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Relevant bibliographies by topics / Volcanic activity prediction

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Academic literature on the topic 'Volcanic activity prediction'

Author: Grafiati

Published: 4 June 2021

Last updated: 28 July 2024

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Journal articles on the topic "Volcanic activity prediction"

1

Wyman, Teresa M. "Prediction of Seismic and Volcanic Activity." Science & Technology Libraries 8, no. 3 (November 29, 1988): 55–83. http://dx.doi.org/10.1300/j122v08n03_08.

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Iguchi, Masato, Surono, Takeshi Nishimura, Muhamad Hendrasto, Umar Rosadi, Takahiro Ohkura, Hetty Triastuty, et al. "Methods for Eruption Prediction and Hazard Evaluation at Indonesian Volcanoes." Journal of Disaster Research 7, no. 1 (January 1, 2012): 26–36. http://dx.doi.org/10.20965/jdr.2012.p0026.

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We report methods, based on geophysical observations and geological surveys, for the prediction of eruptions and the evaluation of the activity of 4 volcanoes in Indonesia. These are Semeru, Guntur, Kelud and Sinabung volcanoes. Minor increases in tilt were detected by borehole tiltmeters prior to eruptions at the Semeru volcano depending on the seismic amplitude of explosion earthquakes. The results show the possibility of prediction of the type and magnitude of eruption and the effectiveness of observation with a high signalto-noise ratio. The establishment of background data is important for evaluating volcanic activity in longterm prediction. Typical distributions of volcanic and local tectonic earthquakes were obtained around the Guntur volcano, where geodetic monitoring by continuous GPS observation is valuable. The cumulative volume of eruptive products is valuable for evaluating the potential for future eruption. The eruptive rate of the Kelud volcano is ca 2×106m3/y (dense rock equivalent), but the volume of the 2007 eruption was only 2×107m3, suggesting a still high potential for eruption. Based on geological surveys and dating, an eruption scenario is proposed for the activity of Mt. Sinabung, where phreatic eruptions occurred in 2010 after a historically long dormancy.

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Rummel, Lisa, Alexander Bartels, and Franz May. "Using a multi-criteria approach for a regional differentiation of the likelihood of future volcanic activity in Germany." Safety of Nuclear Waste Disposal 2 (September 6, 2023): 143. http://dx.doi.org/10.5194/sand-2-143-2023.

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Abstract. Future volcanic activity, which might influence the long-term stability of radioactive waste repositories, must be evaluated critically. In Germany, according to the Repository Site Selection Act (StandAG), areas in which Quaternary volcanism is either present or future volcanic activity is expected within the next 1 Ma must be excluded from the site selection process for a high-level radioactive waste repository. However, while regions with Quaternary volcanism are reasonably well known in Germany, forecasting volcanic activity in intraplate fields is difficult, as many processes and their interaction control the spatial distribution of the volcanic centres. To develop an appropriate method to forecast possible regions of volcanic activity, a semi-quantitative, multi-criteria approach is used that combines a variety of indicators including, amongst others, seismic anomalies in the mantle, gravity data, tectonic activity, sutures, ground motion, earthquakes, mantle degassing centres and the geochronological data of volcanic rocks. The used indicators provide possible information about the source of melting in the mantle, the ascent of melt through the lithosphere and the eruption process at the surface. In total, 30 indicators were defined and ranked according to their presumed relevance for the long-term prediction of volcanism, following the results of two expert surveys. Quantifiable parameters were selected for the individual indicators, and threshold values were assigned and related to levels of significance. The parameters were uniformly applied for Germany in order to enable a transparent and equal risk assessment of future volcanic activity in all of the federal states. To consider the uncertainties regarding the distribution and manifestation of parameters in addition to their mostly unknown underlying large-scale processes, buffer zones were defined in which the values of relevance decrease with increasing distance from the initial parameter extent. By combining all parameters into an overall index, the presented results allow the regional differentiation of the likelihood of future volcanic eruptions in Germany. The robustness of the results is shown by varying the weights of the used parameters in the Germany-wide risk map. Different categories for the probability of future volcanic activity can be defined and used, depending on the needs and assessment of the volcanic hazard potential.

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Shiogama, Hideo, Seita Emori, Takashi Mochizuki, Sayaka Yasunaka, Tokuta Yokohata, Masayoshi Ishii, Toru Nozawa, and Masahide Kimoto. "Possible Influence of Volcanic Activity on the Decadal Potential Predictability of the Natural Variability in Near-Term Climate Predictions." Advances in Meteorology 2010 (2010): 1–7. http://dx.doi.org/10.1155/2010/657318.

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Initialization based on data assimilations using historical observations possibly improves near-term climate predictions. Significant volcanic activity in the future is unpredictable and not assumed in future climate predictions. To examine the possible influence of unpredictable future volcanic activity on the decadal potential predictability of the natural variability, we performed a 2006–2035 climate prediction experiment with the assumption that the 1991 Mt. Pinatubo eruption would take place again in 2010. The Pinatubo forcing induced not only significant cooling responses but also considerable noises in the natural variability. The errors due to the Pinatubo forcing grew faster than that arising from imperfect knowledge of the observed state, leading to a rapid reduction of the decadal potential predictability of the natural variability.

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Scharrer, K., R. Malservisi, Ch Mayer, O. Spieler, and U. Münzer. "Combination of SAR remote sensing and GIS for monitoring subglacial volcanic activity – recent results from Vatnajökull ice cap (Iceland)." Natural Hazards and Earth System Sciences 7, no. 6 (November 27, 2007): 717–22. http://dx.doi.org/10.5194/nhess-7-717-2007.

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Abstract. This paper presents latest results from the combined use of SAR (Synthetic Aperture Radar) remote sensing and GIS providing detailed insights into recent volcanic activity under Vatnajökull ice cap (Iceland). Glaciers atop active volcanoes pose a constant potential danger to adjacent inhabited regions and infrastructure. Besides the usual volcanic hazards (lava flows, pyroclastic clouds, tephra falls, etc.), the volcano-ice interaction leads to enormous meltwater torrents (icelandic: jökulhlaup), devastating large areas in the surroundings of the affected glacier. The presented monitoring strategy addresses the three crucial questions: When will an eruption occur, where is the eruption site and which area is endangered by the accompanying jökulhlaup. Therefore, sufficient early-warning and hazard zonation for future subglacial volcanic eruptions becomes possible, as demonstrated for the Bardárbunga volcano under the northern parts of Vatnajökull. Seismic activity revealed unrest at the northern flanks of Bardárbunga caldera at the end of September 2006. The exact location of the corresponding active vent and therefore a potentially eruptive area could be detected by continuous ENVISAT-ASAR monitoring. With this knowledge a precise prediction of peri-glacial regions prone to a devastating outburst flood accompanying a possible future eruption is possible.

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German, Josephine D., Anak Agung Ngurah Perwira Redi, Ardvin Kester S. Ong, Yogi Tri Prasetyo, and Vince Louis M. Sumera. "Predicting Factors Affecting Preparedness of Volcanic Eruption for a Sustainable Community: A Case Study in the Philippines." Sustainability 14, no. 18 (September 9, 2022): 11329. http://dx.doi.org/10.3390/su141811329.

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Volcanic eruption activity across the world has been increasing. The recent eruption of Taal volcano and Mt. Bulusan in the Philippines affected several people due to the lack of resources, awareness, and preparedness activities. Volcanic eruption disrupts the sustainability of a community. This study assessed people’s preparedness for volcanic eruption using a machine learning ensemble. With the high accuracy of prediction from the ensemble of random forest classifier (93%) and ANN (98.86%), it was deduced that media, as a latent variable, presented as the most significant factor affecting preparedness for volcanic eruption. This was evident as the community was urged to find related information about volcanic eruption warnings from media sources. Perceived severity and vulnerability led to very high preparedness, followed by the intention to evacuate. In addition, proximity, subjective norm, and hazard knowledge for volcanic eruption significantly affected people’s preparedness. Control over individual behavior and positive attitude led to a significant effect on preparedness. It could be posited that the government’s effective mitigation and action plan would be adhered to by the people when disasters, such as volcanic eruptions, persist. With the threat of climate change, there is a need to reevaluate behavior and mitigation plans. The findings provide evidence of the community’s resilience and adoption of mitigation and preparedness for a sustainable community. The methodology provided evidence for application in assessing human behavior and prediction of factors affecting preparedness for natural disasters. Finally, the results and findings of this study could be applied and extended to other related natural disasters worldwide.

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Dryukova, E. D., G. M. Nerobelov, M. S. Sedeeva, A. V. Kiselev, A. G. Mahura, and V. I. Gorny. "Integration of Satellite Monitoring and Mathematical Modeling in the Analysis of the Nature of Elevated Sulfur Dioxide Concentrations in the Surface Air of the Northern Part of Finland." Известия Российской академии наук. Физика атмосферы и океана 59, no. 4 (July 1, 2023): 450–60. http://dx.doi.org/10.31857/s0002351523040041.

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The article is devoted to the investigation of the nature of the increment in surface concentration of toxic gas sulfur dioxide (SO2) in Northern Finland. The study is carried out for June 2011 when the increased near-surface SO2 concentration was registered at Finnish observation station Inari Raja-Jooseppi together with the surface wind blowing from the territory of the Kola Peninsula. The hypothesis of natural increment of near-surface SO2 concentration as a result of Grímsvötn volcano eruption (Iceland) is verified using satellite SO2 observations by OMI, numerical weather prediction and atmospheric chemistry model Enviro-HIRLAM and particle dispersion model HYSPLIT. The results show that not only local man-made sources, but also the remote transfer of pollutants from volcanic eruptions can cause an increased near-surface SO2 concentration. To verify this hypothesis, a large set of statistics is required in Northern Finland during periods of volcanic activity in Iceland.

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Senyukov, S. L. "Monitoring and prediction of volcanic activity in Kamchatka from seismological data: 2000–2010." Journal of Volcanology and Seismology 7, no. 1 (February 2013): 86–97. http://dx.doi.org/10.1134/s0742046313010077.

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Guemas, Virginie, Susanna Corti, J. García-Serrano, F. J. Doblas-Reyes, Magdalena Balmaseda, and Linus Magnusson. "The Indian Ocean: The Region of Highest Skill Worldwide in Decadal Climate Prediction*." Journal of Climate 26, no. 3 (February 1, 2013): 726–39. http://dx.doi.org/10.1175/jcli-d-12-00049.1.

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Abstract The Indian Ocean stands out as the region where the state-of-the-art decadal climate predictions of sea surface temperature (SST) perform the best worldwide for forecast times ranging from the second to the ninth year, according to correlation and root-mean-square error (RMSE) scores. This paper investigates the reasons for this high skill by assessing the contributions from the initial conditions, greenhouse gases, solar activity, and volcanic aerosols. The comparison between the SST correlation skill in uninitialized historical simulations and hindcasts initialized from estimates of the observed climate state shows that the high Indian Ocean skill is largely explained by the varying radiative forcings, the latter finding being supported by a set of additional sensitivity experiments. The long-term warming trend is the primary contributor to the high skill, though not the only one. Volcanic aerosols bring additional skill in this region as shown by the comparison between initialized hindcasts taking into account or not the effect of volcanic stratospheric aerosols and by the drop in skill when filtering out their effect in hindcasts that take them into account. Indeed, the Indian Ocean is shown to be the region where the ratio of the internally generated over the externally forced variability is the lowest, where the amplitude of the internal variability has been estimated by removing the effect of long-term warming trend and volcanic aerosols by a multiple least squares linear regression on observed SSTs.

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Lombardo, Valerio, Stefano Corradini, Massimo Musacchio, Malvina Silvestri, and Jacopo Taddeucci. "Eruptive Styles Recognition Using High Temporal Resolution Geostationary Infrared Satellite Data." Remote Sensing 11, no. 6 (March 19, 2019): 669. http://dx.doi.org/10.3390/rs11060669.

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The high temporal resolution of the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument aboard Meteosat Second Generation (MSG) provides the opportunity to investigate eruptive processes and discriminate different styles of volcanic activity. To this goal, a new detection method based on the wavelet transform of SEVIRI infrared data is proposed. A statistical analysis is performed on wavelet smoothed data derived from SEVIRI Mid-Infrared( MIR) radiances collected from 2011 to 2017 on Mt Etna (Italy) volcano. Time-series analysis of the kurtosis of the radiance distribution allows for reliable hot-spot detection and precise timing of the start and end of eruptive events. Combined kurtosis and gradient trends allow for discrimination of the different activity styles of the volcano, from effusive lava flow, through Strombolian explosions, to paroxysmal fountaining. The same data also allow for the prediction, at the onset of an eruption, of what will be its dominant eruptive style at later stages. The results obtained have been validated against ground-based and literature data.

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Dissertations / Theses on the topic "Volcanic activity prediction"

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Roman, Diana Christine. "Changes in local stress field orientation in response to magmatic activity /." view abstract or download file of text, 2004. http://wwwlib.umi.com/cr/uoregon/fullcit?p3136443.

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Doherty, Angela Louise. "Blue-sky eruptions, do they exist? : implications for monitoring New Zealand's volcanoes." Thesis, University of Canterbury. Geological Sciences, 2009. http://hdl.handle.net/10092/2855.

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The term “blue-sky eruption” (BSE) can be used to describe eruptions which are unexpected or have no detected precursory activity. Case study analyses indicate that they have a diverse range of characteristics and magnitudes, providing both direct and indirect hazards and occur in both under-developed and developed countries. BSEs can be a result of physical triggers (e.g. the lack of physically detectable precursors or a lack of understanding of the eruption model of the volcano), social triggers (such as an inadequate monitoring network), or a combination of the two. As the science of eruption forecasting is still relatively young, and the variations between individual volcanoes and individual eruptions are so great, there is no effective general model and none should be applied in the absence of a site-specific model. Similarly, as methods vary between monitoring agencies, there are no monitoring benchmarks for effective BSE forecasting. However a combination of seismic and gas emission monitoring may be the most effective. The United States began a hazard and monitoring review of their volcanoes in 2005. While the general principles of their review would be beneficial in a monitoring review of New Zealand’s volcanoes, differences in styles of volcanism, geographic setting and activity levels mean changes would need to be review to fully appreciate the risk posed by New Zealand’s volcanoes. Similarly, the monitoring benchmarks provided in the U.S. review may not be fully applicable in New Zealand. While advances in technology may ultimately allow the effective forecasting of some BSEs, the immediate threat posed by unexpected eruptions means that effective management and mitigation measures may be the only tools currently at our disposal to reduce the risks from BSEs.

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Miggins, Daniel Paul. "Temporal and geochemical insights related to volcanic and plutonic activity within Big Bend National Park, Texas." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2009. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Janssen, Volker Surveying &amp Spatial Information Systems Faculty of Engineering UNSW. "A mixed-mode GPS network processing approach for volcano deformation monitoring." Awarded by:University of New South Wales. School of Surveying and Spatial Information Systems, 2003. http://handle.unsw.edu.au/1959.4/20771.

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Ground deformation due to volcanic magma intrusion is recognised as an important precursor of eruptive activity at a volcano. The Global Positioning System (GPS) is ideally suited for this application by being able to measure three-dimensional coordinate changes of the monitoring points over time. Due to the highly disturbed ionosphere in equatorial regions, particularly during times of maximum solar activity, a deformation monitoring network consisting entirely of single-frequency GPS receivers cannot deliver baseline solutions at the desired accuracy level. In this thesis, a mixed-mode GPS network approach is proposed in order to optimise the existing continuous single-frequency deformation monitoring system on the Papandayan volcano in West Java, Indonesia. A sparse network of dual-frequency GPS receivers surrounding the deformation zone is used to generate empirical 'correction terms' in order to model the regional ionosphere. These corrections are then applied to the single-frequency data of the inner network to improve the accuracy of the results by modelling the residual atmospheric biases that would otherwise be neglected. This thesis reviews the characteristics of existing continuously operating GPS deformation monitoring networks. The UNSW-designed mixed-mode GPS-based volcano deformation monitoring system and the adopted data processing strategy are described, and details of the system's deployment in an inhospitable volcanic environment are given. A method to optimise the number of observations for deformation monitoring networks where the deforming body itself blocks out part of the sky, and thereby significantly reduces the number of GPS satellites being tracked, is presented. The ionosphere and its effects on GPS signals, with special consideration for the situation in equatorial regions, are characterised. The nature of the empirically-derived 'correction terms' is investigated by using several data sets collected over different baseline lengths, at various geographical locations, and under different ionospheric conditions. Data from a range of GPS networks of various sizes, located at different geomagnetic latitudes, including data collected on Gunung Papandayan, were processed to test the feasibility of the proposed mixed-mode deformation monitoring network approach. It was found that GPS baseline results can be improved by up to 50% in the midlatitude region when the 'correction terms' are applied, although the performance of the system degrades in close proximity to the geomagnetic equator during a solar maximum.

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Boué, Anaïs. "Data mining and volcanic eruption forcasting." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAU007/document.

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L'intégration de méthodes de prédiction des éruptions volcaniques dans une stratégie de surveillance globale peut être un outil d'aide à la décision précieux pour la gestion des crises, si les limites des méthodes utilisées sont connues. La plupart des tentatives de prédictions déterministes des éruptions volcaniques et des glissements de terrain sont effectuées avec la méthode FFM (material Failure Forecast Method). Cette méthode consiste à ajuster une loi de puissance empirique aux précurseurs de sismicité ou de déformation des éruptions. Jusqu'à présent, la plupart des travaux de recherche se sont attachés à faire des prédictions a posteriori, basées sur la séquence complète de précurseurs, mais le potentiel de la méthode FFM pour la prédiction en temps réel, en n'utilisant qu'une partie de la séquence, n'a encore jamais été évaluée. De plus, il est difficile de conclure quant-à la capacité de la méthode pour prédire les éruptions volcaniques car le nombre d'exemples publiés est très limité et aucune évaluation statistique de son potentiel n'a été faite jusqu'à présent. Par conséquent, il est important de procéder à une application systématique de la FFM sur un nombre important d'éruptions, dans des contextes volcaniques variés. Cette thèse présente une approche rigoureuse de la FFM, appliquée aux précurseurs sismiques des éruptions volcaniques, développée pour une application en temps réel. J'utilise une approche Bayésienne basée sur la théorie de la FFM et sur un outil de classification automatique des signaux ayant des mécanismes à la source différents. Les paramètres d'entrée de la méthode sont les densités de probabilité des données, déduites de la performance de l'outil de classification. Le paramètre de sortie donne la distribution de probabilité du temps de prédiction à chaque temps d'observation précédant l'éruption. Je détermine deux critères pour évaluer la fiabilité d'une prédiction en temps réel : l'étalement de la densité de probabilité de la prédiction et sa stabilité dans le temps. La méthode développée ici surpasse les applications classiques de la FFM, que ce soit pour des applications en a posteriori ou en temps réel, en particulier parce que l'information concernant l'incertitude sur les donnée est précisément prise en compte. La classification automatique des signaux sismo-volcaniques permet une application systématique de cette méthode de prédiction sur des dizaines d'années de données pour des contextes volcaniques andésitiques, au volcan Colima (Mexique) et au volcan Mérapi (Indonésie), et pour un contexte basaltique au Piton de la Fournaise (La Réunion, France). Je quantifie le nombre d'éruptions qui ne sont pas précédées de précurseurs, ainsi que les crises sismiques qui ne sont pas associées à des épisodes volcaniques. Au total, 64 séquences de précurseurs sont étudiées et utilisées pour tester la méthode de prédiction des éruptions développée dans cette thèse. Ce travail permet de déterminer dans quelles conditions la FFM peut être appliquée avec succès et de quantifier le taux de réussite de la méthode en temps réel et en a posteriori. Seulement 62% des séquences précurseurs étudiées dans cette thèse sont utilisable dans le cadre de la FFM et la moitié du nombre total d'éruptions sont prédites a posteriori. En temps réel, seulement 36% du nombre total d'éruptions auraient pu être prédites. Cependant, ces prédictions sont précises dans 83% des cas pour lesquels les critères de fiabilités sont satisfaites. Par conséquent, il apparaît que l'on peut avoir confiance en la méthode de prédiction en temps réel développée dans cette thèse mais que la FFM semble être applicable en temps réel uniquement si elle est intégrée dans une statégie de prédiction plus globale. Cependant, elle pourrait être potentiellement utile combinée avec d'autres méthodes de prédictions et supervisée par un observeur. Ces résultats reflètent le manque de connaissances actuelles concernant les mécanismes pré-éruptifs
Eruption forecasting methods are valuable tools for supporting decision making during volcanic crises if they are integrated in a global monitoring strategy and if their potentiality and limitations are known. Many attempts for deterministic forecasting of volcanic eruptions and landslides have been performed using the material Failure Forecast Method (FFM). This method consists in adjusting an empirical power law on precursory patterns of seismicity or deformation. Until now, most of the studies have presented hindsight forecasts, based on complete time series of precursors, and do not evaluate the method's potential for carrying out real-time forecasting with partial precursory sequences. Moreover, the limited number of published examples and the absence of systematic application of the FFM makes it difficult to conclude as to the ability of the method to forecast volcanic eruptions. Thus it appears important to gain experience by carrying out systematic forecasting attempts in various eruptive contexts. In this thesis, I present a rigorous approach of the FFM designed for real-time applications on volcano-seismic precursors. I use a Bayesian approach based on the FFM theory and an automatic classification of the seismic events that do not have the same source mechanisms. The probability distributions of the data deduced from the performance of the classification are used as input. As output, the method provides the probability of the forecast time at each observation time before the eruption. The spread of the posterior probability density function of the prediction time and its stability with respect to the observation time are used as criteria to evaluate the reliability of the forecast. I show that the method developed here outperforms the classical application of the FFM both for hindsight and real-time attempts because it accurately takes the uncertainty of the data information into account. The automatic classification of volcano-seismic signals allows for a systematic application of this forecasting method to decades of seismic data from andesitic volcanoes including Volcan de Colima (Mexico) and Merapi volcano (Indonesia), and from the basaltic volcano of Piton de la Fournaise (Reunion Island, France). The number of eruptions that are not preceded by precursors is quantified, as well as the number of seismic crises that are not followed by eruptions. Then, I use 64 precursory sequences and apply the forecasting method developed in this thesis. I thus determine in which conditions the FFM can be successfully applied and I quantify the success rate of the method in real-time and in hindsight. Only 62% of the precursory sequences analysed in this thesis were suitable for the application of FFM and half of the total number of eruptions are successfully forecast in hindsight. In real-time, the method allows for the successful predictions of only 36% of the total of all eruptions considered. Nevertheless, real-time predictions are successful for 83% of the cases that fulfil the reliability criteria. Therefore, we can have a good confidence on the method when the reliability criteria are met, but the deterministic real-time forecasting tool developed in this thesis is not sufficient in itself. However, it could potentially be informative combined with other forecasting methods and supervised by an observer. These results reflect the lack of knowledge concerning the pre-eruptive mechanisms

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Janssen, Volker. "A mixed-mode GPS network processing approach for volcano deformation monitoring /." 2003. http://www.library.unsw.edu.au/~thesis/adt-NUN/public/adt-NUN20031219.104708/index.html.

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Granger, Kenneth John. "The Rabaul volcanoes : an application of geographical information systems to crisis management." Master's thesis, 1988. http://hdl.handle.net/1885/140922.

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Lim, Leng Leng. "Modelling of volcanic ashfall : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Mathematics at Massey University, Albany, New Zealand." 2006. http://hdl.handle.net/10179/1472.

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Modelling of volcanic ashfall has been attempted by volcanologists but very little work has been done by mathematicians. In this thesis we show that mathematical models can accurately describe the distribution of particulate materials that fall to the ground following an eruption. We also report on the development and analysis of mathematical models to calculate the ash concentration in the atmosphere during ashfall after eruptions. Some of these models have analytical solutions. The mathematical models reported on in this thesis not only describe the distribution of ashfall on the ground but are also able to take into account the effect of variation of wind direction with elevation. In order to model the complexity of the atmospheric flow, the atmosphere is divided into horizontal layers. Each layer moves steadily and parallel to the ground: the wind velocity components, particle settling speed and dispersion coefficients are assumed constant within each layer but may differ from layer to layer. This allows for elevation-dependent wind and turbulence profiles, as well as changing particle settling speeds, the last allowing the effects of the agglomeration of particles to be taken into account.

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Books on the topic "Volcanic activity prediction"

1

Tazieff, Haroun. Le volcanisme et sa prévention. Paris: Masson, 1990.

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Vogt, Gregory. Predicting volcanic eruptions. New York: F. Watts, 1989.

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Wolfe, Edward W. Volcanic-hazard zonation for Mount St. Helens, Washington, 1995. [Reston, Va.]: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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Wolfe, Edward W. Volcanic-hazard zonation for Mount St. Helens, Washington, 1995. [Reston, Va.]: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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Wolfe, Edward W. Volcanic-hazard zonation for Mount St. Helens, Washington, 1995. [Reston, Va.]: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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Wolfe, Edward W. Volcanic-hazard zonation for Mount St. Helens, Washington, 1995. [Menlo Park, CA]: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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Wolfe, Edward W. Volcanic-hazard zonation for Mount St. Helens, Washington, 1995. [Reston, Va.]: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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Wolfe, Edward W. Volcanic-hazard zonation for Mount St. Helens, Washington, 1995. [Reston, Va.]: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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Wolfe, Edward W. Volcanic-hazard zonation for Mount St. Helens, Washington, 1995. [Menlo Park, CA]: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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Wolfe, Edward W. Volcanic-hazard zonation for Mount St. Helens, Washington, 1995. [Reston, Va.]: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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Book chapters on the topic "Volcanic activity prediction"

1

Chester, David, Angus Duncan, Rui Coutinho, and Nicolau Wallenstein. "Evaluation and prediction of hazards." In Earthquakes and Volcanic Activity on Islands, 136–67. London: Routledge, 2021. http://dx.doi.org/10.4324/9780429028007-4.

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Sparks, R. S. J., and W. P. Aspinall. "Volcanic activity: Frontiers and challenges in forecasting, prediction and risk assessment." In Geophysical Monograph Series, 359–73. Washington, D. C.: American Geophysical Union, 2004. http://dx.doi.org/10.1029/150gm28.

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Melekestsev, I. V., O. A. Braitseva, and V. V. Ponomareva. "Prediction of Volcanic Hazards on the Basis of the Study of Dynamics of Volcanic Activity, Kamchatka." In IAVCEI Proceedings in Volcanology, 10–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-73759-6_2.

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"Chapter 14 Seismic monitoring of volcanic activity and prediction of volcanic eruptions." In Introduction to Volcanic Seismology, 235–52. Elsevier, 2003. http://dx.doi.org/10.1016/s1871-644x(03)80214-0.

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Shkuratskyy, Viacheslav, Aminu Bello Usman, and Michael S. O'Dea. "The Application of Machine Learning for Predicting Global Seismicity." In Handbook of Research on AI Methods and Applications in Computer Engineering, 222–52. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-6937-8.ch011.

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Abstract:

An earthquake is one of the deadliest natural disasters. Forecasting an earthquake is a challenging task since natural causes such as rainfall or volcanic eruptions disrupt data. Earthquakes can also be caused by human beings, such as mining or dams. Solar activity has also been suggested as a possible cause of earthquakes. Solar activity and earthquakes occur in different parts of the solar system, separated by a huge distance. However, scientists have been trying to figure out if there are any links between these two seemingly unrelated occurrences since the 19th century. In this chapter, the authors explored the methods of how machine learning algorithms including k-nearest neighbour, support vector regression, random forest regression, and long short-term memory neural networks can be applied to predict earthquakes and to understand if there is a relationship between solar activity and earthquakes. The authors investigated three types of solar activity: sunspots number, solar wind, and solar flares, as well as worldwide earthquake frequencies that ranged in magnitude and depth.

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Rothery, David A. "Dead Worlds." In Satellites of the Outer Planets, 63–98. Oxford University PressNew York, NY, 1999. http://dx.doi.org/10.1093/oso/9780195125559.003.0005.

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Abstract Rather than describe the moons of the outer planets one planet at a time, they are presented here in classes defined by the extent to which each exhibits evidence of geological processes. This chapter describes the worlds that show few or no signs of geological activity on their surfaces except those associated with and recorded by impact cratering. As introduced in chapter 1, heavily cratered surfaces must be older than less cratered areas because the latter can be assumed to have once been heavily cratered themselves but to have had their craters obliterated by geological processes such as tectonism (deformation) or volcanism. Chapter 6 discusses worlds exhibiting clear signs of such geological resurfacing having overprinted and partly destroyed the earlier cratered terrains, and where such activity evidently belongs to a past era. Chapter 7 covers those worlds where this sort of geological activity is continuing today or is at least very young. Finally, chapter 8 hazards some predictions about what conditions might be like on the few icy worlds of whose surfaces we have no good images.

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Akbar Firoozi, Ali, and Ali Asghar Firoozi. "Non-seismic and Complex Source Tsunami: Unseen Hazard." In Earthquake Ground Motion [Working Title]. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.1002308.

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Tsunamis, commonly induced by undersea earthquakes, are formidable natural hazards capable of causing widespread devastation. This comprehensive chapter examines the complex dynamics of tsunamis, their generation mechanisms, and their broad-reaching impacts. The multifaceted nature of tsunami triggers, both seismic and non-seismic, is dissected, highlighting the role of undersea earthquakes, landslides, volcanic eruptions, and meteorological events in driving these devastating natural phenomena. The intricate interplay of seismic parameters such as magnitude, depth, and activity type is elaborated, underscored by an insightful case study on the 2011 Tohoku Earthquake and Tsunami. A pivotal part of the discussion lies in the exploration of non-seismic triggers of tsunamis, an area often overshadowed in tsunami studies. The impact of landslide-induced and volcanically triggered tsunamis is considered alongside the contentious topic of meteorologically influenced tsunami events. Delving further into the genesis of tsunamis, the chapter explores the influences of bathymetry and tectonic structures, particularly in the context of non-seismic tsunami generation. The chapter serves as a beacon for continuous research and predictive modeling in the field of tsunami studies, emphasizing the necessity for societal preparedness and strategic risk mitigation against these potent natural disasters.

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Conference papers on the topic "Volcanic activity prediction"

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Hanamuro, Takahiro, Ken-Ichi Yasue, Yoko Saito-Kokubu, Koichi Asamori, Tsuneari Ishimaru, and Koji Umeda. "Current R & D Activities in the Study on Geosphere Stability." In ASME 2010 13th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2010. http://dx.doi.org/10.1115/icem2010-40018.

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The Japanese islands are located in a tectonically active zone. The scientific base is required for assessing the geosphere stability for long-term isolation of radioactive waste in Japan. JAEA is promoting the establishment of investigation method for geotectonic events affecting geosphere stability and prediction model for the future changes of geological environments, that is necessary for site selection and safety assessment of the HLW geological disposal. For seismicity and faulting, detection techniques for active faults without topographic surface expression, such as using helium isotope ratios in hot spring gases or detection of hydrogen gas, and studies on the assessment of fault evolution have been developed. For volcanism and geothermal activity, heat sources for anomalous geothermal activity in non-volcanic regions are considered. Detection techniques for high-temperature fluids and magma deep underground, using geophysical and geochemical approaches, were constructed. For uplift, denudation and climatic/sea-level changes, a methodology to predict the future topographic change was developed. Also, for dating techniques as an essential part to proceed on these studies, C-14 and Be-10 dating using AMS and (U-Th)/He dating using QMS and ICP-MS have been developed. We are planning the establishment of assessment methods for geosphere stability including assessment of the activity of faults encountered in underground excavations, development of long-term prediction model of volcanism and hydrothermal activities, and hydrogeological analyses considering topographic change.

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Marchese, Francesco, Carolina Filizzola, Giuseppe Mazzeo, Rossana Paciello, Nicola Pergola, and Valerio Tramutoli. "Robust satellite techniques for thermal volcanic activity monitoring, early warning and possible prediction of new eruptive events." In 2009 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2009. http://dx.doi.org/10.1109/igarss.2009.5418258.

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