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Statistics in Volcanology is a comprehensive guide to modern statistical methods applied in volcanology written by today's leading authorities. The volume aims to show how the statistical analysis of complex volcanological data sets, including time series, and numerical models of volcanic processes can improve our ability to forecast volcanic eruptions. Specific topics include the use of expert elicitation and Bayesian methods in eruption forecasting, statistical models of temporal and spatial patterns of volcanic activity, analysis of time series in volcano seismology, probabilistic hazard assessment, and assessment of numerical models using robust statistical methods. Also provided are comprehensive overviews of volcanic phenomena, and a full glossary of both volcanological and statistical terms. Statistics in Volcanology is essential reading for advanced undergraduates, graduate students, and research scientists interested in this multidisciplinary field.
'Statistics in Volcanology' is a comprehensive guide to modern statistical methods applied in volcanology written by today's leading authorities. The volume aims to show how the statistical analysis of complex volcanological data sets, including time series, and numerical models of volcanic processes can improve our ability to forecast volcanic eruptions.
Disasters are large intractable problems that test the ability of communities and nations to effectively protect their populations and infrastructure, to reduce both human and property loss, and to rapidly recover. The randomness of impacts and problems, and uniqueness of incidents demand dynamic, real-time, effective and cost efficient solutions. For this reason, we need quantitative risk-based methods for decision-making under uncertainty to be developed and applied to volcanology. Volcanic activity is a natural phenomenon that can turn into a disaster under certain conditions. They are natural processes that cannot be controlled, but their potentially disastrous effects can be mitigated. Volcanoes have implicit a natural hazard which can threaten human lives and properties of those communities living near by. The eruptions of volcanoes considered "dormant" or "inactive" have been liable for major disasters in the past. The volcanic hazard from volcanoes with a long term recurrence tends to be ignored, especially when little or no historical data exists. This is the case of Teide - Pico Viejo Stratovolcanoes in the island of Tenerife. Due to the limited scientific observability of the interior of a volcano, there is a lot of uncertainty in forecasting volcanic eruptions. During a volcanic crisis decision-makers need to take important life and death decisions under strict time and uncertainty constrains. They are afraid of getting a decision wrong, causing unnecessary economic disruption and public anxiety and distress. There is an increasing recognition of the need of combining mathematical models, together with statistical and operations research methods to address disaster management. The interdisciplinary science of mathematics applied to the study of volcanology and volcanic hazard is an important approach which will help understand volcanic processes by integrating keen volcanological insights with sound statistical modeling and artful application of computational power. The aim of this thesis is to work with volcanologists to try and address, with the appropriate statistical methods, those questions they raise, and have volcanologists collaborate with statisticians to learn about the advantages in the application of statistical techniques to the interpretation of volcanic data. Here, we propose and analyze different statistical methodologies to interpret volcanic data and assess volcanic hazard. The statistical technique will depend on the nature of the data and the type of problem we want to address. The models will be used to analyze and interpret the historical and geological volcanic data for Teide-Pico Viejo stratovolcanoes (TPV) and the Canary Islands archipelago. The first statistical method is an Elicitation of Expert Judgment using the so-called Classical Model to assign probabilities of occurrence to each possible eruptive scenario that can be outlined from the eruption history of the volcano, and our knowledge of other analogous volcanoes. The aim was to assess the long-term volcanic hazard of TPV, following an unrest episode in 2004 which created discrepancies among scientists regarding the nature of the unrest and the level of hazard. The second statistical method is a Bayesian Inference approach to compute the long-term probability for each volcanic scenario. The idea to use this method came after seeing the limitations on the Classical Model. The third method is a Non-parametric one-way unbalanced ANOVA using the Kruskal - Wallis test. This study was suggested following the publication for the first time of the World Collapse Caldera Database (WCCD) by the Group of Volcanology of Barcelona. The fourth statistical methodology NHGPP (Non-homogeneous generalized Pareto-Poisson process) uses extreme value theory to study eruptive time series combining geological and historical records. This methodology is applied to the Canary Islands eruptive time series to study volcanic recurrence.
Volcanic eruptions are common, with more than 50 volcanic eruptions in the United States alone in the past 31 years. These eruptions can have devastating economic and social consequences, even at great distances from the volcano. Fortunately many eruptions are preceded by unrest that can be detected using ground, airborne, and spaceborne instruments. Data from these instruments, combined with basic understanding of how volcanoes work, form the basis for forecasting eruptionsâ€"where, when, how big, how long, and the consequences. Accurate forecasts of the likelihood and magnitude of an eruption in a specified timeframe are rooted in a scientific understanding of the processes that govern the storage, ascent, and eruption of magma. Yet our understanding of volcanic systems is incomplete and biased by the limited number of volcanoes and eruption styles observed with advanced instrumentation. Volcanic Eruptions and Their Repose, Unrest, Precursors, and Timing identifies key science questions, research and observation priorities, and approaches for building a volcano science community capable of tackling them. This report presents goals for making major advances in volcano science.
This book contains 12 chapters dealing with the studies on volcanoes, their geological and geophysical setting, the theoretical aspects and the numerical modeling on volcanoes, the applications of volcanoes to the industry, and the impact of volcanoes on the human health, in different geological settings and using several techniques and methods, including the volcanology, the seismology, the statistical methods to assess the correlation between seismic and volcanic activity (modified Ripley's K-function to regional seismicity), the field geological survey of volcanic successions, the analytical methods of petrologic analysis, the petrography of the volcanic rocks with the individuation of the modal compositions of volcanic rocks and their comparison with major elements and trace elements in variation diagrams, and the argon isotopic measurements performed through the peak height comparison (unspiked) method. The oceanographic methods have also been applied to case studies of submarine volcanic edifices located in the Canary Islands (Atlantic Ocean), including the sampling of the water column with a conductivity-temperature-depth (CTD) sensor rosette with 24 Niskin bottles, in order to determinate key physical and chemical parameters, such as the total-scale pH, the total dissolved inorganic carbon (C), the total alkalinity (A), the temperature, the salinity, and the dissolved oxygen. Problems of volcanic risk mitigation have also been treated, regarding the eruption disasters in Indonesia, a country where a high number of people live next to the volcanoes, and characterized by the lack of public awareness of the eruption disasters. Petrographic methods have been successfully applied to the study of the Cretaceous magmatism of the layered gabbroids of the Chukotka region (Pekulney Ridge, Russia), and geodynamic implications have been successfully established through geological and petrographic studies. The relationships among the mantle wedge, the convective heat and mass transfer, the infiltration metasomatism, the zoning, and the mathematical models have been applied to the comprehension of complex volcanic areas through the theoretical aspects of volcanic studies on magmatic chambers coupled with numerical modeling, including finite element models (FEMs) in the individuation of volcanic deformations.
This open access book summarizes the findings of the VUELCO project, a multi-disciplinary and cross-boundary research funded by the European Commission's 7th framework program. It comprises four broad topics: 1. The global significance of volcanic unrest 2. Geophysical and geochemical fingerprints of unrest and precursory activity 3. Magma dynamics leading to unrest phenomena 4. Bridging the gap between science and decision-making Volcanic unrest is a complex multi-hazard phenomenon. The fact that unrest may, or may not lead to an imminent eruption contributes significant uncertainty to short-term volcanic hazard and risk assessment. Although it is reasonable to assume that all eruptions are associated with precursory activity of some sort, the understanding of the causative links between subsurface processes, resulting unrest signals and imminent eruption is incomplete. When a volcano evolves from dormancy into a phase of unrest, important scientific, political and social questions need to be addressed. This book is aimed at graduate students, researchers of volcanic phenomena, professionals in volcanic hazard and risk assessment, observatory personnel, as well as emergency managers who wish to learn about the complex nature of volcanic unrest and how to utilize new findings to deal with unrest phenomena at scientific and emergency managing levels. This book is open access under a CC BY license.