Short-term volcanic hazard assessment through Bayesian inference: Retrospective application to the Pinatubo 1991 volcanic crisis

© 2014 . One of the most challenging aspects of managing a volcanic crisis is the interpretation of the monitoring data, so as to anticipate to the evolution of the unrest and implement timely mitigation actions. An unrest episode may include different stages or time intervals of increasing activity that may or may not precede a volcanic eruption, depending on the causes of the unrest (magmatic, geothermal or tectonic). Therefore, one of the main goals in monitoring volcanic unrest is to forecast whether or not such increase of activity will end up with an eruption, and if this is the case, how, when, and where this eruption will take place. As an alternative method to expert elicitation for assessing and merging monitoring data and relevant past information, we present a probabilistic method to transform precursory activity into the probability of experiencing a significant variation by the next time interval (i.e. the next step in the unrest), given its preceding evolution, and by further estimating the probability of the occurrence of a particular eruptive scenario combining monitoring and past data. With the 1991 Pinatubo volcanic crisis as a reference, we have developed such a method to assess short-term volcanic hazard using Bayesian inference.This research has been partially funded by the European Commission (FP7 Theme: ENV.2011.1.3.3-1; Grant 282759: VUELCO) and by the Aon Benfield UCL Hazard Centre. All data and information used to reproduce the results in the case study have been extracted from the public source Punongbayan and Newhall (1996) edited monograph on the Mt Pinatubo eruption.Peer Reviewe

Probabilistic approach to decision-making under uncertainty during volcanic crises: retrospective application to the El Hierro (Spain) 2011 volcanic crisis

© 2014, The Author(s). Understanding the potential evolution of a volcanic crisis is crucial for designing effective mitigation strategies. This is especially the case for volcanoes close to densely populated regions, where inappropriate decisions may trigger widespread loss of life, economic disruption, and public distress. An outstanding goal for improving the management of volcanic crises, therefore, is to develop objective, real-time methodologies for evaluating how an emergency will develop and how scientists communicate with decision-makers. Here, we present a new model Bayesian Decision Model (BADEMO) that applies a general and flexible, probabilistic approach to managing volcanic crises. The model combines the hazard and risk factors that decision-makers need for a holistic analysis of a volcanic crisis. These factors include eruption scenarios and their probabilities of occurrence, the vulnerability of populations and their activities, and the costs of false alarms and failed forecasts. The model can be implemented before an emergency, to identify actions for reducing the vulnerability of a district; during an emergency, to identify the optimum mitigating actions and how these may change as new information is obtained; and after an emergency, to assess the effectiveness of a mitigating response and, from the results, to improve strategies before another crisis occurs. As illustrated by a retrospective analysis of the 2011 eruption of El Hierro, in the Canary Islands, BADEMO provides the basis for quantifying the uncertainty associated with each recommended action as an emergency evolves and serves as a mechanism for improving communications between scientists and decision-makers.This research has been funded by the European Commission (FP7 Theme: ENV.2011.1.3.3-1; Grant 282759: VUELCO).Peer Reviewe

Long-term volcanic hazard assessment on El Hierro (Canary Islands)

Long-term hazard assessment, one of the bastions of risk-mitigation programs, is required for land-use planning and for developing emergency plans. To ensure quality and representative results, long-term volcanic hazard assessment requires several sequential steps to be completed, which include the compilation of geological and volcanological information, the characterisation of past eruptions, spatial and temporal probabilistic studies, and the simulation of different eruptive scenarios. Despite being a densely populated active volcanic region that receives millions of visitors per year, no systematic hazard assessment has ever been conducted on the Canary Islands. In this paper we focus our attention on El Hierro, the youngest of the Canary Islands and the most recently affected by an eruption. We analyse the past eruptive activity to determine the spatial and temporal probability, and likely style of a future eruption on the island, i.e. the where, when and how. By studying the past eruptive behaviour of the island and assuming that future eruptive patterns will be similar, we aim to identify the most likely volcanic scenarios and corresponding hazards, which include lava flows, pyroclastic fallout and pyroclastic density currents (PDCs). Finally, we estimate their probability of occurrence. The end result, through the combination of the most probable scenarios (lava flows, pyroclastic density currents and ashfall), is the first qualitative integrated volcanic hazard map of the island.This research was partially funded by IGME, CSIC and the European Commission (FT7 Theme: ENV.2011.1.3.3-1; Grant 282759: “VUELCO”), and MINECO grant CGL2011-16144-E.Peer reviewe

HASSET: A probability event tree tool to evaluate future volcanic scenarios using Bayesian inference

Event tree structures constitute one of the most useful and necessary tools in modern volcanology for assessment of hazards from future volcanic scenarios (those that culminate in an eruptive event as well as those that do not). They are particularly relevant for evaluation of long- and short-term probabilities of occurrence of possible volcanic scenarios and their potential impacts on urbanized areas. In this paper, we introduce Hazard Assessment Event Tree (HASSET), a probability tool, built on an event tree structure that uses Bayesian inference to estimate the probability of occurrence of a future volcanic scenario and to evaluate the most relevant sources of uncertainty from the corresponding volcanic system. HASSET includes hazard assessment of noneruptive and nonmagmatic volcanic scenarios, that is, episodes of unrest that do not evolve into volcanic eruption but have an associated volcanic hazard (e.g., sector collapse and phreatic explosion), as well as unrest episodes triggered by external triggers rather than the magmatic system alone. Additionally, HASSET introduces the Delta method to assess precision of the probability estimates, by reporting a 1 standard deviation variability interval around the expected value for each scenario. HASSET is presented as a free software package in the form of a plug-in for the open source geographic information system Quantum Gis (QGIS), providing a graphically supported computation of the event tree structure in an interactive and user-friendly way. We also include further in-depth explanations for each node together with an application of HASSET to Teide-Pico Viejo volcanic complex (Spain). © 2013 The Author(s).This work was supported by the European Commission (FP7 Theme: ENV.2011.1.3.3-1; grant 282759: VUELCO)Peer Reviewe

Using Statistics to Quantify and Communicate Uncertainty During Volcanic Crises

This open access book provides a comprehensive overview of volcanic crisis research, the goal being to establish ways of successfully applying volcanology in practice and to identify areas that need to be addressed for future progress. It shows how volcano crises are managed in practice, and helps to establish best practices. Consequently the book brings together authors from all over the globe who work with volcanoes, ranging from observatory volcanologists, disaster practitioners and government officials to NGO-based and government practitioners to address three key aspects of volcanic crises. First, the book explores the unique nature of volcanic hazards, which makes them a particularly challenging threat to forecast and manage, due in part to their varying spatial and temporal characteristics. Second, it presents lessons learned on how to best manage volcanic events based on a number of crises that have shaped our understanding of volcanic hazards and crises management. Third, it discusses the diverse and wide-ranging aspects of communication involved in crises, which merge old practices and new technologies to accommodate an increasingly challenging and globalised world. The information and insights presented here are essential to tapping established knowledge, moving towards more robust volcanic crises management, and understanding how the volcanic world is perceived from a range of standpoints and contexts around the globe.Peer Reviewe

VOLCANBOX: a new software platform to minimise volcanic risk

One of the most important tasks of modern volcanology is to minimise the risk of volcanic eruptions. Their impact can affect considerably human life and the environment. It is clear that a volcanic eruption, although it can be at the same time fascinating and impressive, presents similar or even more problems than more frequent natural events. It is possible to live near a volcanic area if we consider the benefits that volcanoes can gives us, but it is important to be aware of the existing threat and to know how to minimise the risk. Understanding the potential evolution of a volcanic crisis is crucial for designing effective mitigation strategies. In this work we present an integrated software platform specially designed to assess and manage volcanic risk, VOLCANBOX. This new platform contains user-friendly free e-tools able to be used with personal computers specifically addressed to long- and short-term hazard assessment, vulnerability analysis, decision-making, and volcanic risk management. E-tools are developed in QGIS, the more widely used free open source Geographic Information System, and are designed to be implemented before an emergency, to identify optimum mitigating actions and how these may change as new information is obtained. Furthermore, e-tools contained in the VOLCANBOX allow to identify the most appropriate probabilistic and statistical techniques for volcanological data analysis and treatment in the context of quantitative hazard and risk assessment. Forecasting volcanic eruptions and predicting the most probable scenarios are subjected to a high degree of uncertainty, which needs to be quantified and clearly explained when transmitting scientific information to decision makers.Peer Reviewe

ST-HASSET for volcanic hazard assessment: A Python tool for evaluating the evolution of unrest indicators

Short-term hazard assessment is an important part of the volcanic management cycle, above all at the onset of an episode of volcanic agitation (unrest). For this reason, one of the main tasks of modern volcanology is to use monitoring data to identify and analyse precursory signals and so determine where and when an eruption might occur. This work follows from Sobradelo and Martí [Short-term volcanic hazard assessment through Bayesian inference: retrospective application to the Pinatubo 1991 volcanic crisis. Journal of Volcanology and Geothermal Research 290, 111, 2015] who defined the principle for a new methodology for conducting short-term hazard assessment in unrest volcanoes. Using the same case study, the eruption on Pinatubo (15 June 1991), this work introduces a new free Python tool, ST-HASSET, for implementing Sobradelo and Martí (2015) methodology in the time evolution of unrest indicators in the volcanic short-term hazard assessment. Moreover, this tool is designed for complementing long-term hazard assessment with continuous monitoring data when the volcano goes into unrest. It is based on Bayesian inference and transforms different pre-eruptive monitoring parameters into a common probabilistic scale for comparison among unrest episodes from the same volcano or from similar ones. This allows identifying common pre-eruptive behaviours and patterns. ST-HASSET is especially designed to assist experts and decision makers as a crisis unfolds, and allows detecting sudden changes in the activity of a volcano. Therefore, it makes an important contribution to the analysis and interpretation of relevant data for understanding the evolution of volcanic unrest. © 2016 Elsevier Ltd.This research was funded by the European Commission (FP7 Theme: ENV.2011.1.3.3-1; Grant 282759: VUELCO and EC ECHO Grant SI2.695524: VeTOOLS).Peer reviewe

Global volcanic unrest in the 21st century: An analysis of the first decade

We define volcanic unrest as the deviation from the background or baseline behaviour of a volcano towards a behaviour which is a cause for concern in the short-term because it might prelude an eruption. When unrest is preceded by periods of quiescence over centuries or millennia it is particularly difficult to foresee how a volcano might behave in the short-term. As a consequence, one of the most important problems is to assess whether unrest will culminate in an eruption or not. Here, we review and evaluate global unrest reports of the Smithsonian Institution Global Volcanism Program (GVP) between January 2000 and July 2011. The aim of the evaluation is to establish the nature and length of unrest activity to test whether there are common temporal patterns in unrest indicators and whether there is a link between the length of inter-eruptive periods and unrest duration across different volcano types. A database is created from the reported information on unrest at 228 volcanoes. The data is categorised into pre-eruptive or non-eruptive unrest indicators at four different subaerial volcano types and submarine volcanoes as defined by the GVP. Unrest timelines demonstrate how unrest evolved over time and highlight different classes of unrest including reawakening, pulsatory, prolonged, sporadic and intra-eruptive unrest. Statistical tests indicate that pre-eruptive unrest duration was different across different volcano types. 50% of stratovolcanoes erupted after about one month of reported unrest. At large calderas this median average duration of pre-eruptive unrest was about twice as long. At almost five months, shield volcanoes had a significantly longer unrest period before the onset of eruption, compared to both large calderas and stratovolcanoes. At complex volcanoes, eruptive unrest was short lived with only a median average duration of two days. We find that there is only a poor correlation between the length of the inter-eruptive period and unrest duration in the data; statistical significance was only detected for the pair-wise comparison of non-eruptive unrest at large calderas and stratovolcanoes. Results indicate that volcanoes with long periods of quiescence between eruptions will not necessarily undergo prolonged periods of unrest before their next eruption.Our findings may have implications for hazard assessment, risk mitigation and scenario planning during future unrest crises. © 2013 The Authors.This work was supported by a Royal Society URF grant to JG and by the European Commission (FP7 Theme: NV.2011.1.3.3-1; Grant 282759: “VUELCO”).Peer Reviewe