore, the weak continuous tremor may originate in the heated water-saturated layer.
Volcanic tremor frequently occurs as a precursor of eruptions as well as accompanying eruptions. A clear relationship between tremor and eruptions is seen in our study period from February to September 2011 (Figs. 8 and 9), although the relationship is unclear in middle and late March 2011, when seismic waves from the 11 March, 2011, To-hoku earthquake and its large aftershocks affected the continuous long-term array analysis. The synchronization of weak continuous tremor and eruptions suggests that hydrothermal activity is also activated by magma transport during eruption periods.
In conclusion, we used a single seismic array to locate weak continuous tremor in the Kirishima group and evaluate its activity. However, the deployment of several seismic arrays compensates for the limited quality of individual slowness measurements and possible structural effects on the wave field, enabling successful estimates of the locations of volcanic tremor and earthquakes with emergent initial phases (Métaxian et al., 2002). Therefore, a multi-array analysis is required to better determine the source locations of the tremor and emergent earthquakes. A probabilistic approach using a three-dimensional (3D) velocity structure is efficient in constraining source locations of explosion earthquakes and tremor (Almendros et al., 2001a, b; La Rocca et al., 2004). The next stage of seismic array observation at volcanoes, then, would use multiple arrays and a 3D velocity structure for the array analysis. Furthermore, the procedure described in this study, which requires limited computing time, can be adapted to real-time volcano monitoring, in which data from a seismic array are transmitted from seismometers to a central office in real time. These advances will contribute to our understanding of magmatic systems and our ability to forecast eruptive activity.
Manami Nakamoto informed us of the timing problem for a station in our seismic array. Jun Oikawa kindly provided the one-dimensional velocity structure used in the Kirishima Volcano Observatory, Earthquake Research Institute, University of Tokyo. Tsuyoshi Watanabe calculated the positions of seismometers using GPS data. We are grateful to Takao Ohminato, an anonymous reviewer, and the guest editor Motoo Ukawa for reviewing our manuscript and valuable comments. This work was partially supported by the Japanese Society for the Promotion of Science Institutional Program for Young Researcher Overseas Visits. This work was partly completed at the University of Bristol during a six-month stay by HN as a visiting fellow in 2011. This study was supported by a Grant-in-Aid for Special Purposes (Grant Number 22900001) from the Ministry of Education, Culture, Sports, Science and Technology.
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