Hazard interaction analysis for multi-hazard risk assessment: a systematic  classification based on hazard-forming environment

Liu, Baoyin; Siu, Yim Ling; Mitchell, Gordon

doi:10.5194/nhess-16-629-2016

Cited by 96 publications

(50 citation statements)

References 26 publications

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“…This statement also notes the need for agreement within the geoscience community on how to model cascades of natural hazards. This call joins many previous calls (Delmonaco et al, 2007;Kappes et al, 2012;Marzocchi et al, 2012;Gill and Malamud, 2014;Liu et al, 2016) encouraging the assessment of interacting natural hazards and their integration into multi-hazard methodologies. Assessing interaction networks is therefore important as they are a fundamental part of hazard and disaster events.…”

Section: Risk Assessments and Risk Management Benefit By Better Matchmentioning

confidence: 51%

“…Methodologies to identify and visualise potential natural hazard interactions also exist (e.g. Tarvainen et al, 2006;Han et al, 2007;De Pippo et al, 2008;Kappes et al, 2010;van Westen et al, 2014;Gill and Malamud, 2014;Liu et al, 2016), including a progression towards more quantitative approaches (e.g. Neri et al, 2013;Marzocchi et al, 2012).…”

Section: Single Vs Multi-hazardmentioning

confidence: 99%

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Hazard interactions and interaction networks (cascades) within multi-hazard methodologies

2016

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Abstract. This paper combines research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between multi-layer single-hazard approaches and multi-hazard approaches that integrate such interactions. This synthesis suggests that ignoring interactions between important environmental and anthropogenic processes could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. In this paper we proceed to present an enhanced multi-hazard framework through the following steps: (i) description and definition of three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment, (ii) outlining of three types of interaction relationship (triggering, increased probability, and catalysis/impedance), and (iii) assessment of the importance of networks of interactions (cascades) through case study examples (based on the literature, field observations and semi-structured interviews). We further propose two visualisation frameworks to represent these networks of interactions: hazard interaction matrices and hazard/process flow diagrams. Our approach reinforces the importance of integrating interactions between different aspects of the Earth system, together with human activity, into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability between successive hazards, and (iii) prioritise resource allocation for mitigation and disaster risk reduction.

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Section: Risk Assessments and Risk Management Benefit By Better Matchmentioning

confidence: 51%

Section: Single Vs Multi-hazardmentioning

confidence: 99%

Hazard interactions and interaction networks (cascades) within multi-hazard methodologies

2016

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“…Another example can be found in the Global Earthquake Model, which aims to assess so-called integrated risk by combining hazard (seismic), exposure and vulnerability of structures with metrics of socio-economic vulnerability and resilience to seismic risk (Burton and Silva, 2015). Multi-risk assessment studies resulting from a combination of multiple hazards and vulnerabilities are also receiving growing scientific attention (Eakin et al, 2017;Gallina et al, 2016;Karagiorgos et al, 2016;Liu et al, 2016;Markolf et al, 2018;Wahl et al, 2015;Zscheischler et al, 2018). These new approaches are seen with increasing international interest, particularly with regard to climate change adaptation (Balbi et al, 2010;Terzi et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

The whole is greater than the sum of its parts: a holistic graph-based assessment approach for natural hazard risk of complex systems

Arosio

Martina

Figueiredo

2020

Nat. Hazards Earth Syst. Sci.

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Abstract. Assessing the risk of complex systems to natural hazards is an important but challenging problem. In today's intricate socio-technological world, characterized by strong urbanization and technological trends, the connections and interdependencies between exposed elements are crucial. These complex relationships call for a paradigm shift in collective risk assessments, from a reductionist approach to a holistic one. Most commonly, the risk of a system is estimated through a reductionist approach, based on the sum of the risk evaluated individually at each of its elements. In contrast, a holistic approach considers the whole system to be a unique entity of interconnected elements, where those connections are taken into account in order to assess risk more thoroughly. To support this paradigm shift, this paper proposes a holistic approach to analyse risk in complex systems based on the construction and study of a graph, the mathematical structure to model connections between elements. We demonstrate that representing a complex system such as an urban settlement by means of a graph, and using the techniques made available by the branch of mathematics called graph theory, will have at least two advantages. First, it is possible to establish analogies between certain graph metrics (e.g. authority, degree and hub values) and the risk variables (exposure, vulnerability and resilience) and leverage these analogies to obtain a deeper knowledge of the exposed system to a hazard (structure, weaknesses, etc.). Second, it is possible to use the graph as a tool to propagate the damage into the system, for not only direct but also indirect and cascading effects, and, ultimately, to better understand the risk mechanisms of natural hazards in complex systems. The feasibility of the proposed approach is illustrated by an application to a pilot study in Mexico City.

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“… Field observations (Section 2.4). Reconnaissance trips, giving an overview of the Guatemala's hazard-forming environment (defined in Liu et al, 2016).…”

Section: Regional Interaction Frameworkmentioning

confidence: 99%

“…We reduce the likelihood of missing key hazards by reviewing multiple evidence types to ensure a comprehensive and evidenced classification. We include 26 to 32 more hazard subtypes than existing regional interaction frameworks (e.g., Tarvainen et al, 2006;Kappes et al, 2010;Liu et al, 2016). In addition to the 37 natural hazard sub-types in Table 8, we could also consider how a changing climate influences natural hazards (see McGuire and Maslin, 2012, for a full discussion), or other groups of processes, such as biological hazards (e.g., epidemics), technological hazards (e.g., structural collapse), and anthropogenic processes (e.g., vegetation removal).…”

Section: Relevant Natural Hazards and Hazards Classificationmentioning

confidence: 99%

Regional Interaction Frameworks to Support Multi-Hazard Approaches to Disaster Risk Reduction (With an Application to Guatemala)

Gill

Malamud

Barillas³

et al. 2018

Preprint

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Abstract. Here we present an interdisciplinary approach to developing comprehensive, systematic and evidenced regional interaction frameworks to support multi-hazard approaches to disaster risk reduction. We apply this approach in Guatemala, developing regional interaction frameworks for national and sub-national (Southern Highlands) spatial extents. The regional interaction frameworks are constructed and populated using five evidence types: (i) publications and reports (internationally accessible) (93 peer-review and 76 grey literature sources); (ii) publications and reports (locally accessible civil protection bulletins) (267 bulletins from 11 June 2010 to 15 October 2010); (iii) field observations; (iv) stakeholder interviews (19 semi-structured interviews) (v) stakeholder workshop results (16 participants). These five evidence types were synthesised to determine an appropriate natural hazards classification scheme for Guatemala, with 6 natural hazard groups, 19 hazard types, and 37 hazard sub-types. For a national spatial extent in Guatemala, we proceed to construct and populate a regional interaction framework (matrix form), identifying 50 possible interactions between 19 hazard types. For a sub-national spatial extent (Southern Highlands of Guatemala), we construct and populate a regional interaction framework (matrix form), identifying 114 possible interactions between 33 hazard sub-types relevant in the Southern Highlands. We also use this evidence to explore networks of multi-hazard interactions and anthropogenic processes that can trigger natural hazards. We present this information through accessible visualisations to improve understanding of multi-hazard interactions in Guatemala. We believe that our regional interaction frameworks approach to multi-hazards is scalable, working at global to local scales with differing resolutions of information. Our approach can be replicated in other geographical settings, with regional interaction frameworks helping to enhance cross-institutional dialogue on hazard interactions, and their likelihood and potential impacts.

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Hazard interaction analysis for multi-hazard risk assessment: a systematic classification based on hazard-forming environment

Cited by 96 publications

References 26 publications

Hazard interactions and interaction networks (cascades) within multi-hazard methodologies

Hazard interactions and interaction networks (cascades) within multi-hazard methodologies

The whole is greater than the sum of its parts: a holistic graph-based assessment approach for natural hazard risk of complex systems

Regional Interaction Frameworks to Support Multi-Hazard Approaches to Disaster Risk Reduction (With an Application to Guatemala)

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