Forecasting Of Volcanic Eruptions Research Articles

Universal machine learning approach to volcanic eruption forecasting using seismic features

Introduction: Volcano seismology has successfully predicted several eruptions and includes many reliable methods that have been adopted extensively by volcanic observatories; however, there are several problems that still lack solutions. Meanwhile, the overwhelming success of data-driven models to solve predictive complex real-world problems positions them as an effective addition to the monitoring systems deployed in volcanological observatories.Methods: By applying signal processing techniques on seismic records, we extracted four different seismic features, which usually change their trend when the system is approaching an eruptive episode. We built a temporal matrix with these parameters then defined a label for each temporal moment according to the real state of the volcanic activity (Unrest, Pre-Eruptive, Eruptive). To solve the remaining problem developing early warning systems that are transferable between volcanoes, we applied our methodology to databases associated with different volcanic systems, including data from both explosive and effusive episodes, recorded at several volcanic scenarios with open and closed conduits: Mt. Etna, Bezymianny, Volcán de Colima, Mount St. Helens and Augustine.Results and Discussion: This work proposes the use of Neural Networks to classify the volcanic state of alert based on the behaviour of these features, providing a probability of having an eruption. This approach offers a Machine Learning tool for probabilistic short-term volcanic eruption forecasting, transferable to different volcanic systems. This innovative method classifies the state of volcanic hazard in near real-time and estimates a probability of the occurrence of an eruption, resulting in a period from at least hours to several days to forecast an eruption.

Modeling deformation, seismicity, and thermal anomalies driven by degassing during the 2005-2006 pre-eruptive unrest of Augustine Volcano, Alaska

Understanding the subsurface processes that generate volcanic unrest, including surface deformation, earthquakes, temperature increase, and gas emissions, is essential to improve the forecasting of volcanic eruptions. Volcanic gases exsolved from magma reservoirs can transfer heat towards the surface when the system is open, or pressurize the volcano and lead up to eruptions when the system is closed. Hence, the nature of the observed precursory signals is greatly dependent on whether exsolved volatiles accumulate or escape. In this study, we develop a two-dimensional finite element model to calculate the thermal and poroelastic responses of a volcano to gases that exsolve from depth and migrate to the surface through a pre-existing fractured conduit. This model is explored through a set of sensitivity tests to quantify the controls of gas fluxes and permeability on geophysical observables; and is used to interpret surface deformation (GPS), ground temperature, and seismicity data recorded before the 2006 eruption of Augustine volcano, Alaska, by utilizing the Ensemble Kalman Filter data assimilation technique and Coulomb stress calculations. Our results show that the permeable transfer of gas through a fractured conduit can yield a measurable thermal anomaly at the surface for at least one year before the eruption, consistent with ground- and remote sensing-based data. Moreover, gas flux increased about ten times around three months before the eruption, which might have accelerated hydrothermal alteration and reduced permeability of the conduit by several orders of magnitude, thus accumulating gases inside the volcanic edifice, generating surface deformation, and triggering volcano-tectonic earthquakes. Eventually, failure of the sealed pathways due to high overpressure led to the eruption. Multi-physical numerical models coupling gas flow with host rock deformation and heat transfer are useful tools to understand the triggering mechanisms of volcanic eruptions driven by volcanic gases.

Tephrostratigraphy and Eruption History of Kozushima Volcano, Izu Islands, Central Japan during the Last 30,000 Years

Kozushima is a volcanic island, located in the northern part of the Izu Islands, approximately 170 km SSW of central Tokyo. The volcanism of Kozushima Volcano started at 80-60 ka and formed monogenetic volcanoes. The latest eruption occurred in AD 838, and was associated with the formation of the lava dome and pyroclastic cone of Tenjo-san. In order to contribute to the long-term forecasting of volcanic eruptions on the Izu Islands off Tokyo, the tephrostratigraphy and eruption history of Kozushima Volcano during the last 30,000 years is reconstructed. According to the geological surveys, the widespread Kikai-Akahoya (K-Ah; 7.3 cal ka) and Aira-Tanzawa (AT; 30.0 cal ka) tephras from southern Kyushu, and Niijima-Mukaiyama (Nj-My; AD 886), Niijima-Shikinejima (Nj-Sk; 8 cal ka) and Niijima-Miyatsukayama (Nj-Mt; 12.8 cal ka) tephras from the Niijima Volcano 20 km NNE of Kozushima are recognized. Tephras that also erupted from Kozushima Volcano are Kozushima-Tenjosan (Kz-Tj; AD 838), Kozushima-Ananoyama (Kz-An; 7-9 c), Kozushima-Chichibuyama-A′ (Kz-CbA′; 14-12.8 cal ka), Kozushima-Chichibuyama-A (Kz-CbA; 30-22 cal ka), and Kozushima-Chichibuyama-B (Kz-CbB; ca. 30 ka). Kz-An is formed by the activity of the northern volcanic chains (Kobe-yama–Anano-yama–Hanatate) just before the Tenjo-san eruption. Kz-CbA′ is distributed in southern Kozushima. Source vent and distribution of Kz-CbA′ have not yet been identified. The eruption history of Kozushima volcano over the last 30,000 years is as follows. At ca. 30 ka, Kz-CbB erupted in the central Kozushima, and the Nachi-san dome and Takodo-yama dome formed. At 30-22 ka, the Kz-CbA eruption in the southern Kozushima and the formation of the southern volcanic chain occurred. After the eruption of Kz-CbA′, the formation of the northern volcanic chain was followed by the eruption of Tenjo-san volcano. In addition, the eruption rate of Kozushima volcano is estimated during the last 30,000 years to be approximately 0.06 km3/1000 y in DRE.

Indicators of Volcanic Eruptions Revealed by Global M4+ Earthquakes

AbstractDetermining whether seismicity near volcanoes is due primarily to tectonic or magmatic processes is a challenging but critical endeavor for volcanic eruption forecasting and detection, especially at poorly monitored volcanoes. Global statistics on the occurrence and timing of earthquakes near volcanoes both within and outside of eruptive periods reveal patterns in eruptive seismicity that may improve our ability to discern magmatically driven seismicity from purely tectonic seismicity. In this paper, we catalog magnitude four and greater (M4+) earthquakes near volcanoes globally and compute statistics on their occurrence with respect to various eruptive and volcanic attributes, evaluating their utility as diagnostic indicators of eruptions. Using a 2‐week time window and a 30 km radius around the volcanoes, we find that 11% of eruptions are preceded by at least one M4+ earthquake, but only 1% of such earthquakes is followed by eruption. However, earthquakes located 5–15 km from the volcano, those with normal faulting mechanisms and/or large nondouble‐couple components, and those occurring as groups are more commonly associated with eruptions, providing significant forecasting utility in some cases. Similarly, certain volcanoes are more likely to exhibit such precursors, such as those with long repose periods. We illustrate the use of these data in eruption forecasting scenarios, including rapid identification of analogous earthquake sequences at other volcanoes. When integrated within the context of multiparametric, multidisciplinary probabilistic assessments of volcanic activity, global earthquake statistics can improve eruption forecasts, and our work provides a model for use on other rapidly expanding global volcanological databases.

Invited perspectives: The volcanoes of Naples: how can the highest volcanic risk in the world be effectively mitigated?

Abstract. The Naples (southern Italy) area has the highest volcanic risk in the world due to the coexistence of three highly explosive volcanoes (Vesuvius, Campi Flegrei and Ischia) with extremely dense urbanisation. More than 3 million people live to within 20 kilometres from a possible eruptive vent. Mitigating such an extreme risk is made difficult because volcanic eruption forecasting is currently an empirical procedure with a very uncertain outcome. This paper starts by recalling the state of the art of eruption forecasting, and then describes the main hazards in the Neapolitan area, shortly presenting the activity and present state of its volcanoes. Then, it proceeds to suggest the most effective procedures to mitigate the extreme volcanic and associated risks. The problem is addressed in a highly multidisciplinary way, taking into account the main economic, sociological and urban issues. The proposed mitigation actions are then compared with the existing emergency plans, developed by Italian Civil Protection, by highlighting their numerous, very evident faults. Our study, besides regarding the most complex and extreme situation of volcanic risk in the world, gives guidelines for assessing and managing volcanic risk in any densely urbanised area.

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.

Editorial: Towards Improved Forecasting of Volcanic Eruptions

Editorial: Towards Improved Forecasting of Volcanic Eruptions

Origin of Shallow Volcanic Tremor: The Dynamics of Gas Pockets Trapped Beneath Thin Permeable Media

AbstractLinking volcano‐seismic signals with subsurface processes is crucial to improve the forecasting of volcanic eruptions. One of the most enigmatic signals is shallow volcanic tremor, a highly periodic ground vibration that is typically sourced beneath the crater of active volcanoes, is long lasting (from minutes to years), appears during unrest periods, and frequently precedes eruptions. In this paper, we demonstrate that shallow tremor can be produced by periodic pressure oscillations emerging spontaneously beneath permeable media (e.g., fractured magma caps). These pressure oscillations are the result of three concurrent processes: (a) the transient porous flow of gases through the permeable cap; (b) the temporary accumulation of these gases beneath the cap, forming a gas pocket; and (c) the random supply of volatiles from deeper levels. For highly permeable media (≥10−12 m2; realistic for shallow volcanic edifices), the pressure in subsurface gas pockets is governed by the equation of a linear oscillator; hence, under proper conditions, periodic pressure oscillations emerge during the transfer of gases from the Earth's interior to the surface. Our model is consistent with geophysical data showing that the tremor source is localized at a fixed region and can explain the main characteristics of ground vibrations, including frequency gliding, variations of seismic amplitude prior to eruptions, and the different types of tremor observed. For thin permeable caps (<100 m), we find that different eruption mechanisms (e.g., magma ascent vs. cap sealing) leave distinct footprints in the tremor properties, thus opening new perspectives to forecast the type and style of impending eruptions.

The relation between differential stress, driving pressure ratio, tensile strength and reservoir failure in a magmatic system – Towards eruption forecasting

In this study a relation is established between differential stress (σd), driving magma pressure ratio (R′) and tensile strength (T) of a rock mass in a volcanic system. It is shown that in σd vs. R′ space, the T curve follows equation of rectangular hyperbola and for dyking or volcanic eruption to occur, this T curve must be exceeded. It is proposed that this theoretical relation can be exploited to understand magma reservoir failure and for volcanic eruption forecasting. Applicability of this concept is demonstrated on Santorini volcanic system (Greece) for which considerable background information is available from previous studies. Published dyke orientation and aspect ratio data from Santorini yield σd and R′ values of 8.04 MPa and 0.22 respectively. Considering a weak quality host rock mass in Santorini, tensile strength curve for T = 1.5 MPa is plotted in σd vs R′ space. Considering magma reservoir volume and rock physical property estimates to be valid, and assuming σd and absolute stress to be constant, it is argued that change in reservoir dynamics would be controlled by variations in volume of magma released from the deeper magma reservoir to shallow reservoir (Vr) in Santorini. Values of R′ and Vr for the events of non-dyking in Santorini are also calculated. Minimum R′ and Vr required to induce dyking and eruption are estimated and it is concluded that the proposed theory can be generally applied for eruption forecasting.

Seismic Anisotropy Reveals a Dynamic Link Between Adjacent Magmatic Segments Prior to Dyke Intrusion

AbstractSeismic anisotropy has increasingly been proposed as a tool in the monitoring of magmatic systems and potential forecasting of volcanic eruptions. We present a detailed study of how seismic anisotropy evolves in an active magmatic rift segment before, during, and after a dyke intrusion in the Afar depression, Ethiopia. Results show that seismic anisotropy prior to the dyke intrusion is controlled by a complex and deforming magma plumbing system beneath the adjacent Dabbahu and Manda‐Hararo magmatic segments. Approximately eight days prior to the dyke intrusion in the Dabbahu segment, the pattern of anisotropy, coupled with lower crustal seismicity, is best explained by the inflation of a lower crustal magma reservoir in the Manda‐Hararo segment. This is the only clearly observed precursory change in seismic anisotropy. During the dyke intrusion, the magnitude of seismic anisotropy increases twofold, before rapidly returning to predyke values once the intrusion has ended. Combining our observations with models of magmatically induced crustal stress, we propose that when the deep magma reservoir beneath the Dabbahu segment becomes overpressured, inflation is triggered in the magma reservoir of the neighboring Manda‐Hararo segment. This provides strong evidence for a hydraulic link between the deep magma systems of the neighboring rift segments and that magma reservoirs beneath the Dabbahu segment can be fed by the lateral flow of magma from an adjacent segment. Our results demonstrate that seismic anisotropy has the potential to be a powerful tool for monitoring deformation in the magma plumbing systems of active volcanoes.

Foundations for Forecasting: Defining Baseline Seismicity at Fuego Volcano, Guatemala

Accurate volcanic eruption forecasting is especially challenging at open vent volcanoes with persistent low levels of activity and relatively sparse permanent monitoring networks. We present a description of seismicity observed at Fuego volcano in Guatemala during January of 2012, a period representative of low-level, open-vent dynamics typical of the current eruptive period. We use this time to establish a baseline of activity from which to build more accurate forecasts. Seismicity consists of both harmonic and non-harmonic tremor, rockfalls, and a variety of signals associated with frequent small eruptions. In addition, there are many small discrete events not necessarily linked to eruptions that we examine in detail here. Using arrival times recorded on a temporary, nine-station network on the edifice of Fuego, we compute a 1-D velocity model and use it to locate earthquakes. The discrete events include 5 families of repeating events. This type of description can act as a template for establishing monitoring efforts at under-studied volcanoes around the world.

Numerical investigation of permeability models for low viscosity magmas: Application to the 2007 Stromboli effusive eruption

Magma permeability is the most important factor controlling the transition between effusive and explosive styles during magma ascent at active volcanoes. When magma permeability is low, gas bubbles in the melt expand as the pressure decreases; above a critical gas volume fraction threshold, magma fragments, generating an explosive eruption. On the contrary, if magma is sufficiently permeable, gas ascends through the conduit towards the surface faster than the magma ascent speed, producing decoupling of gas and magma and reducing the maximum vesicularity. This decoupled flow inhibits fragmentation and leads to either an effusive eruption or quiescent degassing. Accurate modelling of permeability behaviour is therefore fundamental when simulating magma ascent processes. In this work, we compare different permeability models for low viscosity magmas using a 1D steady-state model. We use, as a test case, the 2007 effusive eruption at Stromboli volcano, Italy. We compare the numerical solutions computed using the linear Darcy's law with those obtained using the non-linear Forchheimer relation. Our numerical results show that, using Darcy's law and appropriate permeability models, it is possible to obtain an effusive eruption in agreement with observations. However, we found that, in the shallow conduit, the limit of applicability of Darcy's law (that is the modified Reynolds number Rem < 10) is exceeded due to high gas flow rates. Furthermore, we show that using Forchheimer's law and some parametric expressions for viscous and inertial permeabilities, results can be compatible with an effusive eruption, once appropriate values are chosen. However, one of the parameters required to obtain an effusive eruption, the friction coefficient between gas and melt, is several orders of magnitude lower than that determined from measurements of solid erupted samples. This result requires further experimental verification. We propose that our novel permeability modelling regime is suitable for basaltic volcanism. We highlight that permeabilities derived from studying solid samples are not representative of the actual permeability of a molten magma, at least in the case of low viscosity basaltic magmas. These findings have fundamental implications for the quantification of permeability, modelling of volcanic processes and volcanic eruption dynamics, and the forecasting of volcanic eruptions.

Introducing the Volcanic Unrest Index (VUI): a tool to quantify and communicate the intensity of volcanic unrest

Accurately observing and interpreting volcanic unrest phenomena contributes towards better forecasting of volcanic eruptions, thus potentially saving lives. Volcanic unrest is recorded by volcano observatories and may include seismic, geodetic, degassing and/or geothermal phenomena. The multivariate datasets are often complex and can contain a large amount of data in a variety of formats. Low levels of unrest are frequently recorded, causing the distinction between background activity and unrest to be blurred, despite the widespread usage of these terms in unrest literature (including probabilistic eruption-forecasting models) and in Volcanic Alert Level (VAL) systems. Frequencies and intensities of unrest episodes are not easily comparable over time or between volcanoes. Complex unrest information is difficult to communicate simply to civil defence personnel and other non-scientists. The Volcanic Unrest Index (VUI) is presented here to address these issues. The purpose of the VUI is to provide a semi-quantitative rating of unrest intensity relative to each volcano’s past level of unrest and to that of analogous volcanoes. The VUI is calculated using a worksheet of observed phenomena. Ranges for each phenomenon within the worksheet can be customised for individual volcanoes, as demonstrated in the companion paper for Taupo Volcanic Centre, New Zealand (Potter et al. 2015). The VUI can be determined retrospectively for historical episodes of unrest based on qualitative observations, as well as for recent episodes with state-of-the-art monitoring. This enables a long time series of unrest occurrence and intensity to be constructed and easily communicated to end users. The VUI can also assist with VAL decision-making. We present and discuss two approaches to the concept of unrest.

Training in crisis communication and volcanic eruption forecasting: design and evaluation of an authentic role-play simulation

We present an interactive, immersive, authentic role-play simulation designed to teach tertiary geoscience students in New Zealand to forecast and mitigate a volcanic crisis. Half of the participating group (i.e., the Geoscience Team) focuses on interpreting real volcano monitoring data (e.g., seismographs, gas output etc.) while the other half of the group (i.e., the Emergency Management Team) forecasts and manages likely impacts, and communicates emergency response decisions and advice to local communities. These authentic learning experiences were aimed at enhancing upper-year undergraduate students’ transferable and geologic reasoning skills. An important goal of the simulation was specifically to improve students’ science communication through interdisciplinary team discussions, jointly prepared, and delivered media releases, and real-time, high-pressure, press conferences. By playing roles, students experienced the specific responsibilities of a professional within authentic organisational structures. A qualitative, design-based educational research study was carried out to assess the overall student experience and self-reported learning of skills. A pilot and four subsequent iterations were investigated. Results from this study indicate that students found these role-plays to be a highly challenging and engaging learning experience and reported improved skills. Data from classroom observations and interviews indicate that the students valued the authenticity and challenging nature of the role-play although personal experiences and team dynamics (within, and between the teams) varied depending on the students’ background, preparedness, and personality. During early iterations, observation and interviews from students and instructors indicate that some of the goals of the simulation were not fully achieved due to: A) lack of preparedness, B) insufficient time to respond appropriately, C) appropriateness of roles and team structure, and D) poor communication skills. Small modifications to the design of Iterations 3 and 4 showed an overall improvement in the students’ skills and goals being reached. A communication skills instrument (SPCC) was used to measure self-reported pre- and post- communication competence in the last two iterations. Results showed that this instrument recorded positive shifts in all categories of self-perceived abilities, the largest shifts seen in students who participated in press conferences. Future research will be aimed at adapting this curricula to new volcanic and earthquake scenarios.

Uranium Series Accessory Crystal Dating of Magmatic Processes

Complex and protracted crystallization histories over geologic timescales are recorded in accessory minerals (e.g., zircon, allanite). Although magmatic crystallization was traditionally assumed to occur essentially instantaneously for the purposes of interpreting mineral geochronometers with low absolute time resolution for ancient samples, it emerged relatively recently that magmatic crystallization can occur over extended durations. This discovery arose from applying high-spatial-resolution accessory mineral dating techniques for uranium series isotopes to young volcanic and cognate plutonic rocks. The emerging pattern from these studies is that individual crystals and crystal populations record crystallization episodes lasting from &lt;1,000 to many hundreds of thousands of years. Accessory mineral dating of volcanic rocks and cognate plutonic xenoliths opens new research avenues for crystal age fingerprinting that correlates pyroclastic deposits, lavas, and plutonic rocks by using characteristic age distributions. It also provides direct observations on magmatic accumulation and residence times, and the preeruptive configuration of subterraneous magma bodies and intrusive complexes with implications for the forecasting of volcanic eruptions. Awareness of potentially protracted crystallization in igneous rocks should guide the interpretation of accessory mineral ages.

Eruption time series statistically examined: Probabilities of future eruptions at Villarrica and Llaima Volcanoes, Southern Volcanic Zone, Chile

Probabilistic forecasting of volcanic eruptions is a central issue of applied volcanology with regard to mitigating consequences of volcanic hazards. Recent years have seen great advances in the techniques of statistical analysis of volcanic eruption time series, which constitutes an essential component of a multi-discipline volcanic hazard assessment. Here, two of the currently most active volcanoes of South America, Villarrica and Llaima, are subjected to an established statistical procedure, with the aim to provide predictions for the likelihood of future eruptions within a given time interval. In the eruptive history of both Villarrica and Llaima Volcanoes, time independence of eruptions provides consistency with Poissonian behaviour. A moving-average test, helping to assess whether the distribution of repose times between eruptions changes in response to the time interval considered, validates stationarity for at least the younger eruption record. For the earlier time period, stationarity is not entirely confirmed, which may artificially result from incompleteness of the eruption record, but can also reveal fluctuations in the eruptive regime. To take both possibilities into account, several different distribution functions are fit to the eruption time series, and the fits are evaluated for their quality and compared. The exponential, Weibull and log–logistic distributions are shown to fit the repose times sufficiently well. The probability of future eruptions within defined time periods is therefore estimated from all three distribution functions, as well as from a mixture of exponential distribution (MOED) for the different eruption regimes and from a Bayesian approach. Both the MOED and Bayesian estimates intrinsically predict lower eruption probabilities than the exponential distribution function, while the Weibull distributions have increasing hazard rates, hence giving the highest eruption probability forecasts. This study provides one of the first approaches to subject historical time series of small eruptions (including those of Volcanic Explosivity Index = 2) of very active volcanoes to this type of statistical analysis. Since both Villarrica and Llaima are situated in a region of high population density, the eruption probabilities determined in this study present a valuable contribution to regional hazard assessment.

Using WiMAX to Improve Volcano Monitoring during an Emergency: A Feasibility Study of the WEIRD System Applied to the Campi Flegrei Volcanic Area Scenario (Southern Italy)

IEEE Standard for Local and Metropolitan Area Networks (hereafter IEEE 802.16; online at http://standards.ieee.org/getieee802/802.16.html) is one of the most promising mobile and fixed broadband wireless access technologies for next-generation all-IP networks in the 3.5 GHz band (European spectrum profile). Commonly known as Universal WiMAX (worldwide inter-operability for microwave access), this access technology reaches a high bit rate and covers large areas with a single base station, making it possible to offer connectivity to end users in a cost-effective way. A further useful property of the WiMAX technology is that the transmission can be used both in line-of-sight (LOS) and non-line-of-sight (NLOS) environments, allowing highly feasible communications (WiMAX Forum 2004). Thanks to these features, IEEE 802.16 opens the way to the use of wireless technologies in the environmental monitoring of areas such as seismic and volcanic zones. Volcanic eruptions, in particular, are among the highest natural risks in the world. About 600 volcanoes have erupted in historical times, and many are located near densely populated areas. An adequate monitoring system is essential to understanding the physical processes preceding an eruption and for mitigating the risk of such an event. Active volcano surveillance is primarily based on the analysis of geophysical and geochemical parameters gathered by monitoring networks. Seismological methods are among the most useful methods for monitoring volcanoes. In fact, several types of seismic signals, e.g. , volcano-tectonic earthquakes (VT), long-period events (LP), and volcanic tremors, can occur before and during an eruption (McNutt 2005). The analysis and interpretation of these seismic signals is a very important task for volcanic eruption forecasting. WiMAX technology can be applied to provide broadband wireless access in volcano monitoring scenarios to solve some of the problems that prevent us from improving surveillance of volcanic activities during emergencies. In particular, this paper focuses on a novel …

Towards forecasting volcanic eruptions using seismic noise

During inter-eruption periods, magma pressurization yields subtle changes of the elastic properties of volcanic edifices. We use the reproducibility properties of the ambient seismic noise recorded on the Piton de la Fournaise volcano to measure relative seismic velocity variations of less than 0.1 % with a temporal resolution of one day. Our results show that five studied volcanic eruptions were preceded by clearly detectable seismic velocity decreases within the zone of magma injection. These precursors reflect the edifice dilatation induced by magma pressurization and can be useful indicators to improve the forecasting of volcanic eruptions.

Volcanic steam output directly measured in fumaroles: the observed variations at Vulcano Island, Italy, between 1983 and 1987

The mass of steam emitted by the fumaroles of the crater of Vulcano (Aeolian Islands, Italy) was evaluated by using a direct measuring method. Measurements were effected with this method between 1983 and 1987 in nine field campaigns, the results of which are given in this paper. The steam flux measurements were performed by an instrument expressly designed for steam condensation. The estimates of the thermal energy transported daily by the steam gave values of up to 10E12 J. The sharp variations in the total mass outputs recorded in 1984 and 1985 are here interpreted as being a consequence of the probable accumulation of fluid pressure at depth, during the evolution of volcanic activity. The different results obtained from the various areas of the fumarolic field during the evolutionary phases have led to the hypothesis that different subsystems exist that feed the fumaroles, and that their activity is triggered by volcano-tectonics. This method can be applied in the evaluation of both fumarolic steam and thermal energy outputs, and therefore it is particularly useful in geothermal exploration, in the evaluation of the environmental impact of volcanic degassing, and in the forecasting of volcanic eruptions. The evaluation of the steam output is also useful for quantifying the release of other gaseous species and giving univocal interpretations regarding their variations in concentrations. Furthermore this direct method provides a new way of calibrating the flux estimates effected by other telemetric techniques (Lidar, Cospec, etc.).

Bayesian analysis of volcanic eruptions

The simple Poisson model generally gives a good fit to many volcanoes for volcanic eruption forecasting. Nonetheless, empirical evidence suggests that volcanic activity in successive equal time-periods tends to be more variable than a simple Poisson with constant eruptive rate. An alternative model is therefore examined in which eruptive rate(λ) for a given volcano or cluster(s) of volcanoes is described by a gamma distribution (prior) rather than treated as a constant value as in the assumptions of a simple Poisson model. Bayesian analysis is performed to link two distributions together to give the aggregate behavior of the volcanic activity. When the Poisson process is expanded to accomodate a gamma mixing distribution on λ, a consequence of this mixed (or compound) Poisson model is that the frequency distribution of eruptions in any given time-period of equal length follows the negative binomial distribution (NBD). Applications of the proposed model and comparisons between the generalized model and simple Poisson model are discussed based on the historical eruptive count data of volcanoes Mauna Loa (Hawaii) and Etna (Italy). Several relevant facts lead to the conclusion that the generalized model is preferable for practical use both in space and time.