360 Intrusions in a Miniature Volcano: Birth, Growth, and Evolution of an Analog Edifice

Most volcanoes throughout the world have been monitored with geophysical data (seismology and geodesy) for no more than three decades, a relatively short time compared to their overall life. The consequence is that we lack a long observation of volcanic growth and behavior to get a more complete picture of the interaction between edifice stress state and magma transfer. Here we present the birth and evolution of a 83 x 83 cm analog model, where we reproduce for the first time volcanic growth over 360 successive intrusions (15 mL every half hour, at a rate of 3 mL/min) in an analog elasticity-dominated material (pigskin gelatine). By observing the development of this model volcano, we hope to provide insights to the study of long-term volcanic activity. In particular, we are interested in stress accumulation/release cycles and their role in the triggering of distant eruptions. Our model volcano started as a flat topography and ended 3.82 cm in height at the summit. It displayed cyclic eruptive patterns with alternating phases of eruptive and purely intrusive behavior. Alike to many intraplate volcanoes in nature, main dyke swarms produced in the experiment were disposed in a three-branched radial pattern centered above the injection source (“volcanic rift zones”). They were accompanied by two radial sill networks, at source depth and edifice base. Long-term radial compressive stress building during dyke swarming was likely compensated by radial compressive stress release during sill emplacement. Near-surface stresses, deduced from the main orientation eruptive fissures and “dry” fractures, became more localized as the volcano grew. At the end of the experiment, the shallow stress field was interpreted as generally extensional radial at the summit, extensional tangential on the flanks, and compressive radial in distal areas. This experiment showcases the potential of studying long-term stress permutations in volcanic edifices in the understanding of their morphology and successive activity phases

A dynamic extreme value model with applications to volcanic eruption forecasting

Extreme events such as natural and economic disasters leave lasting impacts on society and motivate the analysis of extremes from data. While classical statistical tools based on Gaussian distributions focus on average behaviour and can lead to persistent biases when estimating extremes, extreme value theory (EVT) provides the mathematical foundations to accurately characterise extremes. In this paper, we adapt a dynamic extreme value model recently introduced to forecast financial risk from high frequency data to the context of natural hazard forecasting. We demonstrate its wide applicability and flexibility using a case study of the Piton de la Fournaise volcano. The value of using EVT-informed thresholds to identify and model extreme events is shown through forecast performance.Comment: Math Geosci (2023

Identifying analogues for data-limited volcanoes using hierarchical clustering and expert knowledge: a case study of Melimoyu (Chile)

Determining the eruption frequency-Magnitude (f-M) relationship for data-limited volcanoes is challenging since it requires a comprehensive eruption record of the past eruptive activity. This is the case for Melimoyu, a long-dormant and data-limited volcano in the Southern Volcanic Zone (SVZ) in Chile with only two confirmed Holocene eruptions (VEI 5). To supplement the eruption records, we identified analogue volcanoes for Melimoyu (i.e., volcanoes that behave similarly and are identified through shared characteristics) using a quantitative and objective approach. Firstly, we compiled a global database containing 181 variables describing the eruptive history, tectonic setting, rock composition, and morphology of 1,428 volcanoes. This database was filtered primarily based on data availability into an input dataset comprising 37 numerical variables for 438 subduction zone volcanoes. Then, we applied Agglomerative Nesting, a bottom-up hierarchical clustering algorithm on three datasets derived from the input dataset: 1) raw data, 2) output from a Principal Component Analysis, and 3) weighted data tuned to minimise the dispersion in the absolute probability per VEI. Lastly, we identified the best set of analogues by analysing the dispersion in the absolute probability per VEI and applying a set of criteria deemed important by the local geological service, SERNAGEOMIN, and VB. Our analysis shows that the raw data generate a low dispersion and the highest number of analogues (n = 20). More than half of these analogues are in the SVZ, suggesting that the tectonic setting plays a key role in the clustering analysis. The eruption f-M relationship modelled from the analogue’s eruption data shows that if Melimoyu has an eruption, there is a 49% probability (50th percentile) of it being VEI≥4. Meanwhile, the annual absolute probability of a VEI≤1, VEI 2, VEI 3, VEI 4, and VEI≥5 eruption at Melimoyu is 4.82 × 10−4, 1.2 × 10−3, 1.45 × 10−4, 9.77 × 10−4, and 8.3 × 10−4 (50th percentile), respectively. Our work shows the importance of using numerical variables to capture the variability across volcanoes and combining quantitative approaches with expert knowledge to assess the suitability of potential analogues. Additionally, this approach allows identifying groups of analogues and can be easily applied to other cases using numerical variables from the global database. Future work will use the analogues to populate an event tree and define eruption source parameters for modelling volcanic hazards at Melimoyu

Estimates of plume height from infrasound for regional volcano monitoring

Present efforts in volcano monitoring, particularly in Southeast Asia, rely on the combination of local data (generally gathered at less than 100 km from the volcano), and satellite remote sensing. While this combination has its strengths, there are still weaknesses that the use of ground-based remote sensing data - such as distant infrasound measurements - could help alleviate. Infrasound offers tools for detecting and characterizing volcanic plumes independent of cloud cover and time of day. Larger volcanic eruptions generate infrasound that is related to the plume and offers a unique view into eruption dynamics within the context of monitoring. Past research has demonstrated that infrasound can be used to estimate source parameters, such as the rate at which material is ejected from volcanic vents during eruptions; these are key input parameters into empirical and numerical models to estimate the height of volcanic plumes, atmospheric ash transport and dispersion. Here, we demonstrate the use of remote infrasound in estimating the height of volcanic plumes, including a case study on the May 30, 2014 plume from the volcano Sangeang Api in Indonesia. We were able to determine the plume height using infrasound gathered from 2000 to over 5000 km distance from the volcano. During the January 2020 eruption of Taal volcano in the Philippines, this method was applied to remote infrasound recorded 1650 km to the east. We show that our workflow can be implemented in near real-time, offering an effective tool for rapid plume height measurement, including associated uncertainties, when volcanic clouds are not visible from the ground or space

Toward continuous quantification of lava extrusion rate: Results from the multidisciplinary analysis of the 2 January 2010 eruption of Piton de la Fournaise volcano, La Reunion

International audienceThe dynamics of the 2–12 January 2010 effusive eruption at Piton de la Fournaise volcano were examined through seismic and infrasound records, time-lapse photography, SO2 flux measurements, deformation data, and direct observations. Digital elevation models were constructed for four periods of the eruption, thus providing an assessment of the temporal evolution of the morphology, the volume and the extrusion rate of the lava flow. These data were compared to the continuous recording of the seismic and infrasonic waves, and a linear relationship was found between the seismic energy of the tremor and the lava extrusion rate. This relationship is supported by data from three other summit eruptions of Piton de la Fournaise and gives total volume and average lava extrusion rate in good agreement with previous studies. We can therefore provide an estimate of the lava extrusion rate for the January 2010 eruption with a very high temporal resolution. We found an average lava extrusion rate of 2.4 m3s−1 with a peak of 106.6 m3s−1 during the initial lava fountaining phase. We use the inferred average lava extrusion rate during the lava fountaining phase (30.23 m3s−1) to estimate the value of the initial overpressure in the magma reservoir, which we found to range from 3.7×106 Pa to 5.9×106 Pa. Finally, based on the estimated initial overpressure, the volume of magma expelled during the lava fountaining phase and geodetic data, we inferred the volume of the magma reservoir using a simple Mogi model, between 0.25 km3 and 0.54 km3, which is in good agreement with previous studies

Synoptic analysis of a decade of daily measurements of SO2 emission in the troposphere from volcanoes of the global ground-based Network for Observation of Volcanic and Atmospheric Change

Volcanic plumes are common and far-reaching manifestations of volcanic activity during and between eruptions. Observations of the rate of emission and composition of volcanic plumes are essential to recognize and, in some cases, predict the state of volcanic activity. Measurements of the size and location of the plumes are important to assess the impact of the emission from sporadic or localized events to persistent or widespread processes of climatic and environmental importance. These observations provide information on volatile budgets on Earth, chemical evolution of magmas, and atmospheric circulation and dynamics. Space-based observations during the last decades have given us a global view of Earth's volcanic emission, particularly of sulfur dioxide (SO2). Although none of the satellite missions were intended to be used for measurement of volcanic gas emission, specially adapted algorithms have produced time-averaged global emission budgets. These have confirmed that tropospheric plumes, produced from persistent degassing of weak sources, dominate the total emission of volcanic SO2. Although space-based observations have provided this global insight into some aspects of Earth's volcanism, it still has important limitations. The magnitude and short-term variability of lower-atmosphere emissions, historically less accessible from space, remain largely uncertain. Operational monitoring of volcanic plumes, at scales relevant for adequate surveillance, has been facilitated through the use of ground-based scanning differential optical absorption spectrometer (ScanDOAS) instruments since the beginning of this century, largely due to the coordinated effort of the Network for Observation of Volcanic and Atmospheric Change (NOVAC). In this study, we present a compilation of results of homogenized post-analysis of measurements of SO2 flux and plume parameters obtained during the period March 2005 to January 2017 of 32 volcanoes in NOVAC. This inventory opens a window into the short-term emission patterns of a diverse set of volcanoes in terms of magma composition, geographical location, magnitude of emission, and style of eruptive activity. We find that passive volcanic degassing is by no means a stationary process in time and that large sub-daily variability is observed in the flux of volcanic gases, which has implications for emission budgets produced using short-term, sporadic observations. The use of a standard evaluation method allows for intercomparison between different volcanoes and between ground- and space-based measurements of the same volcanoes. The emission of several weakly degassing volcanoes, undetected by satellites, is presented for the first time. We also compare our results with those reported in the literature, providing ranges of variability in emission not accessible in the past. The open-access data repository introduced in this article will enable further exploitation of this unique dataset, with a focus on volcanological research, risk assessment, satellite-sensor validation, and improved quantification of the prevalent tropospheric component of global volcanic emission

A Bayesian approach to infer volcanic system parameters, timing, and size of Strombolian events from a single tilt station

Persistently active volcanoes are characterized by frequent eruptions, in which volatiles dissolved in magma play an important role in controlling the explosivity. Inverting techniques on geodetic data sets have been used to retrieve information about key controlling parameters of these eruptions. However, up to date, several data sets are combined to obtain reliable estimates of the physical parameters using a physical model, hindering the possibility to provide forecasting tools for time and magnitude of eruptions at volcanoes with limited monitoring network. In this work, we propose an approach to extract valuable information out of limited data sets through inverting techniques dealing with limited number of sensors, but high frequency of events. Our method exploits time series of tilt signals recorded by a single station to estimate, by mean of the Bayesian statistics and a physics‐based model, the range of the controlling parameters. The method was developed and tested on a synthetic volcanic system before being applied on data from Semeru volcano (Indonesia). Finally, we tested the possibility to forecast explosion magnitude and timing using data recorded by a single tilt station. Results show that data from a limited network or even a single tilt station is sufficient to estimate the controlling parameters. The information obtained is shown to be useful for estimating the time and magnitude of future events, which can enhance the monitoring systems of those volcanoes characterized by frequent, potentially dangerous events.Published versio

Shear wave measurements of a gelatin’s Young’s modulus

Gelatin is a commonly used material for analog experiments in geophysics, investigating fluid-filled fracture propagation (e.g., magmatic dikes), as well as fault slip. Quantification of its physical properties, such as the Young’s modulus, is important for scaling experimental results to nature. Traditional methods to do so are either time consuming or destructive and cannot be performed in situ. We present an optical measurement technique, using shear waves. Polarizing filters enable visualization of the deviatoric stresses in a block of gelatin, so shear wave propagation can be observed. We demonstrate how the wave velocity can be measured and related to the Young’s modulus, show how the results are comparable to another methodology and discuss processing techniques that maximize the measurement precision. This methodology is useful for experimentalist, as it is simple to implement into a laboratory setting, can make precise, time-efficient estimates of the material strength and additionally is non-destructive and can be performed in situ.Ministry of Education (MOE)National Research Foundation (NRF)Published versionThis research was supported by the National Research Foundation Singapore (award NRF2015−NRF−ISF001−2437) and the Singapore Ministry of Education under the Research Centres of Excellence initiative

360 intrusions in a miniature volcano : birth, growth and evolution of an analog edifice

International audienceVolcanoes throughout the world have been monitored with complete geophysical data for no more than three decades, a relatively short time compared to their overall life. The consequence is that we lack a long observation of volcanic growth and behavior to get a more complete picture of the interaction between edifice stress state and magma transfer. Here we present the birth and evolution of a 83x83 cm analog model, where we reproduce for the first time volcanic growth over 360 successive intrusions (15 mL every half hour, at a rate of 3 mL/min) in an analog elasticity-dominated material (pigskin gelatine). Our model volcano started as a flat topography and ended 3.82 cm in height at the summit. It displayed cyclic eruptive patterns with alternating phases of eruptive and purely intrusive behavior. Alike to many intraplate volcanoes in nature, main dyke swarms produced in the experiment were disposed in a three-branched star pattern centered above the injection source (“volcanic rift zones”). Two radial sill networks, at source depth and edifice base, surrounded them. The interaction of edifice growth and magma transfer was dominated by long-term radial compressive stress building during dyke swarming and radial compressive stress release/compensation during sill emplacement. Near-surface stresses, deduced from the main orientation eruptive fissures and “dry” fractures, became more localised as the volcano grew. At the end of the experiment, the shallow stress field was interpreted as generally extensional radial at the summit, extensional tangential on the flanks, and compressive radial in distal areas

Magma expansion and fragmentation in a propagating dyke

International audienc