Volcano-tectonic Research Articles

A Bayesian reassessment of the relationship between seismic moment and magmatic intrusion volume during volcanic unrest

Volcano-tectonic (VT) earthquake swarms are usual precursors to volcanic eruptions and their dynamic phenomenologies are an invaluable eruption forecasting tool. A power-law relationship between cumulative seismic moment release and intrusion volume has been proposed for both well injection sites and VT swarms. Here we compile data from 17 geodetically-studied VT swarms and use a Bayesian methodology to assess the relationship between cumulative moment release and subsurface volume change. We find that the empirical relationship derived from injection sites systematically underpredicts volume changes observed during VT swarms near volcanoes. A new relationship derived specifically from VT swarms provides a better fit, but large uncertainties mean that estimates of intruded volume range by three orders of magnitude (95% confidence) for a given cumulative seismic moment release. We further subdivide the dataset, and although the sample size is too small to meet conventional statistic hypothesis significance tests, qualitative inspection suggests that the seismic moment release is proportionally larger for unrest swarms which culminate in eruption. We conclude that the currently available dataset is too sparse and the uncertainties too large for use for reliably forecasting eruption magnitude; however, as the dataset of cases grows, further analysis along these same lines may provide improved diagnostic insights into eruption-related processes that may be driving seismic moment release in VT swarms.

Monochromatic Long-Period Seismicity Prior to the 2012 Earthquake Swarm at Little Sitkin Volcano, Alaska

Detection of the earliest stages of unrest is one of the most challenging and yet critically needed aspects of volcano monitoring. We investigate a sequence of five unusual long-period (LP) earthquakes that occurred in the days prior to the onset of a months-long volcano-tectonic (VT) earthquake swarm beneath Little Sitkin volcano in the Aleutian Islands during late 2012. The long-period earthquakes had two distinctive characteristics: their signals were dominated by a monochromatic spectral peak at approximately 0.57 Hz and they had impulsive P and S-wave arrivals on a seismometer located on Amchitka Island 80 km to the southeast of the volcano. In each case, the monochromatic earthquakes ended with a higher-frequency event after approximately 2 min of duration. We find evidence that the five monochromatic LP earthquakes resulted from the resonance of a tabular magma body at middle crustal depths (15 km) on the western side of Little Sitkin. Based on the resonant frequency and quality factor of the monochromatic LP earthquakes, we infer the magma body to have a lateral extent of 500 m and a thickness of 9 m. We interpret that a magmatic intrusion excited the monochromatic LP earthquakes and subsequently increased the stress beneath the volcano, leading to the onset of the shallow (<10 km depth) VT swarm five days later.

LP or VT signals? How intrinsic attenuation influences volcano seismic signatures constrained by Whakaari volcano parameters

Long Period (LP) seismicity is considered a key indicator of fluid migration in the volcanic edifice, with a source mechanism typically ascribed to fluid resonance in the volcano conduit and fractures. Our viscoelastic numerical wave propagation models at laboratory and field scales are based on quantitative estimates of wave speeds and intrinsic attenuation from Whakaari rocks saturated with a range of fluid types. Such models display path effects in homogeneous and layered media that influence the frequency content and duration of the seismic waveforms. We find that volcano-tectonic (VT) earthquakes can resemble short-duration LP events when propagating through fully or partially gas-saturated ash tuff deposits. Meanwhile, in a shallow volcanic subsurface comprising low-velocity, attenuative ash tuff and high-velocity, low-attenuation lava layers, VT signals may be distorted to resemble long-duration LP events. Such geological models are built based on interpretations of the shallow hydrothermal system at Whakaari volcano, and discussed in the context of other volcanoes around the world.

Evolution of Seismicity During a Stalled Episode of Reawakening at Cayambe Volcano, Ecuador

Cayambe Volcano is an ice-capped, 5,790 m high, andesitic-dacitic volcanic complex, located on the equator in the Eastern Cordillera of the Ecuadorian Andes. An eruption at Cayambe would pose considerable hazards to surrounding communities and a nationally significant agricultural industry. Although the only historically documented eruption was in 1785, it remains persistently restless and long-period (LP) seismicity has been consistently observed at the volcano for over 10 years. However, the sparse monitoring network, and complex interactions between the magmatic, hydrothermal, glacial, and tectonic systems, make unrest at Cayambe challenging to interpret. In June 2016 a seismic “crisis” began at Cayambe, as rates of high frequency volcano-tectonic (VT) earthquakes increased to hundreds of events per day, leading to speculation about the possibility of a forthcoming eruption. The crisis began 2 months after the Mw7.8 Pedernales earthquake, which occurred on the coast, 200 km from Cayambe. Here we show that the 2016 seismicity at Cayambe resulted from four distinct source processes. Cross correlation, template matching, and spectral analysis isolate two source regions for VT earthquakes–tectonic events from a regional fault system and more varied VTs from beneath the volcanic cone. The temporal evolution of the LP seismicity, and mean Q value of 9.9, indicate that these events are most likely generated by flow of hydrothermal fluids. These observations are consistent with a model where a new pulse of magma ascent initially stresses regional tectonic faults, and subsequently drives elevated VT seismicity in the edifice. We draw comparisons from models of volcano-tectonic interactions, and speculate that static stress changes from the Pedernales earthquake put Cayambe volcano in an area of dilation, providing a mechanism for magma ascent. Our findings provide a better understanding of “background” seismicity at Cayambe allowing faster characterization of future crises, and a benchmark to measure changes driven by rapid glacial retreat.

Use of Local Seismic Network in Analysis of Volcano-Tectonic (VT) Events Preceding the 2017 Agung Volcano Eruption (Bali, Indonesia)

This study provides an attempt to analyze the pre-eruptive seismicity events for volcano eruption forecasting. After more than 50 years of slumber, Agung volcano on Bali Island erupted explosively, starting on November 21, 2017. The eruption was preceded by almost 2 months of significant increase of recorded seismicity, herein defined as “seismic crisis.” Our study provides the first analysis of VT events using data from eight local seismic stations deployed by the Center for Volcanology and Geological Hazard Mitigation of Indonesia (CVGHM) to monitor the Agung Volcano activity. In total, 2,726 Volcano-Tectonic (VT) events, with 13,023 P waves and 11,823 S wave phases, were successfully identified between October 18 and November 30, 2017. We increased the accuracy of the hypocenter locations of these VT events using a double-difference (DD) relative relocation and a new velocity model appropriate to the subsurface geological conditions of Agung volcano. We found two types of seismicity during the recording period that represent the VT events relating to fracture network reactivation due to stress changes (during the seismic crisis) and magma intrusion (after the seismic crisis). The characteristics of each event type are discussed in terms of Vp/Vs values, phase delay times, seismic cluster shapes, and waveform similarity. We interpret that the upward migrating magma reached a barrier (probably a stiff layer) which prohibited further ascent. Consequently, magma pressurized the zone above the magma chamber and beneath the barrier, reactivated the fracture zone between Agung and Batur volcanoes, and caused the seismic crisis since September 2017. In early November 2017, the barrier was finally intruded, and magma and seismicity propagated toward the Agung summit. This reconstruction provides a better depth constraint as to the previous conceptual models and explains the long delay (∼10 weeks) between the onset of the seismic crisis and the eruption. The distinction between the fracture reactivation and magma intrusion VT events observed in this study is significant for eruption forecasting and understanding the subsurface structure of the magmatic system. Based on the results obtained in this study, we emphasize the importance of prompt analysis (location and basic seismic characteristics) of the seismic crisis preceding the Agung eruption.

Repeating Earthquakes During Multiple Phases of Unrest and Eruption at Mount Agung, Bali, Indonesia, 2017

In 2017, Mount Agung produced a small (VEI 2) eruption that was preceded by an energetic volcano-tectonic (VT) swarm (>800 earthquakes per day up to M4.9) and two months of declining activity. The period of decreased seismic activity complicated forecasting efforts for scientists monitoring the volcano. We examine the time history of earthquake families at Mount Agung in search of additional insight into the temporal changes in the shallow crust prior to eruption. Specifically, we analyze the period of declining seismic activity about five weeks prior to the eruption when forecasting uncertainty was greatest. We use REDPy (Hotovec-Ellis and Jeffries, 2016) to build a catalog of 6,508 earthquakes from 18 October 2017–15 February 2018 and group them into families of repeating earthquakes based on waveform similarity using a cross-correlation coefficient threshold of 0.8. We show that the evolution of earthquake families provides evidence that Mount Agung was progressing toward eruption even though overall earthquake rates and seismic-energy-release declined. We find that earthquake families that dominated seismicity during the beginning of the crisis ceased near the onset of tremor on 12 November 2017. Then, earthquake families took on characteristics commonly observed during effusive phases of eruptions on 15 November—a full six days before the first phreatomagmatic eruption on 21 November 2017 and a full ten days before the actual onset of lava effusion on 25 November 2017. We interpret the transitions in seismicity as the manifestation of a three-phase physical model including an Intrusion Phase, a Transition Phase, and a Eruptive Phase. During the Intrusion Phase, seismicity was dominated by VT earthquakes with a relatively high percentage of repeaters (59%) grouped into numerous (65) simultaneous families. During the Eruptive Phase, seismicity included both VT and low frequency earthquakes that grouped into relatively long-lived families despite a low overall percentage of repeaters (14%). The Transition Phase exhibited characteristics of earthquake families between the Intrusion Phase and Eruptive Phase. We conclude that the time history of earthquake families provides insight into the evolution of the stress distribution in the volcanic edifice, the development of the volcanic conduit, and seismogenesis of magma effusion. Finally, we discuss the role that repeating earthquakes could play in real-time monitoring at restless volcanoes. Our work suggests eruption forecasts can be improved by incorporating automatic processing codes to assist seismologists during sustained periods of high earthquake rates, even at sparsely monitored volcanoes.

Imaging the Subsurface Structure of Mount Agung in Bali (Indonesia) Using Volcano-Tectonic (VT) Earthquake Tomography

Local seismic tomography is a well-known and commonly used method for obtaining detailed information about the internal structure of volcanoes. The eruption of Mt. Agung in 2017 was a vital opportunity scientifically because it is the first eruption that had sufficient seismic observation networks to carry out local seismic tomography at this volcano. In this study, we investigate the subsurface structure of Mt. Agung in Bali, which is one of the highest risk volcanoes in Indonesia. We conducted travel-time tomography using P- and S-wave arrival times of volcano-tectonic (VT) events to determine the three-dimensional (3D) Vp, Vs, and Vp/Vs ratio structure beneath Mt. Agung. We used 1,926 VT events, with corresponding 9482-P and 8683-S wave arrival times recorded by eight seismic stations over an observation time spanning from October 18 to December 31, 2017. We obtain the hypocenter solution for VT events using the maximum likelihood estimation algorithm and use an optimum 1D velocity model as input for the Joint 3-D seismic tomographic inversion. Local earthquake tomography revealed five anomalous regions that are useful to describe the overall seismic activity around Mt. Agung. We interpret these anomalous regions qualitatively due to limited data resolution in this study. We have successfully localized a high Vp/Vs ratio (∼1.82), low Vs (−1.9%) and high Vp (+3.8%), within a low seismicity zone at depths between 2 and 5 km below the Mt. Agung summit, which may be related to a shallow magma reservoir. There is also an anomalous region between Mt. Agung and Batur with moderate to high Vp/Vs ratios (1.76–1.79) where most of the earthquakes recorded before the 2017 eruption originated. We interpret this anomaly to be related to the existence of sub-vertical dyke complex at depths between 8 and 14 km. The results of our study provide new insights into the subsurface structure of the magma plumbing system beneath Mt. Agung, which can be used to improve the quality of determining the location of the hypocenter and source modeling for future eruption forecasting.

Aseismic strain episodes at Campi Flegrei Caldera, Italy

Abstract. Since 2004 a research project has been developed to monitor subsurface deformation of Italian volcanoes using borehole strainmeters and long-baseline tiltmeters. Six Sacks-Evertson dilatometers were installed around Campi Flegrei caldera and Vesuvius during 2004–2005 (Scarpa et al., 2007), and in 2008 these instruments were supplemented by two arrays of 28–280 m long water-tube tiltmeters in underground tunnels. Relevant strainmeter and tiltmeter data have been collected and analysed from the instruments installed near Campi Flegrei caldera during the recent unrest episodes. In the period 2004–2005 strain, tilt and GPS data from Campi Flegrei indicate the onset of surface deformation that accompanied a low rate of vertical displacement that continued to 2006, corresponding to an increase of CO2 emission. This strain episode preceded caldera microseismic activity by a few months, as was observed also during a significant inflation episode in 1982. Other transient strain episodes occurred in October 2006, which were accompanied by a swarm of VT (Volcano-Tectonic) and LP (Long Period) events, in 2009, at the time of renewed gas emission activity at Solfatara, and again in March 2010, several minutes before a seismic swarm. The time scale of these transient strain events ranges from some hours to several days, putting tight constraints on the origin of ground uplifts at Campi Flegrei. Their location is compatible with a source inferred from long term deformation signals, located about 4 km beneath Pozzuoli. A proposed mechanism for these aseismic strain episodes is that they are associated with magma growth in reservoirs with occasional pressure relief associated with the leakage of gas.

Dike Inflation Process Beneath Sakurajima Volcano, Japan, During the Earthquake Swarm of August 15, 2015

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.

The 2002–2005 Changbaishan Volcanic Unrest Triggered by the 2002 M 7.2 Wangqing Deep Focus Earthquake

One of the most active intraplate volcanoes in East Asia, Changbaishan volcano experienced unrest from July 2002 to July 2005. On 2002/06/28, the M 7.2 Wangqing deep-focus earthquake occurred ∼290 km northeast of Changbaishan volcano. While some studies have suggested a possible triggering relationship, the physical mechanism of such distant interaction is still not well understood. Using a template matching technique, which cross-correlates waveform of known events with continuous data, we perform systematic detection of microseismic events recorded by station CBS near Changbaishan volcano from July 1999 to July 2007. The detected earthquakes can be further categorized into three different types: volcano-tectonic (VT) events, long-period (LP) events and harmonic-spectra (HS) events. We detect 3763 VT events between July 2002 and July 2007. The intense VT earthquake swarm during the period from July 2002 to July 2005, along with recurring LPs and HSs and other geodetic/geochemical evidence, suggest magma movement during unrest. Compared with the hand-picked catalogue, the catalogue obtained by template matching technique reveals a delayed-triggering relationship between Wangqing deep-focus earthquake and unrest. The small magnitudes of the VT events and the limited numbers of LP and HS events suggest that the Wangqing mainshock likely triggered bubble excitation in the mid-crust magma system, resulting in overpressure and a small magma injection into the shallow magma chamber at a depth of ∼5 km, leading to the 3-years unrest.

Modeling Magma System Evolution During 2006–2007 Volcanic Unrest of Atka Volcanic Center, Alaska

AbstractSurface deformation and seismicity provide critical information to understand the dynamics of volcanic unrest. During 2006–2007, >80 mm/yr uplift was observed by interferometric synthetic aperture radar (InSAR) at the central Atka volcanic center, Alaska, coinciding with an increasing seismicity rate. On November 25, 2006, a phreatic eruption occurred at the Korovin volcanic vent, 5‐km north of the central Atka, following the drainage of its crater lake a month prior to the eruption. The InSAR data are assimilated into three‐dimensional finite element models using the Ensemble Kalman Filter to investigate: (1) the pressure source creating the surface deformation; (2) the triggering of the volcano‐tectonic (VT) earthquakes in the Atka volcanic center; and (3) the triggering of the phreatic eruption at Korovin. The models show that the pressure source required to create the surface deformation is a NE‐tilted, oblate ellipsoid, which rotated from steep to gentle dipping from June to November 2006 before the eruption. The modeled dilatancy in a pre‐existing weak zone, coinciding with the Amlia‐Amukta fault, driven by the pressure source has a spatial and temporal correlation with the evolution of the VT earthquakes during the unrest. The fault dilatancy may have increased the connected porosity and permeability of the fault zone allowing fluid injection which triggered the observed seismicity. In addition, the dilatated fault may have increased the fluid capacity of the fault zone by ∼105 m3, causing the discharge of the crater lake at Korovin. Consequently, the phreatic eruption of the Korovin volcano may have been triggered.

Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting

Cleveland and Tana are remote volcanoes located in the central Aleutian volcanic arc on the eastern end of the Islands of Four Mountains (IFM). The persistently active Mount Cleveland volcano, on the western side of Chuginadak Island, is surrounded by several closely spaced Quaternary volcanic centers including Carlisle, Herbert, Kagamil, Tana, and Uliaga, and numerous small satellite vents on Chiginadak between Cleveland and Tana. The Alaska Volcano Observatory (AVO) installed two permanent broadband seismometers on Chuginadak Island in 2014, and we operated a temporary broadband network focused on the western side of the island in 2015–2016. Collectively, these stations provided the first seismic observations of this frequently active volcano and the surrounding Holocene-aged volcanic vents. During the study period (July 2014–January 2019), eruptive activity at Cleveland was characterized by small explosions separated by periods of lava effusion that formed small domes in the volcano's summit crater. We characterize seismicity beneath Chuginadak Island through automated analysis of event waveform frequency content, development of a one-dimensional P-wave velocity model, calculation of earthquake hypocenters, magnitudes, focal mechanisms, and identification of earthquake families. This analysis reveals the full range of seismic event types expected in a highly active volcanic environment and includes Volcano-Tectonic (VT) earthquakes, Long-Period (LP) events, and explosion signals. LP events appear to cluster at shallow depth beneath the active crater of Mount Cleveland and almost all of the explosions occur without identifiable short-term (hours to days) seismic precursors. VT earthquakes beneath Mount Cleveland occur at depths of 2 to 8 km below sea level (BSL) and range in magnitude from −0.2 to 1.8. VT focal mechanisms have horizontal P-axes that align with the regional axis of maximum stress. These observations, and a relatively slow one-dimensional seismic velocity model, are consistent with a shallow body of magma that is fed through a deeper conduit system. The time-history of VT earthquakes and shallow LP events suggest their occurrence may track the transfer of magma and fluids from the mid-crust to the shallow portions of the conduit system and may provide a means to anticipate future explosions and periods of dome growth. VT hypocenters also extend ~7 km northeast of Cleveland's summit at depths of 5 to 10 km BSL, under a group of Holocene-aged vents between Mount Cleveland and Tana. These earthquakes have vertically-oriented P-axes and a greater percentage occur in families. These observations, combined with observations of vent orientation and morphology and gas flux, suggest the area between Cleveland and Tana represents a zone of complicated volcano-tectonic interaction, similar to calderas elsewhere in the Aleutian arc. The presence of a larger volcanic system in the eastern IFM could influence magmatism and account for the multiple closely spaced volcanic centers in this region.

A machine-learning approach for automatic classification of volcanic seismicity at La Soufrière Volcano, Guadeloupe

The classification of seismo-volcanic signals is performed manually at La Soufrière Volcano, which is time consuming and can be biased by subjectivity of the operator. We propose here a machine-learning-based model for classification of these signals, to handle large datasets and provide objective and reproducible results. To describe the properties of the signals, we used 104 statistical, entropy, and shape descriptor features computed from the time waveform, the spectrum, and the cepstrum. First, we trained a random forest classifier with a dataset provided by the Observatoire Volcanologique et Sismologique de Guadeloupe that consisted of 845 labeled events that were recorded from 2013 to 2018: 542 volcano-tectonic (VT); 217 Nested; and 86 long period (LP). We obtained an overalll accuracy of 72%. We determined that the VT class includes a variety of signals that cover the VT, Nested and LP classes. After visual inspection of the waveforms and spectral characteristics of the data set, we introduced two new classes: Hybrid and Tornillo. A new random forest classifier was trained with this new information, and we obtained a much better overall accuracy of 82%. The model is very good for recognition of all event classes, except Hybrid events (67% accuracy, 70% precision). Hybrid events are often considered to be a mix of VT and LP events. This can be explained by the nature of this class and the physical processes that include both fracturing and resonating components with different modal frequencies. By analyzing the feature weights and by training a model with the most important features, we show that a subset of the 14 best features is sufficient to obtain a performance that is close to that of the model with the whole feature set. However, these best features are different from the 13 best features obtained for another volcano in Peru, with only one feature common to both sets of best features. Therefore, the model is not universal and it must be trained for each volcano, or it is too specific to the one station used here.

On finding possible frequencies for recognizing microearthquakes at Cotopaxi volcano: A machine learning based approach

Adequate detection and classification of seismic events are crucial for understanding the internal status of a Volcano. Machine learning-based classifiers use different features from the time, frequency, and scale domains related to seismic events. Regarding power spectrum-based features, several methods can be used to compute such features. However, the more suitable method for analyzing volcanic activity is undetermined. This paper presents a study about the main frequency bands, which allows maximizing the performance metrics of an automated classifier for long-period (LP) and volcano-tectonic (VT) events based on parametric (Yule-Walker and Burg) and non-parametric (Welch and Multitaper) power spectrum density estimation methods. Feature selection using embedded (pruning) and wrapper (recursive feature elimination) methods was applied to select the main frequencies that maximize the balanced error rate of suitable classification algorithms, such as decision trees (DT) and support vector machines (SVM). Bootstrapping was used to estimate a confidence interval for the frequencies of the microearthquakes. An amplitude threshold difference of at least 3 dB was used to guarantee that possible frequency features that characterize each type of event do not overlap between classes. The method who achieved the worst overall performance was not considered by the voting strategy. A Dataset from Cotopaxi volcano was used to test the proposed classification schema. The best results show for DT classifier a total of 10 key frequencies, while for SVM classifier 39 key frequencies grouped in three main frequency bands, as main features to distinguish LP events from VT earthquakes. The best classification results were achieved by the Welch method with the DT and by the Multitaper method with the SVM classifiers. Furthermore, the study confirms that there is a frequency band above 40 Hz, which seems like a critical feature for the detection and classification of stages.

Temporal change of the magma plumbing system at Galeras volcano, Colombia, revealed by repeated seismic tomography in 2009–2018

We performed repeated three-dimensional seismic tomography in 2009–2018 for the area influenced by the intersection of the Silvia–Pijao (Buesaco) and Cauca–Almaguer fault systems beneath Galeras volcano, Colombia. We analyzed two periods, 2009–2012 and 2013–2018, which were characterized by explosive eruptive activity and relative quiescence at Galeras, respectively. We used P- and S-wave arrival times of 2848 (2009–2012) and 2289 (2013–2018) earthquakes that occurred beneath the volcano. P- and S-wave velocity (Vp and Vs, respectively) anomalies and their changes between the two periods were interpreted to be associated with magma movement in the volcanic plumbing system, which was controlled by the intersection of the faults. Two possible pathways of magma ascent and accumulation were identified in the fault systems. One, located SW of the active crater, consisted of areas with high Vp/Vs values (>1.9) at depths of −2 to 4 km below sea level, and the other located NE of the active crater with high and low Vp/Vs values. The low-Vp/Vs (<1.7) area at depths of 0 to 2 km may represent vesiculated magma that was partly erupted during explosive eruptions in 2009–2010. These anomalies, found in 2009–2012, displayed clear changes in 2013–2018. Large surface deformation observed between January 2013 and February 2014 may be associated with magma movement from the SW pathway. The largest volcano-tectonic (VT) earthquake, with a magnitude of 5.1, ever recorded at Galeras occurred on 12 June 2018 and was followed by a swarm of VT earthquakes. This VT activity may have been caused by magma intrusion along the NE pathway. On the basis of our tomographic images and geodetic, petrological, and geochemical results, we propose a model of the plumbing system beneath Galeras during 2009–2018.

A New Volcanic Seismic Signal Descriptor and its Application to a Data Set From the Cotopaxi Volcano

This article proposes a new volcano seismic signal descriptor for improving the area under the receiver operating characteristic curve (AUC) in the classification of long-period (LP) and volcano-tectonic (VT) seismic events. It aims to describe a volcanic seismic event from a different and novel point of view that involves image processing techniques instead of classical seismic signal processing strategies, such as frequency or scale analysis. The proposed descriptor allows exploring the seismic signal space for obtaining the determination of the event patterns and, subsequently, the extraction of intensity-, shape-, and texture-based features into a numeric vectorial output for supplying a set of selected machine learning classifiers with different taxonomies. The descriptor was validated on a seismic signal database collected at the Cotopaxi volcano, containing a total of 637 events, including LP, VT, and other types of seismic events (e.g., rockfall or icequakes). An accuracy value of 96% was obtained in the determination of the event patterns using the signal database, while the values of 0.95 and 0.96 were obtained for the AUC when using a feedforward backpropagation artificial neural network classifier on two experimental data sets, containing feature vectors representing signal with and without event overlapping, respectively. The obtained results demonstrate that the proposed descriptor is capable of providing adequate seismic signal representations in a different feature space and that its output provides competitive results in the classification of volcanic seismic events.

Local magnitude, coda magnitude, and radiated energy of volcanic tectonic earthquakes from October 2010 to December 2011 at Sinabung volcano, Indonesia

In August 2010, Sinabung volcano began erupting after more than a thousand years of dormancy. Following several weeks of phreatic eruptions, the eruptions ceased and Sinabung entered what became an inter-eruptive period of dominantly seismic unrest. While standard equations for understanding the size of an earthquake (local magnitude (ML), coda magnitude (MC), and seismic energy release (ER)) have long been developed, it is best practice to fine tune these relations for a given region and period of study to more accurately describe seismicity and to directly compare it with other volcanic systems. More accurate descriptions of magnitudes and energy release are vital to accurate volcanic eruption forecasting and evaluation of seismic and volcanic risk. In this study, we use high-frequency volcano-tectonic (VT) earthquakes recorded on a temporary three-component network installed between October 2010 and December 2011 in the region around Sinabung volcano to better constrain the seismic parameters of and better understand this previously unstudied volcano. We determine region-specific formulas for ML, MC, and ER as follows: $$ {\mathrm{M}}_{\mathrm{L}}={\log}_{10}A+1.1252{\log}_{10}r+0.0280\ r-2.5427,\kern0.5em {\mathrm{M}}_{\mathrm{C}}=0.7764\ {\log}_{10}{t}_{coda}+0.0676\ r-0.7185,\kern0.5em \mathrm{and}\kern0.5em {\log}_{10}\left({\mathrm{E}}_{\mathrm{R}}\right)=1.5720{\mathrm{M}}_{\mathrm{L}}+11.5258, $$ where A, r, and tcoda are maximum amplitude on a Wood-Anderson seismogram, hypocentral distance (km), and the coda duration (s), respectively. Constants in the ML equation have physically interpretable meanings. The constant for the geometrical spreading term (log10r term) equals one for perfect spherical spreading of the waveform. Our value is greater than one and thus suggests that wavefronts spread at a slightly different rate than for simple spherical spreading. The constant for the attenuation term (r term) is consistent with locally mapped attenuative deposits (limestones and tuffs) and previous 3D tomographic results. Our MC equation differs from a previous study, likely because different data in a different time period were used. Earthquake hypocenters are consistent with those located in previous tomographic studies, and we interpret the earthquakes in this study as distal VT earthquakes induced by continued magmatic intrusion at Sinabung over the period of October 2010–December 2011.

In-depth comparison of deep artificial neural network architectures on seismic events classification

One of the most challenging tasks in volcanic data analysis is the classification of seismic events. By knowing them, it is possible to take decisions in advance, providing benefits for the neighboring societies as, for instance, how such events may impact users' life and cropland areas. Although there are several approaches to perform such task, Deep Neural Networks (DNN) have been barely considered to deal with seismic signals, as discussed in our related work. In this sense, we started our research with a wide set of experiments to analyze the DNN performance while discriminating seismic activities through two common network architectures: a 2D Convolutional Neural Networks (CNN) and the Long Short-Term Memory (LSTM) network. In attempt to draw a parallel of DNN and classical supervised learning strategies, we extended our study by comparing those two architectures against the Multilayer Perceptron (MLP), which would be the simplest and most common baseline to take into account. Our MLP network was implemented after combining a basic architecture with elements from DNN models as dropout, flatten, and batch normalization layers. From this first analysis, we confirmed the need of additional neural network layers to obtain good classification results for seismic events, given the MLP required more DNN-based pipeline operations to improve its overall performance, making it comparable to the previous results obtained by our research group. As a natural extension, we designed a new DNN architecture by assessing additional network layers specifically devoted to extract features from seismic signals, thus improving the overall classification of Volcano activities involving the following events: Volcano-Tectonic (VT), Long Period (LP), Tremor (TR) and Tectonic (TC). Such design motivated the study of current DNN architectures tackling similar problems to classify raw signals from which SoundNet was taken as the most prominent candidate, thus leading to a new CNN architecture here proposed and referred to as SeismicNet. As our final contribution, SeismicNet provided classification results among the best in the literature without demanding explicit signal pre-processing steps though.

Improved 1D velocity model and deep long-period earthquakes in Kanlaon Volcano, Philippines: Implications for its magmatic system

We determined an improved 1D P-wave velocity model for Kanlaon Volcano, one of the most active volcanoes in the Philippines, for use in precise earthquake relocation. The inversion for velocity model was conducted using the program VELEST, which solved the coupled hypocenter–velocity problem from dataset of 251 local earthquakes recorded by the Kanlaon Volcano Seismic Network from 2014 to 2017. Using the improved velocity model, we relocated the volcano-tectonic (VT) earthquakes in Kanlaon with hypoDD, resulting in better-constrained hypocenter locations based on the decrease in RMS and corresponding error assessment tests. Subsequently, we relocated swarms of long-period volcanic earthquakes that occurred from September 1, 2017 to August 31, 2018 and prompted the Philippine Institute of Volcanology and Seismology to raise the volcano's alert level. These long-period earthquakes had emergent arrivals, hence we applied a cross-correlation procedure using REDPy to obtain an improved arrival time picks. These improved hypocenters revealed the existence of deep long-period (DLP) earthquakes that occurred at depths of 23 to 36 km beneath the volcano. These are the first DLP events documented in Kanlaon since the establishment of the Kanlaon Volcano Observatory in 1961. They were found to belong into families based on similarity of waveforms suggesting they were produced by repetitive, non-destructive sources. The occurrences of DLPs in Kanlaon reflected the pressurization of its deep-seated magmatic system. Their identification is critical in assessing the current state of Kanlaon Volcano especially since its last magmatic eruption was in 1902.

The 2018 unrest phase at La Soufrière of Guadeloupe (French West Indies) andesitic volcano: Scrutiny of a failed but prodromal phreatic eruption

After 25 years of gradual increase, volcanic unrest at La Soufrière of Guadeloupe reached its highest seismic energy level on 27 April 2018, with the largest felt volcano-tectonic (VT) earthquake (ML 4.1 or MW 3.7) recorded since the 1976–1977 phreatic eruptive crisis. This event marked the onset of a seismic swarm (180 events, 2 felt) occurring after three previous swarms on 3–6 January (70 events), 1 st February (30 events, 1 felt) and 16–17 April (140 events, 1 felt). Many events were hybrid VTs with long-period codas, located 2–4 km below the volcano summit and clustered within 2 km along a regional NW-SE fault cross-cutting La Soufrière. Elastic energy release increased with each swarm whereas inter-event time shortened. At the same time, summit fractures continued to open and thermal anomalies to extend. Summit fumarolic activity increased significantly until 20 April, with a maximum temperature of 111.4 °C and gas exit velocity of 80 m/s, before declining to ~95 °C and ~33 m/s on 25 April. Gas compositions revealed increasing C/S and CO2/CH4 ratios and indicate hydrothermal P-T conditions that reached the critical point of pure water. Repeated MultiGAS analysis of fumarolic plumes showed increased CO2/H2S ratios and SO2 contents associated with the reactivation of degassing fractures (T = 93 °C, H2S/SO2 ≈ 1). While no direct evidence of upward magma migration was detected, we attribute the above phenomena to an increased supply of deep magmatic fluids that heated and pressurized the La Soufrière hydrothermal system, triggering seismogenic hydro-fracturing, and probable changes in deep hydraulic properties (permeability) and drainage pathways, which ultimately allowed the fumarolic fluxes to lower. Although this magmatic fluid injection was modulated by the hydrothermal system, the unprecedented seismic energy release and the critical point conditions of hydrothermal fluids suggest that the 2018 sequence of events can be regarded as a failed phreatic eruption. Should a similar sequence repeat, we warn that phreatic explosive activity could result from disruption of the shallow hydrothermal system that is currently responsible for 3–9 mm/y of nearly radial horizontal displacements within 1 km from the dome. Another potential hazard is partial collapse of the dome's SW flank, already affected by basal spreading above a detachment surface inherited from past collapses. Finally, the increased magmatic fluid supply evidenced by geochemical indicators in 2018 is compatible with magma replenishment of the 6–7 km deep crustal reservoir feeding La Soufrière and, therefore, with a potential evolution of the volcano's activity towards magmatic conditions.