Impact Assessment Framework Accounting for the Life Cycle of Volcanic Ash

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Thesis

Reference

Impact Assessment Framework Accounting for the Life Cycle of Volcanic Ash

DOMINGUEZ BARRAGAN, Lucia

Abstract

Every eruption offers a unique opportunity to contemplate and understand volcanic phenomena and their imminent interaction with the environment and societies. Understanding the complexity of volcanic eruptions due to the large variability of volcanic processes and products and the multiple dimensions of vulnerability of the increasingly interdependent and interconnected societies, requires an in-depth analysis of past events, not only regarding hazards but also the associated consequences. The aim of this thesis is to propose an impact assessment framework accounting both for primary (tephra fallout) and secondary (wind ash-remobilisation) hazards as well as for the complex cascading effects associated with the damage and disruption to the critical infrastructures. With the 2011-2012 Cordón Caulle (Chile) eruption as case study, the complex connection between hazard, exposure and vulnerability aspects are investigated. As an application of the framework, the cascading effects associated with the power supply infrastructure in three communities of Argentina is investigated.

DOMINGUEZ BARRAGAN, Lucia. Impact Assessment Framework Accounting for the Life Cycle of Volcanic Ash. Thèse de doctorat : Univ. Genève, 2020, no. Sc. 5463

DOI : 10.13097/archive-ouverte/unige:141677 URN : urn:nbn:ch:unige-1416779

Available at:

http://archive-ouverte.unige.ch/unige:141677

Disclaimer: layout of this document may differ from the published version.

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Impact Assessment Framework Accounting for the Life Cycle of Volcanic Ash

THÈSE

présentée à la Faculté des sciences de l’Université de Genève

pour obtenir le grade de Docteur ès sciences, mention Sciences de la Terre

par

Lucia Dominguez Barragan

d’ Espagne (née à Bogotá, Colombie)

Thèse N^o 5463

Genève

Atelier de reprographie ReproMail 2020

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la meseta patagónica. Da la impresión de que estamos viviendo un desafío que nos hace la naturaleza, para probar hasta dónde puede llegar la resistencia del hombre y la de los animales”

“I believe that this last ash fallout was something like, rushing the facts, to highlight the trails of the impoverishment in this suffering region of the Patagonian plateau. It gives the impression that we are living a challenge that nature impose us, to test how far the resistance of man and animals can go”

Elias Chucair, Ingeniero Jacobacci, October 20, 2011.

In "Del Archivo de la Memoria". Ed. Del Cedro, 2013.

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I would like to express my most sincere gratitude to my supervisor Prof. Costanza Bonadonna for giving me the opportunity to become a volcanologist. I have learned many things in the field of Earth Sciences but also about professional and human relationships. Thanks for your trust and your special way of motivating me to go beyond my limits.

I also want to express my deepest gratitude to Dr. Corine Frischknecht, for her support and patience that has allowed me to learn the great importance of responsibility and thoroughness, two essential qualities in both professional and personal areas. In fact, the healthy balance between Costanza and Corine has taught me that the term "resilience" is part of our daily lives, and this course was divided into theoretical and practical modules.

My gratitude also for the other members of the Committee: Prof. Scira Menoni, for providing me with a global and more realistic vision of risk; Prof. Jenni Barclay, from whom I learnt there was other ways to communicate science; and Prof. Raffaello Cioni for his special and wide vision of volcanic eruptions and products. Thanks for having showed me your rigor to treat each single pyroclast!.

Special thanks go to the people that initiated me in the field of volcanology:

Prof. Ana Elena Concha for showing me the beauty of nature from xenoliths and crystals; Dr. Luz Stella Gómez for introducing me to the world of nanoparticles;

and Héctor Cepeda for his scientific and human vision of volcanoes. Without your sentence "It’s never too late for volcanoes", I would have never started a PhD.

I would also like to thank the friends and colleagues of the first floor: Sebastian (for always being there, no matter the country!), Mohsen (for your all-purpose tool- box), Federico (for your constant happiness), Stefano, Jow, Allan and Valentin (for their laughter and love... and Paquita of course!), Matt (for watering my plants), Bocar (for your perspective of the real life), Valérie (for your sincerity and tender- ness), and Irene (for your smiling support). Special thanks goes to Eduardo for

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code with me (just: don’t forget that the turron is spanish!), Paul for teaching me your strict but flexible way to do science and things in life, and last but not least to Laura for your fascination between plagioclases and pottery clays...I learned so much from you!.

I am deeply grateful to Donald Bran and Pablo Forte to have introduced me to the Patagonia where they knew, there was a lot of ash moving all around. Pablo, thanks for the long evenings talking about the political context in Argentina with some mates. Thanks to Leonardo Mingari for showing me the wide and complex perspective of aeolian processes from the atmospheric sciences. I am also grateful to the communities of Villa La Angostura, San Carlos de Bariloche and Ingeniero Jacobacci (particularly Donald -el pato- Jr., Jazmin, Virginia y Manu) for their trust, assistance and support.

I would like to thank all the members of the Department of Earth Sciences, particularly Agathe, Rossana, Fred, Nino, Elisabeth, Phine, Christine, Rolanda and Mirka for their invaluable help and assistance.

Special thanks to all the friends that have waited with patience, particularly to Ewa for having adopted my daughter Ana during the last months.

I am deeply thankful to my parents and family for having instilled me the princi- ples of responsibility, perseverance, commitment and hope, without which the hard work that represents a PhD would not be possible. Special thanks to Alex for having me portray as a detective geologist, and to Raquelita for her language support.

Finally, I have no words to express my gratitude to my journey companions, Gus, Sam and Ana, who have supported me with patience and love, and have always worried if I have to cross a moving bridge over a volcano (as Shrek had to...).

This work was supported by the Swiss National Science Foundation (project N.

200021_163152)

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Summary ix

Résumé en Français xi

1 Introduction 1

1.1 Overall view of risk from natural hazards . . . 2

1.2 Impact studies in a volcanic setting . . . 9

1.2.1 Pre-event impact assessment . . . 9

1.2.2 Post-event impact assessment . . . 13

1.3 The life cycle of volcanic ash . . . 17

1.4 The case study of the 2011-2012 Cordón Caulle eruption . . . 19

1.4.1 Geographical and political context . . . 21

1.5 Thesis objectives and structure . . . 22

2 Aeolian remobilisation of the 2011-Cordón Caulle tephra-fallout deposit 27 2.1 Introduction . . . 27

2.2 Terminology . . . 29

2.2.1 Previous studies of aeolian processes . . . 29

2.2.2 Wind-remobilisation phenomena . . . 30

2.2.3 Wind-transport mechanisms . . . 31

2.2.4 Deposition mechanisms and associated deposits . . . 34

2.3 Cordón Caulle eruption: primary tephra-fallout deposit . . . 36

2.4 Materials and Methods . . . 38

2.4.1 Data collection . . . 38

2.4.2 Analyses . . . 38

2.5 Results . . . 39

2.5.1 Field observations of ash-remobilised deposits . . . 39

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2.5.2 Physical characterisation of particles . . . 45

2.6 Discussion . . . 50

2.6.1 Particle size and shape analysis: implications for transport mechanisms . . . 50

2.6.2 Interpretation of ash-remobilised deposits in the Patagonian steppe . . . 54

2.7 Conclusions . . . 58

2.8 Appendix 2.A . . . 60

3 Mass flux decay timescales of volcanic particles due to aeolian processes 67 3.1 Introduction . . . 67

3.2 Results . . . 71

3.2.1 Wind-remobilisation of the Cordón Caulle tephra-fallout deposit: spatial and temporal distribution . . . 71

3.2.2 Horizontal mass flux decay of volcanic particles . . . 74

3.2.3 Role of meteorological conditions and material supply on the streamwise mass flux . . . 77

3.5 Materials and Methods . . . 87

3.5.1 Chronology of the 2011-2012 CC eruption . . . 87

3.5.2 Sampling strategy and data collection . . . 88

3.5.3 Streamwise saltation theory . . . 89

3.5.4 Fitting procedure for the double exponential decay . . . 93

3.5.5 Uncertainty analysis . . . 94

3.6 Appendix 3.A . . . 96

4 Integrative Impact Assessment Framework for volcanic eruptions 101 4.1 Introduction . . . 101

4.1.1 Forensic Investigation of Disasters . . . 105

4.1.2 Analytical tools . . . 108

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4.1.3 Data requirements . . . 111

4.2 Integrative Impact Assessment: proposed conceptual framework . . . 112

4.3 Case study: 2011-2012 Cordón Caulle eruption, Chile . . . 118

4.3.1 Acquisition and source of data . . . 118

4.4 Results . . . 121

4.4.1 Preliminary assessment of impacts due to tephra fallout and wind ash remobilisation . . . 122

4.4.2 Application of the proposed framework: the case of the power system in the three target localities . . . 131

4.7 Appendix 4.A - Data Repository . . . 156

4.8 Appendix 4.B - Interviews . . . 156

4.9 Appendix 4.C - Dependency matrix scores . . . 159

5 Conclusions and future perspectives 161 5.1 The importance of the long-lasting secondary hazards within the life cycle of volcanic ash . . . 161

5.2 Necessity of structured and inclusive post-event impact assessments (IA) . . . 164

5.3 Need of collaborative efforts in order to co-design and co-produce efficient post-event Impact Assessments . . . 166

5.4 Future research perspectives . . . 168

A Appendix: Workshop Consensual Document 171 A1 Executive Summary . . . 171

A2 Resumen . . . 174

A3 Introducción . . . 177

A4 Tema I: Gestión de la crisis durante la erupción del Cordón Caulle en 2011 . . . 179

A5 Tema II: Impacto en las Infraestructuras Críticas (IFC) . . . 181

A6 Tema III – Impacto en la agricultura y medio ambiente . . . 185

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A7 Tema IV – Gestión de riesgo volcánico desde las instituciones . . . 187

A8 Conclusiones, desafíos y recomendaciones . . . 191

A9 Agradecimientos . . . 194

A10 Material suplementario . . . 195

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1.1 Impact assessment frameworks . . . 9

1.2 Location of the study area . . . 20

1.3 Timeline of the 2011-2012 CC eruption and associated phenomena . . 21

2.1 WMO classification for lithometeors applied to volcanic ash . . . 33

2.2 2011-2012 CC stratigraphy and sampling location . . . 37

2.3 Schematised W-E transect and deposits of this study . . . 40

2.4 Meteorological conditions: precipitations and wind . . . 42

2.5 Detailed remobilised deposits . . . 43

2.6 Primary and remobilised grainsize distributions . . . 46

2.7 Granulometry features . . . 48

2.8 Backscattered SEM images . . . 50

2.9 Comparison of shape parametes . . . 51

2.10 Grainsize and shape analysis respect to the threshold friction velocity 54 2.11 Interpretation of remobilised deposits . . . 56

A2.1 WMO Lithometeors classification . . . 60

A2.2 Shape factors for primary and remobilised ash . . . 63

3.1 Global distribution of major wind-remobilisation events . . . 68

3.2 Primary tephra-fallout - Unit III. Sampling dataset . . . 72

3.3 Mass flux decays with time at collector S4 . . . 75

3.4 Decay timescales as a function of particle size . . . 76

3.5 Role of meteorological conditions . . . 78

3.6 Streamwsie mass flux model for supply-limited systems . . . 79

A3.1 Threshold friction velocity and grainsize distributions comparison . . 98

4.1 Historical evolution of risk approaches . . . 102

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4.2 Theoretical components and examples of applications of various root

cause tools . . . 109

4.3 Relational diagram for CI interdependencies . . . 113

4.4 Post-event impact assessment methodology proposed in this study . . 114

4.5 Classification of impacts according to their causal order . . . 116

4.6 Theoretical structure of this framework . . . 117

4.7 Detailed impact analysis for the three target localities analysed in this study . . . 124

4.8 Scheme showing an overview of the cascading effects associated with CI . . . 127

4.9 Dependency matrix among different sectors . . . 128

4.10 Dependency color scale . . . 129

4.11 Power network of Argentina . . . 133

4.12 Location of the CI and CF for the three localities . . . 134

4.13 Impacts on the power system: photographies . . . 135

4.14 Power outages record for IJ and SCB . . . 137

4.15 Severity of power outage impacts . . . 138

4.16 Insulator flashover fishbone diagram . . . 141

4.17 Insulator flashover fault tree . . . 143

4.18 Event tree describing the loss of functionality of the power system . . 144

4.19 Event tree describing the loss of functionality of the road network . . 145

4.20 Insulator damage collection template . . . 150

C4.1 Dependency matrix scores among different sectors . . . 159

5.1 Cartoon illustrating the capabilities of the forensic investigation . . . 166

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1.1 Disruption and damage levels for expected impacts on the power sup-

ply system . . . 12

1.2 Main characteristics of the 3 target localities analysed in this study . 22 2.1 Lithometeors classification according to the World Meteorological Office 32 2.2 Summary of distinctive features of primary tephra-fallout versus wind ash-remobilisation deposits. . . 35

2.3 Averaged volume percentage (%) per grainsize class for primary tephra- fallout deposit and remobilised samples. . . 49

A2.1 Averaged descriptive statistics for primary and remobilised samples. . 61

A2.2 Comparison of primary and remobilized shape descriptors for the 3 size classes . . . 62

3.1 Caveats on the estimation of parameters . . . 95

A3.1 Summary of parameters used in this study . . . 96

A3.2 Grainsize classes analysed in this study . . . 97

A3.3 Sample collection periods at the site S4 . . . 97

A3.4 Model input parameters for primary particles . . . 98

4.1 Sectors and systems analyzed in this study . . . 119

4.2 Metadata summary . . . 120

4.3 Impact database features . . . 120

4.4 Impact data resources . . . 122

4.5 Degree of dependency and necessity across systems . . . 131

B4.1 List of interviews . . . 158

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Every eruption offers a unique opportunity to contemplate and understand volcanic phenomena and their imminent interaction with the environment and societies. Un- derstanding the complexity of volcanic eruptions due to the large variability of volcanic processes and products and the multiple dimensions of vulnerability of the increasingly interdependent and interconnected societies, requires an in-depth analysis of past events, not only regarding hazards but also the associated consequences. The most recent event of the Puyehue-Cordón Caulle Volcanic Complex in 2011 (Chile) revealed that even moderate size long-lasting eruptions can initiate a dynamic and stochastic life cycle of volcanic ash whose processes, timescales and impacts are very difficult to evaluate. Characterised by a highly explosive magma of rhyolitic composition, this eruption produced a widespread tephra-fallout deposit with a volume of about ∼1km³, covering more than 100,000 km² in Argentina. Driven by strong winds, the fine ash fraction has been remobilised since the beginning of the eruption as a result of a very effective wind erosion process that is still ongoing.

The complex hazard scenarios, involving both primary tephra fallout and secondary remobilisation, have generated important damages and disruptions across various sectors, particularly in the Argentine provinces of Rio Negro and Neuquén. In 2012, the Civil Protection of Argentina reported a total economic loss of USD 462 million, corresponding to the 0.32 % of the National Annual Budget of the country. However, the economic losses in the long-term due to the wind remobilisation of ash is incal- culable. Significant advances in probabilistic hazard assessments of primary tephra fallout have been achieved in the last couple of decades. However, less importance has been dedicated to the characterisation of wind remobilisation of volcanic ash.

In this thesis, a comprehensive study of the aeolian phenomena, the transport and deposition mechanisms as well as a detailed analysis of the spatial distribution and temporal evolution is conducted.

Since wind erosion of pyroclastic deposits is of interest to volcanological, atmo-

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spheric and soil sciences, a common nomenclature is proposed based on the classification of lithometeors of the World Meteorological Organisation (WMO). Additionally, the correlation of the primary volcanic source with the associated ash-remobilisation highlighted important distinctive features of primary and secondary deposits. This is fundamental for the understanding and modelling of the hazards associated with both phenomena. Timescales of remobilisation events are controlled by a complex interaction of meteorological conditions, surface properties and particle depletion with time. Ash remobilisation follows a two-phase exponential decay with two contrasting timescales: i) a first phase, dominated by fresh volcanic particles, with a mass flux decay of 1-74 days; and ii) a second phase, where soil stabilisation processes are developing, with a mass flux decay of 3-52 months. The depletion of particles plays a major role in volcanic regions where an almost instantaneous release of a large amount of particles subsequently decays with time. An exponential model based on the variation of the erodibility with time is used here to reproduce the mass fluxes of remobilised ash measured in the field.

Due to this combination of primary and secondary hazards, and the important connections among the systems affected, data analysis shows that major impacts of the Cordón Caulle eruption were associated with long and non-linear chains of cascading effects. In order to clearly separate causes and effects, a structured and inclusive post-event impact assessment framework is proposed and applied for the evaluation of damages and disruptions on the critical infrastructures. The forensic analysis of disasters combined with the techniques of the root cause analysis converge in a bow-tie structure that is the core of this framework. The bow-tie consists of the logical tools of a fault tree connected to subsequent event trees that describe the causal order of impacts. The versatility of the logical tools allows for the analysis at different level of detail. The framework presented in this study provides a proactive strategy to reduce volcanic risk by clearly identifying and working to intervene on the root causes of the most vulnerable aspects, rather than facing the immediate symptoms of impacts. The outcomes of this framework serve as a basis for the design of a structured impact assessment of critical infrastructures that could be useful and usable in a future event.

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Chaque éruption volcanique offre une opportunité unique pour contempler et com- prendre les phénomènes associés ainsi que leur interaction immédiate avec les sociétés et l’environnement. La compréhension de la complexité des éruptions volcaniques qui résulte de la grande variabilité des processus et produits volcaniques ainsi que des multiples dimensions de la vulnérabilité des sociétés, de plus en plus interdépen- dantes et interconnectées requiert une analyse approfondie des événements du passé, tant du point de vue des aléas que de leurs conséquences associées. L’événement le plus récent du complexe volcanique Puyehue-Cordón Caulle en 2011 (Chili) a révélé que même les éruptions durables d’intensité modérée peuvent générer un cycle de vie dynamique et stochastique des cendres volcaniques dont les processus, les échelles de temps et les impacts sont difficiles à évaluer. Caractérisée par un magma hautement explosif de composition rhyolitique, cette éruption a généré un dépôt de tephra très étendu, avec un volume d’environ 1 km³, couvrant plus de 100,000 km² en Argentine. Les vents forts ont remobilisé la fraction de cendres fines dès le début de l’éruption au moyen d’un processus d’érosion efficace toujours en cours. Les scénarios complexes d’aléas, incluant les retombées primaires ainsi que la remobilisation secondaire des cendres, ont causé d’importants dommages et perturbations dans de nombreux secteurs, notamment dans les provinces argentines du Rio Negro et à Neuquén. En 2012, la protection civile d’Argentine a rapporté des pertes économiques totales de USD 462 millions, correspondant à 0.32 % du budget annuel national du pays. Cependant, les pertes économiques à long terme dues à la remobilisation des cendres par le vent sont incalculables. Durant les vingt dernières années, des avancées significatives ont été réalisées en modélisation de l’évaluation probabiliste des aléas liés à la chute primaire de tephra. Cependant, une importance moindre a été portée à la caractérisation de la remobilisation par le vent. Par conséquent, cette thèse contient une étude complète des phénomènes éoliens, des mécanismes de transport et de dépôt, ainsi qu’une analyse détaillée de

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la distribution spatio-temporelle.

Etant donné que l’érosion par le vent des dépôts pyroclastiques est devenue un sujet d’intérêt pour la volcanologie, les sciences de l’atmosphère et du sol, une nomenclature commune est proposée, basée sur la classification des lithométéores de l’Organisation météorologique mondiale (OMM). De plus, la corrélation entre la source volcanique primaire et la remobilisation de cendres associée a mis en évidence d’importants aspects distinctifs des dépôts primaires et secondaires. Ce résultat est fondamental pour la compréhension et la modélisation des dangers associés à ces deux phénomènes. Les échelles de temps des événements de remobilisation sont contrôlées par une interaction complexe entre les conditions météorologiques, les propriétés de surface et l’épuisement particules disponibles avec le temps. La remobilisation des cendres suit une loi de décroissance exponentielle en deux phases avec deux échelles de temps distinctes : i) une première phase, dominée par les particules volcaniques récentes, avec une décroissance du flux massique de 1-74 jours; et ii) une seconde phase, où la stabilisation du sol se développe, avec une décroissance du flux massique de 3-52 mois. L’appauvrissement de particules joue un rôle majeur dans les régions volcaniques où une libération presque instantanée d’une grande quantité de particules décroît ensuite avec le temps. Un modèle exponentiel basé sur la variation d’érodabilité dans le temps est proposé ici pour reproduire les flux massiques de cendres remobilisées mesurés sur le terrain.

En raison de cette combinaison d’aléas primaires et secondaires, et les liens importants entre les systemes affectés, l’analyse des données montre que les impacts majeurs de l’éruption du Cordón Caulle ont été associés à des chaînes longues et non linéaires d’effets en cascade. Afin de séparer clairement les causes et les effets, un cadre structuré et inclusif d’évaluation des impacts post-événement est proposé et appliqué pour l’évaluation des dommages et des perturbations sur les infrastructures critiques. L’analyse forensique des désastres, combinée avec les techniques de l’analyse de cause racine, converge vers une structure en « nœud papillon » ou

« bow-tie », qui est au centre de ce cadre d’analyse. La structure « nœud papillon », est composée d’un arbre de défaillances connecté à des arbres d’événements, qui décrivent l’ordre causal des impacts (i.e. dommages physiques, la perte fonc-

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tionnelle, l’impact systémique). La polyvalence de ces outils logiques permet une analyse à différent niveaux de détail. Le cadre d’analyse présenté dans cette étude fournit une stratégie préventive pour la réduction du risque volcanique, en s’efforçant d’intervenir sur ceux-ci, plutôt que de faire face aux symptômes immédiats des impacts. Les résultats de ce cadre pourront servir de base à la conception d’une évaluation structurée de l’impact sur les infrastructures critiques qui pourra s’avérer utile et utilisable lors d’un futur événement.

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Introduction

As a volcanologist I would like to witness and record each single stage of volcanic eruptions, like a graphic reporter that carefully follows every detail of one of the most powerful and astonishing phenomena on Earth. The complex interaction among the large amount of pyroclastic material emitted during explosive eruptions with the atmosphere and the surface will determine the impacts that eruptions produce in the environment and societies. The eruption of Novarupta (USA) on 6th June 1912 was the largest volcanic eruption of the 20th century and one of the 5 largest eruptions recorded in history [Hildreth and Fierstein, 2012]. With about 17 km³ of rhyolitic tephra emitted, the loose deposits of this eruption continue to be remobilised at present. At least 30 major events have been recorded by the Geological Survey of United States since 2003. Remobilised ash have extend up to 250 km in the Gulf of Alaska, and ash clouds have reached 1 to 3.4 km above sea level [Wallace et al., 2015]. With a duration of hours to days, these events often trigger ash alerts emitted by the Alaska Volcano Observatory and the National Weather Service of US¹. The Novarupta eruption demonstrated the huge implications of explosive eruptions at various time and space scales. Ninety-nine years later, the Cordón Caulle volcano erupted on 4th June 2011. Without neglecting the proportions, this eruption showed that even moderate size eruptions can initiate a long-lasting cycle of volcanic ash, whose phenomena and associated impacts require accurate data acquisition strategies in order to understand, constrain and assess its consequences, which ultimately will contribute to volcanic risk reduction.

1https://www.nps.gov/articles/aps-18-1-8.htm

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1.1 Overall view of risk from natural hazards

Although human beings have experienced the force of natural disasters from ancient times, it was not until the Buyin-Zara earthquake struck Iran in 1962 with more that 12,000 fatalities, that the General Assembly of the United Nations (UN) adopted measures against natural disasters². Over the decades, the UN have developed strategies mainly in the field of disaster management including humanitarian aid, technical assistance and development of early warning systems. At the end of the 90s, and after the International Decade for Natural Disaster Reduction (1990-1999) promoted by the UN, the international community was more awared that disaster prevention is the main long-term strategy for reducing disaster impacts. Since then, three World Conferences have determined the evolution from a disaster management towards a risk management perspective for risk reduction. The outcomes of these conferences are the Yokohama Strategy for a safer world (1994), focused on the importance of prevention, preparedness and mitigation to reduce disaster losses [UN-GA, 1994]; the Hyogo Framework for action (2005-2015), focused on the im- plication of the national and local institutions, the improvement of early warning systems and the development of a culture of resilience [ISDR, 2005]; and theSendai Framework for DRR (2015-2030), that recognized that the States have the primary role in risk reduction but with a shared responsability with other stakeholders (e.g.

local government, private sector, communities). The Sendai framework highlighted four priorities for action: i) understanding risk in all its dimensions of hazard, vulnerability, exposure and capacity; ii) strengthening disaster risk governance (national and local sectors); iii) investing in resilience (structural and non-structural measures); and iv) enhancing preparedness for a effective response, to build back better [UNISDR, 2015b]. This research project intends to build on these DRR strategies by yielding some insights in the understanding of the impact and consequences of volcanic eruptions.

The Global Assessment Reports (GAR), promoted by the UN General Assembly for the monitoring and implementation process of the Hyogo and Sendai Frame-

2https://www.undrr.org/about-undrr/history

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works³, are published biannually since 2009. In a volcanic context, a dedicated section to volcanic risk was included for the first time in the 2015-GAR on DRR [UNISDR, 2015a]. Volcanic risk was then defined as a function of hazard, population, exposure and volcanic monitoring capacity. This report also highlighted that, whilst expected losses related to volcanic hazards may be lower than those from other natural hazards at global scale, they can be considerably significant in the affected regions. Furthermore, they concluded that volcanic ash fallout can have widespread impacts on economy and the environment, way beyond the volcanic source areas [UNISDR, 2015a]. Other international efforts include the EU-funded projects EX- PLORIS (2002-2006), ENSURE (2008-2011) and MIAVITA (2008-2012); the New Zealand DEVORA program (2008-2015); and the UK-based consortium STREVA (2012-2019). All these projects have provided fundamental insights into volcanic risk assessments. In particular, the ENSURE framework (Enhancing resilience of communities and territories facing natural and na-tech hazards) was a platform to launch vulnerability-based studies, as a complement to the hazard-based studies.

Within this project, the multiple dimensions of vulnerability (i.e. physical, systemic, social and economic) were coherently established for different exposed systems (e.g.

built environment, critical infrastructures), for the first time in a volcanic setting.

Applications of the ENSURE framework were completed by Galderisi et al. [2013]

for the Vulcano Island (Italy).

Despite this significant effort, no risk framework exists that encompass the complexity of volcanic eruptions. One of the major challenges to the scientific community yet lies in how to combine the risk components. Focused on the purposes of volcanic monitoring and public warning to ensure the safety around a volcano, Fournier d’Albe [1979] was the first author visualizing risk as a sort of mathematical operation under the following formula:

Risk=V alue ·Hazard ·V ulnerability (1.1) Although the concept of vulnerability was loosely defined as the degree of losses, and Fournier d’Albe [1979] considered it as "relatively easy to assess", the author

3https://gar.unisdr.org

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interestingly recognized that preparedness and pre-eruption planning (seen here as capacity) were key to reduce vulnerability.

Paradoxically, whilst our daily life is surrounded by all risk components, their convolution remains umbiguous. Despite the fact that risk components have evolved with time, there is still not a general agreement on their assessment among the volcanological community [Bonadonna et al., 2018]. In this study, the concept established by the UN-General Assembly of risk as a function of hazard, exposure, vulnerability and capacity (Eq. 3.4) is cautiously decomposed, in order to deeply understand the contribution of each constitutive element and to investigate more efficient methods to integrate them.

Risk=f(hazard, exposure, vulnerability, capacity) (1.2) Therefore, in this study we use the terminology adapted from the last 2016 General Assembly of the United Nations, within the Sendai Framework [UN-GA, 2016], unless other references are cited. Accordingly,

• Risk is defined as "the potential loss of life, injury, or destroyed or damaged assets which could occur to a system, society or a community in a specific period of time, determined probabilistically as a function of hazard, exposure, vulnerability and capacity".

• Hazard refers to "the process, phenomenon or human activity that may cause loss of life, injury or other health impacts, property damage, social and economic disruption or environmental degradation".

• Exposure is "the inventory of people, infrastructure, housing, production capacities and other tangible human assets located in hazard -prone areas".

• Vulnerability refers to "the conditions determined by physical, social, economic and environmental factors or processes which increase the susceptibility of an individual, a community, assets or systems to the impacts of hazards".

• Capacity is "the combination of all the strengths, attributes and resources available within an organization, community or society to manage and reduce

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disaster risks and strengthen resilience".

• Disaster Impact is "the total effect, including negative effects (e.g. economic losses) and positive effects (e.g. economic benefits), of a hazardous event or a disaster".

• Disaster Damage is "usually measured in physical units (e.g. kilometers of roads) and describes the total or partial destruction of physical assets, the disruption of basic services and damages to sources of livelihood in the affected areas".

In this study,damage refers to physical harms, andimpactwhen other aspects are involved (e.g. loss of function, economic impacts, social disruption or discomfort).

Additionally, risk implies potential economic losses that are described by the monetary value of the total or partial destruction of physical assets (direct economic losses), and the decline in economic value added as a consequence of direct economic loss and/or human and environmental impacts (indirect losses).

Why is volcanic risk particularly complex with respect to other natural phenomena?

Hazard contributors Volcanic eruptions are rare compared to other natural phenomena. Whilst it is true that on our planet roughly 70 volcanoes erupt each year [Siebert et al., 2015], according to the Knowledge Platform for Disaster Risk Reduc- tion⁴, only 99 volcanic disasters had occurred from 1998 to 2017, corresponding to the 1.4% of the disasters associated with natural phenomena. Contrastingly, floods cause the 43.4%, followed by storms, 28.2%; earthquakes, 7.8%; extreme temper- ature events, 5.2%; landslides, 5.2%; droughts, 4.8%; and wildfires, 3.5%. These numbers demonstrate that each eruption offers a unique opportunity to observe volcanic phenomena, to characterize the associated hazards and to assess the potential impacts.

Volcanic eruptions are a compounded natural phenomenon capable of produc- ing a large variability of processes and products at different time and space scales.

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Volcanic hazards are an intricate function of the eruptive source parameters (e.g.

magma composition, eruptive style) and the local meteorological and surface conditions (e.g. wind direction and speed, topography). As a result, a broad range of volcanic hazards and associated impacts can be expected over the systems that are exposed to a volcano. Primary hazards, as a direct result of both explosive and effu- sive volcanic processes, include pyroclastic density currents, tephra dispersal, tephra fallout, ballistic sedimentation, lava flows and gas release. Secondary hazards im- ply the syn- or post-eruptive reworking transport of volcanic material by wind or water (i.e. wind ash-remobilisation, lahars); or the hazards induced by volcanic phenomena (e.g. flank collapses, volcanic tsunamis and earthquakes) [Sigurdsson, 2015; Jenkins et al., 2015b]. Affected areas are also intrinsically related to the type of hazard; whilst pyroclastic density currents often impact proximal areas to the volcanic vent, tephra dispersal can be spread over wide areas. Some of the volcanic hazards can occur simultaneously, e.g. pyroclastic density currents can occur syn- eruptively with tephra fallout. Some of these multi-hazard cases can lead to very complex long-lasting scenarios, such as is the case of ash that can be remobilised years or even millennia after the source eruption (Chapter 2). Additionally, volcanic products can be of contrasting i) sizes (e.g. bombs and blocks>64 mm, vs fine ash

<64 µm); ii) densities (e.g. blocky lavas vs light pumices); iii) temperatures (e.g.

lava vs lahar mudflows); iii) viscosities (e.g. highly viscous p¯ahoehoe lavas vs low viscous and very fluida’¯a lavas). For all these reasons, volcanic eruptions can cause a large range of consequences that generally overlap in space and time.

Exposure contributors Exposure assessment and its evolution over time are important components of the risk equation. Parallel to the industrial and technological develoment, modern societies are increasingly exposed to natural hazards. It is not only a matter of the global population growth, but also how the population is spatially distributed [Chester et al., 2000] and how the built environment surface have evolved [Pesaresi et al., 2017]. In 2015, more than 1 billion people (14.3% of the global population) lived within 100 km of a Holocene volcano. The number of people living within 100 km of a volcano with at least one significant eruption rose from 227 to 414 million since 1971 to 2015 [Pesaresi et al., 2017; Freire et al.,

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2019]. Additionally, the built environment has increased from 16.3 km² to 39.1 km² from 1975 to 2015 [Pesaresi et al., 2017], showing the high degree of building growth within active and dangerous volcanic areas. Regardless of whether building codes have been applied or not, this urban growth implies a strong dependency on critical infrastructures (CI from now on). World Bank statistics show that all CI services have increased monotonically since 1971. As an example, the electric power con- sumption has increased worldwide from∼875.000 kWh (kiloWatt-hours) in 1971 to

∼3,000.000 kWh in 2014⁵. As a result, the combination of global population growth, rapid urbanization, and increasing dependency to the critical infrastructures allow for important systemic impacts at global level [UNISDR, 2015a].

Vulnerability contributors The least characterized component of the risk equation that also has the largest impact is vulnerability. In a simple way, this concept refers to all the intrinsic features of an exposed element that predispose it to suffer a certain degree of impact. Since volcanic phenomena are largely variable in products and processes, it is very difficult to disentangle the different impacts that an eruption may entail, as they often overlap in time and space, and, consequently, it is very difficult to quantify them. These impacts can involve various physical features (due to multi-hazard contributors), systemic relations (among the different systems exposed), social and political conditions. Although several type of vulnerabilities have been defined in different disciplines, concepts of the ENSURE framework, re- stricted to the physical and systemic dimensions of vulnerability [Foerster et al., 2009; Sapountzaki et al., 2009], will be used throughout this study.

Physical vulnerability includes all these attributes related to the type of material, structure design and quality of the elements and/or systems exposed (e.g. roofs characteristics, number of stories) [Foerster et al., 2009]. More complex, the concept of systemic vulnerability derives from the fact that disaster impacts are usually an intricate chain of direct and indirect effects, where multiple systems interact and evolve constantly over time [Sapountzaki et al., 2009]. This chain is usually known as cascading effects, ripple effects or domino effects (e.g. Gasparini and Garcia- Aristizabal [2014]; Pescaroli and Alexander [2015]; Menoni et al. [2017]). Pescaroli

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and Alexander [2015] defined the cascading effects as the dynamics present in disasters, in which the impact of a physical event, or the development of an initial technological or human failure, generates a sequence of events in the subsystems that result in physical, social or economic disruptions. Thus, a basic impact can trigger other phenomena that lead to consequences with significant magnitudes.

For instance, a systemic impact may occur as the result of some physical damage in a certain system element that is critical for other different system [Sapountzaki et al., 2009]. Enchained failures are very common on critical infrastructures, public facilities and community services, and may lead to more severe impacts than the physical damage itself [Menoni et al., 2017]. The importance of distinguishing be- tweenvulnerability to stress and vulnerability to loss come thus to the fore; the first related to the impact due to a direct stress (hazard-related), and therefore associated with physical processes; and the second due to the "juxtaposed" impacts of interconnected systems [Sapountzaki et al., 2009].

Assessing vulnerability within a volcanic context is not a straightforward task.

There are no existing and standardized frameworks that establish i) which dimensions of vulnerability are applicable and/or relevant to volcanic multi-hazards, and ii) how to efficiently assess these dimensions to, ultimately, quantify them. Once again, the major challenge lies in how to constrain the complex interaction among volcanic multi-hazards, multi-dimensional vulnerability, and exposure, in such a way that legitimately contributes to risk reduction.

Risk assessment in a more widely form, can be measured in terms of theexpected impact [Gasparini and Garcia-Aristizabal, 2014; Menoni et al., 2017]. As a result, impact assessments become a fundamental pillar of volcanic risk assessments. It is important to stress here that vulnerability and impact are different terms that are commonly confused. Whilst vulnerability is strictly related to the intrinsic features of the element exposed, impact concerns the real effect, or expected consequence, over an element, as a response to a certain hazard because -due to its intrinsic features- the element is more or less prone to suffer that particular impact. Depend- ing on the time of the time of analysis, pre-event orpost-event impact assessments can be conducted.

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1.2 Impact studies in a volcanic setting

Impact assessments can be classified in two main branches: i) pre-event impact assessments, and 2)post-event impact assessments [Menoni et al., 2017; Bonadonna et al., in press], both essentially evaluated at different timeframes, before and after the event, as the classification suggests (Fig. 1.1). Depending on the purposes and resolution of the study, and the quality and quantity of data, impact assessments can be carried out quantitatively, qualitatively or as a combination of both.

Exposed

element Vulnerability

conditions Hazard features

Exposure

assessment Vulnerability

assessment Hazard

assessment

Pre-event impact assessment Forecast the probability of potential expected impacton an element with certain vulnerability conditions, in the

case of a given hazard intensity

Exposed

element Vulnerability

conditions Hazard intensity Observedimpact

Post-event impact assessment Assess the impact occurred as a consequence of a past hazardous event

over a system with particular vulnerability conditions

INPUT INPUT INPUT

INPUT

INPUT INPUT

- Empirical data - Analytical/numerical - Experimental - Experts judgement

- Empirical data - Experts judgement

feed

necessary feed for

Figure 1.1: Impact assessment frameworks. Modified from Menoni et al. [2017] and Bonadonna et al. [in press].

1.2.1 Pre-event impact assessment

Pre-event impact assessment (pre-event IA) is designed to forecast the probability of the potential expected impact on exposed elements with certain vulnerability conditions, varying in function of hazard intensity (Fig. 1.1). Pre-event impact assessments result of a combination of hazard, exposure and vulnerability assessments in a given location and at a specific time of analysis. As previously discussed, within the context of volcanic risk, the complexity of both multi-hazard scenarios and the multiple dimensions of vulnerability make difficult to achieve reliable vulnerability assessments that account for both physical and systemic vulnerabilities.

One of the most applied strategies to quantify physical vulnerability is to identify and describe the potential physical damage caused to an element at risk due to a

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given hazard intensity, through the so-calledfragility orvulnerability curves [Wilson et al., 2017; Menoni et al., 2017]. In other words, fragility curves describe the probability of failure of an element at risk depending on the hazard intensity level, due to its degree of weakness. Based on a classification of the different elements exposed, one can categorize their degree of vulnerability as a function of thresholds. Fragility curves are generally derived from real damage data, as well as from analytical and numerical modelling combined with experiments [Wilson et al., 2017; Menoni et al., 2017] (Fig. 1.1). In volcanology, important progress on fragility curves related to tephra fallout, pyroclastic density currents and lahars have been accomplished in the last three decades. Pioneering studies of Blong [1981]; Booth et al. [1983]; Blong [1984]; Spence et al. [1996] and Pomonis et al. [1999] contributed to the development of fragility curves for roof collapse due to tephra fallout load [Spence et al., 2005]; and window glazing due to pressure, and failure of reinforced concrete frames due to lateral load, both related to pyroclastic density currents [Spence et al., 2004;

Petrazzuoli and Zuccaro, 2004]. Damage scales for dynamic pressure impact of pyroclastic density currents have also been developed by Baxter et al. [2005]. For the case of lahars, Jenkins et al. [2015a] developed fragility curves of masonry buildings due to the impact pressure, and more recently, Daga et al. [2018] have investigated failure models and developed fragility curves associated with lahar depth to road bridges. Experimental and empirical studies of Wardman et al. [2012, 2014]; López et al. [2016] and Lopez Chachalo [2017] elucidated the physical processes behind the flashover of electrical insulators in the power network due to the contamination of tephra; however, specific fragility curves do not exist yet. Finally, fragility curves of the transportation network (i.e. road, rail, airports, maritime transportation) due to the loss of visibility because of the ash settling have been developed by Blake et al.

[2016, 2017b]. Additionally, some experimental advances on the causes of skid resistance of roads due to the accumulation of tephra have also been conducted by Blake et al. [2017a]. Further readings can be found in the exhaustive review conducted by Bonadonna et al. [in press].

It is important to highlight that physical vulnerability studies focused on i) the identification of controlling vulnerability factors, ii) the modelling of failure processes

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that lead to an impact, based on various physical measures, such as pressure, load or visibility, iii) the categorization of the studied element in vulnerability classes, and iv) the definition of damage/impact scales or states. This analysis is essentially complex due to the multi-hazard character of volcanic eruptions (few sophisticated studies have combined multi-hazard scenarios of pyroclastic density currents, tephra fallout and earthquakes, [Zuccaro and Ianniello, 2004; Esposti Ongaro et al., 2007, 2008; Zuccaro et al., 2004]), and the scarcity of statistically meaningful and real damage data, which does not allow a regular improvement of fragility curves [Wilson et al., 2014], as it is the case in seismic risk, that relies on substantially larger damage datasets [Menoni et al., 2017].

Furthermore, when trying to constrain systemic vulnerability, the issue becomes particularly challenging. According to Sapountzaki et al. [2009] and Van Der Veen and Logtmeijer [2005], systemic vulnerability can be characterized in terms ofinter- dependence, transferability and redundancy. Interdependence is the degree to which an activity or system relates to each other (e.g. pumps of the water system depend on electricity to keep functioning); redundancy is the degree of criticality of an element in a network and it is intrinsically related to the ability to respond by using substitutes (e.g. a secondary road if the main road is impacted); and transferability refers to the capacity to transfer or relocate a function if the system is not able to supply it (e.g. the use of helicopters if the roads are blocked). Systemic vulnerability is therefore intrinsically associated with the functionality of CI.

At this time there is not any guideline, framework or approach to efficiently quantify systemic vulnerability in a volcanic context. The pioneering study of Wilson et al. [2014] summarized the impact to critical CI due to tephra fallout, pyroclastic density currents, lava flows and lahars, based on an extensive catalogue of historical observations from several eruptions. Owing to difficulties in identifying clear impact trends as a function of a single hazard parameter (as it is done for physical vulnerability), the authors proposed a conceptual model with a continuum impact scale, from tolerance, through disruption and right up to damage, with increasing hazard intensity. Tolerance means that CI retain all functions and continue to operate uninterrupted throughout volcanic eruption. Disruption refers to impacted

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Level Level 0 Level 1 Level 2 Level 3

Description No damage Cleaning required Repair required Replacement or fi- nancially expensive repair

Threshold

(mm) <3 3-10 10-100 >100

Damage No damage

Possible abrassion to some moving parts, infiltration of tephra into substantial gravel

Damage to exposed equipment especially those with moving parts, possible elctrical line breakage

Structural damage to some equipment at generation and transmis- sion/distribution sites, irreparable damage to moving parts

Disruption No disruption

Temporary disruption caused by insulator flashover, cleaning and repair

Widespread disruption to electrical supply with possible permanent disruption

Table 1.1: Disruption and damage levels for expected impacts on the power supply system as a function of tephra-fallout thickness (mm), from Wilson et al. [2014].

CI by volcanic hazards causing it to operate at reduced function until restoration is undertaken. Finally, damage is reserved when physical damage occurs until repair is undertaken. Based on this approach, Wilson et al. [2014] proposed scales of Disruption and Damage States (DDS) for expected impacts to CI due to tephra fallout (i.e. DDS as a function of tephra thickness), pyroclastic density currents (i.e. DDS as a function of dynamic pressure), lava flows (i.e. DDS as a function of flow depth), and lahar velocity (i.e. DDS as a function of flow velocity). These DDS scales are specified for power and water supply, wastewater network, airports, roads, rail, marine transportation, vehicles, communications, buildings and critical components. An example of the most refined scale associated with the tephra fallout over electrical power supply system is shown in the Table 1.1. In a similar way, Jenkins et al. [2015b] categorised the impacts on CI per sector in five DDS levels (D0 to D5), where D0 corresponds tono damage, and D5 to a level beyond economic repair. Other authors have also proposed different metrics for the loss of functionality of CI (e.g. full service, rolling outages, no electricity service) [Hayes et al., 2016;

Deligne et al., 2017; Blake et al., 2017c].

Although these DDS scales are a first attempt to correlate both physical damage and systemic impact to a given hazard intensity metric, the intricated relations of a

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complex chain of impacts, that are commonly associated with CI, is not really considered. The complexity of impacts on CI cannot only be related to a single hazard parameter (e.g. tephra thickness), or to a single vulnerability source (e.g. physical aspects of components), disregarding key contributions of systemic vulnerability and system capacity to respond. This was demonstrated by Craig et al. [2016a], when trying to apply both Wilson et al. [2014] and Jenkins et al. [2015b] DDS scales to the real case study of the 2011-2012 eruption of the Cordón Caulle volcano (Chile).

Craig et al. [2016a] found that impacts were mainly related to important systemic disruptions rather than long-term physical damage, and, that most systems recover after clean-up and rapid response measures, all these factors independent of tephra thickness. Therefore, impact dynamics is clearly underestimated by using these scales.

Whilst it is true that the proposed scales represent an important step on the classification of impacts on CI, they are still an inventory with a mixture of various physical damages and disruptions which are not clearly interconnected (See Table 1.1). The concepts of physical (e.g. CI design), and systemic (e.g. inter- dependency) vulnerabilities, as well as the effects of rapid response and mitigation measures, crucial for CI functionality, are not considered. Furthermore, the effect of secondary hazards on the long-term disruption of CI, particularly associated with wind-remobilisation of tephra, is not considered either. As a consequence, the use of these DDS scales to forecast expected impacts in pre-event IA is still not suitable.

To summarize, pre-event IA requires reliable and comprehensive hazard, exposure and vulnerability assessments. However, these assessments need to be fed by empirical (real) impact data, analytical and numerical modelling, experimental data and experts judgement (Fig. 1.1). It is the reason why post-event impact assessments are indispensable to capture the complexity of real events and to improve pre-event IA.

1.2.2 Post-event impact assessment

Post-event impact assessment (post-event IA) is designed to assess the impacts that occurred as a consequence of a hazardous event affecting a system characterized by

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certain vulnerability conditions (Fig. 1.1). Fed by empirical impact data and experts judgment, post-event IA will provide the information to elicit what types of impact occurred associated to a specific event, and also to prioritise areas of intervention in the case of subsequent cascading consequences. The outcomes of a post-event IA are indispensable to improve IA in the case of future events [Menoni et al., 2017;

Bonadonna et al., in press] (Fig. 1.1).

In volcanology, existing post-event IA, mainly qualitative, describe impacts in relation to a single hazard parameter (e.g. tephra thickness). Quantitatively, the most complete studies have been conducted for the evaluation of physical damage of buildings due to tephra fallout, pyroclastic density currents and lahars (e.g. Blong [1984, 2003]; Spence et al. [1996, 2005]; Jenkins et al. [2015a]; Hayes et al. [2019]);

and these studies have led to the development and improvement of fragility curves as previously discussed. One of the earliest post-event IA dedicated to CI was conducted by Johnston et al. [2000]. Based on a comparison of 2 similar volcanic eruptions but occurring 50 years apart, Johnston et al. [2000] demonstrated the importance of societal vulnerability in indirect impacts involving social and economic losses. Stewart et al. [2006], for the first time, proposed a simple impact model for the water supply system, based on measurements of the tephra composition of several eruptions, and its relation with the acidification and soluble contaminants of potable water. Some other studies compiling impacts on CI, generally related to tephra thickness, are the extensive post-event IA of Wilson et al. [2011, 2012];

Magill et al. [2013]; Wilson et al. [2014]; Craig et al. [2016a]; Elissondo et al. [2016a].

Interestingly, all these studies highlighted the relevance of impacts associated with secondary hazards, in particular, wind-remobilisation of volcanic ash and lahars, as they are a source of important disruptions. Finally, significant advances on the understanding of impacts related to public health (e.g. Horwell and Baxter [2006];

Carlsen et al. [2012]; Baxter and Horwell [2015]), and agriculture (e.g. Thorarinsson [1979]; Wilson et al. [2011]; Craig et al. [2016b]; Forte et al. [2018]), which are particularly important for both society and environment, have been done.

From these post-event IA, we can conclude that most of disaster impacts are related to complex systemic interconnections which cannot be related to a single

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hazard parameter or vulnerability aspect, and, therefore, they are very difficult to quantify. A more recent approach to investigate past events, in a more holistic and structured manner, have been developed within the FORensic INvestigation of Disasters program (FORIN) of the Integrated Research on Disaster Risk (IRDR)⁶, launched by the International Council for Science (ICSU), the International Social Science Council (ISSC) and the UNISDR [Burton, 2010]. This approach aims to fully integrate the different aspects of risk, combining natural, socio-economic, health and engineering sciences as well as policy-making. The core of this approach is to an- swer the what, who, when, how and why the different impacts occur, through a systematic and integrative analysis of the main drivers, or the so-called,root causes of impacts [Blaikie et al., 1994; Oliver-Smith et al., 2013]. FORIN framework as a whole provided the first conceptual cornerstone towards more deeper and integrative impact studies [Burton, 2010; Fraser et al., 2014]. However, current FORIN application studies are more oriented on the social and political context, rather than developing clear and technical methodologies that can be applied, as also stated by Mendoza [2019].

In the field of volcanic risk, forensic investigation is in its infancy stages. First studies looking from a retrospective and a multi-disciplinary approach have been carried on in the STREVA project (Strengthening resilience in volcanic areas)⁷. Based on dedicated workshops, involving researchers and in-country stakeholders, STREVA methodology combined the physical processes of various past eruptions and its associated impacts into a holistic analysis of the social and physical vulnerabilities of the communities (e.g. [Wilkinson, 2013; Armijos and Few, 2017; Armijos et al., 2017; Few et al., 2017; Hicks and Few, 2015; Sword-Daniels et al., 2015; Pyle et al., 2018; Barclay et al., 2019]). Another study achieved by Wantim et al. [2018]

proposed a first classification of impacts based on a detailed post-event IA.

Despite of the last decades efforts, volcanic post-event IAs have not yet produced the amount of data required to better constrain pre-event impact assessments that allow to forecast impacts. The following limitations are identified:

,→ Due to the lack of quantifiable data collection guidelines, most of analysis

6http://www.irdrinternational.org/projects/forin/about-forin/

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are limited to a qualitative (narrative) description. As a result, reliable impact data that can support the development of fragility curves and account for the complex systemic relations that lead to cascading effects is very scarce. Innovative strategies are then required to better understand the causes of impacts, and therefore identify areas where interventions and mitigation measures should be prioritized.

,→ Individual post-event IAs are based on a specific realised event. A complete catalogue based on both systematic data collection and structured analysis is therefore required to construct robust conclusions in the future (and, eventually, develop accurate fragility curves and impact scales).

Since these needs are essential to DRR, other perspectives linked to the forensic investigation of disasters have been implemented by the European Commission.

Notably, the efforts made by the Joint Research Centre of the Institute for the Protection and Security of the Citizen [De Groeve et al., 2013, 2014, 2015] concluded in a guidance to record and share impact data. In addition, the EU-funded projects IDEA (Improving Damage Assessments to Enhance cost-benefit Analysis, 2014) focused on floods, MATRIX (New Multi-Hazard and Multi-Risk Assessments Methods for Europe, 2010-2013), and SYNER-G (Systemic Seismic Vulnerability and Risk Analysis for Buildings, Lifeline Networks and Infrastructures Safety Gain, 2009-2012), both focused on seismic risk, provided important insights on forensic methodologies. Finally, from the Reinsurance perspective (Zurich Re)⁸, the need to build more resilient societies against floods drove to the PERC methodology (Post-event Review Capability, 2013) [Venkateswaran et al., 2015].

An integrative forensic analysis framework could help assessing past events, in order to better understand what could be done to reduce potential damages and impacts. This thesis aims to contribute with a novel approach for impact assessment accounting for the entangled relation of physical and systemic vulnerabilities of critical infrastructures, and the long-lasting consequences associated with tephra fallout. The case study, focused on the Cordón Caulle (CC) eruption occurred from June 2011 to December 2012 [OVDAS, 2012], demonstrated that society faces high risk from even small to moderate size eruptions. Indeed, this eruption is a

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clear example where various sectors, strongly impacted by tephra fallout, triggered a large chain of cascading effects where systemic vulnerability played a major role.

Additionally, the CC eruption demonstrated that secondary hazards, in particular wind-remobilisation of ash, lead to long-lasting consequences that are still generating disruptions and health issues in the communities exposed.

1.3 The life cycle of volcanic ash

Fragmentation of magma during explosive volcanic eruptions generates a large amount of particles of various sizes that are injected into the atmosphere. This is the beginning of the cycle of ash (i.e. particles <2 mm) that involves complex transport and deposition mechanisms. Primary processes involving particles include both dispersal by wind in the atmosphere and subsequent sedimentation (i.e. tephra fallout) and hot and fast flows travelling down the slopes of volcanoes (i.e. pyroclastic density currents, PDCs) [Fisher, 1961]. Once deposited, loose particles are involved in a continuous process triggered by the action of erosive (implying motion), compaction and weathering (in situ) agents [Cas and Wright, 1987]. Within the life cycle of ash, we focus here on the primary fallout and its subsequent remobilisation by wind. In particular, wind-remobilisation of volcanic ash has been often neglected within the volcanology community despite demonstrating its role in aggravating the impacts caused by primary tephra fallout [Hincks et al., 2006; Wilson et al., 2011; Baxter and Horwell, 2015; Carlsen et al., 2015; Forte et al., 2018].

The importance of ash remobilisation was at first mentioned by Fisher and Schmincke [1984] and Cas and Wright [1987]. However, it was not until Hobbs et al. [1983] characterized the size range of particles prone to be resuspended in the areas affected by the 1981-Mount St. Helens eruption (USA), that remobilisation of ash was seen as a serious trigger factor of loss of visibility causing disruption impacts after the eruptions. The recent ash remobilisation events associated with both Grímsvötn (2011) and Eyjafjallajökull (2010) eruptions in Iceland, the Hudson (1991) and Cordón Caulle (2011-2012) eruptions in Chile, and the Novarupta (1912) eruption in USA, demonstrated that this secondary hazard has the potential to pose

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significant threats leading to health impacts and society disruptions, immediately after the eruption, as well as in the medium- and long-term.

Existing studies of ash remobilisation have been focused on i) the associated impacts [Bitschene, 1995; Hincks et al., 2006; Hadley et al., 2004; Wilson et al., 2011; Carlsen et al., 2015; Forte et al., 2018], the characterization of ii) the associated deposits [Hobbs et al., 1983; Liu et al., 2014; Miwa et al., 2018], and iii) the physical processes through laboratory experiments [Douillet et al., 2014; Del Bello et al., 2018], numerical modelling [Barsotti et al., 2010; Leadbetter et al., 2012; Folch et al., 2014; Reckziegel et al., 2016; Mingari et al., 2017], and comparative studies with mineral dust and sand erosion [Thorsteinsson et al., 2012; Arnalds et al., 2013;

Langmann, 2013; Panebianco et al., 2017].

Despite the significant advances of the last couple of decades, the understanding of ash-remobilisation processes is still very scarce. Previous studies allow to predict that wind-remobilisation of volcanic ash is a global concern as:

,→ It can affect areas larger than the ones originally affected by primary tephra fallout;

,→ It can produce considerable high secondary ash clouds from random sources that can be erroneously interpreted as primary volcanic eruptions;

,→ It is complex not only because it depends on primary volcanic sources, but also on local meteorological and surface conditions;

,→ Its intermittent behaviour, but long-lasting occurrence is very difficult to forecast.

In order to build hazard scenarios and improve the numerical models, a comprehensive understanding of the life cycle of volcanic ash, with a special focus on the phenomena characterization, the analysis of both primary and secondary deposits and products, as well as the estimation of the associated physical processes, timescales and impacts, is therefore fundamental.

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1.4 The case study of the 2011-2012 Cordón Caulle eruption

Located in Chile, the Puyehue-Cordón Caulle Volcanic Complex is a Pleistocene- Holocene aged (i.e. <2.6 Ma) that belongs to the Southern Volcanic Zone of the Central Andres (Fig. 1.2). This Complex comprises a 20 km-long NW-SE oriented fissure system (Cordón Caulle, CC), and a stratovolcano topped by a summit caldera to the SE (Puyehue). At least 11 historical eruptions have occurred in the last 250 years (1751-2011) [Lara et al., 2006; Global Volcanism Program, 2013b], all of them of VEI⁹2, except for the VEI 3 eruptions in 1921 and 1960, and the VEI 4-5 eruption in 2011-2012 [Castro et al., 2013; Pistolesi et al., 2015; Bonadonna et al., 2015c].

There is a relatively high frequency of eruptions, with 1 eruption of VEI 3 or larger each 40 years, recorded regularly since 1893, with an historical hiatus between 1759 and 1893 because the area was not populated [Lara et al., 2006].

The 2011-2012 CC eruption was a long-lasting rhyolitic eruption classified as small-moderate size to sub-plinian, with a cumulative volume of 1 km³ and a VEI 4-5 [Pistolesi et al., 2015] (Fig. 1.2b). The resulting tephra-fallout deposit was characterized by a multi-layered stratigraphy due to fluctuating plume heights and wind directions (Fig. 1.3). The climatic phase developed plumes with heights between ca.

9-12 km above the vent during the first 3-4 days, 4-9 km during the following week and <6 km after the 14 of June (Fig. 1.3). Due to the prevailing eastern winds, a wide area in Argentina (>100,000 km²) was affected by tephra dispersion and sedimentation through the whole eruption (Fig. 1.2b). Thickness and grainsize of the deposited tephra varied with distance from the emission source. Whilst proximal areas such as Villa La Angostura, located 54 km east from the vent, received 15-17 cm of coarse to fine ash, distal areas such as Ingeniero Jacobacci, located 240 km SE of the vent, received 5-7 cm of very fine ash [Pistolesi et al., 2015] (Fig. 1.2b).

9Volcanic Explosivity Index [Newhall and Self, 1982]

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Figure 1.2: Location of the study area.