Alexander Yates

Understanding volcanic unrest episodes and determining whether they will escalate to hazardous eruptions is a key research goal for improving volcano monitoring procedures. Ruapehu volcano, one of the most active in Aotearoa New Zealand, underwent a significant period of unrest in 2022 that was characterized by high levels of seismic tremor and a heating cycle in the summit crater lake. The tremor was notable for featuring prolonged periods of “drumbeats” as well as harmonic tremor. Conventional methods of earthquake location estimations struggle to locate the source due to the emergent nature of the tremor as well as the relatively sparse seismic network around the volcano. Here we use the network covariance matrix method to isolate and locate the tremor source within the volcano. Our results suggest low‐level tremor commenced 3 months prior to the unrest episode, coinciding with a brief earthquake swarm at similar depths. Tremor and drumbeats during the unrest episode were continuously located at shallow (<500 m) depths beneath the summit crater lake, placing the source within or just below the hydrothermal system. We propose a source mechanism where resonance due to magmatic fluid flux is regulated by highly viscous, liquid elemental sulfur within the hydrothermal system. This study highlights how network covariance analysis can be a powerful tool for monitoring and locating seismic tremor during unrest episodes at Ruapehu volcano.

Identifying volcanic transitions from quiescence to unrest and tracking subsurface evolution remains critically challenging. We analyzed continuous seismic records from Askja volcano (Iceland) from 2008--2024 using coda wave interferometry to track relative seismic velocity variations (dv/v) as a proxy for subsurface changes during renewed volcanic intrusion. This analysis is complemented with three additional methods: network covariance matrix analysis, Displacement Seismic Amplitude Ratio (DSAR) single-station analysis, and sensitivity kernel analysis, alongside GNSS, earthquake catalog, and meteorological datasets. Since August 2021, dv/v measurements revealed an abrupt transition from regular seasonal oscillations (±0.2\%) to predominantly negative values reaching -0.7\% near the inflation center, coinciding with 76 cm GNSS-detected ground uplift by August 2024. DSAR indicated higher seismic attenuation near the inflation source, suggesting volatile accumulation in the shallow subsurface through June 2022, followed by marked decreases associated with depressurization. Sensitivity kernel analysis demonstrated wave sensitivity reaches down to 3 km depth, encompassing the shallow reservoir levels. Integrated seismic observations revealed magma-induced seismic velocity drops, followed by system reorganization with frequency-dependent recovery, and finally establishment of a new state with hydrothermal circulation maintaining altered seismic properties. This approach demonstrates the effectiveness of continuous seismic monitoring for detecting volcanic unrest transitions and tracking evolving subsurface processes.

Distributed Acoustic Sensing (DAS) offers unprecedented spatial resolution relative to conventional seismic networks. This provides new opportunities to investigate the composition of the recorded seismic wavefield in volcanic environments, which are often highly heterogeneous. At Mt Etna, recent work (Yates et al. 2026) has highlighted the presence of stable spectral peaks that emerge during broadband volcanic tremor. Using seismic stations from the permanent monitoring network, these were found to vary significantly between stations and to respond to seismic velocity changes through proportional frequency shifts. Combined, these observations support the interpretation that they originate from persistent scattering structures that cause resonance-like effects in heterogeneous environments. In this study, we present a preliminary analysis of DAS data acquired between Zafferana and Linera on the eastern flank of Mt Etna in 2019 (~15 km length). Anthropogenic noise is found to dominate the recorded wavefield during a significant proportion of the day. However, stable spectral peaks are clearly visible during periods of reduced activity (late evening / early morning). We quantify the spatial variability of these peaks, taking advantage of the high spatial resolution offered by DAS. Our work provides the opportunity to (1) better constrain the relative roles of source, path, and site effects in generating stable spectral peaks, and (2) assess subsurface heterogeneity through quantification of the characteristic length scales over which spectral peaks vary. Together, this approach demonstrates the potential of DAS to provide insights into the subsurface at spatial scales not resolvable with conventional seismic networks. This work has been performed in the frame of USCV-DAS, a Transnational Access to the Eastern Sicily testbed supported by the EU project Geo-INQUIRE. Geo-INQUIRE is funded by the European Commission under project number 101058518 within the HORIZON-INFRA-2021-SERV-01 call.ReferencesYates, A. S., Heuninck, S., Barajas, A., Bektas, H., Caudron, C., De Angelis, S., & Zuccarello, L. (2026). Tracking subsurface changes via frequency shifts in volcanic tremor spectral lines: observations from Mt Etna. Geophysical Research Letters, 53(2), e2025GL117819.

Accurate subsurface characterization is fundamental to the successful development of geothermal systems. Such comprehensive knowledge allows determining geological structures that govern local fluid circulation and heat transport. As drilling represents one of the largest cost factors in geothermal development, ensuring that wells target zones of high hydraulic conductivity and permeability can substantially reduce exploration risk and overall project costs. Passive seismic techniques, being both inexpensive and non-invasive, have proven to be effective tools for both geothermal exploration and monitoring. Among them, Horizontal-to-Vertical spectral ratios (H/V) are often used to map subsurface topography. Their interpretation and inversion, however, often rely on prior knowledge of local shear-wave velocity or subsurface layering.In this case study we employ a trans-dimensional Bayesian framework to invert H/V curves from more than 70 survey points across a prospective aquifer thermal energy storage system in rural Belgium, which will supply about 160 housing units. Our approach enables the generation of pseudo-2D shear-wave velocity profiles across the site without requiring additional information to constrain the inversion. Low velocity zones are identified which can be related to karstification and geological layering suggested by geological maps. The results are further validated with direct field measurements. Borehole logs from exploration wells drilled on the basis of our results indicate high hydraulic conductivity and are supported by water table measurement from cone penetration testing. The derived profiles offer valuable information to guide well placement and optimize drilling decisions by reducing uncertainty in subsurface conditions. Our findings demonstrate that passive seismological techniques, combined with probabilistic inversion approaches can serve as a cost-effective tool in support of the energy transition.

Ruapehu is one of the most active volcanoes in Aotearoa New Zealand, with over 100 eruptive events over the last 135 years. In 2022, the volcano underwent a significant period of unrest which included a new heating phase in the summit crater lake, increases in gas emissions, and strong levels of seismic tremor, the most intense observed at the volcano for nearly 30 years. The tremor was also notable for featuring a sequence of highly-periodic low frequency “drumbeats”. Both tremor and drumbeats were hypothesised to originate from within a shallow hydrothermal system but a sparse seismic network precluded accurate location information. Here we utilised the network covariance matrix approach to map the location of tremor within the Ruapehu volcanic system before and during the 2022 unrest episode. We find low level tremor is detectable up to three months before the unrest begins, beginning shortly before a small sub-summit earthquake swarm approximately 3 - 4 km below the summit. Tremor during the unrest period is primarily located at shallow depths, within 500 m of the summit vent, suggesting a mechanism within the shallow hydrothermal system. This study was the first to apply the network covariance method for studying tremor at Ruapehu and demonstrates the technique’s value as an effective tool for real-time volcanic tremor monitoring in Aotearoa New Zealand.

Episodes of volcanic tremor provide valuable insights into subsurface processes at active volcanoes, yet the physical origin of temporal variations in tremor spectra remains debated. Previous work at Mt. Etna (Italy) demonstrated a strong correlation between relative frequency changes (df/f) during broadband volcanic tremor and seismic velocity changes (dv/v) derived from passive seismic interferometry. Such correspondence suggests that tremor spectra are responding to changes in medium properties rather than variations in the tremor source.Here, we extend this observation beyond Etna to include Tungurahua volcano (Ecuador) and Rincón de la Vieja volcano (Costa Rica). At both volcanoes, we observe consistent correlations between df/f extracted from broadband tremor and dv/v. At Tungurahua, these changes are linked to earthquake-induced damage and meteorological processes, once again suggesting that their modulation reflects changes in the phase velocity within near-surface layers.The persistent relationship between dv/v and df/f at both Tungurahua and Rincón de la Vieja not only supports previous interpretations at Etna, but shows that such a relationship is present across varied volcanic systems. This strengthens the case for using df/f during broadband tremor as a proxy for tracking subsurface changes within volcanic systems, particularly where using traditional methods may be challenging. Furthermore, our results highlight the need to clarify the respective roles of source, path, and site effects in shaping the recorded seismic wavefield in volcanic environments. Doing so avoids misattributing spectral changes as source-driven, and opens the door to exploiting tremor spectra for monitoring purposes.

Episodes of volcanic tremor provide valuable insights into the dynamics of subsurface processes at active volcanoes. Previous studies have suggested that evolving tremor properties may relate to changes in the stress conditions of the plumbing system. However, a strong causative link has remained elusive. At Etna volcano, we observe subtle changes in the frequency of stable spectral lines recorded during broadband tremor over 8 months in 2020. Comparison with seismic velocity changes computed using passive seismic interferometry reveals a remarkable correlation between relative frequency and seismic velocity changes. The most significant of these changes are interpreted to result from a shear‐wave velocity decrease in response to local seismicity. We argue that these observations are best explained by resonance within near‐surface structures. These findings demonstrate that monitoring frequency shifts of stable spectral lines produced during tremor can provide meaningful insights into subsurface properties.

Episodes of volcanic tremor provide valuable insights into the dynamics of subsurface processes at active volcanoes. Previous studies have suggested that evolving tremor properties may relate to changes in the stress conditions of the plumbing system. However, a strong causative link has remained elusive. At Etna volcano, we observe subtle changes in the frequency of stable spectral lines recorded during broadband tremor over a eight-months in 2020. Comparison with seismic velocity changes computed using passive seismic interferometry reveals a remarkable correlation between relative frequency (df/f) and seismic velocity (dv/v) changes. Modeling of precipitation-induced pore pressure changes suggest that the most significant velocity and frequency changes recorded reflect shallow environmental forcing. We argue that these observations are best explained by resonance within near-surface structures. These findings demonstrate that monitoring frequency shifts of stable spectral lines produced during tremor can provide meaningful insights into subsurface properties.

In urban environments, shallow geothermal heating and cooling systems can play a crucial role in the transition towards renewable energy sources. One such site (USquare) is a transformed military barracks in Brussels, where over one hundred boreholes were drilled (~120 m) and equipped with heat exchangers as part of a low-enthalpy geothermal heating network for a multi-use urban development project. Fourteen of these were equipped with fiber optic cables that can provide continuous temporal monitoring of downhole conditions during operation. This includes Fiber Bragg Grating sensors (FBGs), providing point measurements of temperature, and Distributed Acoustic Sensing (DAS) towards recording strain along the length of the fiber. In this work, we present the experimental setup and initial results for subsurface monitoring at USquare. We compute the root mean square (RMS) amplitude of seismic noise across all channels, with promising results when compared with known hydro-geological logs. Consideration is also given to the impact of the urban environment on the stability of measurements due to variability in anthropogenic seismic sources. Finally, we show preliminary results applying seismic noise interferometry to downhole measurements. This includes computing auto-correlations from the individual channels and also cross-correlations with surface geophones. These findings highlight the potential of fiber optic sensing technologies for monitoring geothermal operations in urban environments, paving the way for more sustainable energy solutions.