# Volcanic Unrest and Pre-eruptive Processes: A Hazard and Risk Perspective

J. Gottsmann, J.-C. Komorowski, J. Barclay

► To cite this version:

J. Gottsmann, J.-C. Komorowski, J. Barclay. Volcanic Unrest and Pre-eruptive Processes: A Hazard and Risk Perspective: In: J. Gottsmann, J. Neuberg, B. Scheu (Eds), Volcanic Unrest -- From Science to Society. Volcanic Unrest, Springer International Publishing, pp.1-21, 2017, Advances in Volcanology, 978--3--319--58411--9. 10.1007/11157_2017_19. hal-03961068

HAL Id: hal-03961068

https://hal.science/hal-03961068

Submitted on 7 Feb 2023

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
Joachim Gottsmann

Jürgen Neuberg

Bettina Scheu *Editors*

# Volcanic
Unrest

## From Science to Society
**Advances in Volcanology**

An Official Book Series of the International
Association of Volcanology and Chemistry
of the Earth's Interior – IAVCEI, Barcelona,
Spain

**Series editor**

Karoly Nemeth, Palmerston North, New Zealand
More information about this series at http://www.springer.com/series/11157
Joachim Gottsmann · Jürgen Neuberg
Bettina Scheu
Editors

# Volcanic Unrest

From Science to Society

<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

Springer Open
Editors

Joachim Gottsmann

School of Earth Sciences

University of Bristol

Bristol, Bath and North East Somerset

UK

Bettina Scheu

Ludwig Maximilian University of

Munich

Munich, Bayern

Germany

Jürgen Neuberg

Faculty of Environment

University of Leeds

Leeds, UK

<figure><img src="image_4.png" /></figure>

ISSN 2364-3277

Advances in Volcanology

ISBN 978-3-319-58411-9

https://doi.org/10.1007/978-3-319-58412-6

ISSN 2364-3285 (electronic)

ISBN 978-3-319-58412-6 (eBook)

Library of Congress Control Number: 2018961003

© The Editor(s) (if applicable) and The Author(s) 2019. This book is published open access.

**Open Access** This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence and indicate if changes were made.

The images or other third party material in this book are included in the book's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the book's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This Springer imprint is published by the registered company Springer Nature Switzerland AG
The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Volcanic unrest is a manifestation of complex subsurface processes which might or might not herald an imminent volcanic eruption. Short-term (hours to few weeks) unrest activity before an eruption may in hindsight be interpreted as “pre-eruptive”. Protracted periods or waning of unrest without a clear relationship between unrest and future eruptive activity may be deemed “non-eruptive”.

Periods of unrest challenge both scientists and decision-makers to interact effectively and efficiently to minimise societal risk during the unrest and in anticipation of a possible imminent eruption.

The scientific challenge is to identify whether unrest phenomena are pre-eruptive or non-eruptive early on in a developing unrest crisis. The challenge for decision-makers is to respond with the “right” decision during an emerging crisis.

Expectations from many different stakeholders including the media and the general public need to be managed amid epistemic (the unknown subsurface processes hidden from the observer) and aleatoric uncertainty (their stochastic variability).

Numerous examples in the recent past have shown that periods of unrest are hazardous and costly even without leading to imminent eruption (e.g. at La Soufriere, Guadeloupe, in 1976; at Campi Flegrei, Italy, in 1982–1984; at Long Valley Caldera/Mammoth Mountain, USA, in the 1980s and 1990s).

Tensions between different stakeholders can arise particularly during protracted periods (years to decades) of unrest at volcanoes with significant and growing populations, when trust in scientific knowledge is challenged amid the need for economic and societal development and growth.

*Volcanic Unrest: From Science to Society*—highlights the complexities of volcanic unrest from both scientific and societal perspectives and provides a summary of findings from the project entitled “Volcanic Unrest in Europe and Latin America: Phenomenology, eruption precursors, hazard forecast, and risk mitigation (VUELCO)”. The multi-disciplinary and cross-boundary research project was funded by the European Commission’s 7th framework programme for research, technological development and demonstration under grant agreement no. 282759 and brought together an international team of academics from the social and natural sciences, as well as personnel from volcano observatory and civil protection agencies.
The project was designed in response to a call by the EC for a “collaborative project (small- or medium-scale focused research project) for specific cooperation actions (SICA) dedicated for international cooperation partner countries with focus on Latin America”.

The work was conducted at ten partner institutions across Europe and Latin America during 2011–2015. Most of the findings have been published in dedicated scientific journals over the past few years, and others will be published in the years to come.

The purpose of this open-access book is to summarise and publicise the key findings of the project for a broad audience. Seventeen and one appendix chapters focus on four broad topics relevant to the understanding of volcanic unrest in the context of scientific and societal challenges:

1. The significance of volcanic unrest at the natural hazard and risk interface,

2. Geophysical and geochemical fingerprints of unrest and precursory activity,

3. Subsurface dynamics leading to unrest phenomena,

4. Stakeholder interaction and volcanic risk governance.

This book aims to make our research accessible to both scientific and non-scientific audiences with interest in the different aspects of volcanic unrest, its impact and consequences. The chapters have been written with the intention to make the findings accessible to a broad audience. This entails a balancing act between keeping the scientific jargon at bay, whilst also satisfying the curiosity of scientific readers from different disciplines. In addition, most chapters are accompanied by Spanish-language abstracts.

As a consequence, the style of the chapters is different in several ways from the general peer-reviewed scientific literature. Most chapters have a summary/review character of findings from the project, which were originally published in dedicated journals. The chapters hence provide syntheses and articulations of concepts rather than comprehensive compilation of data and the available literature. However, all chapters provide the reader with references to original publications that will permit a wider reading and study of the findings behind the chapters.

The book is a joint effort between editors, authors, reviewers and publishers.

All chapters have undergone peer review, and we are indebted to all reviewers from the VUELCO community as well as the following external reviewers who provided their expert opinions and comments:

S. de Angelis, F. Arzilli, O. Bachmann, F. Costa, N. Deligne, J. Gardner, H. Gonnermann, A. Hicks, S. Hurwitz, S. Jenkins, P. Lesage, C. Newhall, C. Pritchard, G. Woo.

We thank J. Schwarz at Springer for her patience and expert handling of all things related to publishing this book.

Munich, Germany
Bristol, UK
Leeds, UK

Bettina Scheu
Joachim Gottsmann
Jürgen Neuberg
# Contents

<table><tr><td>Volcanic Unrest and Pre-eruptive Processes: A Hazard and Risk Perspective</td><td>1</td></tr><tr><td>J. Gottsmann, J.-C. Komorowski and J. Barclay</td><td></td></tr><tr><td>The Role of Laws Within the Governance of Volcanic Risks</td><td>23</td></tr><tr><td>R. J. Bretton, J. Gottsmann and R. Christie</td><td></td></tr><tr><td>Deterministic Versus Probabilistic Volcano Monitoring: Not "or" But "and"</td><td>35</td></tr><tr><td>D. Rouwet, R. Constantinescu and L. Sandri</td><td></td></tr><tr><td>Probabilistic E-tools for Hazard Assessment and Risk Management</td><td>47</td></tr><tr><td>Stefania Bartolini, Joan Martí, Rosa Sobradelo and Laura Becerril</td><td></td></tr><tr><td>The Need to Quantify Hazard Related to Non-magmatic Unrest: From BET_EF to BET_UNREST</td><td>63</td></tr><tr><td>Laura Sandri, Roberto Tonini, Dmitri Rouwet, Robert Constantinescu, Ana Teresa Mendoza-Rosas, Daniel Andrade and Benjamin Bernard</td><td></td></tr><tr><td>Groundwater flow and volcanic unrest</td><td>83</td></tr><tr><td>Alia Jasim, Brioch Hemmings, Klaus Mayer and Bettina Scheu</td><td></td></tr><tr><td>Experimental Simulations of Magma Storage and Ascent</td><td>101</td></tr><tr><td>C. Martel, R. A. Brooker, J. Andújar, M. Pichavant, B. Scaillet and J. D. Blundy</td><td></td></tr><tr><td>Magma Chamber Rejuvenation: Insights from Numerical Models</td><td>111</td></tr><tr><td>C. P. Montagna, P. Papale, A. Longo and M. Bagagli</td><td></td></tr><tr><td>Magma Mixing: History and Dynamics of an Eruption Trigger</td><td>123</td></tr><tr><td>Daniele Morgavi, Ilenia Arienzo, Chiara Montagna, Diego Perugini and Donald B. Dingwell</td><td></td></tr><tr><td>Gases as Precursory Signals: Experimental Simulations, New Concepts and Models of Magma Degassing</td><td>139</td></tr><tr><td>M. Pichavant, N. Le Gall and B. Scaillet</td><td></td></tr></table>
<table><tbody><tr><td><strong>Crystals, Bubbles and Melt: Critical Conduit Processes Revealed by Numerical Models</strong></td><td>155</td></tr><tr><td>M. E. Thomas, J. W. Neuberg and A. S. D. Collinson</td><td></td></tr><tr><td><strong>When Does Magma Break?</strong></td><td>171</td></tr><tr><td>Fabian B. Wadsworth, Taylor Witcher, Jérémie Vasseur, Donald B. Dingwell and Bettina Scheu</td><td></td></tr><tr><td><strong>Volcano Seismology: Detecting Unrest in Wiggly Lines</strong></td><td>185</td></tr><tr><td>R.O. Salvage, S. Karl and J.W. Neuberg</td><td></td></tr><tr><td><strong>The Ups and Downs of Volcanic Unrest: Insights from Integrated Geodesy and Numerical Modelling</strong></td><td>203</td></tr><tr><td>J. Hickey, J. Gottsmann, P. Mothes, H. Odbert, I. Prutkin and P. Vajda</td><td></td></tr><tr><td><strong>Fluid Geochemistry and Volcanic Unrest: Dissolving the Haze in Time and Space.</strong></td><td>221</td></tr><tr><td>Dmitri Rouwet, Silvana Hidalgo, Erouscilla P. Joseph and Gino González-Ilama</td><td></td></tr><tr><td><strong>Geophysical Footprints of Cotopaxi's Unrest and Minor Eruptions in 2015: An Opportunity to Test Scientific and Community Preparedness.</strong></td><td>241</td></tr><tr><td>Patricia A. Mothes, Mario C. Ruiz, Edwin G. Viracucha, Patricio A. Ramón, Stephen Hernández, Silvana Hidalgo, Benjamin Bernard, Elizabeth H. Gaunt, Paul Jarrín, Marco A. Yépez and Pedro A. Espín</td><td></td></tr><tr><td><strong>Volcanic Unrest Simulation Exercises: Checklists and Guidance Notes</strong></td><td>271</td></tr><tr><td>R. J. Bretton, S. Ciolli, C. Cristiani, J. Gottsmann, R. Christie and W. Aspinall</td><td></td></tr><tr><td><strong>Appendix: Volcanic Unrest: Terminology and Definitions</strong></td><td>299</td></tr><tr><td><strong>Bibliography</strong></td><td>313</td></tr></tbody></table>
<figure><img src="image_5.png" /></figure>

# Volcanic Unrest and Pre-eruptive Processes: A Hazard and Risk Perspective

J. Gottsmann, J.-C. Komorowski and J. Barclay

## Abstract

Volcanic unrest is complex and capable of producing multiple hazards that can be triggered by a number of different subsurface processes. Scientific interpretations of unrest data aim to better understand (i) the processes behind unrest and their associated surface signals, (ii) their future spatio-temporal evolution and (iii) their significance as precursors for future eruptive phenomena. In a societal context, additional preparatory or contingency actions might be needed because relationships between and among individuals and social groups will be perturbed and even changed in the presence of significant uncertainty. Here we analyse some key examples from three international and multidisciplinary projects (VUELCO, CASAVA and STREVA) where issues around the limits of volcanic knowledge impact on volcanic risk governance. We provide an overview of the regional and global context of volcanic unrest and highlight scientific and societal challenges with a geographical emphasis on the Caribbean and Latin America. We investigate why the forecasting of volcanic unrest evolution and the exploitability of unrest signals to forecast future eruptive behaviour and framing of response protocols is

<footnote>J. Gottsmann (✉)
School of Earth Sciences, University of Bristol,
Bristol, UK
e-mail: j.gottsmann@bristol.ac.uk</footnote>

<footnote>J. Gottsmann
The Cabot Institute, University of Bristol, Bristol,
UK</footnote>

<footnote>J.-C. Komorowski
Institut de Physique du Globe de Paris et Université
Paris Diderot, Université Sorbonne Paris Cité, CNRS
UMR 7154, Paris, France</footnote>

<footnote>J. Barclay
School of Environmental Sciences, University of
East Anglia, Norwich, UK</footnote>
challenging, especially during protracted unrest. We explore limitations of current approaches to decision-making and provide suggestions for how future improvements can be made in the framework of holistic volcanic unrest risk governance. We investigate potential benefits arising from improved communication, and framing of warnings around decision-making timescales and hazard levels.

## Resumen

La agitación volcánica es compleja y capaz de generar múltiples peligros que pueden ser desencadenados por un número diferente de procesos subsuperficiales. Las interpretaciones científicas sobre datos de agitación volcánica tienen como objetivo el mejor entendimiento de (i) los procesos detrás de la agitación volcánica y sus señales superficiales asociadas, (ii) su evolución espacial-temporal y (iii) su significado como precursores de fenómenos eruptivos a futuro. Dentro de un contexto social, acciones adicionales preparatorias o de contingencia podrían ser requeridas debido a que las relaciones entre individuos y dentro de grupos sociales serán perturbadas e inclusive modificadas ante la presencia de incertidumbre significativa. Aquí nosotros analizamos algunos ejemplos clave a partir de tres proyectos internacionales y multidisciplinarios (VUELCO, CASAVA y STREVA) en los cuales las cuestiones alrededor de los límites del conocimiento volcánico tienen impacto en la gestión pública del riesgo volcánico. Proveemos una perspectiva general del contexto regional y global de la agitación volcánica y sobresaltamos retos científicos y sociales con énfasis geográfico en el Caribe y América Latina. Investigamos porqué el pronóstico de la evolución en la agitación volcánica y el aprovechamiento de señales de agitación volcánica para el pronóstico de comportamiento eruptivo a futuro y el enmarque de protocolos de respuesta es un reto, especialmente durante periodos de agitación prolongada (años a décadas) en los que algunos retos surgen desde la utilización de señales de agitación para pronosticar la evolución de agitación a largo plazo y sus eventuales consecuencias. Exploramos las limitantes de actuales enfoques para la toma de decisiones y proveemos sugerencias acerca de cómo pueden hacerse reformas a futuro dentro del marco holístico de gobernanabilidad ante el riesgo de agitación volcánica. Investigamos los potenciales beneficios que surgen por comunicación mejorada, y delimitando alertas alrededor de escalas de tiempo para la toma de decisiones y los niveles de alerta. Proponemos la necesidad de la cooperación a través de las fronteras científicas tradicionales, una valoración más amplia del riesgo natural y una mayor interacción de los sectores interesados.
# 1 Introduction

Volcanic unrest is a complex multi-hazard phenomenon of volcanism. Although it is fair to assume that probably all volcanic eruptions are preceded by some form of unrest, the cause and effect relationship between subsurface processes and resulting unrest signals (geophysical or geochemical data recorded at the ground surface, phenomenological observations) is unclear and surrounded by uncertainty (e.g., Wright and Pierson 1992). Unrest may, or may not lead to eruption in the short-term (days to months). If an

eruption were to ensue it may involve the eruption of magma or may be non-magmatic and mainly driven by expanding steam and hot water (hydrothermal fluids) (Table 1). These conundrums contribute significant uncertainty to short-term hazard assessment and forecasting of volcanic activity and have profound impact on the management of unrest crises (e.g., Marzocchi and Woo 2007).

While institutional and individual decision-making in response to this unrest should promote the efficient and effective mitigation or management of risk, informed decision-making

<table><caption>**Table 1** Summary of processes contributing to unrest signals in space and time, possible outcomes and hazards/impact of unrest</caption><thead><tr><th>Nature of processes</th><th>Processes</th><th>Signals</th><th>Hazards/Impact</th><th>Unrest Outcome</th></tr></thead><tbody><tr><td>Magmatic</td><td>Magma and/or melt and/or volatile migration (input, loss or ascent from reservoir), chemical differentiation, thermal convection, thermal perturbation (heating or cooling), pore fluid migration reservoir rejuvenation, crystallization and other phase changes</td><td>Seismicity, ground deformation, changes in potential fields, changes in gas and/or ground water chemistry, changes in heat flux, changes in volatile flux</td><td>Ground deformation, shaking and rupture and associated infrastructure damage; water table level changes; toxic gas emissions, contamination of ground water, atmosphere and crops; edifice destabilization; toxic gas emissions</td><td>Waning and return to background activity; eruptive activity (magmatic and/or phreatic)</td></tr><tr><td>Tectonic/gravitational</td><td>Faulting, changes in local/regional stress fields, edifice gravitational spreading, crustal loading, pore fluid migration</td><td></td><td></td><td>Waning and return to background activity; eruptive activity (magmatic and/or phreatic)</td></tr><tr><td>Hydrothermal</td><td>Fluid migration, phase changes, changes in temperature and/or pressure, chemical changes, pore pressure variations, porosity and permeability changes (sealing), host-rock alteration</td><td></td><td></td><td>Waning and return to background activity; phreatic eruptive activity</td></tr></tbody></table>

Processes can act individually, in unison or in any combination
is fundamentally dependent on the early and reliable identification of changes in the subsurface dynamics of a volcano and their “correct” assessment as precursors to an impending eruption. However, uncertainties in identifying the causative processes of unrest impact significantly on the ability to “correctly” forecast the short-term evolution of unrest.

When a volcano evolves from dormancy through a phase of unrest, scientific interpretations of data generated by this unrest relate to (i) the processes behind unrest and their associated surface signals, (ii) their potential future spatio-temporal evolution (i.e., hydrothermal vs. phreatic vs. magmatic processes and their intensity) and (iii) their significance as precursors for future eruptive phenomena. Scientific interpretations framed towards the governance of and social responses to the risk implicit in the potential onset of an eruption focus on: (i) understanding the epistemic (relating to the limits of existing knowledge) and aleatoric (relating to the intrinsic variability of natural processes) uncertainties surrounding these data and their impact on decision making and emergency management, (ii) the communication of these uncertainties to emergency managers and the citizens at risk, and (iii) understanding how best to manage evolving crises through the use of forecasted scenarios.

## 2 Motivation

The analysis presented in this chapter synthesises wider results and experiences gained in three major research consortia with focus on volcanic hazards and risks: (1) The VUELCO project, (2) the CASAVA project, and (3) the STREVA project.

The European Commission funded VUELCO project (2011–2015; “Volcanic unrest in Europe and Latin America: Phenomenology, eruption precursors, hazard forecast, and risk mitigation; www.vuelco.net) focused on multi-disciplinary research on the origin, nature and significance of

volcanic unrest and pre-eruptive processes from the scientific contributions generated by collaboration of ten partners in Europe and Latin America. Dissecting the science of monitoring data from unrest periods at six target volcanoes in Italy (Campi Flegrei caldera), Spain (Tenerife), the West Indies (Montserrat), Mexico (Popocatépetl) and Ecuador (Cotopaxi) the consortium created strategies for (1) enhanced monitoring capacity and value, (2) mechanistic data interpretation and (3) identification of eruption precursors and (4) crises stakeholder interaction during unrest.

The CASAVA project (2010–2014; Agence nationale de la recherche, France; Understanding and assessing volcanic hazards, scenarios, and risks in the Lesser Antilles—implications for decision-making, crisis management, and pragmatic development; https://sites.google.com/site/casavaanr/, last accessed 11-10-2016) implemented an original strategy of multi-disciplinary fundamental research on the quantitative assessment of volcanic risk for the Lesser Antilles region with emphasis on Guadeloupe and Martinique. The aim of the project was to improve the capacity to anticipate and manage volcanic risks in order to reduce reactive ‘repairing’ post-crisis solutions and promote the emergence of a society of proactive volcanic risk prevention in case of a future eruption. Part of this was achieved via a forensic analysis of past crises, described here.

The STREVA Project (2012–2018 funded by the UK Natural Environment and Economic and Social Research Councils; www.streva.ac.uk) was designed as a large interdisciplinary project to develop new means to understand how volcanic risk should be assessed and framed. It uses the ‘forensic’ interdisciplinary analysis of past volcanic eruptions in four settings to understand the key drivers of volcanic risk. The aim is to use this analysis to generate future plans that will reduce the negative consequences of future eruptions on populations and their assets. STREVA works closely with partners in the Caribbean, Ecuador and Colombia, focussing the
forensic analysis on long-lived eruptions of Soufrière Hills Volcano (Montserrat) and Tungurahua (Ecuador) and shorter duration eruptions of La Soufrière (St. Vincent) and Nevado del Ruiz (Colombia). The focus of the ‘forensic analysis’ process in the STREVA project has been to understand the key drivers of risk and resilience during long-lived volcanic crises. Nonetheless the analysis of the initial phases of activity from these eruptions provide some insights into the acute uncertainties of unrest and the social, political and scientific consequences of that uncertainty.

## 3 Volcanic Unrest: Scientific and Social Context

Volcanic unrest can be defined in a scientific context: “The deviation from the background or baseline behaviour of a volcano towards a behaviour or state which is a cause for concern in the short-term (hours to few months) because it might prelude an eruption” (Phillipson et al. 2013). The term “eruption” in the context of a possible unrest outcome could either relate to a magmatic or non-magmatic (phreatic or hydrothermal) origin including the possible evolution from phreatic to magmatic activity or an alternation or mix between the two (e.g., Rouwet et al. 2014). In a social context, these concerns might necessitate additional preparatory or contingency actions in response to the unrest phenomena or the preparation for an eruption given that the organisation and preparedness of communities and those who manage them will be perturbed and even changed in the context of significant uncertainty (Barclay et al. 2008 and next section).

## 4 Challenges and Key Questions Relating to Volcanic Unrest

### 4.1 Wider Perspective

Whether or not unrest results in eruption, either of magmatic or non-magmatic origin, and

whether (in hindsight) “correct” or “false” forecasts are issued to suggest there could be an imminent eruption are among the central questions that need answering as soon as unrest is detected.

The cost of scientific uncertainty regarding the causes and outcome of volcanic unrest may be substantial not only in terms of direct or indirect financial implications such as explored in Sect. 5, but also regarding knock-on (secondary) effects such as public trust in the accuracy or inaccuracy of scientific knowledge, public perception of the relationships between signals of unrest and volcanic risk and future public compliance with orders to evacuate or improve preparedness in the medium to long term.

A multitude of subsurface processes may contribute to unrest signals and some are summarised in Table 1. Not all processes are pre-eruptive and the challenge lies in deciphering the causes of unrest with a view to establish early on in a developing crises whether a volcanic system develops towards a state where an eruption may ensue. Whether or not unrest leads to eruption depends on many parameters. In general the main concern during volcanic unrest lies with the potential for a magmatic eruption. For this to occur magma must rise from depth and break through the surface. The dilemma for scientists is that magma movement does not create uniquely attributable unrest signals and does not necessarily lead to eruption (Table 1). For example, seismicity and ground uplift, both common indicator of unrest, may be induced by the replenishment of a magma reservoir, the ascent of magma towards the surface or the redistribution of aqueous fluids and fluid phase changes (see Salvage et al. 2017; Hickey et al. 2017; Mothes et al. 2017 for examples from VUELCO volcanoes). Similarly, an increase in the gas and heat flux (Christopher et al. 2015) at the surface may be induced by magmatic or hydrothermal processes and even tectonic stress changes have also been shown to trigger such behaviour (e.g., Hill et al. 1995). In fact, non-magmatic eruptions are associated with significant hazards and have or could have caused fatalities in the past such as for example Bandai in 1888 (Sekiya and Kikuchi
1890), Te Maari Tongariro in 2012 (e.g., Jolly et al. 2014) and recently at Ontake in 2014 (e.g., Maeno et al. 2016). Many unrest processes contribute to non-eruptive secondary hazards such as flank instability and collapse (e.g. Reid 2004).

## 4.2 Uncertain Causes and Uncertain Effects

Substantial uncertainties surround both the interpretation of the drivers of unrest and the assessment of the potential evolution and outcome of unrest. Critical questions include: Will an eruption ensue? If so, will it occur in the short-term (days to months) or long-term (years to decades)? What will be the nature and intensity of the eruption (magmatic vs. phreatic)?

In the case of magmatic unrest, magma ascent towards the surface can lead to a magmatic eruption with potential for the formation of lava flows, pyroclastic flows, lahars, ash-fall and ballistics. These processes impact the proximal (few tens to hundreds of meters), medial (kilometers) and distal (tens of kilometres or more) areas around the volcano. Conversely unrest driven by sub-surface hydrothermal activity may peak in a phreatic eruption and while impacted areas are rather proximal to the volcano, associated ballistics and dilute pyroclastic density currents triggered by laterally-directed explosions and emplacement of a debris avalanche from a partial edifice collapse can lead to an anomalously high loss of lives as recently shown by the September 27, 2014 Mount Ontake eruption, the deadliest eruption in more than 100 years in Japan (e.g. Maeno et al. 2016).

The challenge, however, is to identify and discriminate signals that are indicative of reactivation leading towards a major expulsion of magmatic material from those associated with a slight deviation from background levels and potential waning of unrest phenomena (Table 1).

The fundamental limitation for volcanologists is that it is not possible to directly observe causative processes at depth. Thus interpretations of these drivers rely on the secondary interpretation of observable signals associated with those processes (Salvage et al. 2017) or the reproduction of interpreted processes via laboratory experiments (Wadsworth et al. 2016). In addition, many volcanic processes are intrinsically non-linear and characterized by a chain-link reaction such that minor variations of some uncertain parameters might have ultimately significant consequences on the eruptive outcome. Such non-linear processes coupled with episodic and aleatoric uncertainties are complex to understand and model. This chapter analyses some key examples across the three aforementioned projects where issues around the limits of volcanic knowledge exacerbated risk and makes suggestion for how future improvements can be made.

## 4.3 The Hazard and Risk Interface

### Scientific Challenges

In the light of the above, from a scientific point of view the early identification of the cause of unrest and its likely outcome and evolution is pivotal for effective and efficient risk assessment, risk management and the design of mitigation efforts. In order to address the key scientific question of whether unrest is a prelude to imminent eruption or whether it will wane after some time without eruption several questions require answering first (note, that the list is not exhaustive):

* Is the anomalous behaviour unambiguously indicative for a change in the volcano's behaviour and for a deviation from its background state?

* How reliable is the assessment of unrest as a prelude to eruption, particularly in the absence of data on past events?
* What are the mechanistic processes at depth leading to observed unrest signals?

* Are monitoring signals indicative of magmatic, hydrothermal or tectonic unrest?

* Can the unrest be caused by perturbations and changes in the host-rock properties (e.g. porosity, permeability, mechanical properties) rather than by distinct endogenic processes of hydrothermal or magmatic origin?

* What are the uncertainties surrounding monitoring signals and inferred sub-surface processes (see Hickey et al. 2017 and Salvage et al. 2017)?

* Do secondary processes (e.g. hydrothermal system perturbation, meteorological forcing) modify primary signals from deeper-seated magmatic processes?

* What are the consequences of signal modification for the assessment of the process-to-signal-to-outcome causal link?

* Does one follow a deterministic or probabilistic approach for observations and forecasting (e.g., Hincks et al. 2014; Aspinall and Woo 2014; Rouwet et al. 2017)?

* What is the likelihood of a specific eruptive or non-eruptive scenario to manifest (e.g., Bartolini et al. 2017)?

* Which types of eruptions did the volcano produce in the past?

* If an eruption is to occur, what is its likely nature: magmatic, or phreatic or a mix?

* How much lead-time before eruption is there based on previous experience; how much lead-time is there in the absence of previous experience?

* Which eruptive or non-eruptive unrest episodes at analogue volcanoes can provide clues for the interpretation of signals and forecasting of unrest evolution and outcome (e.g., Sheldrake et al. 2016)?

* What is the likely size of the eruption and the associated hazards and risks and impacted area?

* What is the temporal evolution of eruptive intensity once the eruption has started? i.e.,

what is the likelihood that the eruption (a) will have its paroxysmal phase in the first 24 h of eruption (42% of eruptions do, according to Siebert et al. (2015)); or (b) will have a more progressive escalation over several months that will culminate in a paroxysm; or (c) will be characterised by peaks in activity separated by more or less long-lasting pauses or strong decline of activity preceding another rapid increase and peak of activity?

## Societal Challenges

At the same time, the political, sociological, cultural and economic (grouped here under the term ‘societal’) implications from unrest need addressing in order to respond appropriately to the emerging natural hazard (Wynne 1992) Here we provide a (non-exhaustive) list of questions for risk managers and/or politicians in the context of risk governance during volcanic unrest:

* What is the best-practice to provide maximum response time, while minimizing vulnerability and optimizing the cost/benefit ratio (see Fig. 1) of mitigation actions in a developing unrest crises?

* What is the best practice to issue or raise an alert?

* When and how to decide to raise an alert and to take action?

* What are the potential (legal) consequences of a false positive or false negative (see Table 2 and Bretton et al. 2015)?

* What are the consequences of a true positive (Table 2)?

* What is the basis for raising an alarm: the outcomes of unrest (e.g., instability of buildings due to ground deformation or seismicity; toxic degassing and environmental contamination) or the potential for eruption?

* How to best disseminate what information on unrest and its potential consequences, when, and via which communication vehicle(s) to the public?
<figure><img src="image_6.png" /><figcaption>**Fig. 1** Cost-benefit relationship as a tool for decision-making. **a** In the context of volcanic unrest risk management, actions of given quantity Q (for example, number of shelters or evacuees) are associated with costs in relation to their expected benefits (expressed by a financial value). An optimal relationship between costs of mitigation efforts and resultant benefits can be achieved when the difference between investment and benefit is greatest (shown by stippled red line). The example is based on concepts of</figcaption></figure>

capital management theory presented in Brealey et al. (2011). **b** Cost (C) versus loss (L) model for volcanic risk management (after Marzocchi and Woo 2007). If, in this decision-making framework, the expected expense (cost) for mitigation action is to be minimised, then action is required if the probability (p) of an adverse event to occur exceeds the ratio between the cost of the action and the expected loss (L/C). See discussion for a wider appraisal of the challenges arising from such an analysis

<table><caption>**Table 2** Concept of successful and unsuccessful forecasting</caption><thead><tr><th></th><th>Event forecast</th><th>Event not forecast</th></tr></thead><tbody><tr><th>Event occurs</th><td>True positive</td><td>False negative (Type II error)</td></tr><tr><th>Event does not occur</th><td>False positive (Type I error)</td><td>True negative</td></tr></tbody></table>

* How to account for uncertainty and the diversity of expert opinions in deciding the alert level?

* In what context does this occur such as political pressures, concurrent natural or other hazards (pandemic, famine, cyclone, etc.)
## 4.4 Cost-Benefit Analysis (CBA)

In the previous paragraphs, several questions related to how to get both the scientific analysis ('what is going on?') and the societal response ('how to respond?') 'right'. One measure employed to quantify the economic consequences of action or no-action under imminent threat and a tool for informed institutional decision-making is the cost-benefit analysis (Marzocchi and Woo 2007) whereby one aims to find a good answer to the question: "Given an assessment of costs and benefits related to risk mitigation efforts, which actions should be recommended?" Figure 1 shows the concept of evaluating the optimum ratio between the cost and benefit of mitigation efforts and provides a cost-benefit matrix for the design of action plans in response to a future [short-term in context of this chapter) adverse event of given probability (p) (Brealey et al. 2011; Marzocchi and Woo 2007)]. A critical issue in CBA is the 'minimum value of a human life', which we will not discuss further here. The interested reader is referred to, for example, Woo (2015) for further details on this quantification. Another interesting point relates to what might be regarded as a 'cost' and a 'benefit' in a response to an unfolding unrest crisis with an uncertain outcome (see also Sect. 6).

# 5 Global and Regional Context of Volcanic Unrest

## 5.1 Unrest Durations and Characteristics

Phillipson et al. (2013) reviewed global unrest reports of the Smithsonian Institution Global Volcanism Program (GVP) between January 2000 and July 2011 to establish the nature and length of unrest activity, to test whether there are common temporal patterns in unrest indicators and to test whether there is a link between the length of inter-eruptive periods and unrest duration across different volcano types.

Using available formation on unrest at 228 volcanoes they defined unrest timelines to demonstrate how unrest evolved over time and highlight different classes of unrest including reawakening, pulsatory, prolonged, sporadic and intra-eruptive unrest (see Fig. 2 for an example from Cotopaxi volcano). Statistical analyses of the data indicate that pre-eruptive unrest (where there is a causal link between unrest and an eruption within the observation period) duration was different across different volcano types with 50% of stratovolcanoes erupting within one month of reported unrest. The median average

<figure><img src="image_7.png" /><figcaption>**Fig. 2** Timeline of reported anomalous activity at Cotopaxi volcano (Ecuador) in 2001/2002. This period of pulsatory unrest lasted for more than 3 years with a heightened level of activity in 2001 and 2002. The unrest did not lead to an eruption in the short-term (weeks to</figcaption></figure>

months), but Cotopaxi entered an eruptive phase in August 2015 after a short-period of renewed unrest activity starting in April 2015 (see Mothes et al. 2017 for details). The data shown in the graph are from Phillipson et al. (2013)
duration of pre-eruptive unrest at large calderas was about two months, while at shield volcanoes a median average five months of unrest was reported before eruptive activity. The shortest median average duration is reported for complex volcanoes where eruptive unrest was short at only two days. Overall there appears to be only a very weak correlation between the length of the inter-eruptive period and pre-eruptive unrest duration. This may indicate that volcanoes with long periods of quiescence between eruptions will not necessarily undergo prolonged periods of unrest before their next eruption (Fig. 3). Phillipson et al. (2013) found statistically relevant information only from reports of anomalous seismic behaviour, most other monitoring signals are either not recorded or not reported as unrest criteria. The authors reported a noteworthy lack of geodetic data/information and in particular

satellite remote sensing data in the available reports. Recently Biggs et al. (2014), addressed the latter and systematically analysed 198 volcanoes with more than 18 years of satellite remote sensing deformation data for their deformation behaviour. 54 volcanoes that showed deformation also erupted during the observation period. Their analysis does not imply any causal link, or even a temporal relationship between any specific eruptions and episodes of deformation and is hence not directly comparable to the causal and predictive analysis by Phillipson et al. (2013). However, given that 46% of deforming volcanoes erupted while 94% of non-deforming volcanoes did not erupt provides “strong evidential worth of using deformation data as a trait association with eruption” (Biggs et al. 2014).

It is important to note that exploitable records on volcanic unrest are limited and the available

<figure><img src="image_8.png" /><figcaption>**Fig. 3** Comparison between the inter-eruptive period (IEP) and unrest duration (UD) from the data set presented in Phillipson et al. (2013). **a** shows entire data set (n = 118) **b** shows a subset of the data for clarity of inter-eruptive periods <150 years. The *p*-values of the Pearson's correlation test are *p* = 0.93 for the entire data set, *p* = 0.60 for the subset of non-eruptive unrest (n = 58) and *p* = 0.20 for the subset of eruptive unrest</figcaption></figure>

(n = 60). The null hypothesis (“the UD is independent of the IEP”) is hence statistically acceptable when considering the entire data set. Considering the subset of pre-eruptive unrest, however, the statistical tests do not provide enough evidence to fully accept the null hypothesis since the associated *p*-value of 0.20 might hint towards some weak correlation between the two variables
data sets are far from complete. Key issues are the lack of or poor instrumentation at most volcanoes, the lack of reporting by observers particularly if an unrest turns out to be minor and without immediate consequences, and the lack of integrating unrest data from satellite remote sensing. The GVP generally lacks the post-facto integration of unrest indicators from satellite-remote sensing data (e.g., Fournier et al. (2010) and Biggs et al. (2014) for deformation and Carn et al. (2011) for degassing). In this respect, it is vitally important to recognise and support initiatives to collate and exploit worldwide volcano monitoring data such as for example the WOVOdat project (Venezky and Newhall 2007). Only by significantly increasing the knowledge-base on the spatial and temporal evolution of the unrest-eruption relationship can we embark on statistically sound exploitations of the data with a potential to improve forecasting capabilities early on in developing unrest crises.

## 5.2 Socio-Economic Contexts

### The Wider Perspective

Nowadays, about 800 million people live on or in direct vicinity of active volcanoes (Brown et al. 2015). The overwhelming majority of this population lives in low and middle income countries (countries with an annual gross national income per capita of less than US$12,700) including the focus area of the VUELCO, STREVA and CASAVA projects: the wider Latin American (LA) region extending from Mexico, through Central America and the Caribbean to South America. This region hosts about 330 Holocene volcanic centres compared to 84 in Europe and one quarter of the reported global fatalities attributed to volcanic events occurred there (Global Volcanism Program 2013).

Volcanic disasters are among the least audited of all natural disasters and therefore our knowledge on the impact of volcanic activity beyond claiming lives is largely incomplete (Benson 2006; Auker et al. 2013). Huge uncertainty surround estimates for indirect losses from for

example disease or starvation as a result of volcanic activity. Beyond increased human vulnerability, the direct and indirect financial impacts from volcanic activity can be immense as demonstrated by the relatively small-scale eruption of Iceland's Eyjafjallajökull volcano in April 2010 and the associated air travel disruption. This eruption demonstrated the vulnerability of modern infrastructure to volcanic hazards on an unprecedented scale with losses to the aviation industry alone at a minimum of US$2.5 Billion (European Commission 2010).

Equally there are social, political and financial implications for “false positives” related to volcanic unrest. In these instances actions are taken in response to an imminent threat, which then did not manifest. In the case of volcanic unrest the imminent threat is generally defined as a volcanic eruption, although the multi-hazard nature of volcanic unrest (e.g., ground shaking, ground uplift or subsidence, ground rupture, ground instability, toxic gas emissions, contaminated water supplies) and possibly ensuing eruptive activity (magmatic vs. phreatomagmatic vs. phreatic) makes the definition of ‘imminent threat’ rather complex.

Although there is little systematic gathering and synthesis of data relating to financial or social losses associated with these episodes there are some well-documented analyses. Examples include:

1. On Guadeloupe in the French West Indies a major evacuation over a period of 4 months in excess of 70,000 individuals was initiated in 1976, as a result of abnormal levels of volcanic seismicity and degassing (see also next section). The estimated cost of the unrest was about US$340 Million at the 1976 exchange rate (data compiled using Lepointe 1999; Tazieff 1980; Blérald 1986; Baunay 1998; Kokelaar 2002; Annen and Wagner 2003), which translates to more than US$ 1.2 Billion at the time of this writing (July 2016). At the time the cost equaled to ca. 60% of the Gross National Product of the Guadeloupe economy (Blérald 1986). 90% of these costs were incurred by the costs of the evacuation,
and the costs associated with the rehabilita-
tion and salvage of the economy in Guade-
loupe after the evacuation.

(2) Unrest at Rabaul volcano in Papua New Guinea (an LDC) between 1983 and 1985, had significant adverse implications for both the private and public sectors. Considerable economic costs were incurred, estimated at over US$22.2 Million at the 1984 rate of exchange although an eruption did not occur until 10 years later (Benson 2006).

(3) Evacuation and rehousing of 40,000 inhabitants of the Pozzuoli area in the Campi Flegrei volcanic area of Italy resulted as a response to intense seismicity and ground uplift in the early 1980s. Although decision-makers did not release notice that this was in part due to the threat from an imminent eruption (see also Sect. 4.3.2), it is true that the re-location of these inhabitants moved them from the area of highest threat in the event of an eruption. At the time there was no agreement amongst scientists as to the cause of the unrest (Barberi et al. 1984) and the scientific discussion as to the cause of these events is still ongoing more than 30 years after the crisis.

The following paragraphs focus on two examples of short-term and long-term volcanic unrest crises response and provide more detailed insights into the volcanic risk governance in two different jurisdictions.

Short-Term Crisis Example: The 1976–
1977 La Soufrière of Guadeloupe Unrest

The unrest on Guadeloupe culminated in a series
of explosive eruptions of hot gas, mud and rock
(termed phreatic eruption) without the direct
eruption of magma before waning in 1977
(Feuillard et al. 1983; Komorowski et al. 2005;
Hincks et al. 2014). Fortunately no fatalities
were caused by the activity. Had the unrest on
Guadeloupe led to a magmatic eruption, then the
cost of the unrest would have likely been neg-
ligible. Although the precautionary evacuation
caused a substantial economic loss with severe
social consequences, it is acknowledged that the

"proportion of evacuees who would have owed their lives to the evacuation, had there been a major eruption, was substantial" (Woo 2008). The CASAVA project undertook an exhaustive hindsight analysis of the process of scientific decision-making for the unrest and eruptive crisis of 1976-1977 at La Soufrière de Guadeloupe. The crisis caused significant hardships and loss of livelihood for the evacuated population and the whole society in Guadeloupe as a result of controversial crisis management associated with a forecast of a major magmatic eruption that did not occur (false positive) (Feuillard et al. 1983; Fiske 1984; Komorowski et al. 2005; Hincks et al. 2014). Given the evidence of continued escalating pressurisation and the uncertain transition to a devastating magmatic eruption, authorities declared a 4-month evacuation of ca. 70,000 people on August 15, 1976 that provoked severe socio-economical consequences for months to years thereafter. This evacuation is still perceived as unnecessary and reflecting an exaggerated use of the "principle of precaution" on behalf of the government.

However, some level of risk governance (i.e.
evacuation of the most exposed area) was justifi-
fied in hindsight given the persistent ashfalls and
environmental contamination from acid degas-
sing as well as the hazards from a series of
non-magmatic eruptions (e.g., pyroclastic flows
from laterally directed explosions, partial edifice
collapse, mudflows) (Komorowski et al. 2005;
Hincks et al. 2014).

The (in hindsight) erroneous identification of
the presence of ‘fresh glass’ in the ejecta and its
interpretation as evidence of the magmatic origin
of the unrest and thus of its possible outcome, led
to a major controversy amongst scientists that
was widely echoed in the media. Lack of a
comprehensive monitoring network prior to the
crisis, limited knowledge of the eruptive history,
and living memory of past devastating eruptions
in the Lesser Antilles contributed to a high
degree of scientific uncertainty and a publically-
expressed lack of consensus and trust in available
expertise. Consequently analysis, forecast, and
crisis response were highly challenging for
scientists and authorities in the context of esca-
lating and fluctuating activity and societal pres-
sure. The high uncertainty about a so-called
“unequivocal” impending disaster fostered a
binary zero-sum strongly opinionated approach
in the scientific discourse. The public debate thus
became polarized on issues of opposing “truths”
served by contrasted scientific expertise rather
than on how science could help constrain epis-
temic and aleatoric uncertainty and foster
improved decision-making in the context of
uncertainty (Komorowski et al. 2017). This sit-
uation acted as an ideal crucible to fuel a
media-hyped controversy on the crisis and its
management. A recent retrospective Bayesian
Belief Network analysis of this crisis (Hincks
et al. 2014) demonstrates that a formal evidential
case could have been made to support the
authorities’ concerns about public safety and
decision to evacuate in 1976.

As part of the CASAVA project we conducted
focus group interviews, issued questionnaires,
and ran role playing games with the population
currently living in areas potentially threatened by
renewed unrest and eruptive activity from La
Soufrière, (be it magmatic or non-magmatic). We
found that the current population's risk percep-
tion increases to a level of preparing to evacuate
chiefly on the basis of the timing and nature of
scientific information issued publically by the
volcano observatory. This implies that the pop-
ulation is prone to self-evacuate ahead of any
official evacuation order given by the authorities
in charge of civil protection and crisis response.

Long-Term Crises Examples: Soufrière Hills (Montserrat) and Tungurahua (Ecuador)

The forensic analyses of the STREVA project
have focussed on the integration of new
social-science based understandings of popula-
tion response and recovery with the scientific
insights prompted by these long-lived eruptions.
This has similarities with the ‘FORIN’ approach
advocated by the International Program on Inter-
grated Risk for Disaster Reduction (Burton
2010). In this description we focus particularly
on the initial stages of the eruptions.

The long-lived volcanic crisis of the Soufrière Hills Volcano is probably one of the most written about volcanic eruptions, encompassing a wide variety of perspectives, scientific, social-scientific and personal, in that writing. As a consequence of the activity on the island of Montserrat a population of over 10,500 was reduced to just 2850 (the population has since risen to 4922 [2011 census], Hicks and Few 2015). At the onset of eruption (1995) an assessment of risk existed (Wadge and Isaacs 1988) but was not acted on or acknowledged by the authorities, and so preparedness was low, exacerbated by the recent passage of Hurricane Hugo (1989) which had caused 11 fatalities and rendered 3000 homeless. Governance on Montserrat was reforming in the wake of the economic and social crisis induced by the hurricane (Wilkinson 2015). The protracted uncertainty in the early stages of the eruption coupled with a lack of coherence in governance between the UK and local governments lead to the projected evacuation of 1300 people in temporary public shelters, which suffered from overcrowding, lack of privacy, poor sanitation and lack of access to good nutrition. Ultimately, this led to a partial disregard for evacuation advice and a strong pulse of outwards migration. In the longer term, the long-lived volcanic eruption has acted to exaggerate pre-existing vulnerabilities in the local population (Hicks and Few 2015).

The early stages of the current Tungurahua (Ecuador) eruptive episode that started in 1999 typify a further challenge for the management of unrest prior to or between surface activity at the early stages of a volcanic crisis. Initially the local population were evacuated by a compulsory evacuation order but when the initial phases proceeded more slowly than had been expected by local authorities and communities, civil unrest and disturbance happened with the re-occupation by force and ultimately abandonment of the evacuation order. These arose from the acute economic and social pressures visited on the population by the evacuation (Mothes et al. 2015). Subsequently, the response of the monitoring organisation to these pressures represents a new prototype for collaborative monitoring and
management of restive volcanoes (Mothes et al. 2015; Stone et al. 2014). The growth of trust, and attempts to maximise resilience in the face of repeated unrest episodes provides strong evidence for collaborative approaches to risk management (Few et al. 2017). Nonetheless tensions still exist, largely arising from our current incapacity to predict the intensity or magnitude of eruptions from signals relating to new unrest. There can be problems in this risk system implicit in anticipating the ‘maximum expected’ outcome from unrest.

# 6 Discussion

## 6.1 The Caveats of Volcanic Unrest Response

Managing volcanic unrest episodes is extremely complex and challenging due to the multi-hazard nature of unrest. The risks to be assessed and mitigated include both those associated with the unrest itself as well as those from the potential future eruptive activity. Whilst ground deformation, seismicity, thermal flux or anomalous degassing are indicators of possible future activity these phenomena also pose significant immediate threats to population, infrastructure and other assets in affected areas during the unrest.

From a scientific point of view, hazard assessment relating to eruptive activity has made considerable progress in recent years partly through the deployment of increasingly powerful computational models and simulation capabilities (e.g., Esposti Ongaro et al. 2007; Manville et al. 2013) as well as through advances in the development of probabilistic eruption forecasting tools (e.g., Marzocchi et al. 2008; Aspinall 2006; Aspinall and Woo 2014) and improvements to fundamental understandings of the root drivers of changing activity (e.g., Cashman and Sparks 2013).

Despite these crucial advances for short-term eruption forecasting, the knowledge-base on volcanic unrest, its significance as an eruption

precursor, its exploitability regarding forecasting of potential eruptive behaviours and framing of response protocols (e.g., CBA) remains weak for a number of reasons:

(1) The scientific interpretation of volcanic unrest is surrounded by substantial uncertainty, ambiguity and ignorance (Stirling 2010) regarding causes and eventual outcome. Since the contributing subsurface processes cannot be directly observed, volcanic unrest is likely among the least understood phenomena in volcanology for a variety of reasons:

(i) Incomplete knowledge of the mechanistic processes and their dynamic behaviour over time within a magma reservoir and its surroundings (host-rock, hydrothermal system, meteoric recharge, local and regional structural context) that trigger the geo-physical, geochemical and geodetic signals recorded at the surface during unrest periods (Table 1).

(ii) Consequently, the interpretation, of the departure of monitoring signals from a long-term baseline level or in the absence of baseline data a crescendo or decrescendo of signals collected during periods of unrest are often ambiguous or non-unique. While this can in practice be addressed in models through epistemic and aleatoric uncertainties, ambiguities in the interpretation will remain.

(2) Ambiguity, uncertainty and ignorance (Stirling 2010) have impact on probabilistic forecasting of duration, spatio-temporal evolution, causal relationship between sequential events and outcomes of unrest episodes (see Sandri et al. 2017) and on remedial actions to mitigate current and future adverse effects. Uncertainties in the decision-making process may give rise to “false alerts” (i.e., false positives; see Table 2) and actions by civil protection with adverse impacts on the compliance of affected communities in future unrest events.

(3) Lack of globally accepted and standardised approach for the terminology, methodology,
criteria, protocols and best practice employed to evaluate and respond to volcanic unrest by different stakeholders such as academia, volcano observatories and the Civil Protection Agencies. This absence of commonly recognised standards can result in the critical issue of managerial risk vulnerability (i.e., standard equivocality' after Bretton et al. 2015). It also often impacts negatively on the effectiveness of communication between stakeholders, hinders or delays effective and efficient decision-making processes and hampers the dialogue among members of scientific, governmental and civil communities (De la Cruz-Reyna and Tilling 2008). However, it is important to note that internationally-defined standards should not be rigidly imposed irrespective of local, cultural, political and social practices (e.g., Bretton et al. 2015; IAVCEI 2016).

(4) Globally, there is no commonly accepted and standardised denominator between those that provide and those that receive scientific advice regarding the level of appropriate scientific complexity to be considered. This may hamper a wider discourse on scientific and technological advances in the quantification of unrest phenomena and resultant uncertainties with other stakeholders. From the scientist's perspective this may generate the notion that the public, administrators, mass media and governmental entities do not appreciate the “excellence of the science” behind unrest characterisation and use the inherent uncertainty as a rationale to go into denial over the hazards posed during unrest. From a sociological point of view, however, decision-making apparently prompted solely by the present or likely volcanic hazards, does not account for local context and can result in a lack of trust in either scientific expertise or government representatives, (Johnson 1987; Haynes et al. 2008; Christie et al. 2015; Komorowski et al. 2017).

## 6.2 Some Ways Forward

The issues identified above can contribute less optimal unrest response and risk mitigation actions. Although there are other strong contributors to societal vulnerability, we have shown that scientific uncertainty combined with a lack of social awareness and preparedness does act to increase the vulnerability of a society to hazardous unrest phenomena with possibly adverse outcomes. Here, we propose future avenues which can form part of a Risk Governance Framework (IGRC 2017; Fig. 4) including research that could gather critical evidence for some of the key drivers of decisions that result in adverse outcomes for affected populations in the face of an unrest crisis. Such research could also contribute to the analysis of and identification of key targets for future research in volcanology and the social sciences.

### (a) Cost-Benefit Analysis

CBA, where the economic impacts of different decisions are quantified, can be difficult at the unrest hazard and risk interface. The case studies presented here demonstrate that intangible assets such as social and cultural cohesion and capital as well as trust (in the context of CBA analysis this would be intentional trust in the sense of Dasgupta (1988); i.e., the subjective probability assigned to compassionate action by an individual or a group of individuals) between different stakeholders can have a strong impact on individual and institutional vulnerabilities during crises.

Analyses that include a wider range of definitions and types of ‘costs’ and ‘benefits’ of mitigation efforts (e.g. loss of empowerment, a loss of cultural identity or cultural references), informed by past experiences would facilitate a discourse between different stakeholders. This would entail the need to attribute a financial value to, for example, mental well-being, social networks and cohesions and would necessarily trigger a wider discourse of the impacts of decision-making beyond the avoidance of ‘cost
<figure><img src="image_9.png" /><figcaption>**Fig. 4** The International Risk Governance Council (IRGC 2017) Risk Governance Framework adapted for the specific case of volcanic unrest. *Hazard and Risk Pre-assessment*—"peacetime framing" the hazard and risk in order to provide a structured definition of the baseline behaviour of the volcano and its consequences, of how the hazard and risk are framed by different stakeholders, of how the risk may best be handled, and of the thresholds to be met or exceeded to declare a state of unrest. *Hazard and Risk Appraisal*—combining a scientific risk assessment of the current unrest hazards (using for example a rating scheme of unrest intensity, e.g., Potter et al. 2015) and its probability with a systematic concern assessment (of public concerns and perceptions) to provide the knowledge base for subsequent decisions in an emerging unrest crises. *Risk Characterisation and Evaluation*—in which the scientific data and a thorough understanding of societal values affected by the risk are used to evaluate the risk as acceptable, tolerable (requiring mitigation), or intolerable (unacceptable). *Risk Management*—the actions and remedies needed to avoid, reduce transfer or retain the unrest risk and risks from probable unrest outcomes. *Risk Communication*—how stakeholders and civil society understand the unrest risk and participate in the risk governance process. *Risk Categorisation and Evaluation*—categorising the knowledge about the cause-effect relationships as either simple, complex, uncertain or ambiguous. In the context of volcanic unrest this may include the categorisation of the outcome of unrest and probable future eruptive activity</figcaption></figure>

to lives'. Ideally this discourse would be framed
during 'peace-time' (i.e. not in response to an
unfolding unrest crisis) and involve participation
from a wide spectrum of scientific and societal
stakeholders. The necessity to move beyond
circumscribed appraisal methods such as the
CBA is also evident from the response to

protracted (several years or decades) unrest
requiring an above back-ground level of
long-term vigilance (e.g. yellow/vigilance level
for La Soufrière of Guadeloupe since 1999,
Komorowski et al. 2005; OVSG-IPGP 1999–
2016 or at the Campi Flegrei caldera since 1969;
Ricci et al. 2013). In such cases there are obvious
long-term strategies that could be developed to
improve social well-being and economic devel-
opment (e.g. developing resilient critical infras-
tructures such as roads, bridges, public electrical
water and sewer systems and communications
networks) that would significantly enhance the
quality of life for years of “peace time” from the
volcano while ensuring a more efficient crisis
response and recovery should the volcano erupt
and impact the society.

(b) Improved communication

Open and multi-directional communication pro-
cesses are of paramount importance in fostering
the development of a shared representation and
understanding among all stakeholders of the
nature, magnitude, dynamics, and societal and
environmental consequences of unrest and its
potential eruptive outcome on multiple spatio-
temporal scales (e.g. Barclay et al. 2008, 2015;
Komorowski et al. 2017). While communicating
this information in a timely and comprehensible
format is challenging, the evidence presented
here suggests that a continuous discourse is
needed between different stakeholders ideally
both before, during and after an unrest situation.
The case studies presented here demonstrate that
part of this discourse should involve a discussion
about the appropriate scientific complexity in the
communication between scientific and
non-scientific stakeholders is essential, so that
the information exchange is ‘useful, usable and
used’ (Aitsi-Selmi et al. 2016) and fit for the
decision-making purpose to which it is intended
(Fischhoff 2013). Wider discourse could for
example include regular information bulletins
from monitoring agents to the civil society and
authorities, the development of scenario-based
approaches in simulation exercises involving the
civil society and the wider appraisal of less
tangible ‘assets’ (i.e., live stock or cultural capital) in risk governance efforts.

Dialogues between those responsible for monitoring hazards and those responsible for managing risk, as well as the communities at risk cannot only help to understand the most important aspects of scientific information to convey but could also lead to an improved understanding of the context into which emergency response actions must be made (e.g. Christie et al. 2015), and encourage citizens at risk to act on advice. In particular more systematic studies that analyse the effectiveness of different techniques and strategies in achieving these goals would be very useful (see Fearnley et al. 2017 for a recent compilation). These efforts should help address reluctance by the public to follow emergency-response advice in an emerging unrest crises.

### (c) Wider natural risk appraisal

In a similar vein, the implementation of advice on volcanic risk could be more effective if it is considered in the context of other natural risks and social challenges (e.g., Wilkinson et al. 2016). By definition the onset of a volcanic eruption involves the anticipation of impacts from multiple hazards but the risk associated with volcanic hazards are often considered in isolation, and as a low probability, high consequence hazard, ignored in advance of an unrest crisis. This lack of dialogue and preparation has been identified above as a strong contributor to tensions during unrest crises. Volcanic regions only very rarely suffer solely from the impacts of a single natural hazard (e.g. volcanic small-island developing states discussed in Wilkinson et al. 2016; Komorowski et al. 2017). Therefore methods that consider the multi-hazard context more clearly may ultimately help communities at risk cope with uncertainty in face of volcanic hazards. This may be particularly the case, if they are able to identify ‘co-benefits’ during volcano “peace time” where preparedness or mitigation measures yield benefits for more than one hazard scenario (Wilkinson et al. 2016). This improvement of social well-being is likely to allow the

society to take better decisions when times of impeding adversity arise.

### (d) Framing of warnings around decision-making timescales and hazard level

Typically changes in alert levels are strongly tied to pre-determined changes in geophysical and geochemical signals or phenomenological observations and have carefully worked out associated actions. In our case studies, difficulties have arisen when the time-scale over which mitigating actions can be taken is much shorter than needed to implement mitigating actions such as evacuation or much longer than the timescale over which unrest or new eruptive activity impacts on the population at risk. In the case of the former, lives or assets may be put at risk and in the case of the latter, possessions and livelihoods can be negatively impacted with repercussions on trust and political stability. Managing decade or longer periods of protracted moderate-level unrest amid significant epistemic and aleatoric uncertainty on its outcome constitutes major challenges for scientists, authorities, the population, and the media.

The development of novel probabilistic formalism for decision-making could help reduce scientific uncertainty and better assist public officials in making urgent evacuation decisions and policy choices should the current and ongoing unrest lead to renewed eruptive activity. To improve decision-making around changing alert or hazard levels, improved modelling efforts of the time-scales and pathways of population mobilisation or actions (both as forward modelling and as analysis of past events) and better understanding of the consequences of protracted unrest or eruptive activity on the vulnerabilities of affected populations (e.g. Few et al. 2017) could improve choices to be made in responding to changing or escalating activity as well as chain-link scenarios.

Further, focussing on the time-scales associated with the responses to unrest (from the time taken to mobilise populations in an acute emergency, to the time-limits of tolerability of evacuation processes and finally the time-scales over
which services and livelihoods deteriorate in
response to protracted unrest) could provide
important indicators for the time-scales over
which alert levels (and attendant actions) need
attention. In turn this perspective could inform
scientific targets for improved forecasting, with
strong effort expended to reduce uncertainty over
time intervals that match those most critical to
effective societal action.

7 Conclusions

We have identified a number of scientific and
sociological problems surrounding volcanic
unrest and have highlighted key aspects of risk
governance at the interface between scientists,
emergency managers and wider societal stake-
holders. We have in particular focussed on the
issue of scientific uncertainty and its impact on
preparatory or contingency actions that might be
needed because relationships between and
among individuals and social groups will be
perturbed or even changed. Especially, during
periods of protracted unrest (years to decades)
challenges arise from the exploitability of unrest
signals to forecast long-term unrest evolution and
its eventual outcome. This impacts directly on
establishing the probability for and the timing
and type of future eruptive behaviour as well as
the definition of appropriate response protocols.
To improve communication and trust between
stakeholders as well as the framing of warnings
around decision-making timescales and hazard
levels of unrest, we propose that bridging across
traditional scientific boundaries, wider natural
risk appraisal and broader stakeholder interaction
is needed.

**Acknowledgements** The VUELCO project received funding by the EC-FP7 program under grant agreement number 282759, the CASAVA project (ANR-09-RISK-002) was funded by the Agence Nationale de la Recherche (France) and the STREVA Project (NE/J020052/1) was funded by the UK NERC and ESRC. We acknowledge the useful insights and comments from two anonymous reviewers.

References

Aitsi-Selmi A, Blanchard K, Murray V (2016) Ensuring science is useful, usable and used in global disaster risk reduction and sustainable development: a view through the Sendai Framework lens. Palgrave Commun (2) doi:10.1057/palcomms.2016.16

Annen C, Wagner J-J (2003) The impact of volcanic eruptions during the 1990s. Nat Hazards Rev 4:169-175

Aspinall WP (2006) Structured elicitation of expert judgment for probabilistic hazard and risk assessment in volcanic eruptions. In: Mader HM, Coles SG, Connor CB, Connor LJ (eds) Statistics in volcanology. The geological society for IAVCEI, 15-30

Aspinall WP, Woo G (2014) Santorini unrest 2011–2012: an immediate Bayesian belief network analysis of eruption scenario probabilities for urgent decision support under uncertainty. J Appl Volcanol 3:12

Auker MR, Sparks RSJ, Siebert L, Crossweller S, Ewert J (2013) A statistical analysis of the global historical volcanic fatalities record. J Appl Volcanol 2:2

Barclay J, Haynes K, Mitchell T, Solana C, Teeuw R, Darnell A, Crosweller HS, Cole P, Pyle DM, Lowe C, Fearnley C, Kelman I (2008) Framing volcanic risk within disaster risk reduction: finding ways for the social and physical sciences to work together. In: Liverman DGE, Pereria CPG, Marker B (eds) Communicating environmental geoscience. Geological Society Special Publication, 305

Barclay J, Haynes K, Houghton BF, Johnston DM (2015) Social processes in volcanic risk reduction. In: Sigurdsson H et al (eds) Encyclopaedia of volcanology, 2nd edn. Elsevier, Amsterdam.

Barberi F, Corrado G, Innocenti F, Luongo G (1984) Phlegraean Fields 1982–1984: brief chronicle of a volcano emergency in a densely populated area. Bull Volcanol 47:175–185

Bartolini S, Marti J, Sobradelo R, Becerril L (2017) Probabilistic e-tools for hazard assessment and risk management. Adv Volcanol 1–15

Baunay Y (1998) Gestion des risques et des crises: l'exemple de deux crises d'origines volcaniques dans les Caraïbes: Montserrat 1995-1998 et la Guadeloupe 1976-1977. Mémoire de Maîtrise de Géographie, Université de Paris 1, Panthéon-Sorbonne, Paris, unpublished, 164 pp.

Biggs J, Ebmeier SK, Aspinall WP, Lu Z, Pritchard ME, Sparks RSJ, Mather TA (2014) Global link between deformation and volcanic eruption quantified by satellite imagery: Nat Commun 5

Blérald APh (1986) Histoire éruptive de la Guadeloupe et de la Martinique du XVIIème siècle à nos jours, Editions Karthala, Paris, 336 p

Benson C (2006) Volcanoes and the economy. In: Marti J, Ernst GGJ (eds) Volcanoes and the environment. Cambridge University Press, pp 440–467.
Brealey R, Myers S, Allen F (2011) Principles of corporate finance. McGraw, 872 p

Bretton R, Gottsmann J, Aspinall WP, Christie R (2015) Implications of legal scrutiny processes (including the L'Aquila trial and other recent court cases) for future volcanic risk governance. J Appl Volcanol 4:18

Brown SK, Auker MR, Sparks RSJ (2015) Populations around Holocene volcanoes and development of a population exposure index. In: Loughlin SC et al (eds) Global volcanic hazards and risk 'populations around volcanoes and the development of a population exposure index. Cambridge

Burton I (2010) Forensic disaster investigations in depth: a new case study model. Environ Mag 52(5):36–41

Cashman KV, Sparks RSJ (2013) How volcanoes work: a 25 year perspective. Geol Soc Am Bull. doi:10.1130/b30720.1

Carn SA, Froyd KD, Anderson BE, Wennberg P, Crounse J, Spencer K, Dibb JE, Krotkov NA, Browell EV, Hair JW, Diskin G, Sachse G, Vay SA (2011) In situ measurements of tropospheric volcanic plumes in Ecuador and Colombia during TC4. J Geophys Res Atmos, 116

Christie R, Cooke O, Gottsmann J (2015) Fearing the knock on the door: critical security studies insights into limited cooperation with disaster management regimes. J Appl Volcanol 4:19

Christopher TE, Blundy J, Cashman K, Cole P, Edmonds M, Smith PJ, Sparks RSJ, Stinton A (2015) Crustal-scale degassing due to magma system destabilization and magma-gas decoupling at Soufrière Hills Volcano, Montserrat: Geochemistry, Geophys Geosys 16(9):2797–2811

Dasgupta P (1988) Trust as a commodity. In: Gambetta D (ed) Trust: making and breaking of cooperative relations. Blackwell, Oxford, 49–72

De la Cruz-Reyna S, Tilling RI (2008) Scientific and public responses to the ongoing volcanic crisis at Popocatépetl Volcano, Mexico: importance of an effective hazards-warning system. J Volcanol Geotherm Res 170:121–134

Esposti Ongaro T, Cavazzoni C, Erbacci G, Neri A, Salvetti MV (2007) A parallel multiphase flow code for the 3D simulation of volcanic explosive eruptions. Parallel Comput 33:541–560

European Commission (2010) Press Release 27. April, 2010). http://ec.europa.eu/commission_2010-2014/kallas/headlines/news/2010/04/doc/information note volcano_crisis.pdf

Fearnley C, Bird D, Haynes K, Jolly G, McGuire B (eds) (2017) Observing the volcano world: volcano crisis communication. Advances in volcanology, IAVCEI. Springer, Berlin, 350 p

Feuillard M, Allegre CJ, Brandeis G, Gaulon R, Le Mouel JL, Mercier JC, Pozzi JP, Semet MP (1983) The 1975–1977 crisis of La Soufrière de Guadeloupe (FWI): a still-born magmatic eruption. J Volcanol Geotherm Res 16:317–334

Few R, Armijos T, Barclay J (2017) Living with Volcan Tungurahua: the dynamics of vulnerability during prolonged volcanic activity. Geoforum 80:72–81

Fischhoff B (2013) The sciences of science communication. In: Proceedings of the National Academy of Sciences of the United States of America, 110 (Supplement 3), 14033–14039. doi:10.1073/pnas.1213273110

Fiske R (1984) Volcanologists, journalists, and the concerned local public: a tale of two crises in the eastern Caribbean. In: Boyd F (ed) Explosive volcanism: inception, evolution and hazards. Studies in geophysics. National Academy Press, Washington DC, pp 170–176

Fournier TJ, Pritchard ME, Riddick SN (2010) Duration, magnitude, and frequency of subaerial volcano deformation events: new results from Latin America using InSAR and a global synthesis. Geochem Geophys Geosys 11:Q01003. doi:10.01029/02009GC002558

Global Volcanism Program (2013) Volcanoes of the World, v. 4.5.5. In: Venzke E (ed) Smithsonian Institution. Downloaded 04 May 2017. http://dx.doi.org/10.5479/si.GVP.VOTW4-2013

Haynes K, Barclay J, Pidgeon NF (2008) The issue of trust and its influence on risk communication during a volcanic crisis. Bull Volcanol 70:605–621

Hicks A, Few R (2015) Trajectories of social vulnerability during the Soufriere Hills volcanic crisis. J Appl Volcanol 4:10

Hill DP, Johnston MJS, Langbein JO, Bilham R (1995) Response of Long Valley caldera to the Mw = 7.3 Landers, California, Earthquake. J Geophys Res 100 (B7):12985–13005

Hickey J, Gottsmann J, Mothes P, Odbert HM, Prutkin I, Vajda P (2017) The ups and downs of volcanic unrest: insights from integrated geodesy and numerical modelling. Adv Volcanol 1–17

Hincks T, Komorowski J-C, Sparks RSJ, Aspinall WP (2014) Retrospective analysis of uncertain eruption precursors at La Soufrière volcano, Guadeloupe, 1975–77: volcanic hazard assessment using a Bayesian Belief Network approach. J Appl Volcanol 3:3

IAVCEI task force on crises protocols (2016) Toward IAVCEI guidelines on the roles and responsibilities of scientists involved in volcanic hazard evaluation, risk mitigation, and crisis response. Bull Volcanol 8(31). doi:10.1007/s00445-00016-01021-00448

IRGC (2017) https://www.irgc.org/risk-governance/irgc-risk-governance-framework/. Last accessed 05/02/2017.

Johnson BB (1987) Accounting for the social context of risk communication. Sci Technol Stud, 103–111

Jolly AD, Jousset P, Lyons JJ, Carniel R, Fournier N, Fry B, Miller C (2014) Seismo-acoustic evidence for an avalanche driven phreatic eruption through a beheaded hydrothermal system: an example from the 2012 Tongariro eruption. J Volcanol Geotherm Res 286:331–347
Kokelaar BP (2002) Setting, chronology and consequences of the eruption of Soufrière Hills Volcano, Montserrat (1995–1999). In: Druitt TH, Kokelaar BP (eds) The eruption of Soufrière Hills Volcano, Montserrat, from 1995 to 1999, vol 21. Geological Society, London, Memoirs, pp 1–44

Komorowski J-C, Boudon G, Semet M, Beauducel F, Anténor-Habazac C, Bazin S, Hammouya G (2005) Guadeloupe. In: Lindsay JM, Robertson REA, Shepherd JB, Ali S (eds) Volcanic Atlas of the Lesser Antilles, Seismic Research Unit, The University of the West Indies, Trinidad and Tobago, WI, 65-102

Komorowski J-C, Morin J, Jenkins S, Kelman I (2017) Challenges of volcanic crises on small islands states. In: Fearnley C, Bird D, Haynes K, Jolly G, McGuire B (eds) Observing the volcano world: volcano crisis communication', Advances in Volcanology, IAVCEI, Springer, Berlin, pp 1–18. doi:10.1007/11157_2015_15

Lepointe E (1999) Le rêveil du volcan de la Soufrière en 1976: la population guadeloupéenne à l'épreuve du danger. In: Yacou A (ed) Les catastrophes naturelles aux Antilles – D'une Soufrière à l'autre. CERC Université Antilles et de la Guyane, Editions Karthala, Paris, pp 15–71

Maeno F, Nakada S, Oikawa T, Yoshimoto M, Komori J, Ishizuka Y (2016) Reconstruction of a phreatic eruption on 27 September 2014 at Ontake volcano, central Japan, based on proximal pyroclastic density current and fallout deposits. Earth, Planets and Space 68:82

Manville V, Major JJ, Fagents SA (2013) Modeling lahar behavior and hazards. In: Fagents S, Gregg T, Lopes R (eds) Modeling volcanic processes: the physics and mathematics of volcanism. Cambridge University Press, pp 300–330

Marzocchi W, Woo G (2007) Probabilistic eruption forecasting and the call for an evacuation. Geophys Res. Lett 34:L22310. doi:10.21029/22007GL031922

Marzocchi W, Sandri L, Selva J (2008) BET_EF: a probabilistic tool for long- and short-term eruption forecasting. Bull Volc 70:623–632

Mothes P, Yepes HA, Hall ML, Ramon PA, Steele AL, Ruiz MC (2015) The scientific-community interface over the 15 year eruptive episode of the Tungurahua Volcano, Ecuador. J Appl Volcanol 4:9

Mothes P, Ruiz MC, Viracucha EG, Ramón PA, Hernández S, Hidalgo S, Bernard B, Gaunt EH, Jarrín P, Yépez MA, Espín PA (2017) Geophysical footprints of Cotopaxi's unrest and minor eruptions in 2015: an opportunity to test scientific and community preparedness. Adv Volcanol 1–30

OVSG-IPGP (1999–2013) Bulletin mensuel de l'activité volcanique et sismique de Guadeloupe. Monthly public report, Observatoire Volcanologique et Sismologique de Guadeloupe - Institut de Physique du Globe de Paris, Gourbeyre (ISSN 1622-4523). http://www.ipgp.fr/fr/ovsg/bulletins-mensuels-de-lovsg. Last accessed 11-10-2016

Phillipson G, Sobradelo R, Gottsmann J (2013) Global volcanic unrest in the 21st century: an analysis of the first decade. J Volcanol Geotherm Res 264:183–196

Potter S, Scott B, Jolly G, Neall V, Johnston D (2015) Introducing the volcanic unrest index (VUI): a tool to quantify and communicate the intensity of volcanic unrest. Bull Volcanol 77:1–15

Reid ME (2004) Massive collapse of volcano edifices triggered by hydrothermal pressurization. Geology 32:373–376

Ricci T, Barberi F, Davis MS, Isaia R, Nave R (2013) Volcanic risk perception in the Campi Flegrei area. J Volcanol Geoth Res 254:118–130

Rouwet D, Sandri L, Marzocchi W, Gottsmann J, Selva J, Tonini R, Papale P (2014) Recognizing and tracking volcanic hazards related to non-magmatic unrest: a review. J Appl Volcanol 3:17

Rouwet D, Constantinescu R, Sandri L (2017) Deterministic versus probabilistic volcano monitoring: not “or” but “and”. Adv Volcanol. doi:10.1007/11157_2017_8

Sandri L, Tonini R, Rouwet D, Constantinescu R, Mendoza-Rosas AT, Andrade D, Bernard B (2017) The need to quantify hazard related to non-magmatic unrest: from BET_EF to BET_UNREST. Adv Volcanol. doi:10.1007/11157_2017_11159

Salvage RO, Karl S. Neuberg J (2017) Volcano seismology: detecting unrest in wiggly lines. Adv Volcanol 1–17

Sekiya S, Kikuchi Y (1890) The eruption of Bandai-san. Tokyo Imp Univ Coll Sci J 3:91–172

Sheldrake TE, Sparks RSJ, Cashman KV, Wadge G, Aspinall WP (2016) Similarities and differences in the historical records of lava dome-building volcanoes: Implications for understanding magmatic processes and eruption forecasting. Earth Sci Rev 160:240–263

Siebert L, Cottrell E, Venzke E, Andrews B (2015) Earth's volcanoes and their eruptions: an overview. In: Sigurdsson H et al (eds) The encyclopedia of volcanoes, 2nd edn. Elsevier, Amsterdam. http://dx.doi.org/10.1016/B978-0-12-385938-9.00012-2

Stone J, Barclay J, Simmons P, Cole PD, Loughlin SC, Ramon P, Mothes P (2014) Risk reduction through community-based monitoring: the vigias of Tungurahua. Ecuador. J. Appl. Volcanol. 3:11

Stirling A (2010) Keep it complex. Nature 468:1029–1031

Tazieff H (1980) About the Soufrière of Guadeloupe. J Volcanol Geotherm Res 8:3–6

Venezky D, Newhall C (2007) “WOVODat Design Document; The Schema, Table Descriptions, and Create Table Statements for the Database of Worldwide Volcanic Unrest (WOVODat Version 1.0).” U.S. Geological Survey Open-File Report, 184.

Woo G (2008) Probabilistic criteria for volcano evacuation decisions. Nat Hazards 45(1):87–97

Woo G (2015) Cost-Benefit analysis is volcanic risk. In: Papale P (ed) Volcanic Hazards, Risks and Disasters. Springer, pp 289–300. https://www.elsevier.com/books/volcanic-hazards-risks-and-disasters/papale/978-0-12-396453-3
Wadge G, Isaacs MC (1988) Mapping the volcanic hazards from Soufriere Hills Volcano, Montserrat, West Indies using an image processor. J Geol Soc 145(4):541–551

Wadsworth FB, Vasseur J, Scheu B, Kendrick JE, Lavallée Y, Dingwell DB (2016) Universal scaling of fluid permeability during volcanic welding and sediment diagenesis. Geology 44(3):219–222

Wilkinson E (2015) Beyond the volcanic crisis: co-governance of risk in Montserrat. J Appl Volcanol 4:3

Wilkinson E, Lovell E, Carby B, Barclay J, Robertson REA (2016) The dilemmas of risk sensitive development on a small volcanic island. Resources 5 (2):21. doi:10.3390/resources5020021

Wright TL, Pierson T (1992) Living with volcanoes. No. 1073. US Geologic Survey

Wynne B (1992) Uncertainty and environmental learning: reconceiving science and policy in the preventive paradigm. Glob Environ Change 2:111–127

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

<figure><img src="image_10.png" /></figure>
<figure><img src="image_11.png" /></figure>

# The Role of Laws Within the Governance of Volcanic Risks

R. J. Bretton, J. Gottsmann and R. Christie

## Abstract

The governance of volcanic risks does not take place in a vacuum. In many cultures, volcanic risks are perceived to be susceptible to governance with the objective of achieving their effective mitigation, and have become the responsibility of the institutions and stakeholders of relevant social communities. An array of international, national and local laws dictate governance infrastructures, the roles of duty holders and beneficiaries and the relationships between them (the stakeholders), duties and rights (the stakes) and acceptable standards of safety and wellbeing (the ultimate rewards). Many regional, national and local stakeholders (individuals and entities) have a range of different, yet complementary, roles, duties, rights and powers. Much of this chapter, which has two main sections, represents a summary of a longer paper (Bretton et al. 2015) that addresses legal aspects of the future governance of volcanic risks. After a general introduction to relevant terminology in the first section, the second section describes the significant threat posed by periods of volcanic unrest.

R. J. Bretton (✉) · J. Gottsmann
School of Earth Sciences, University of Bristol,
Wills Memorial Building, Queens Road, BS8 1RJ
Bristol, UK

R. J. Bretton · J. Gottsmann · R. Christie
The Cabot Institute, University of Bristol, Wills
Memorial Building, Queens Road, BS8 1RJ Bristol,
UK

R. Christie
School of Sociology, Politics and International
Studies, University of Bristol, 4 Priory Road, BS8
1TU Bristol, UK
The third section contains a general introduction to the critical concept of risk which lies at the heart of governance and provides a more detailed description of the many roles that national laws play. Reference is also made to international law which has an increasingly important role in the absence of relevant national laws, or when national laws are inadequate, ineffective or unenforced.

Keywords

Hazard · Risk · Risk governance · Legal duties

# 1 Introduction

This chapter describes the ways in which laws create the administrative and functional infrastructures that facilitate the effective mitigation of volcanic risks.

For the sake of brevity and clarity, we draw upon the existing rich discourse on relevant terminology (e.g. Fournier d'Albe 1979; Luhmann 1998, 1992; Power 2007, 2009; UN/ISDR 2009; Smith and Petley 2009; MIAVITA 2012) and adopt a number of brief working definitions.

A ‘hazard’ is an event (defined by risk-related temporal, spatial and other parameters) that may cause adverse effects. It is a complex function being the “probability of any particular area being affected by a destructive volcanic manifestation within a given period of time” (Fournier d’Albe 1979, 321). A ‘volcanic hazard’ is a volcanic scenario (defined by risk-related temporal, spatial and physical parameters) that may cause adverse consequences to people and/or valued assets.

In the early 1970s, definitions of risk identified the product of three separate and distinct elements—‘vulnerability’ on ‘exposure’ to a defined ‘hazard’ (UNESCO 1972). Bankoff et al. (2004) refers to volcanic hazards being one of three variables (hazard, exposure and vulnerability) that are convolved to produce volcanic risks. For the purposes of governance, it may be helpful to quantify each identified exposure in units of both number (i.e. the number of people exposed) and time (given that, by way of

example, non-resident workers may be less exposed than full-time residents and ‘vulnerability’ may be related to length of exposure).<fnref n="1" />

‘Governance’ is a complex concept attracting a multitude of definitions (Walker et al. 2010). Although it “encompasses an array of organisations, practices and ideas” (Rothstein et al. 2012) that change over time, for sake of clarity, we embrace following definition.

Governance is the sum of the many ways individuals and institutions, public and private, manage their common affairs. It is a continuing process through which conflicting or diverse interests may be accommodated and co-operative action may be taken. It includes formal institutions and regimes empowered to enforce compliance, as well as informal arrangements that people and institutions either have agreed to or perceive to be in their interest (Commission on Global Governance 1995, 4).

‘Risk governance’ includes all attempts to manage the three constituent variables of risk including steps to mitigate volcanic hazards (there are very few successful examples of this), reduce the exposure of people, assets etc. and reduce their vulnerability when exposed. This expression is adopted not only as an analytic term to describe stakeholders undertaking mitigation activities but also for ‘normative’ (i.e. evaluative standard) purposes. Risk governance

<footnote n="1">¹The 18th report of the Scientific Advisory Committee on Montserrat Volcanic Activity contains a good example of a risk assessment which adopts this approach. It differentiates between the risks faced by residents in Zone A and those of workers involved in the shipment of sand from Plymouth Jetty.</footnote>
has a set of definable ‘good’ qualities that provide for the effective integration of the key components of how risks are handled by risk stakeholders (Walker et al. 2010; IRGC 2009).

## 2 Geological Background

Active volcanism can involve complex multi-hazard phenomena. Precursory unrest provides, by means of its signals, the monitoring data upon which evidence-based short-term hazard analysis is grounded. However, periods of mild unrest, even if they may not lead to an eruption, can themselves present a range of hazards including earthquakes, ground deformation, hydrothermal changes/eruptions and gas/water chemistry changes. These precursory hazards can create societal risks that can escalate unnecessarily and therefore require very careful management. Unrest periods create, not only uncertainty about what is happening and resulting public alarm, anxiety and speculation, but also demands for information and advice (Johnston et al. 2002).

The evolution of an unrest period will depend upon its underlying causative processes, which can lead to different outcomes in different locations and with different spatial and physical properties (Rouwet et al. 2014; Sobradelo and Marti 2015).

Volcanic hazard communications and risk mitigation decisions rely upon the suitable and sufficient collection, and the correct analysis and interpretation of monitoring data, and the geological record (Newhall and Hoblitt 2002; Sparks et al. 2012; Rouwet et al. 2014). The analysis of monitoring data, which will often be limited in both quantity and quality, is challenging and there are many uncertainties in identifying causes and thereafter anticipating the evolution of unrest and imminent eruption (Sparks et al. 2012; Phillipson et al. 2013; Sobradelo and Marti 2015).

Hazard analysis is difficult and the risk governance stakes are high. Poorly handled unrest periods cause social, economic and political problems, even without an eruption. “Adverse

response may take the form of the release of inappropriate advice, media speculation, unwarranted emergency declarations and premature cessation of economic activity and community services” (Johnston et al. 2002, 228).

## 3 Risk Governance and Roles of Law

The concept of risk as something that can be managed through human intervention is a relatively new one and important because it has become an increasingly pervasive concept in many societies. Risk is also associated with notions of choice, responsibility and blame (OECD 2015).

Risk evolved from its modest origins in the seventeenth century and became in the nineteenth century a principle for the objectification of possible experience—not only of the hazards of personal life and private venture, but also of the common venture of society (Gordon 1991).

By the late nineteenth century, risk had “become central to the rhetoric of regulation”. State regulation of risk emerged as the means by which the state controlled economic activities in Western societies. The traditional objects of state regulation were manufactured risks, most particularly those resulting from scientific and technological innovation within manufacturing processes. The usual style of state regulation was “command and control” by imposing formal, structured and active risk management duties. The state exercised control through the promulgation of primary (i.e. enabling) and secondary (i.e. detailed implementing) laws and policing through specialist inspectorates.

In the twenty first century, regulation is no longer confined to non-natural, human-made risks. Many risks are, in whole or in part, recurring social manifestations (i.e. human-made phenomena) with negative consequences (Lauta 2014). In many cultures, particularly western cultures, they are no longer perceived as the consequences of external forces occurring independently of society and insusceptible to mitigation by society. Accordingly, they are now
positioned within, and have become the respon-
sibility of, the institutions and stakeholders of
relevant social communities (Lauta 2014). These
human-made risks are perceived to be susceptible
to regulation with the objective of achieving their
effective mitigation. By way of illustration, the
population of Naples has greatly increased since
1944 and many would argue that the resulting
increase in volcanic risk exposure is human-
made and capable of regulation.

Low probability-high impact risks pose a particular challenge for legislators. In fact there are three related challenges, namely scientific uncertainty, a low likelihood of occurrence, and significant societal consequences. Whilst the elevated consequences of these risks call for some level of regulation, the intrinsic uncertainty and low probability of their occurrence make it difficult to review the evidentiary scientific jus- tification, to assess costs and benefits, and to identify means by which chosen regulatory goals can be pursued (Simoncini 2013).

In the absence of a tragedy, it is difficult to
measure the performance of law-backed societal
risk governance by the usual measures of:
(1) economy (e.g. value for money) for input and
process; (2) efficiency (e.g. quality delivered on
time) for process and output; and (3) effective-
ness for output and outcome. The indicators of
outcome (the intended and unintended results) of
the integrated governance system will be related
to the impacts on, and the consequences for,
public good, safety, security, health and welfare
but it will be a challenge for any related targets
(e.g. benchmarks and performance standards) to
be SMART—Specific, Measurable, Achievable,
Relevant and Timed (OECD 2002).

By contrast, in a fact-finding process of
scrutiny after a tragedy, the use of SMART tar-
gets may become more practicable. It may be
possible to measure hazard characterisation out-
puts against planned targets for timely delivery,
user-friendliness, outcome-focussed, and
temporal/spatial/intensity forecast accuracy.
Based upon findings of fact, it may be feasible to
quantify the resulting risk-mitigation impact
measured in lives and assets saved.

Notwithstanding these challenges, many
jurisdictions have national laws that attempt to
regulate the management of risks arising from
natural hazards. Many reflect the shift in para-
digm, at both international and national levels,
from focussing on ex-post, reactive response (the
phases of emergency response and post-disaster
longer term recovery) to ex-ante, pro-active risk
management and mitigation (the phase of plan-
ning and preparedness) (UN SC-DRR 2009).

As illustrated in Fig. 1, national laws create
governance infrastructures, duties of care and
duty holders, rights and rights holders, enabling
powers, regulators, enforcement powers, and
lastly scrutiny venues. Each will now to consid-
ered in turn.

## 3.1 The Creation of National Risk Governance Infrastructures

National laws tend to identify, authorise and fund
risk governance bodies (e.g. government
departments and agencies, and public corpora-
tions) and public officials (e.g. individuals such
governors, mayors, prefects and village heads)
within a coherent legal and administrative
framework, in other words, a risk governance
infrastructure. These laws often use and build
upon existing entities within existing adminis-
trative frameworks that have multi-level national,
regional, district, municipal etc. political divi-
sions and subdivisions.

In some jurisdictions, formal legal infrastruc-
tures anticipate and rely upon less formal struc-
tures and relationships at local levels nearer
at-risk communities. For example, in Ecuador,
the risk governance infrastructure relies upon the
engagement and commitment of local represen-
tatives (e.g. chiefs and elders) and volunteers,
such as hazard wardens/monitors, for both hazard
data gathering and risk mitigation.

In some jurisdictions, such as Italy, the laws
favour the imposition of duties upon individuals,
rather than impersonal legal entities such as
government departments/agencies and public
companies. Legal duties may be founded upon an
<figure><img src="image_12.png" /><figcaption>**Fig. 1** The many roles of law in the governance of natural hazards set out in a generalised legal framework</figcaption></figure>

individual having effective decision-making powers and control over financial resources rather than upon an individual holding a particular title or occupying a particular post (Bergman et al. 2007).

These infrastructures can be complex, confusing, fragmented and multi-level. They are often the creations of multiple sets of national primary (enabling) and secondary (detailed implementing) legislation supplemented as necessary by further provisions at ministerial, inter-ministerial, regional, provincial and local levels of government.

Occasionally additional specialised bodies are established (e.g. emergency management agencies, research/monitoring institutes and volcano observatories) with the creation of statutory roles to be filled by appointed individuals.

In a few known jurisdictions (e.g. USA, Canada and the Philippines) laws also regulate to varying degrees the qualification, licensing and registration of geologists and the practice of geology per se.

## 3.2 The Creation of Duty and Rights

National laws allocate to bodies and individuals (duty holders such as volcano observatories and civil protection authorities) high level management functions with responsibilities (duties of care), which are owed to the particular classes of people for whose benefit the duties were created (rights holders).

Since modest beginnings in the 1840's near Vesuvius Italy, the role of over 100 volcano observatories around the world has evolved. Observatories have at least two overlapping roles which involve a synergy of observation and theory. They have been described as 'critical in the volcanic risk reduction cycle'<fnref n="2" /> (Jolly 2015, 302), and employ and/or engage scientists who practice at the hazard-risk interface. The World Organisation of Volcano Observatories (WOVO), a Commission of the International

<footnote n="2">²This cycle includes periods before, during and after periods of volcanic unrest that may or may not lead to an eruption (Jolly 2015, 302).</footnote>
<table><caption>**Table 1.1** Volcano observatories—three contrasting regimes</caption><thead><tr><th></th><th></th></tr></thead><tbody><tr><td><strong>Montserrat—One individual with no powers of delegation</strong></td><td>Section 8 of the Montserrat Volcano Observatory Act 2002 states that the Director of the Observatory shall be responsible for “reporting on the status of the volcanic activity in a regular and timely manner to the appropriate authorities” and “assisting in the dissemination to the public of information concerning the status of volcanic activity”</td></tr><tr><td><strong>Alaska, USA—A group of institutions</strong></td><td>“The Alaska Volcano observatory is a joint programme of the United States Geological Survey (USGS), the Geophysical Institute of the University of Alaska Fairbanks (UAFGI) and the State of Alaska Division of Geological and Geophysical Surveys (ADGGS)” (Jolly 2015, 299)</td></tr><tr><td><strong>New Zealand—One institution under powers of delegation given to one individual</strong></td><td>The Institute of Geological and Nuclear Sciences Limited (or GNS Science) is a Crown research institute created in 1992. The GNS has “sole responsibility for providing volcanic activity warnings and hence provides the function of a volcano observatory” (Jolly 2015, 299) under wide powers of delegation given to the Director of Civil Defence Emergency Management in the Civil Defence Emergency Management Act 2002</td></tr></tbody></table>

Association of Volcanology and Chemistry of the Earth's Interior (IAVCEI), is an organization of and for volcano observatories of the world. WOVO's website notes that its “members are institutions that are engaged in volcano surveillance and, in most cases, are responsible for warning authorities and the public about hazardous volcanic unrest”.

Examples of three contrasting regimes are given in Table 1.1.

In some jurisdictions, general disaster management obligations are also imposed on ‘the community’ (i.e. members of the public) and non-government business entities. At-risk individuals and communities, businesses (such as aeroplane makers and operators within the aviation industry) and insurers have active and critical roles to play in the governance of volcanic risks, however, their roles are not the principal focus of either this chapter or Bretton et al. (2015). The needs and sentiments of all duty and rights holders, who depend upon and use geoscientific knowledge of volcanic hazards, must be identified and reflected carefully and clearly in the roles and interface practices of volcanologists.

During an emerging period of volcanic unrest, the relevant duty holders may change as the defined duties are transferred from one duty holder to another—sometimes as a result of changing hazard or risk characterisations. These duties of care can be framed in a wide variety of ways. They may relate to general health and

safety, not specifying any risk creator (a particular hazard, natural or otherwise) or they may be more specific, identifying a particular hazard (ground uplift, earthquakes etc.).

Rights holders may be given the right to a safe and healthy environment, and to be represented, consulted or engaged in risk decisions and/or given information. Additional rights may be given to certain categories of persons due to special vulnerabilities and/or the influence of social structures and practices. These categories may include women, the very poor, older persons, children and people with disabilities (IFRC 2015).

There are two main types of duty of care, which are called here, respectively, ‘functional’ and ‘goal-setting’. Functional duties dictate the fulfilment of a particular role (e.g. a duty to undertake monitoring, to prepare plans and programmes for emergency preparedness or to provide emergency preparedness communications and warnings). Goal-setting duties require the achievement of an outcome (e.g. a duty to ensure the safety and wellbeing of identified rights holders). Not even within the highly regulated field of occupational health are these safety goals absolute (i.e. unqualified). The imposition of an unrealistic absolute duty would give rights holders a theoretical guarantee of health and safety within a risk-free environment.

As a general rule, ‘qualified’ duties of care are therefore laid down. These duties represent
democratic statements or mandates of ‘accept-
able’ or ‘optimal’ risk after mitigation, and
express a rational trade-off between safety and
risk (Hood and Rothstein 2001; Rothstein 2014).
Rothstein (2014) notes “After all, what is an
acceptable risk other than a euphemistic bound-
ary between an *acceptable* adverse outcome and
an *unacceptable* failure”.

Compliance with qualified duties inevitably
requires duties holders to perform a risk-focussed
cost/benefit analysis and a test of proportionality.
A duty holder wishing to establish that societal
risks have been reduced ‘as low as reasonably
practicable’ has to show that the costs (the sac-
rifice) of further feasible safety measures would
be grossly disproportionate to the additional
safety benefits of those measures (based upon
UK Office for Nuclear Regulation 2013).

Laws rarely, if ever, attempt to dictate, in
either general or more detailed terms, the societal
risk management arrangements that will be
required to either fulfil a functional role or
achieve a stated safety outcome. In practice, an
assessment of societal vulnerability has two main
stages. Firstly, the nature and scope of duties of
care must be identified and delineated. This is
essentially a matter of law and involves the legal
interpretation of primary and secondary legisla-
tion and, if relevant, case law. Secondly, it is
necessary to identify the actions that the duty
holder should take to fulfil those duties. This is
far more difficult. Competent lawyers can
describe the safety function or outcome required
in law—in football terms the dimensions and
position of the goal. However, they can offer
very limited guidance regarding the practical
measures that the competent societal risk man-
ager will need to take to achieve legal compli-
ance (i.e. how to actually get the ball over the
goal line).

In the case of food standards and occupational
health and safety standards, it is common for
national laws to set up government agencies to
carry out research, to set performance standards
and offer approved codes of practice or authori-
tative guidance. By contrast, in respect of vol-
canic hazards, at both the international and
national levels, there appear to be neither:

(1) law-based performance standards offering
guidance to societal risk managers; or (2) law
endorsed self-regulatory regimes such as those
that frequented the early stages of food
regulation.

Within the ‘goal-setting’ legislative approach,
referred to above, it is implicit that there is an
obligation on duties holders to establish the
nature and suitability (i.e. the legal adequacy) of
their societal risk management arrangements.
This difficult justification will usually be done
post-facto, in other words, only after the risk
outcome (perhaps a disaster properly so-called) is
known and legal consequences are already being
considered (Simoncini 2011). The justification
will cover, but not be limited to, the arrange-
ments that were necessary for the planning,
organisation, control, monitoring and review of
societal risk mitigation measures. To complete
the authors’ footballing analogy, post-facto legal
processes are analogous to slow motion TV
replays, in full view of partisan onlookers and
experts with hindsight. They determine what has
happened, whether or not a goal has been scored
and, if not, why not and what effect any missed
goal had on the final score (i.e. whether legal
compliance has actually been achieved and, if
not, why not and what the consequences should
have been if compliance had been achieved).

‘Standard equivocality’, which is the absence
of commonly recognised standards (norms), is
likely to exist in the absence of clear ‘legal’
requirements, approved codes of practice or
guidance. The resulting challenges faced by duty
holders are: (1) to find or design authoritative
standards or benchmarks to steer their societal
risk management arrangements; and thereby
(2) to increase their chances of fulfilling their
societal risk duties of care and achieving legal
compliance; and thereby (3) to minimise their
vulnerability to managerial risks.

Rothstein (2002) and Hood (1986) have noted
that, in the absence of commonly agreed and
practical principles or methodologies by which
compliance can be measured ('standard-
unequivocality'), process compliance is difficult
to monitor and enforce. Other obstacles to moni-
toring, surveillance and enforcement include
inherent scientific uncertainty, a dynamic state of scientific knowledge, a lack of expertise within regulatory agencies, and often complex and fragmented multi-level infrastructures. Donovan and Oppenheimer (2014) note complexities in governmental structures presented major challenges to managing volcanic eruptions in Montserrat. Recent crises including the 2010 Icelandic Eyjafjallajökull eruption have highlighted the difficulty of co-ordinating and synthesising scientific input from many different disciplines and institutions and translating these into useful policy advice at very short notice (OECD 2015).

## 3.3 The Creation of Powers

National laws have traditionally granted defined ‘authorities’ to government duty holders backed by administration, protection and intervention powers (ordinary, extraordinary and emergency). Governance, with an emphasis more on control than protection, has often been achieved by the exercise of authority using linear “coercion and enforcement” (Walker et al. 2010).

## 3.4 The Creation of Regulators, Enforcement Powers and Scrutiny Venues

Laws often establish, resource and empower regulators to monitor the performance of duty holders and to take enforcement actions, including prosecutions, against them if necessary. Examples of regulators include the Labour Standards Agency in Japan, the Department of Labour Health and Safety Service in New Zealand and the Occupational Safety and Health Agency in the United States of America. These regulators often have very wide powers similar to, and sometimes exceeding, those of police forces. They include the power to enter premises, to investigate and inspect, to acquire and preserve evidence and to serve notices.

Laws provide the formal scrutiny venues (courts, tribunals etc.) and related procedures for: (1) the ex-ante pro-active enforcement of duties

of care by regulators, generally health and safety agencies; and (2) the ex-post facto reactive scrutiny of events, the identification of duty holders, the assessment of what happened and what should have happened and, if appropriate, the imposition of sanctions and/or the granting of remedies. The latter procedures are required at a national level to comply with the international law ex-post facto obligations which are now considered.

## 3.5 The Role of International Law

In the absence of relevant national laws, or when national laws are inadequate, ineffective or unenforced, there is room for the intervention of international law. The European Court of Human Rights (ECHR) has taken the lead and it is suggested here that in time the Inter-American Court of Human Rights will follow. The European Convention of Human Rights (EConHR) lays down a positive obligation on States to take appropriate steps to safeguard the lives of citizens within their jurisdiction. Article 2(1) EConHR provides that “Everyone’s right to life shall be protected by law. No one shall be deprived of his life intentionally save in the execution of a sentence of a court following his conviction of a crime for which this penalty is provided by law.”

In the context of the management of natural hazards, the most important case involving Article 2 arose in 2008. Budayeva and others v Russia (2008) ECHR 15339/02 concerned a mudslide. In this case, the EHCR considered principles that had been applied in Oneryildiz v Turkey (2004) to a human-made hazard—an industrial risk or dangerous activity such as the operation of a waste site. They were subsequently adopted in Kolyadenko and others v Russia (2012) in respect of natural flash floods.

<footnote>Budayeva and others v Russia</footnote>

<footnote>The town of T was situated in a mountain district. Two tributaries passed through it and were known to have associated mudslides. A mud collector and a dam were constructed in order to protect T. The dam was seriously damaged by a mud and debris</footnote>
flow in August 1999, so funds were requested to construct observation posts to warn of mudslides until it could be repaired, and to carry out certain emergency works to the dam.

Those measures were never implemented. A number of mudslides occurred in July 2000, killing eight residents, including the first applicant's husband, and destroying the applicants' homes.

It was decided to dispense with a criminal investigation into the circumstances of the death of the first applicant's husband, and claims of compensation by the first applicant and others were refused on the basis that a mudslide of such exceptional force could neither have been predicted nor stopped. However, the applicants were granted substitute housing and a lump-sum emergency allowance.

The applicants complained to the ECHR, inter alia, that the authorities had violated the substantive limb of Article 2 of the EConHR. The first applicant asserted that the authorities were responsible for the death of her husband and she and the other applicants asserted that the authorities had failed to take appropriate measures to mitigate the risks to their lives posed by natural hazards.

The Court concluded that the relevant authorities were aware of the mudslides (the hazards) and their capacity to cause devastating consequences (the risks). There was no ambiguity about the scope and timing of the work that needed to be performed (the risk mitigation actions). After 1999, risk mitigation was not given proper consideration by the decision makers and budgetary bodies (the duty holders) and there was no functioning early warning system. State responsibility for the deaths had never been investigated. Each applicant was awarded compensation.

The EHCR determined that the obligation in Article 2 entails, above all, a primary duty on the State to put in place a clear legislative and administrative framework designed to provide effective deterrence against threats to the right to life. This applies in the context of any activity, whether public or not, in which the right to life may be at stake and extends not only to industrial risks and dangerous activities but also to actions and omissions to control natural hazards.

In the cases of Oneryildiz v Turkey (2004), Budayeva v Russia (2008), and Kolyadenko v Russia (2012), the EHCR determined that there is a positive obligation: (1) ex-ante to take substantive regulatory measures to manage risks; and (2) ex-post facto to ensure that any risk eventuated fatalities are followed by a public

investigation. In relation to the latter, procedures must exist for identifying not only shortcomings in the ex-ante regulatory measures but also any errors committed by those responsible (i.e. duty holders). If there are any shortcomings and the infringement of the right to life was not intentional, it is not necessary for criminal proceedings to be brought in every case. It may satisfactory to make available to the victims civil law remedies (either alone or in conjunction with a criminal law remedy), enabling any responsibility of the parties concerned to be established and any appropriate civil redress, such as an order for the payment of damages, to be obtained.

The positive obligations of EConHR State duty holders under the ECHR are summarised in Fig. 2.

## 3.6 The Role of International Institutions and Agencies

In March 2015, the International Federation of Red Cross and Red Crescent Societies (IFRC) and the United Nations (UN) Development Programme issued the pilot version of “The checklist on law and disaster risk reduction”. It encourages accountability mechanisms within legislation to address failures to fulfil risk governance responsibilities. In particular it advocates laws: (1) to establish public reporting or parliamentary oversight mechanisms and transparency requirements for government entities tasked with risk governance responsibilities; (2) to give a mandated role to the judiciary in enhancing accountability; (3) to provide enforceable incentives for compliance and disincentives for non-compliance; and (4) to establish legal and/or administrative sanctions (as appropriate) for public officials, individuals and businesses for a gross (“particularly egregious”) failure to fulfil their duties (IFRC 2015, 16).

The prioritisation of mitigation before response and recovery was recognised within the Sendai Framework for Disaster Risk Reduction 2015–2020 (the Sendai Framework) which
<figure><img src="image_13.png" /><figcaption>**Fig. 2** The obligations of EConHR ‘States’ to manage natural hazards</figcaption></figure>

emerged from the United Nations 3rd World Conference on Disaster Risk Reduction (UN/ISDR 2015). It is suggested here that one inevitable effect of the Sendai Framework will be to enhance the importance of not only the collection and interpretation of monitoring data but also the better characterisation of unrest periods. For the reasons stated in Sect. 2, periods of volcanic unrest, even if they do not lead to an eruption, present multiple hazards and risks which require very careful assessment and mitigation.

## 4 Conclusions

In many cultures, volcanic risks are perceived to be susceptible to governance and have become the responsibility of the institutions and stakeholders of relevant social communities.

Laws create the stakeholders, the stakes and the standards of risk governance. Without

national laws, supplemented by international laws and initiatives, few countries would have the complex administrative infrastructures necessary for the mitigation of volcanic risks.

Although emergency response may still dominate thinking and funding in some jurisdictions, national laws are unlikely to diminish in number and/or reach in the light of the emerging international law governance norms, the IFRC/UN law checklist and the Sendai Framework.

## References

* Bankoff G, Frerks G, Hilhorst D (2004) Mapping vulnerability – disasters, development & people. Earthscan, London and New York

* Bergman D, Davis C, Rigby B (2007) International comparison of health and safety responsibilities of company directors. HSE research report RR 53, 207. http://www.hse.gov.uk/leadership/international.pdf
Bretton RJ, Gottsmann J, Aspinall WP, Christie R (2015) Implications of legal scrutiny processes (including the L'Aquila trial and other recent court cases) for future volcanic risk governance. J Appl Volcanol 4:18. https://doi.org/10.1186/s13617-015-0034-x

Commission on Global Governance (1995) Our global
neighbourhood. Oxford University Press, Oxford

Donovan A, Oppenheimer C (2014) Science, policy and place in volcanic disasters: insights from Montserrat. Environ Sci Policy 38:150-161 (May)

Fournier d'Ibe EM (1979) Objectives of volcanic monitoring and prediction. J Geol Soc136:321-326. doi: https://doi.org/10.1144/gsjgs.136.3.0321

Gordon C (1991) Governmental rationality: an introduction. In Burchell G, Gordon C, Miller P (eds) The foucault effect: studies in Governmentality. Harvester Wheatsheaf, Hemel Hempstead, pp 1-52

Hood C (1986) Administrative analysis: an introduction to rules, enforcement and organisations. Wheatsheaf Books, Sussex

Hood C, Rothstein H (2001) Risk regulation under pressure: problem solving or blame shifting? Adm Soc 33(1):21-53

International Federation of Red Cross, Red Crescent Societies (IFRC) and United Nations Development Programme (2015) The checklist on law and disaster risk reduction, Pilot version, March 2015. IFRC, Geneva, Switzerland. http://www.ifrc.org/PageFiles/115542/The-checklist-on-law-and-drr.pdf

International Risk Governance Council (IRGC) (2009) What is risk governance? www.irgc.org

Jolly G (2015) The role of volcano observatories in risk reduction. In: Loughlin SC, Sparks RSJ, Brown SK, Jenkins SF, Vye-Brown C (eds) Global volcanic hazards and risk. Cambridge University Press, Cambridge

Johnston D, Scott B, Houghton B, Paton D, Dowrick D, Villamor P, Savage J (2002) Social and economic consequences of historic caldera unrest at the Taupo volcano, New Zealand and the management of future episodes of unrest. Bull New Zealand Soc Earthquake Eng 35(4):215-229

Lauta KC (2014) Disaster law. Routledge, Oxford and New York

Luhmann N (1998) Observations on modernity. Stanford University Press, Stanford, CA

Luhmann N (1992) Risk: a sociology theory. de Gruyter, Berlin

MIAVITA (2012) Handbook for volcanic risk management: prevention, crisis management and resilience. MIAVITA team, Orleans

Newhall CG, Hoblitt RP (2002) Constructing event trees for volcanic crises. Bull Volcanol 64:3-20

OECD (Organisation for Economic Co-operation and Development) (2002) Outcome focussed management in the United Kingdom by Ellis K, Mitchell S. OECD Publications, Paris, France

OECD (2015) "Scientific advice for policy making: the role and responsibility of expert bodies and individual scientists", OECD science, technology and industry

policy papers, no 21, OECD Publishing, Paris. http://dx.doi.org/10.1787/5js33ljcpwb-en

Phillipson G, Sobradelo R, Gottsmann J (2013) Global volcanic unrest in the 21st century: an analysis of the first decade. J Volcanol Geoth Res 264(2013):183-196

Power M (2007) Organised uncertainty: designing a world of risk management. Oxford University Press, Oxford

Power M (2009) The risk management of nothing. Acc, Organ Soc 34(2009):849-855

Rothstein H (2002) Neglected risk regulation: the institutional attenuation problem, centre for analysis of risk and regulation. London School of Economics and Political Science, London

Rothstein H (2014) Exploring national cultures of risk governance accessed via http://www.lse.ac.uk/researchAndExpertise/units/CARR/publications/CARRmagR&R25-Rothstein.pdf

Rothstein H, Borraz O, Huber M (2012) Risk and the limits of governance: exploring varied patterns of risk-based governance across. Europe Regul Gov 1-21 http://doi.org/10.111/j.1748-5991.2012.01153.x

Rouwet D, Sandri L, Marzocchi W, Gottsmann J, Selva J, Tonini R, Papale P (2014) Recognizing and tracking volcanic hazards related to non-magmatic unrest: a review. J Appl Volcanol 3(1):17. https://doi.org/10.1186/s13617-014-0017-3

Simoncini M (2011) Regulating catastrophic risks by standards. EJRR (1):37-50

Simoncini M (2013) Governing air traffic management in the single European sky: the search for possible solutions to safety issues. Eur Law Rev Issue 2 (2013):209-228

Smith K, Petley DN (2009) Environmental hazards: assessing risk and reducing disaster. Routledge, London and New York

Sobradelo R, Martí J (2015) Short-term volcanic hazard assessment through Bayesian inference: retrospective application to the Pinatubo 1991 volcanic unrest. J Volcanol Geoth Res 290(2015):1-11

Sparks RSJ, Aspinall WP, Auker M, Crosweller S, Hincks T, Mahony S, Nadim F, Polley J, Syre E (2012) Mapping and characterising volcanic risk, magmatic rifting and active volcanism conference, Addis Ababa, 12 Jan 2012

United Kingdom Office for Nuclear Regulation (2013) Guidance for the demonstration of ALARP (As Low As Reasonably Practicable) NS-TAST-GD-005 Revision 6

United Nations Educational, Scientific and Cultural Organization (UNESCO) (1972) Report of consultative meeting of experts on the statistical study of natural hazards and their consequences Document SC/WS/500 11pp, Paris, France

United Nations Development Programme Safer Communities through Disaster Risk Reduction in Development Programme SC-DRR (2009) Lessons learned: disaster management legal reform—The Indonesian experience UND-, Jakarta, Indonesia
UN/ISDR (2009) Terminology on disaster risk reduction.
Switzerland, Geneva

UN/ISDR (2015) Sendai framework for disaster risk reduction 2015-30

## Legal Authorities and Case Law

Budayeva, others v Russia (2008) Applications 15339/02, 21166/02, 20058/02, 11673 & 15343/02, judgment of 20 March 2008, ECHR 15339/02

Walker G, Whittle R, Medd W, Watson N (2010) Risk governance and natural hazards, Cap Haz-Net WP2 Report, Lancaster Environment Centre, Lancaster University, Lancaster. http://caphaz-net.org/outcomess-results

Kolyadenko, others v Russia (2012) Applications 17423/05, 20534/05, 20678/05, 23263/05, 24283/05, 35673/05, ECHR 17423/05

Oneryildiz v Turkey (2004) Application 48939/99 18 BHRC 145, 41 EHRR 20

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
<figure><img src="image_14.png" /></figure>

# Deterministic Versus Probabilistic Volcano Monitoring: Not “or” But “and”

D. Rouwet, R. Constantinescu and L. Sandri

## Abstract

Volcanic eruption forecasting and hazard assessment are multi-disciplinary processes with scientific and social implications. Our limited knowledge and the randomness of the processes behind a volcanic eruption yield the need to quantify uncertainties on volcano dynamics. With deterministic and probabilistic methods for volcanic hazard assessment not always being in agreement, we propose a combined approach that bridges the two schools of thoughts in order to improve future volcano monitoring. Expert elicitation has proven to be an effective way to bind deterministic research within a probabilistic framework aiming to reduce the uncertainties related to any hazard forecast; yet, numerous exercises based on expert elicitation have revealed that the attempt to reduce uncertainties led to the creation of new ones, often unquantifiable, created by human nature and reasoning during stressful situations. Such reasoning ignores the complexity of volcanic processes and the fact that every scenario has a probability to occur. The recent probabilistic methods and tools marry probabilistic and deterministic approaches and lead to unprecedented models. Nevertheless, probabilistic hazard assessment is often misunderstood as not all of the researchers involved have backgrounds in such matters. A probabilistic method cannot stand-alone

<footnote>D. Rouwet (✉) · L. Sandri
Istituto Nazionale di Geofisica e Vulcanologia,
Sezioni di Bologna, Bologna, Italy
e-mail: dmitrirouwet@gmail.com; dmitri.
rouwet@ingv.it</footnote>

<footnote>R. Constantinescu
Seismic Research Centre, University of West Indies,
Saint Augustine, Trinidad and Tobago</footnote>

<footnote>*Present Address*:
R. Constantinescu
School of Geosciences, University of South Florida,
4202 E. Fowler Avenue, NES 107, Tampa, FL
33620-5550, USA</footnote>
as it depends on data input obtained by deterministic approaches. We propose that, given the symbiotic relationship between the two methods, a probabilistic framework can play a role of moderator between various deterministic disciplines, thus creating a coherent environment for discussion and debate among seismologists, geodesists, geochemists. This can be achieved by training all scientists involved in hazard assessment, probability theory and data interpretation, while at least one group member objectively uses the information provided to produce the probabilities. Hence, numerical outcomes can be interpreted transparently as they represent the quantification of experts' knowledge and related uncertainties. A probabilistic method that incorporates the joint opinions of a group of multi-disciplinary researchers facilitates a more straightforward way of communicating scientific information to decision-makers.

## Resumen extendido

La previsión de erupciones volcánicas y la evaluación del peligro son procesos multidisciplinarios, con implicaciones tanto científicas como sociales. Nuestro conocimiento limitado de los procesos detrás de una erupción volcánica y su aleatoriedad genera la necesidad de cuantificar las incertidumbres sobre las dinámicas del volcán y de mejorar la política de la toma de decisiones durante una crisis volcánica. Sabiendo que existe un desacuerdo sobre el uso de métodos determinísticos o probabilísticos durante la evaluación de la peligrosidad volcánica, revisamos ambos métodos y proponemos un enfoque que sirve como puente entre las dos escuelas de pensamiento y que pueda mejorar las capacidades de monitoreo volcánico en el futuro, hacia el reconocimiento en tiempo de manifestaciones volcánicas y amenazas relacionadas. La elicitación de expertos resulta ser una manera efectiva para relacionar la investigación determinística con el marco probabilístico para poder reducir la incertidumbre relacionada a cualquier intento de previsión de erupción; sin embargo, numerosos ejercicios basados en elicitaciones de expertos revelaron el hecho que este intento de reducir la incertidumbre creó nuevas incertidumbres, a menudo imposible de cuantificar, siendo generada por la naturaleza del pensamiento humano durante situaciones de estrés. El proceso general es sujeto a la personalidad de un/a investigador/a o un grupo de investigadores y sus ideas basadas en su experiencia. Esta manera de pensar interfiere con la complejidad intrínseca de los procesos volcánicos y con el hecho que cada escenario tiene una probabilidad de ocurrencia. Los métodos e instrumentos probabilísticos recientes juntaron los investigadores probabilísticos y determinísticos lo que resultó en modelos e interpretaciones de información sobre volcanes sin precedentes. Sin embargo, la novedad de la evaluación probabilística de peligrosidad es, a menudo, incomprendida debido al hecho que no todos los investigadores involucrados tienen una formación en estas materias teóricas. El método probabilístico no puede existir autónomamente ya que depende de datos de entrada obtenido a través de los estudios determinísticos. Proponemos que, dada la relación simbiótica entre ambos métodos, un marco probabilístico puede jugar el papel como moderador
entre las varias disciplinas deterministas, creando un ambiente coherente para discusiones y debates entre científicos (e.g., sismólogos, geodetas, geoquímicos). Este se puede obtener por medio de entrenamiento de todos los científicos involucrados en el monitoreo volcánico en la teoría probabilística y la interpretación de datos, mientras que al menos un miembro del grupo utiliza de manera objetiva la información disponible para producir las probabilidades numéricas. Así, los resultados numéricos pueden ser interpretados sin duda alguna, ya que representan la cuantificación del conocimiento de los expertos y las incertidumbres relacionadas. Un método probabilístico que incorpora las opiniones conjuntas de un grupo de investigadores multidisciplinarios facilitará una manera más transparente de comunicación de la información científica hacia las autoridades civiles, así mejorando (1) el proceso de toma de decisiones durante una crisis y la mitigación a largo plazo, y (2) el estado de medidas de preparación que incorpora los varios aspectos sociales. En el futuro, los reportes de previsiones emitidos por los científicos deberían incluir los resultados numéricos de los modelos probabilísticos; la arquitectura de monitoreo se debería expander más allá del arreglo clásico “sismo-deformación-gas” hacia un arreglo “sismo-deformación-gas-probabilidad”. Este capítulo de opinión pretende proponer una ideología posible, con el máximo respeto para el volcán, la sociedad, los científicos individuales o los grupos de científicos, y para las autoridades que toman las decisiones, con un objetivo común: mejorar la previsión de amenazas relacionadas a los volcanes para proteger la sociedad.

**Keywords**

Volcano monitoring • Probabilistic hazard assessment • Deterministic research • Bridging and symbiosis • Best practice scheme

**Palabras clave**

Monitoreo volcánico • Evaluación probabilística de amenaza • Investigación determinística • Puente y simbiosis • Esquema de mejor práctica

# 1 Introduction

Volcanoes are intrinsically complex and unpredictable systems manifesting non-linear behaviour in space and time, on the long- and short-term. Understanding how volcanoes evolve with time through the various stages of activity—from quiescence through unrest to eruption—is highly challenging. Awareness of these facts is a basic requisite when working with/on volcanoes. A major goal in volcanology is quantifying uncertainties on volcano dynamics, and learning how to

translate these to decision makers and, occasionally, to the population. The combination of social implications and forecasting future behaviour of complex natural systems makes volcanology a rather unique but “tricky business”. Besides the need to quantify uncertainties and better understand our limited knowledge on volcanoes it is necessary to legally protect volcanologists when exporting their knowledge outside their protected professional community (Bretton et al. 2015).

During the past 40–50 years, volcano monitoring and eruption forecasting during volcanic
crises has been largely dominated by the deter-
ministic approach (Sparks 2003, i.e. most likely
scenarios). Experts with different research back-
grounds track changes in “their” parameters
related to volcanic activity, afterwards discussed
in “protected” round tables, generally behind
locked doors, to eventually come up with a single
voice. This single voice does not and should not
reflect possible internal conflicts or disagree-
ments behind the closed door. Such disagreement
is an often-unstated expression of the uncertainty
due to our lack of knowledge on volcanic pro-
cesses, and the possible unavailability of data
(i.e. epistemic uncertainty) and due to the
intrinsic randomness of the volcanic process
studied (i.e. aleatory uncertainty). The power of
the single voice from the group of experts often
misleads the receivers of the message (decision
makers, authorities or lay public), believing the
experts are “sure” on the evolution of volcanic
activity. This is one of the reasons why volca-
nologists are often, correctly or incorrectly,
highly trusted professionals by the public (Hay-
nes et al. 2008; Donovan et al. 2011).

During the last decade, this “untouchable
aura” around volcano monitoring based on
deterministic research has vanished with the
introduction of probabilistic hazard and eruption
forecasting (e.g., Newhall and Hoblitt 2002;
Sparks 2003; Marzocchi et al. 2004, 2008;
Sparks and Aspinall 2004; Marzocchi and Beb-
bington 2012; Sobradelo et al. 2014; Sobradelo
and Marti 2015). A recent chapter by Newhall
and Pallister (2015) starts from the same false
dichotomy, aiming to spouse the deterministic
and probabilistic points of view in the highly
applicable method of “Multiple Data Sets”.

Marzocchi and Woo (2007) propose a rational
on decision-making based on the hazard/risk
separation principal, using a cost-benefit analyses
as the guiding tool.

Among the methods for probabilistic hazard
assessment and eruption forecasting, many are
based on a Bayesian approach (e.g., Marzocchi
et al. 2004, 2008; Sobradelo et al. 2014; Sobra-
delo and Marti 2015), that allows describing the
probability of interest not as a single numerical
value, but as a probability distribution. In this

view, the probability of an eruption occurring, or
of a given hazardous event hitting a target area, is
described both by a best-evaluation value (for
example the mean or the median of the proba-
bility distribution), and by a dispersion around
such value (represented by standard deviations or
by a confidence interval). These two quantities
can be directly related to two different sources of
uncertainty: the aleatory one and the epistemic
one. In this way, Bayesian approaches allows
quantifying also to what extent our probabilistic
assessments are constrained by data and knowl-
edge. In other words, now we know, as a group
of volcano-experts, to which degree we can be
wrong in our forecasts behind the closed doors.
This black-on-white awareness brought to light
by probability density functions has led to some
key questions, from the in- and outside worlds:
(1) are we, as volcano-experts, replaceable by a
numerical approach?, and (2) we thought you,
volcanologists, knew what was happening, but it
seems you don't know.

This chapter critically reviews both “philoso-
phies” of eruption forecasting and tracking of
volcanic unrest and related hazards, in search of a
combined approach that could become a guide-
line for future volcanic surveillance architectures.
But we still need bridges between two schools
(deterministic and probabilistic) apparently
speaking a different language. Remember that
both methodologies aim for the same goal: the
timely recognition when volcanoes become
hazardous in their various ways of expressions.
This is our common professional and social
responsibility as volcanologists.

## 2 Forecasts based on Deterministic Research

The goal of volcano monitoring based on deter-
ministic research is to link temporal variations of
physical-chemical parameters with variations in
the state of unrest of the physical object volcano
(i.e. unrest, magmatic unrest, non-magmatic
unrest, eruption, hazard; Rouwet et al. 2014).
Every volcanic eruption is intrinsically preceded
by magma rise towards the surface. The major
aim in eruption forecasting is the quick recognition of such magma rise by changes in the physical parameters (deformation, seismicity) and chemical parameters. The most direct way to do so is to determine how, where, when and why the physical object “volcano” responds to magma rise.

Despite the straight-to-goal approach, large uncertainties exist: (1) a volcano remains a complex system (aleatory uncertainty), and (2) our knowledge on the volcano remains limited (epistemic uncertainty). How do we know if we have detected all the signals the volcano eventually releases? Which of these signals are we considering in our forecast framework, and why? Sometimes we may dismiss some signals as being not pertinent, or simply because we are unable to correlate them either with our ‘understanding’, or with the rest of the signals. Some ‘signals’ are considered as stand-alone, at the moment they occur, others are considered within a time evolution.

The quality of the forecast largely depends on the interpretation of the signals and the hypothesis/model of future activity developed as a result of this assumed scientific stringency. The latter is related to the experience and expertise of the deterministic researcher, or better, on how the experience and expertise is perceived by individual researchers or groups, decision makers and the researcher her/himself. It is known that the most informative and valid opinion may not always be that of the most respected or distinguished professional (Selva et al. 2012).

A big advantage in volcano monitoring based on deterministic research is the fact that, if independent monitoring approaches (e.g., geochemistry vs. geophysics) point toward a similar hypothesis on future hazard in time and space, the future scenario will become more likely. Finding a larger number of arguments in favour of certain scenarios is surely an efficient way to decipher volcanic unrest.

The timescale of the forecast is highly ambiguous and based on the limited knowledge on how the volcano (or analogue volcanoes) behaved in the past within the desired time-scale. Sometimes all the ‘signals’ converge towards an

obvious conclusion, yet, there are numerous cases in which activity stopped or pulled back, sometimes for years before an actual eruption. So, the deterministic approach, which is based mostly on a recurrence interval and ‘experience’ of the volcanologist, is limited in providing a sound time scale for the evolution of the ‘activity’, and hence, for a forecast. In deterministic monitoring the “time” concept is not unambiguously defined, can be case dependent or even change within the evolution of an unrest phase. Fortunately, with converging signals through time, the monitoring time window often becomes narrower when building up towards increased unrest or eruption, although the exact time window cannot be rigorously chosen.

Besides the instrumental accuracies (detection limits, analytical errors, data quality), the uncertainty of the forecast cannot be quantified before an eruption. The only way to decrease this “unquantifiable” uncertainty is by increasing our knowledge on volcanoes, be it the specific volcano in unrest or any volcano that has shown similar behaviour in the past. The current development of methods to increase the quality (e.g., novel approaches, numerical modelling) and quantity of data (increase frequency, e.g., by remote sensing and real-time transmission) will undoubtedly help to achieve better insights into volcanic systems.

## 3 Probabilistic Forecasts

Probabilistic methods and tools for both short- and long-term time windows are more and more in the spotlight (Marzocchi et al. 2008; Sandri et al. 2009, 2012, 2014; Lindsay et al. 2010; Selva et al. 2010, 2011, 2012; Sobradelo et al. 2014; Sobradelo and Marti 2015; Bartolini et al. 2013; Becerril et al. 2014). A key review on probabilistic volcano monitoring can be found in Marzocchi and Bebbington (2012).

Within this opinion chapter, we highlight some critical aspects of the probabilistic forecasting method, without entering in the technical and operational details (see Tonini et al. 2016 and Sandri et al. 2017 for further reading).
A probabilistic forecast can provide a global but clear, numerical view of the opinion of, generally, a group of people, based on the volcanic history and knowledge of the volcano. Lately, probabilistic forecasts are more and more applied in real crisis situations. Thus far, the efficiency or accuracy have hardly been evaluated, probably due to the fact that only recently we are reaching statistically relevant numbers of cases to test this critical issue (Newhall and Pallister 2015). Once high numbers of applications are reached, the numerical outcomes of probabilistic methods can even be considered to support long-term hazard analyses, by becoming input information itself.

In practice, probabilistic hazard assessment and eruption forecasting frameworks constructed on the Event-Tree methodology (Newhall and Hoblitt 2002; Newhall and Pallister 2015) rely on a dataset of information about the past activity of a volcano (i.e. past data), theoretical/ mathematical models (i.e. prior data) and a ser- ies of monitoring signals (i.e. parameters) that allow us to track the changes in the system with time (Marzocchi et al. 2008; Sobradelo et al. 2014). This information allows us to compute the probabilities of a specific hazardous outcome. As any such application reveals, the quality of the numerical output depends on the quality and quantity of the input. The risk exists that using a dataset for long-term probabilistic assessment will introduce an uncertainty, since the operators are often biased by the hypothesis or model coming forth of the dataset. Data should hence be considered “just” facts. In both deterministic and probabilistic hazard assessment, volcanologists rely on information about past eruptions: erup- tive behaviour, eruption frequency, and eruption style. Such catalogues of information are inevi- tably incomplete. For instance, traces of smaller scale events could have been literally eroded away from the geological record, buried or masked by larger events and, hence, relics of precursory activity cannot be deduced. Conse- quently, one should limit the part of the cata- logue used, for the period and specific kind of event you desire to forecast, for which it is rea- sonably complete. As such, the foundation of a probabilistic framework represents a source of

intrinsic uncertainty, that can somehow be overcome by quite robust methods for estimating completeness of sections of catalogues (Moran et al. 2011). The most intuitive solution, simply choosing a smaller dataset, usually representing the most recent years/centuries of a volcano’s activity reduces this uncertainty. But this choice alone will be reflected in the quality of the probabilistic assessment. The unknowns of the data catalogue represent the uncertainty in a probabilistic framework, thus forcing volcanol- ogists to ‘select’ how far to track back in time, and which information to use. In other words, we select e.g., only the last 300 years of activity of a volcano just simply because we believe to be more certain on what happened, instead of choosing the last 2000 years. What is the real scientific control of these choices? We cannot say with an acceptable certainty that a volcano will behave like it did in the last 300 or 2000 years. Indeed, with the recent probabilistic methods we are able to quantify the uncertainty of such choices but we are yet to find a sound scientific mechanism that allows us to make objective decisions regarding the data set. After all, the end goal of eruption forecasting is to give a prediction by analysing signals from an extre- mely complex system governed by a large degree of freedom.

Another aspect to tackle is the use of moni- toring information, especially for short-term forecasts. Asking for numerical thresholds for monitoring parameters at the various nodes of event tree structures is intrinsically wrong, as a numerical threshold is an expression of certainty on something we cannot be certain about. For this, volcanologists use monitoring parameters in order to detect anomalies with respect to the volcano’s background activity to be able to track their evolution with time. Moreover, from the beginning, we rely on a subjective choice when we define the unrest, unrest being commonly agreed upon as a state of elevated activity above background that causes concern (Phillipson et al. 2013). This cause of concern, expressed in numerical thresholds is a subjective choice: experts involved in volcano monitoring usually decide thresholds above/below which the
volcano is considered in unrest. But is a volcano really in unrest simply because we observe one day an anomaly in one of the parameters? And if so, how is the choice of a threshold scientifically sound, since most of the time it is based on the “expert’s experience”? Of course, expert’s experience should not be dismissed and never replaced by computer codes, but indeed, such a choice is associated with a large uncertainty that is extremely difficult to quantify. Even the act of reducing the uncertainty of such a choice relies on corroboration with information from other sources (e.g., analogue volcanoes) that is again subjective itself.

The “fuzzy-threshold approach” (upper and lower thresholds) somehow resolves this problem, as it tracks the degree of anomaly, emphasising from a state in which the volcano is ‘not causing concern’ to one ‘causing a degree of concern’. Thresholds can be case-dependent and are therefore in most cases themselves biased. Especially in the case of poorly monitored volcanoes, or of volcanoes without a monitored stage of unrest (e.g., towards higher nodes in the event tree), Boolean (Y/N) parameters are highly preferable.

During an unrest crisis it might be tempting to adapt the numerical values of the thresholds, when e.g., the previous threshold is exceeded while the volcano does not “react on this parameter” as we thought it would have. Nevertheless, once thresholds for parameters are fixed, they should not be modified, in order to track the time evolution of probabilities (and related uncertainties).

# 4 Recommendations: Not “or” But “and”

## 4.1 Expert Elicitation: A Solution?

In general, any choice made by an expert panel regarding when a volcano enters a phase of unrest, what information is pertinent for hazard analyses and how to interpret the precursory signals is done by a discussion-based elicitation process. Each expert in a specific volcanological sub-domain will exercise their opinions, based on

the experience they have, on every parameter within a monitoring setup, with the goal to reach consensus about the most likely scenario/ threshold. All data and interpretations should be heard and evaluated. However, this process is still unduly influenced by the “stronger voice” of the group. We may be certain on something until someone else makes us doubt it. At the moment we start doubting our opinions we will be easily influenced by other, stronger opinions. On the other hand, volcanologists are often forced to make such decisions and be liable for their choices (in court of law, Bretton et al. 2015). The pressure of a volcanic ‘crisis’ and the feeling of liability increases scientists’ reservations when faced with such choices.

A suggestion to improve the expert elicitation process is to introduce a person to act as a “Devil’s advocate”. This will mean that one of the experts is supposed to do exactly the opposite to the group’s decision. If most of the experts agree on a scenario, it is the duty of the latter to completely disagree and evaluate the opposite scenario. This can be a good way to “account” for surprise scenarios. Other ways are to weight final results according to anonymous calibration tests (Cooke method; Cooke 1991; Aspinall et al. 2003; Aspinall 2006, 2010) and/or anonymous estimation of the most reliable members of the group, not necessarily the loudest.

The introduction of probabilistic hazard assessment methods in the multi-disciplinary volcanological community has first led to a dis-credit of the purely deterministic approach. After the usefulness of the probabilistic approach has been demonstrated, and confusion on the differ-ent philosophies has disappeared, or at least decreased, the awareness on framing the various “niche” research branches in a bigger picture resulted into constructive discussions among the various research groups and individuals involved. This results in coherent group thinking and a more collaborative atmosphere among volcanologists. Expert elicitation on its turn has obliged researchers with various backgrounds to absorb new data and ideas from one another. This is definitely a positive side-effect of the probabilistic approaches and expert elicitations.
## 4.2 How to Interpret Uncertainties?

Probabilistic volcanic hazard assessment and eruption forecasting is a relatively new concept in modern volcanology, and often reserved for those with a background in statistics. But, as reality showed (Constantinescu et al. 2016), most of the volcanologists are not fully aware of the probability theory and how its results should be interpreted. A panel of volcano experts usually comprises seismologists, geochemists, geodesists, geologists, petrologists, and not all of them necessarily have a background in probabilistic approaches, especially when such approach is based on the integration of opinions of all members of such a group. One idea to cope with this problem is to train the group members in how the probabilistic methodology works and how results should be interpreted, while another member of the group (the so-called “PROB-runner”) objectively uses the information provided by the expert panel to produce the probabilistic forecast. In this way, the members of the group can interpret the numerical outcomes accounting for the associated uncertainty without questioning and second-guessing the output because they are already aware of the process (Newhall and Pallister 2015; Constantinescu et al. 2016).

The whole idea of the elicitation approach is to allow your mind to explore each possibility without influencing one of the possible outcomes just because one expert believes more in one outcome than the other. It is some sort of letting go. People don't like to admit they might be wrong, so the Event Tree and Cooke elicitation approaches allow them to anonymously change their views upon elicitation. If one is capable of admitting fallibility and look at the big picture with an open mind, allowing all possibilities to unfold, then full discussion can occur and resulting estimates of probabilities will eventually have lower uncertainties. In the end, the idea of probabilities is that all scenarios are possible to happen, some with a larger probability others with a lower one; all have probabilities (and related uncertainties) and nothing should be dismissed simply because 'I strongly believe it can't be, so I don't agree'.

## 4.3 Trust in Scientists?

Even the best scientists can make mistakes. If volcanic unrest or activity is badly forecasted, initial trust in scientists may dissolve in legal proceeding. Ideally, scientists who act to the best of their knowledge should be protected rather than being blamed if they make a bad forecast (Bretton et al. 2015). Trust in scientists depends on how these scientists are portrayed to society and actually how scientific aspects of volcanology are presented to the public. This should be a system with two-way feedback (Christie et al. 2015). Many countries lack volcano-education among communities, but people know that there are some scientists that 'know what they are doing'. People feel protected, but this is a false feeling of safety, propped up by ignorance of the real situation. When disaster strikes, scientists are often the first to blame. If the community will be involved fully in the mitigation and preparedness process (e.g., Gregg et al. 2004; Rouwet et al. 2013; Dohaney et al. 2015), they may be guided by 'compassion' and will understand that volcanologists cannot stop an eruption and protect people, and eventually the blame or trust too often falls on the elected authorities. Elected authorities should be the liaison between science and the general public. Trust is inherent when you are aware of the problem and the person dealing with it. Trust in scientists may grow because they successfully predict an eruption, but sustained growth in trust is due to multi-yearly exposure of the scientific staff to the public (Christie et al. 2015). This involves long years of planning, investing and engagement in educational campaigns. Trust is something that comes in time and involves a feedback loop between people and the scientists.

Within the current scope of this opinion chapter, the probabilistic method often seems to serve as a more transparent way of bridging between the scientists and the elected authorities (decision makers). First, the use of probabilities inherently implies some uncertainty, which in scientifically literate society is essential for public trust. Second, elicitation tools reflect a joint-opinion of a group of experts rather than of one. There is a need for
training and a full understanding of probabilistic
results by the officials. The role of probabilistic
tools should, in our opinion, not intervene in
communication protocols with the lay public, but
should be rather “restricted” to transmit informa-
tion to decision-makers, representing part of the
voice of the group of volcanologists. The efforts in
communicating towards the lay public, in order to
build “trust” amongst the population, should be
decoupled from the background of the involved
scientist (deterministic or probabilistic). Com-
munication protocols are independent of the
applied scientific method, and researchers should
become more skilled to transmit their information
openly towards the public, with the awareness of
the uncertainty their information contains (Hicks
and Few 2015).

## 4.4 Towards Collaborative Volcano Monitoring

A major accomplishment of the probabilistic
method is to have increased harmony among the
various deterministic research environments.
This new dynamic favours the refining of pre-
vious conceptual models that originate from
deterministic research, as the reference frame has
become more complete.

Nevertheless, the probabilistic research
approach is not yet fully accepted by the deter-
ministic community due to criticism and anxiety
to be “replaced” by the probabilistic method
(VUELCO simulations Colima, Campi Flegrei,
Cotopaxi and Dominica). This concern is
unnecessary, since the first requisite for the
probabilistic method to function is the availabil-
ity of data, information, a priori believes and
models, originating from deterministic research.
More input information for the probabilistic
method means significant decreases in the epis-
temic uncertainty of probabilistic outcomes.

Moreover, during volcanic crisis situations,
deterministic researchers still stick to the “round
table” approach and the lack of time inhibits to

efficiently interact with the researchers that run
the probabilistic models (e.g., VUELCO simu-
lation exercises). The latter need more detailed
feedback and input information for single
parameters at the various nodes of the event-tree.
Despite refining the probabilistic model during
pre-crisis by expert elicitations, in the heat of the
moment of the crisis, a wrong interpretation of a
numerical value provided by determinists will
sometimes lead to disastrous numerical outcomes
in the probabilistic models. The PROB-runner
cannot be blamed for not being an expert in all
fields in volcanology, incorporated through
parameters in e.g., BET or HASSET.

Three solutions to this crucial issue are pro-
posed: (1) probabilistic model runners should
actively take part in the “closed-door” discus-
sions by the experts from the various fields,
before incorporating numerical values in proba-
bilistic models, (2) a separate team of experts that
profoundly know the needs and functioning of
probabilistic models should flank the
PROB-runners during crisis. Both realities are
not yet accomplished, and/or (3) an event tree
structure, put forward by a facilitator between the
deterministic and probabilistic research teams
should serve as the base to guide scientific dis-
cussion and get fast to the nucleus of the crisis
(Newhall and Pallister 2015). Future simulation
exercises on volcanic crisis situations should
focus on this training approach, in order to be
prepared when real the crisis strikes.

Moreover, the outcomes of probabilistic
models have to be included in the final reports
transmitted to authorities, and be respected as
one of the many monitoring tools, without
decreasing or increasing their weight and value
within the still deterministic-dominated general
opinion. Since a probabilistic framework offers a
measure of the uncertainty, any interpretation
should not be taken for granted, neither decision
makers should make decisions based solely on a
probability. Probabilities should be considered as
an addition to the information upon which deci-
sions are made, and not as a decisive factor.
# 5 Take Home Ideas

Probabilistic forecasting has become an inherent part within a multi-facet view of research and volcano monitoring; neither deterministic, nor probabilistic methods, can or should stand alone. More than being a means to transmit information between volcanologists and decision making authorities, probabilistic models should also be based on, and promote, deterministic research that can be written up after “round table” discussions (Fig. 1).

Incorporation of probabilistic models in volcano monitoring has many advantages: (1) protecting against oversimplified, over-confident forecasts. Even though decision makers may initially have difficulties to understand uncertainties and prefer black-on-white numbers, Y/N forecasts, they will soon come to appreciate probabilities if they are represented in an understandable way; (2) creating harmony amongst the volcanological community because probabilities will reflect the general view of the monitoring team, and (3) legally protecting the entire monitoring team by probabilities and their uncertainties as forecasts are perfectly traceable and reproducible, if disaster strikes after “erroneous forecasts”. However, to

date, probabilistic forecasts have not been rigorously evaluated to know whether they are an improvement over traditional, non-probabilistic forecast methods. For sure, they do better than traditional methods at estimating uncertainty. We still need tests on whether they are more accurate, and more useful for decision makers than older methods (Newhall and Pallister 2015).

In the future, reports should include the forecast of probabilistic models; a monitoring architecture should expand beyond the classical “seismodeformation-gas” setup and become “seismodeformation-gas-probability” setup (in random order of importance) (Fig. 1). Probabilistic models cannot stand alone, as they need the input and feedback from deterministic research. “Probabilists” should not communicate their numerical outcomes directly to the decision-making authorities: it is better to convey the opinion of an entire group. Probabilistic methods can serve as “moderator” among the various disciplines, while expert elicitations are the “glue” between the deterministic and probabilistic approaches (Fig. 1). Probabilistic methods should knock down walls and stimulate discussion and coherence amongst the various research branches (seismologists, geodesists,

<figure><img src="image_15.png" /><figcaption>**Fig. 1** From dichotomic monitoring setups (deterministic vs. probabilistic forecast, “or” setups) to an “and” strategy. The picture shows VUELCO target volcano Popocatépetl,</figcaption></figure>

Mexico (November 2011, D.R.). Before interpretation of the data (monitoring data, eruptive history or any a priori model) the volcano is considered a “black box”
geochemists, petrologists, geologists). This requires
time, effort and an open-mind by all involved
parties/volcanologists in volcano monitoring.

References

Aspinall WP (2006) Structured elicitation of expert judge-
ment for probabilistic hazard and risk assessment in
volcanic eruptions. In: Mader HM, Coles SG, Con-
nor CB, Connor LJ (eds). Statistics in volcanology.
IAVCEI Publications. ISBN: 978-1-86239-208-3.
pp 15–30

Aspinall WP (2010) A route to more tractable expert advice. Nature 463(21):294–295

Aspinall WP, Woo G, Voight B, Baxter PJ (2003)
Evidence-based volcanology: application to vol canic
crises. J Volcanol Geotherm Res 128:273–285

Bartolini S, Cappello A, Martí J, Del Negro C (2013) QVAST: a new quantum GIS plugin for estimating volcanic susceptibility. Nat Hazards Earth Syst Sci 13:3031–3042. doi:10.5194/nhess-13-3031-2013

Becerril L, Bartolini S, Sobradelo R, Martí J, Morales JM, Galiendo I (2014) Long-term volcanic hazard assessment on El Hierro (Canary Islands). Nat Hazards Earth Syst Sci 14:1853–1870. doi:10.5194/nhess-14-1853-2014

Bretton RJ, Gottsmann J, Aspinall WP, Christie R (2015) Implications of legal scrutiny processes (including the L'Aquila trial and other recent court cases) for future volcanic risk governance. J Appl Volcanol 4:18. doi:10.1186/s13617-015-0034-x

Christie R, Cooke O, Gottsmann J (2015) Fearing the knock on the door: critical security studies insights into limited cooperation with disaster management regimes. J Appl Volcanol 4:19. doi:10.1186/s13617-13015-10037-13617

Constantinescu R, Robertson R, Lindsay JM, Tonini R, Sandri L, Rouwet D, Patrick Smith P, Stewart R (2016) Application of the probabilistic model BET_UNREST during a volcanic unrest simulation exercise in Dominica, Lesser Antilles. Geochem Geophys Geosyst 17:4438–4456. doi:10.1002/2016GC006485

Cooke RM (1991) Experts in uncertainty: opinion and
subjective probability in science. Oxford University
Press. ISBN: 9780195064650

Dohaney J, Brogt E, Kennedy B, Wilson TM, Lindsay JM (2015) Training in crisis communication and volcanic eruption forecasting: design and evaluation of an authentic role-play simulation. J Appl Volcanol 4:12. doi:10.1186/s13617-015-0030-1

Donovan A, Oppenheimer C, Bravo M (2011) Social studies of volcanology: knowledge generation and expert advice on active volcanoes. Bull Volcanol. doi:10.1007/s00445-011-0547-z

Gregg CE, Houghton BF, Johnston DM, Paton D, Swanson DA (2004) The perception of volcanic risk

in Kona communities from Mauna Loa and Hualālai
volcanoes, Hawai'i. J Volcanol Geotherm Res
130:179–196

Haynes K, Barclay J, Pidgeon N (2008) The issue of trust and its influence on risk communication during a volcanic crisis. Bull Volcanol 70:605–621. doi:10.1007/s00445-007-0156-z

Hicks A, Few R (2015) Trajectories of social vulnerability during the Soufrière Hills volcanic crisis. J Appl Volcanol 4:10. doi:10.1186/s13617-015-0029-7

Lindsay J, Marzocchi W, Jolly G, Constantinescu R, Selva J, Sandri L (2010) Towards real-time eruption forecasting in the Auckland Volcanic Field: application of BET_EF during the New Zealand National Disaster Exercise ‘Ruaumoko’. Bull Volcanol 72:185–204. doi:10.1007/s00445-009-0311-9

Marzocchi W, Woo G (2007) Probabilistic eruption forecasting and the call for an evacuation. Geophys Res Lett 34:L22310. doi:10.21029/22007GL031922

Marzocchi W, Bebbington M (2012) Probabilistic erup-
tion forecasting at short and long time scales. Bull
Volcanol. doi:10.1007/s00445-012-0633-x

Marzocchi W, Sandri L, Gasparini P, Newhall C, Boschi E (2004) Quantifying probabilities of volcanic events: The example of volcanic hazard at Mount Vesuvius. J Geophys Res 109:B11201. doi:10.1029/2004JB003155

Marzocchi W, Sandri L, Selva J (2008) BET_EF: a probabilistic tool for long- and short-term erup tion forecasting. Bull Volcanol 70:623–632. doi:10.1007/s00445-007-0157-y

Moran SC, Newhall C, Roman DC (2011) Failed magmatic eruptions: late-stage cessation of mag ma ascent. Bull Volcanol 73:115–122. doi:10.1007/s00445-010-0444-x

Newhall C, Hoblitt RP (2002) Constructing event trees for volcanic crises. Bull Volcanol 64:3–20. doi:10.1007/s004450100173

Newhall C, Pallister J (2015) Using multi data sets to
propagate probabilistic volcanic event trees. In:
Schroder JF, Papale P (eds) Volcanic hazards, risks,
and disasters. Hazards and disasters series. Elsevier,
Amsterdam, pp 203–232

Phillipson G, Sobradelo R, Gottsmann J (2013) Global volcanic unrest in the 21st century: an ana lysis of the first decade. J Volcanol Geotherm Res 264:183–196

Rouwet D, Iorio M, Polgovsky D (2013) A science & arts sensitization program in Chapultenango, 25 years after the 1982 El Chichón eruptions (Chiapas, Mexico). J Appl Volcanol 2:6. doi:10.1186/2191-5040-2-6

Rouwet D, Sandri L, Marzocchi W, Gottsmann J, Selva J, Tonini R, Papale P (2014) Recognizing and tracking hazards related to non-magmatic unrest: a review. J Appl Volcanol 3:17. doi:10.1186/s13617-014-0017-3

Sandri L, Guidoboni E, Marzocchi W, Selva J (2009) Bayesian event tree for eruption forecasting (BET_EF) at Vesuvius, Italy: a retrospective forward application to the 1631 eruption. Bull Volcanol 71:729–745. doi:10.1007/s00445-008-0261-7
Sandri L, Jolly G, Lindsay J, Howe T, Marzocchi W (2012) Combining long-term and short-term probabilistic volcanic hazard assessment with cost-benefit analysis to support decision making in a volcanic crisis from the Auckland Volcanic Field, New Zealand. Bull Volcanol 74:705-723. doi:10.1007/s00445-011-0556-y

Sandri L, Thouret J-C, Constantinescu R, Biass S, Tonini R (2014) Long-term multi-hazard assessment for El Misti volcano (Peru). Bull Volcanol 76:771. doi:10.1007/s00445-013-0771-9

Sandri L, Tonini R, Rouwet D, Constantinescu R, Mendoza-Rosas AT, Andrade D, Bernard B (2017) The need to quantify hazard related to non-magmatic unrest: from BET_EF to BET_UNREST. In: Gottsmann J, Neuberg, J, Scheu B (eds) Volcanic unrest: from science to society—IAVCEI advances in volcanology. Springer

Selva J, Costa A, Marzocchi W, Sandri L (2010) BET_VH: exploring the influence of natural uncertainties on long-term hazard from tephra fallout at Campi Flegrei (Italy). Bull Volcanol 72:717-733. doi:10.1007/s00445-010-0358-7

Selva J, Marzocchi W, Papale P, Sandri L (2012) Operational eruption forecasting at high-risk volcanoes: the case of Campi Flegrei, Naples. J Appl Volcanol 1:5. http://www.appliedvolc.com/content/1/1/5

Selva J, Orsi G, Di Vito MA, Marzocchi W, Sandri L (2011) Probability hazard map for future vent opening at Campi Felgrei caldera. Bull Volcanol, Italy. doi:10.1007/s00445-011-0528-2

Sobradelo R, Bartolini S, Marti J (2014) HASSET: a probability event tree tool to evaluate future volcanic scenarios using Bayesian inference. Bull Volcanol 76:770. doi:10.1007/s00445-013-0770-x

Sobradelo R, Marti J (2015) Short-term volcanic hazard assessment through Bayesian inference: retrospective application to the Pinatubo 1991 volcanic crisis. J Volcanol Geotherm Res 290:1-11. doi:10.1016/j.jvolgeores.2014.11.011

Sparks RSJ (2003) Forecasting volcanic eruptions. Earth Planet Sci Lett 210:1-15. doi:10.1016/S0012-821X(03)00124-9

Sparks RSJ, Aspinall WP (2004) Volcanic activity: frontiers and challenges in forecasting, pre diction and risk assessment. The State of the Planet: Frontiers and Challenges in Geo physics. Geophysical Monograph 150, IUGG Volume 19. doi:10.1029/150GM28

Tonini R, Sandri L, Rouwet D, Caudron C, Marzocchi W, Suparjan P (2016) A new Bayesian Event Tree tool to track and quantify unrest and its application to Kawah Ijen volcano. Geochem Geophys Geosyst 17:2539-2555. doi:10.1002/2016GC006327

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Probabilistic E-tools for Hazard
Assessment and Risk Management

Stefania Bartolini, Joan Martí, Rosa Sobradelo
and Laura Becerril

Abstract

The impact of a natural event can significantly affect human life and the
environment. Although fascinating, a volcanic eruption creates similar or even
greater problems than more frequent natural events due to its multi-hazard
nature and the intensity and extent of its potential impact. It is possible to live
near a volcanic area and take advantage of the benefits that volcanoes offer, but
it is also important to be aware of the existing threats and to know how to
minimise risks. In this chapter, we present an integrated approach using
e-tools for assessing volcanic hazard and risk management. These tools have
been especially designed to assess and manage volcanic risk, to evaluate long-
and short-term volcanic hazards, to conduct vulnerability analysis, and to
assist decision-makers during the management of a volcanic crisis. The
methodology proposed here can be implemented before an emergency in
order to identify optimum mitigating actions and how these may have to be
adapted as new information is obtained. These tools also allow us identifying
the most appropriate probabilistic and statistical techniques for volcanological
data analysis and treatment in the context of quantitative hazard and risk
assessments. Understanding volcanic unrest, forecasting volcanic eruptions,
and predicting the most probable scenarios, all imply a high degree of inherent
uncertainty, which needs to be quantified and clearly explained when
transmitting scientific information to decision-makers.

Resumen

El impacto de un evento natural puede afectar significativamente la vida
humana y el medio ambiente. Aunque fascinante, una erupción volcánica

S. Bartolini (✉) · J. Martí · L. Becerril
Group of Volcanology, SIMGEO (UB-CSIC),
Institute of Earth Sciences Jaume Almera,
ICTJA-CSIC, Lluís Solé I Sabarís S/N, Barcelona
08028, Spain
e-mail: sbartolini.1984@gmail.com

J. Martí
e-mail: joan.marti@ictja.csic.es

L. Becerril
e-mail: lbecerril@ictja.csic.es

R. Sobradelo
WRN Earth Hub Leader, Analytics Technology &
Willis Research Network, London, UK
e-mail: rosa.sobradelo@willistowerswatson.com
puede generar problemas parecidos o incluso mayores que otros eventos naturales más frecuentes, ya que se trata de un fenómeno multipeligro y con un impacto potencial de gran intensidad y magnitud. Vivir cerca de una zona volcánica es posible considerando sus innumerables beneficios, pero sin embargo debemos ser conscientes de la amenaza existente y tomar las medidas oportunas para minimizar el riesgo. En este capítulo, se presenta un enfoque integrado que utiliza herramientas para la evaluación de la peligrosidad y del riesgo volcánico, el análisis de vulnerabilidad, y para ayudar en la gestión de una crisis volcánica. La metodología aquí propuesta puede ser implementada antes de una emergencia con el fin de determinar las medidas óptimas de mitigación y como pueden adaptarse a medida que se obtiene nueva información. Además, estas herramientas se basan en las técnicas probabilísticas y estadísticas más adecuadas para el análisis de datos vulcanológicos y su implementación en el contexto de las evaluaciones cuantitativas del peligro y riesgo. La interpretación del unrest, la predicción de las erupciones volcánicas, y la identificación de los escenarios más probables, implican un alto grado de incertidumbre, que debe ser cuantificado y claramente explicado para transmitir correctamente la información científica a los gestores de las crisis volcánicas.

Keywords

Volcanic risk · Volcanic hazard · Vulnerability · Risk management · Decision-making · E-tools

Introduction

One of the most important tasks in modern vol-
canology is to manage volcanic risk and, conse-
quently, to minimise it. Forecasting volcanic
eruptions and predicting the most probable sce-
narios are tasks that are subject to high degrees of
uncertainty but which need to be quantified and
clearly explained when transmitting scientific
information to decision-makers. Assessing erup-
tion risk scenarios in probabilistic ways has
become one of the main challenges tackled by
modern volcanology (Newhall and Hoblitt 2002;
Marzocchi et al. 2004; Aspinall 2006; Neri et al.
2008; Sobradelo et al. 2014).

The volcanic management cycle consists of
four phases (Sobradelo et al. 2015): (i) the

pre-unrest phase that includes long-term assess-
ment, hazard and risk mapping, and estimation
regarding expected scenarios, volcano monitor-
ing, and emergency planning; (ii) the unrest
phase, which includes short-term assessment,
alert, communication, and information proce-
dures, the implementation of emergency mea-
sures, and the interpretation of eruption
precursors; (iii) the volcanic event itself, repre-
sented by a major change in the state of the
volcano; decisions can be revised as new infor-
mation is obtained and the evolution of the vol-
canic event is updated; (iv) the post-event phase
characterized by rescue and recovery.

Previous studies, focusing attention on the
first phase of volcanic crisis management, have
developed different methodologies for evaluating
hazards. Most of these studies are based on the use of simulation models and Geographic Information Systems (GIS) that enable volcanic hazards such as lava flows, pyroclastic density currents (PDCs), and ash fallout to be modeled and visualised (Felpeto et al. 2007; Toyos et al. 2007; Cappello et al. 2012; Martí et al. 2012; Becerril et al. 2014; Bartolini et al. 2014a, b). The use of spatio-temporal data and GIS has now become an essential part of integrated approaches to disaster risk management in light of the development of new analysis/modelling techniques. These spatial information systems are used for storage, situation analysis, modelling, and visualisation (Twigg 2004). Normally, these studies present a systematic approach based on the estimation of spatial probability, that is, a susceptibility analysis (Martí and Felpeto 2010), a temporal analysis based on Bayesian inference (Marzocchi et al. 2004; Sobradelo et al. 2014), or the evaluation of hazards (Felpeto et al. 2007; Bartolini et al. 2014a, b; Becerril et al. 2014) and vulnerability (Martí et al. 2008; Scaini et al. 2014). These studies have been applied in a number of volcanic areas such as Etna, Sicily (Cappello et al. 2013), Tenerife, Spain (Martí et al. 2012), Peru (Sandri et al. 2014), the island of El Hierro, Spain (Becerril et al. 2014), and Deception Island, Antarctica (Bartolini et al. 2014a). Other procedures have been employed to assess volcanic hazards in Campi Flegrei, Italy (Lirer et al. 2001), Furnas (São Miguel, Azores), Vesuvius, Italy (Chester et al. 2002), and Auckland, New Zealand (Sandri et al. 2012).

These studies underline the fact that scientists are aware of the relationship between volcanic hazards and socio-economic impacts and are in the process of developing new approaches and models to assess its importance. One positive aspect is that, as a result, there is now a choice of freely available models; on the other hand, these models are not integrated into a single platform and have been developed in a variety of different programming languages.

Despite the fact that these tools have been created for application in real situations and have been successfully tested in different volcanic

areas and retrospectively for a number of volcanic crisis (Martí et al. 2012; Sobradelo et al. 2014; Bartolini et al. 2014a, b; Becerril et al. 2014; Scaini et al. 2014), to date they only exist as academic exercises. To convert them into practical tools ready to be used by Civil Protection managers and decision-makers, they must be checked and tested, and then adapted to the real needs of end users.

Probabilities are still the best outcome of scientific forecasting. However, they are not easily understood. Understanding the potential evolution of a volcanic crisis is crucial for designing effective mitigation strategies. One of the main issues when managing a volcanic crisis is how to make scientific information understandable for decision-makers and Civil Protection managers. Thus, we need quantitative risk-based methods for decision-making under conditions of uncertainty that can be developed and applied to volcanology. In order to resolve this problem and to take a step forward in minimising risks, we have defined an integrated approach using user-friendly e-tools, which can be run on personal computers. They are specifically useful for long- and short-term hazard assessment, vulnerability analysis, decision-making, and volcanic risk management. In this chapter, we describe the e-tools designed to manage and to minimise volcanic risk.

## Volcanic Risk: Hazard, Vulnerability, and Value

In general, risk is defined as the probability or likely magnitude of a loss (Blong 2000). In volcanic risk assessment, risk depends on the adverse effects of volcanic hazards and can be defined as the product of three main factors: volcanic hazard, vulnerability to those hazards, and the value of what is at risk.

Volcanic hazard is defined as the probability of any particular area being affected by a destructive volcanic event within a given period of time (Blong 2000). The quantification and evaluation of the volcanic hazard allow us determining which areas will be affected by a
given volcanic event, and to design appropriate
emergency plans and territorial planning.

A vulnerability assessment uses indicators to quantify the physical vulnerability of the elements of each sub-system (buildings, transportation system, urban services, and population) and is a measurement of the proportion of the value likely to be lost as a result of a given event (Blong 2000). In fact, the values of elements-at-risk that can be directly or indirectly damaged by a given hazard will vary. Each hazardous phenomenon affects elements and infrastructures in different ways in terms of their specific physical vulnerability; this in turn will depend on their number (of buildings, people, etc.), monetary value, surface area, and the importance of the elements-at-risk. Indicators are used to determine the specific physical vulnerability of each hazardous phenomenon and sub-system (Scaini et al. 2014).

The value is the number of human lives at
stake, together with the capital value (land,

buildings, etc.) and productive capacity (factories, power plants, highways, etc.) exposed to the destructive events (Blong 2000).

Risk management is a complex process (Fig. 1) since different steps are necessary for evaluating and minimising risk. It can be thought of as the sum of risk assessment—which includes risk analysis and risk evaluation—and risk control. Risk analysis aims to improve prevention tools through the collection and acquisition of data on hazards and risks, and then to disseminate it in the form of maps and scenarios (Thierry et al. 2015). This phase is characterised by five different steps: hazard identification, hazard assessment, elements-at-risk/exposure analysis, vulnerability assessment, and risk estimation (Van Westen 2013). In particular, it is important to distinguish between long- and short-term hazard assessments, which will vary according to the expected period of time over which the process will display significant variations.

<figure><img src="image_16.png" /><figcaption>**Fig. 1** Risk management schematic: steps for evaluating and minimising risk</figcaption></figure>
Long-term assessment is based on historical and geological data, as well as theoretical models, and refers to the time window available—during which time the volcanic system shows no signs of unrest—before an unrest episode occurs. On the other hand, short-term assessment refers to the unrest phase, and complementary information derived from the combination of a long-term analysis with real-time monitoring data is needed to update the status of the volcanic hazard (Blong 2000). Short-term evaluation helps forecast where and when the eruption may take place and the most likely eruptive scenarios.

Once the long-term risk analysis is computed, it is then possible to adopt mitigation measures such as land-use planning and emergency preparations to reduce the risk. In addition, this long-term analysis will help manage the volcanic crisis as it will constitute the basis for the short-term analysis and, combined with a cost-benefit analysis, will assist in correct decision-making (Sobradelo et al. 2015). To evaluate the total risk related to a particular volcanic eruption we have to repeat the evaluation of the vulnerability and the cost-benefit analysis (risk evaluation) for each possible hazard scenario and then sum the results. This will allow us to estimate the impact and the economic losses that will affect society and the environment, and to identify a range of risk management alternatives.

Finally, the second part of risk management is risk control, which consists of the decision-making process involved in managing risks whose aim is to improve crisis management capabilities and implement risk-mitigation measures using the results of risk assessment as an input (Western 2013). During this phase measures must be adopted for reducing vulnerability (people and infrastructure) and developing recovery and resilience capacities after an event has taken place.

## E-tools for Volcanic Hazard and Risk Management

In this section, we present different e-tools that have been specifically designed to assess and manage volcanic risk (Fig. 2). The objective is to combine freely available models to produce a new approach for minimising and managing volcanic risk. These e-tools are based on the assumption that the best way to show how probabilities work is to use the possible scenarios and outcomes of volcanic unrest (an increase in volcanic activity that may or may not precede a volcanic eruption) to design an integrated model that can act as a descriptor of scenarios. The effectiveness of these e-tools has been analysed

<figure><img src="image_17.png" /><figcaption>**Fig. 2** E-tools for assessing and managing volcanic risk that allow to evaluate the possible hazards that could affect a volcanic area and develop appropriate hazard and risk maps</figcaption></figure>
in different volcanic areas showing pros and
contras of these approaches, such as in the case
of El Hierro Island in Canary Islands (Becerril
et al. 2014; Sobradelo et al. 2015), Tenerife in
Canary Islands (Scaini et al. 2014), Deception
Island in Antarctica (Bartolini et al. 2014a), and
La Garrotxa Volcanic Field in Spain (Bartolini
et al. 2014b). User manuals are available at
https://volcanbox.wordpress.com/ and http://
www.vetools.eu.

These e-tools are designed to be implemented
before an emergency in order to identify (i) the
optimum mitigating actions and (ii) the most
appropriate probabilistic and statistical tech-
niques for volcanological data analysis and
treatment in the context of quantitative hazard
and risk assessment, and (iii) how appropriate
responses may change as new information is
obtained. They constitute different steps, as
shown in Fig. 3, in hazard assessment and risk
management.

Storing Data

The results of our analyses are as important as
the input parameters that are used. Given the
nature, variety, and availability of the data we
need to handle, one of the most important
aspects of risk assessment is the management
and exchange of information (De la Cruz-Reyna
1996). The quality of the data will determine the
evaluation of the volcanic risk, which is an
essential part of risk-based decision-making in
land-use planning and emergency management.
Some of the most relevant issues include how
and where to store the data, in which format
should they be made available, and how to
facilitate its use and exchange. Thus, it is
essential to have an appropriate database that is
specifically adapted to the task of evaluating and
managing volcanic risk. For that reason, we
designed VERDI (Volcanic managEment Risk
Database desIgn) (Bartolini et al. 2014c), a

<figure><img src="image_18.png" /><figcaption>**Fig. 3** Steps in volcanic risk assessment applying e-tools to be implemented before an emergency</figcaption></figure>
<figure><img src="image_19.png" /><figcaption>**Fig. 4** The design of the VERDI database (after Bartolini et al. 2014c)</figcaption></figure>

geodatabase with an appropriate architecture for volcanic risk assessment and management that stores the data from which we will extract the input parameters to run our e-tools. VERDI is a spatial database structure (Fig. 4) that allows different types of data, including geological, volcanological, meteorological, monitoring, and socio-economic information, to be manipulated, organised, and managed. The data contained in this database are the basis for applying the

probabilistic models that are the first step in our risk analysis.

## Hazard E-tools

Volcanic hazard assessment consists of simulating eruptive scenarios for use in risk-based decision-making, land-use planning, and emergency management. They must necessarily be
based on a good knowledge of the past eruptive history of the volcano or volcanic area, and will reveal how volcanoes erupted in the past, thereby providing clues to *how* they will erupt in the future. The first step in the quantitative assessment of volcanic hazards is the spatial probability of occurrence of a hazard, i.e. *where* the next eruption may take place and its extent. This analysis is based on the development of susceptibility maps (Martí and Felpeto 2010), that is, the spatial probability of a future vent opening given the past eruptive activity of a volcano and the simulation of possible eruptive scenarios. Another important task is to investigate the temporal probability, in other words, *when* the next eruption will occur in the future and the type of scenarios that are most likely to be involved. Thus, an evaluation of volcanic hazard enables us to infer where and when the next eruption may take place and its magnitude.

## Spatial Analysis

Susceptibility analysis is the evaluation of the spatial distribution of future vent openings (Fig. 5a). This challenging issue is generally tackled using probabilistic methods that use the calculation of a kernel function at each data location to estimate probability density functions (PDFs). Commonly, a Gaussian kernel, describing a normal distribution, is used to estimate local event densities in volcanic fields, which will give the intensity of a new vent opening. This method is based on the distance from nearby volcanic structures and a smoothing parameter, also known as bandwidth. This factor is the most important parameter in the kernel function and represents the degree of randomness in the distribution of past events.

QVAST (QGIS for Volcanic Susceptibility), developed by Bartolini et al. (2013), is a new tool designed to generate user-friendly quantitative assessments of volcanic susceptibility (e.g. the probability of hosting a new eruptive vent). QVAST allows an appropriate method for evaluating the bandwidth for the kernel function to be selected on the basis of input parameters and the shapefile geometry, and can also evaluate the PDF with the Gaussian kernel. When different

input data sets are available for the area, the total susceptibility map is obtained by assigning different weights to each of the PDFs, which are then combined via a weighted sum and modeled in a non-homogeneous Poisson process. This e-tool has been used to evaluate susceptibility on the island of El Hierro (Canary Islands) (Becerril et al. 2014) and on Deception Island (Antarctica) (Bartolini et al. 2014a).

When monitoring data generated during an unrest phase are available, the QVAST e-tool can also be used to update the susceptibility map. In fact, seismicity and surface deformation are good indicators of magma movement and during volcanic unrest variations in shallow volcanotectonic and long-period seismicity, as well as ground deformation, are observed as the magma migrates within the volcanic system (Martí et al. 2013). Thus, QVAST is a highly useful tool that can be applied to both long- and short-term evaluations.

## Temporal Analysis

HASSET (Hazard Assessment Event Tree), developed by Sobradelo et al. (2014), is a probability tool built on an event tree structure that uses Bayesian inference to estimate the probability of occurrence of a future volcanic scenario. It also evaluates the most relevant sources of uncertainty in the corresponding volcanic system. Event tree structures (Newhall and Hoblitt 2002) constitute one of the most useful and necessary tools in modern volcanology for assessing the volcanic hazard of future eruptive scenarios. An event tree is a graphic representation of events in the form of nodes and branches. It evaluates the most relevant sources of uncertainty when estimating the probability of occurrence of a future volcanic event.

The objective of this e-tool is to outline all relevant possible outcomes of volcanic unrest at progressively greater detail and to assess the hazard of each scenario by estimating its probability of occurrence within a future time interval. Each node of the event tree represents a step and contains a set of possible branches (the outcomes for that particular category). The nodes are
<figure><img src="image_20.png" /><figcaption>**Fig. 5** Methodological approach for obtaining a qualitative hazard map: its application to Deception Island (after Bartolini et al. 2014a)</figcaption></figure>

alternative steps from a general prior event, state, or condition that move towards increasingly specific subsequent events and a final outcome. HASSET (Fig. 5b) uses this event tree structure to make estimations of the probabilities for each possibility (branches and nodes) using a statistical methodology known as Bayesian Inference (Newhall and Hobblitt 2002; Marzocchi et al. 2004; Sobradelo et al. 2014). In particular, and based on comparisons with previous event trees for volcanic eruptions, HASSET accounts for the possibility of (i) flank eruptions (as opposed to

only central eruptions), (ii) geothermal or tec-
tonic unrest (as opposed to only magmatic
unrest), and (iii) felsic or mafic lava composition,
as well as (iv) certain volcanic hazards as pos-
sible outcomes of an eruption, and (v) the dis-
tance reached by each hazard.

A user-friendly interface guides the user
through all steps and helps

- enter all the data needed for the analysis;

- compute the estimated probability for each branch in the event tree;