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Understanding Compound, Interconnected, Interacting and
Cascading Risks: A Holistic Framework
Gianluca Pescaroli(1) and David Alexander (1)
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Corresponding author: G. Pescaroli, gianluca.pescaroli @gmail.com
This is the pre-printed and pre-edited version of the following article:
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Pescaroli, G., & Alexander, D. E. (2018). “Understanding Compound, Interconnected,
Interacting and Cascading Risks: A Holistic Framework”. Risk Analysis, doi:
10.1111/risa.13128 . It has been published in final form at:
https://onlinelibrary.wiley.com/doi/full/10.1111/risa.13128
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This article may be used for non-commercial purposes in accordance with Conditions
for Self-Archiving and Green Open Access. Please refer and cite the edited version
available on Risk Analysis’s website. Please also note that this version may still have
some inconsistencies e.g. in the text and in the references.
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1) Institute for Risk and Disaster Reduction, University College London, London, United
Kingdom
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Abstract
In recent years there has been a gradual increase in research literature on the challenges of
interconnected, compound, interacting, and cascading risks. These concepts are becoming
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ever more central to the resilience debate. They aggregate elements of climate change
adaptation, critical infrastructure protection and societal resilience in the face of complex, high-
impact events. However, despite the potential of these concepts to link together diverse
disciplines, scholars and practitioners need to avoid treating them in a superficial or
ambiguous manner. Overlapping uses and definitions could generate confusion and lead to
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the duplication of research effort. This paper gives an overview of the state of the art regarding
compound, interconnected, interacting, and cascading risks. It is intended to help build a
coherent basis for the implementation of the Sendai Framework for Disaster Risk Reduction
(SFDRR). The main objective is to propose a holistic framework that highlights the
complementarities of the four kinds of complex risk in a manner that is designed to support
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the work of researchers and policy makers. This paper suggests how compound,
interconnected, interacting and cascading risks could be used, with little or no redundancy, as
inputs to new analyses and decisional tools designed to support the implementation of the
SFDRR. The findings can be used to improve policy recommendations and support tools for
emergency and crisis management, such as scenario building and impact trees, thus
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contributing to the achievement of a system-wide approach to resilience.
Key Words: compounding risk, interconnected risk, interacting risk, cascading risk, societal
resilience, critical infrastructure, Sendai Framework for Disaster Risk Reduction.
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1. Introduction
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The development of concepts that describe compound, interconnected, interacting and
cascading risks is part of the process of creating new knowledge in order to increase societal
resilience. Since the 1990s and the International Decade for Natural Disaster Reduction, our
understanding of risk in the community has been influenced by the evolving role of science
and technology (Aitsi-Selmi et al., 2016). Different perspectives from disciplines such as
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engineering and social sciences were merged together to provide a coherent approach to risk
analysis, using a basis of knowledge about system performance and uncertainty assessments
(Aven and Kristensen, 2005). Events such as the 2004 Indian Ocean Tsunami lead to the
development of the Hyogo Framework for Action, which provided an international plan
endorsed by the United Nations (UN) to reduce disaster losses and build resilience between
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2005 and 2015. According to the United Nations Office for Disaster Risk Reduction (UNISDR),
disaster risk can be 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”
(www. preventionweb.net, updated 2 February 2017). Here, vulnerability is defined as those
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“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” (www. preventionweb.net, updated 2 February 2017).
The main consequence of this is a degree of circularity, in which the vulnerability of a system
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makes it more sensitive to risk, reflecting the complexity of socio-economic factors that interact
with the physical aspects of hazard (Alexander, 1993; Intergovernmental Panel on Climate
Change, 2012; United Nations Strategy for Disaster Risk Reduction, 2015). The work of the
Society for Risk Analysis has highlighted the existence of other multidisciplinary aspects that
have been used for models and theoretical frameworks, recommending a broad qualitative
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definition of risk and considering different types of ways of describing risk (Aven, 2010; 2016).
At the same time, it has been suggested that there is a tendency in the engineering community
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to associate the definition of risk with the quantification of probabilities, but in order to be
effective, the analysis of systemic accidents and unexpected events must address also
uncertainties and their root causes (Aven, 2010). However, the literature suggests that further
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development is needed “especially in relation to situations of large or deep uncertainty and
emerging risk” (Aven, 2016).The complexity of networked society and the uncertainties
inherent in threats, such as geomagnetic storms, challenge our approach to crisis
management. After a long debate on unknown, low-probability, and high-impact events, it has
been suggested that extreme scenarios could be more common that was previously
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supposed, and that this requires us to develop a new understanding of their drivers (Sornette,
2009).
The problem involves the whole anthropogenic domain. It cannot be limited to the analysis of
hazards and must combine different human and natural factors that affect the magnitude of
risks. It has also been shown that crises challenge the process of governance. They cross
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borders and involve many different aspects of society and the environment (Ansell et al., 2010;
Boin et al., 2014; Galaz et al., 2011). On the other hand, global networks are becoming more
interdependent and it is becoming harder to understand their vulnerabilities. In approaching
safety issues and risk analysis strategies, a paradigm shift is required (Helbing, 2013). There
is a need for a system-wide approach to resilience that is capable of employing penetrating
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analyses, innovative methods, and new tools in order to improve the operational management
of complexity (Linkov et al., 2014).
In this context, in 2015 the UN member states adopted the Sendai Framework for
Disaster Risk Reduction (SFDRR), which was designed to improve upon the Hyogo
Framework for Action. This document identifies seven targets and four priorities areas to
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“prevent new and reduce existing disaster risk”, including better action to reduce exposure
and vulnerabilities. The SFDRR defines “the need for improved understanding of disaster
risk in all its dimensions of exposure, vulnerability and hazard characteristics”. The strategy
for implementing the SFDRR requires innovation in this field and highlights the need to
create policies on key topics such as the security of critical infrastructure and the mitigation
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of contextual factors in crisis situations (UNISDR, 2015).
Notwithstanding the rise of three factormulti-hazard approaches, multidisciplinary
integrations and holistic knowledge sharing (Aitsi-Selmi et al., 2016)--there are persistent
gaps in the research and they need to be addressed. Our limited background knowledge
of emerging risks suggests the need to improve assessment tools, and to achieve an
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adaptive balance between different strategies and mitigation measures (Aven, 2016). The
fragmentation of the literature on compound, interconnected, interacting and cascading
risks can be seen as a part of this challenge, and obstacles must be overcome as the field
develops (Kappes et al., 2012; Leonard et al., 2014; Pescaroli and Alexander, 2015).
Although concepts are very different in their possible applications, there is a tendency to
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use them as synonyms, which tends to cause redundancy and confusion.
This paper aims to highlight the complementarities and differences inherent in compound,
interconnected, interacting and cascading risks. It aims to be compatible with the
implementation of the SFDRR by supporting a better understanding of disaster risk and
clarifying the underlying risk drivers. New forms of risk are still addressed generically in the
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framework and more clarity and precision are needed. Indeed, as noted in the literature,
“the way we understand and describe risk strongly influences the way risk is analysed and
hence it may have serious implications for risk management and decision making” (Aven,
2016). Our aim is to produce a holistic framework that can support focused actions and
research that will help reduce exposure and vulnerability and increase possible
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complementarities instead of duplicating efforts in research and practice. This is essential
in order to maximise the impact and effectiveness of new political and practical
recommendations that are steps in the implementation of SFDRR. as shown in the recently
published Words into Action Guidelines on National Disaster Risk Assessment where all
the relevant elements are included (UNISDR, 2017). In other words, the scope of this paper
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is to help scholars and practitioners to distinguish the different components of complex
events that tend to overlap, supporting more focused actions in terms of measures for
operational resilience and risk modelling.
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To begin with, this paper focuses on compound events, which have been associated mostly
with natural hazards and climate change. Secondly, it approaches the fundamentals of
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interconnected and interacting risks, in which the environmental and human drivers
overlap. Thirdly, cascading risk is explained, distinguishing the complementarities of the
social domain from the failure of critical infrastructure. The concluding section of this paper
presents a holistic framework that can be used to maximize the impact of future research
and policies.
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2. Compound risk
Compound risk is a well-known topic of discussion by scholars and practitioners who are
interested in climate change. It involves both physical components, such as the
understanding of environmental trends, and statistical ones, such as the implications of
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concurrence in forecasting and modelling. In contrast to interconnected and cascading
risks, compound risks and disasters have been defined in official documentation as a clear
area of competence. For example, the 2012 Special Report of the Intergovernmental Panel
on Climate Change (Intergovernmental Panel on Climate Change, 2012) reported
compounding drivers to be the possible sources of extreme impacts and associated them
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very clearly with the hazard component of crisis management. In other words, compound
risk has been referred to as “a special category of climate extremes, which result from the
combination of two or more events, and which are again ‘extreme’ either from a statistical
perspective or associated with a specific threshold” (Intergovernmental Panel on Climate
Change, 2012). The concept is fully explained in a section of the work in which its
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correspondence with the idea of “multiple” events is pointed out. Compound events could
be: (a) extremes that occur simultaneously or successively; (b) extremes combined with
background conditions that amplify their overall impact; or (c) extremes that result from
combinations of “average” events. The examples reported include high sea-level rise
coincident with tropical cyclones, or the impact of heat waves on wildfires. First,
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compounding events such as flooding that occurs in saturated soils may impact the
physical environment. Secondly, health issues due to particular environmental conditions
such as humidity can affect human systems.
Although compound risk can involve events that are not causally correlated, some
exceptions have to be made for common driving forces, such as different phenomena that
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interact during El Niño, or when system-wide feedbacks between different components
strengthen each other, as when drought and heat waves occur in regions that oscillate
between dry and wet conditions. Understanding and assessing this level of interaction
presents different challenges in relation to the forecasting and modelling of such
phenomena. It has been suggested that, because of its implications in terms of discrete
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classes and artificial boundaries, the IPCC definition may be problematic for the
quantification of risk. It could be better to promote a more general approach in which
compound events are intended as extremes derived statistically from drivers with multiple
dependencies (Leonard et al., 2014). Indeed, climate change could increase the complexity
of the system and the possible sources of non-stationarity in the distribution of extremes,
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such as variable and dynamic combinations. With regard to impacts and dependencies
between systems, these may need to be considered in a multidisciplinary way (Leonard et
al., 2014).
A slightly different point of view is reported in the SFDRR (United Nations Strategy for
Disaster Risk Reduction, 2015), in which compounding drivers are associated with both the
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creation of new disaster risk and the need to reduce both exposure and vulnerability.This
seems to contextualise cascading risk more than separate it completely from what
explained earlier, The Words into Action Guidelines on National Disaster Risk Assessment
(UNISDR, 2017) refer to compounding factors as part of “underlying risk drivers”, such as
climate change or urbanisation, but the use of the term 'compound effects' in two different
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chapters intends that it mostly be employed in line with the IPCC definition of concurrence
and combined extreme events (e.g. riverine floods and coastal storms surges).
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The next section will explain better the areas of convergence and complementarities with
interacting and interconnecting risk. It will also discuss the causal background of cascades.
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3. Interacting and interconnected risk
The literature on interacting and interconnected risk focuses on how physical dynamics
develop through the existence of a widespread network of causes and effects. Although
the two concepts are intuitively very similar, interacting risks have been studied more in the
context of earth sciences, while interconnected risks have generally been tackled under the
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headings of globalisation and systems theory. The literature associated with this field has
two main foci. It tends to overlap with compound risk in the hazard domain, and with
cascading risk in the social and technological domains. A similar terminology is used in
research on risk factors in health (Price and Macnicoll, 2015). Overall, the topic has
particular implications for disaster risk reduction, complexity science, and emergency
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management. Common ground for improving the understanding of the composite nature of
disasters has been a relevant part of disaster management and hazard assessment
processes since the 1980s, for example with respect to earthquake-induced landsliding
(Alexander, 1993). However, events such as the 2011 tsunami, and the storm surge
triggered by Hurricane Sandy, have increased the need to improve forecasting strategies
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and early warning methods by those public and private stakeholders who are in charge of
critical infrastructure protection. Although the SFDRR (United Nations Strategy for Disaster
Risk Reduction, 2015) does not refer directly to interacting or interconnected risk, it refers
to the need to strengthen capacity to assess “sequential effects” on ecosystems.
In the case of interacting risks, the mechanisms and combinations of hazards have
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been analysed in their temporal and spatial domains, including reciprocal influences
between different factors and coincidences among environmental drivers (Tarvainen et al.,
2006). Empirical studies have elucidated the relationships between primary hazardous
events and secondary natural hazards of the same category or different categories
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(Marzocchi et al., 2009). Progress in this sector requires both risk assessment strategies
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and understanding of the components of earth systems and their multiple-hazard
perspectives to be improved(Kappes et al., 2012). For example, Gill and Malamud (Gill
and Malamud, 2014) studied systematically interactions between 21 natural hazards. They
found that geophysical and hydrological hazards are receptors that can be triggered by
most of the other types of hazard, while geophysical and atmospheric causes are the most
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common triggers. The results of such studies support a wider understanding of complex
interactions that could be integrated into early warning systems and rapid response tools.
Other studies have created new models based on the analysis of trigger factors, which
enables them to understand relationships among hazards that are interdependent, mutually
reinforcing, acting in parallel or acting in series (Liu et al., 2016).
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However, for multiple-risk assessment to be effective, the complex nature of interacting
and interconnected relationships between different triggers needs to be integrated into a
holistic framework. Some allowance must be made for the social construction of disasters
in a global systems perspective, including reciprocal influences among the social sphere
and the built and natural environments (Hewitt, 1995; Mileti and Noji, 1999). In other words,
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risk can be understood as the result of interaction between changing physical systems and
society, which also evolves over time (Weichselgartner, 2001). In various studies, Helbing
(Helbing, 2013; Helbing et al., 2006) analysed the ‘interconnected causality chains’ that
generate and amplify disasters, framing the impacts of triggering events on both
ecosystems and anthropogenic systems. In this sense, the paths of complex risks that
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generate secondary events are determined by physical elements (for example, a landslide
triggered by an earthquake), the build environment (for instance, critical infrastructure) and
people (hence, behaviour). The level of interconnection and interdependency may be
determined by interactive causality chains which can spread out in space and time.
However, improved understanding of physical interactions has tended to shift national risk
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assessment towards multiple-hazard approaches, further attention should be given to
contemporary society and the built environment. The global interdependency of human,
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natural and technological systems can produce hazards and disasters, but it is increasingly
hard to comprehend and control (Perry and Quarantelli, 2005). Networks have different
levels of interaction and interconnection, perhaps with multiple sources of disruption and
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systemic failure (World Economic Forum, 2016). When events are triggered, the pathways
that determine the scale of the impacts are influenced by the interlinkages between different
domains, for example the interactions by which an earthquake leads to a tsunami, along
with the climate change drivers, and the components of infrastructure such as lifelines
(OECD, 2011).
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As the next step towards the derivation of a holistic framework, the following section
will clarify the specific features of cascading risk.
4. Cascading risk
Among the phenomena analysed in this article, cascading risk is the broadest. For many
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years, it was referred to vaguely as 'uncontrolled chain losses'. Its early diffusion occurred
in the 1980s, when it was used to refer to measurable links and nodes that could
compromise information flows in networked systems (Millen, 1988). In the same period, in
order to define the consequences of organizational failures that happen in tightly coupled
and complex technological systems, cascades were included in the theory of 'normal
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accidents', or 'systemic accidents' (Perrow, 1999). The literature has associated cascades
with the metaphor of “toppling dominoes”, which since the late 1940s has been used in the
chemical processing industry to refer to sequential accidents (Abdolhamidzadeh et al.,
2011; Khan and Abbasi, 1998). This idea has been integrated into the early literature on
NaTech disasters, interacting risk, and cascading events (Cruz et al., 2004; Ma, 2007), but
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recently it has been pointed out that it could be an oversimplification and it could also
decontextualise the problem (Pescaroli and Alexander, 2015; Van Eeten et al., 2011).
In the early 2000s, events such as Hurricane Katrina and the terrorist attacks on the
World Trade Centre shifted the focus of research on cascading risk to the protection of
critical infrastructure, which is understood to be those systems or assets that are vital to
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the functioning of society. Millennial literature has approached cascading risk from the point
of view of how one can model causal interdependencies and mitigate breakdowns (Millen
and Schwartz, 1988), how one can study the processes that could cause blackouts and
trigger cross-scale failures in power grids (Newman et al., 2005). Networked infrastructure
was portrayed in both its functional and social domains, including hardware, services, and
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the secondary and tertiary effects of disruption (Little, 2002). However, cascading risk
remained a fragmented subject that lacked both official definition and an intergovernmental
dimension. It usually referred to a branching structure that originated with a primary trigger
(May, 2007).
Although new models were used to defined thresholds and mitigation strategies, their
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applicability was limited by the absence of testing in real scenarios and networks (Peters
et al., 2008). In political analyses, although the presence of cascading effects was seen as
a driver that could explain the scale of crises, but it remained marginal to any broader
considerations of resilience to extreme events with cross-border dimensions (Ansell et al.,
2010; Boin and McConnell, 2007). The ecological debate focused on the implications of
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cascading risk for climate by associating it with complex causal chains, non-linear changes
and recombination potential. The question of how to manage such crises was not solved
(Galaz et al., 2011).
Only in the late 2000s were empirical data used to demonstrate that cascading failures
are not as rare as was believed. When they were driven by disruptions to the energy,
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telecommunications and internet sectors, they were generally stopped quickly (Luiijf et al.,
2009; Van Eeten et al., 2011). After high–impact events such as the eruption of
Eyjafjallajökull volcano (2010), the triple disaster in Japan (2011) and Hurricane Sandy
(2012), the field evolved towards a greater understanding of the wider implication of
cascades. A wider range of case studies provided new evidence of the disruption of social,
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cultural and economic life, including cross-scale implications for global supply chains and
humanitarian relief (Alexander, 2013; Berariu et al., 2015; Sharma, 2013). Improved
technology stimulated a new phase in modelling the complexity of interactions and
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interdependencies among networked systems. It promoted a more coherent approach to
climate, society, economics, the built environment and cross-sector decision support
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systems (Greenberg et al., 2011; Havlin et al., 2012). In order to understand both random
failures and terrorist attacks on lifelines, critical factors began to be ranked (Buldyrev et al.,
2010; Zio and Sansavini, 2011). Attempts were made to assess cascading disruptions on
a cross-national basis (Galbusera et al., 2016; Jonkeren et al., 2015). In order to assess
the possible impact of cascading risk on emergency management and to translate it into
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generic tools that could raise awareness and information sharing in particular on electricity
disruptions, the risk managers looked for practical and repicable approaches (Hogan,
2013). A few of the official scenarios tackled the loss of power supply caused by non-
conventional triggers such as solar storms, but, in everyday reality, practice was still
distinguished by a lack of buffering strategies and well-codified contingency plans
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(Pescaroli and Alexander, 2016).
The promotion of strategies designed to increase the autonomy and adaptive capacity
of systems could be seen as a partial answer to these problems. In decision-making and
planning, decentralisation and greater empowerment were sought (Helbing, 2015).
However, guidelines for the adoption of coherent mitigation actions are still limited in their
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availablity. In this sense, the Sendai Framework for Disaster Risk Reduction can be
regarded as a first step (UNISDR, 2015) . This document reflects the perception that, in
order to reduce damage to critical infrastructure and loss of vital services, hardware and
software are the joint adjuncts of policies and mitigation actions.
In the projects supported by the European Commission, in particular by the Seventh
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Framework Programmes such as FP7 FORTRESS, FP7 CASCEFF, FP7 SNOWBALL,
FP7CIPRNet, or FP7 STREST, other drivers of research have emerged.Lack of awareness
of critical infrastructure dependencies among planners and responders could be associated
with extended impact of emergencies, requiring different levels of actions for mitigating
worst case scenarios and operational challenges (Luiijf and Klaver, 2013). Assessment and
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modelling of cascading failures in networks can be complemented by greater attention to
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the strategies that are required when disruption happens, as we suggested in some of our
previous works (Nones and Pescaroli, 2016; Pescaroli and Alexander, 2016; 2015;
Pescaroli and Kelman, 2017, Pescaroli and Nones, 2016;Pescaroli et al., 2018).
In particular, our approach proposed that 'cascading risk' should distinguish between
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'cascading effects' and 'cascading disasters', considering that, as time progresses, non-
linear escalation of a secondary emergency could become the main centre of crisis
(Pescaroli and Alexander, 2015). This shifts significantly from the “toppling dominos
metaphor”, which, as suggested earlier (Little, 2002; Boin and McConnell, 2007; Newman
et al., 2005; Peters et al., 2008; Van Eeten et al., 2011), has mostly been employed in the
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context of the process industry shifting attention to critical infrastructure, complex theory
and to the understanding of societal and organisational resilience in policy making and
emergency management. Figure 1, taken from a previous work of ours (Pescaroli and
Alexander, 2016), shows that cascading events can be viewed as the manifestation of
vulnerabilities accumulated at different scales, including socio-technological drivers. The
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possible environmental triggers, shown at the top of the figures, can be associated with
compounding and interconnected risk, while critical infrastructure and complex adaptive
systems (CAS) may be the drivers that amplify the impacts of the cascade.
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Figure 1- Vulnerability path of cascading disasters, scales interactions, and escalations in time and in
space (source: Pescaroli and Alexander 2016).
First, together with the literature on the loss of services, scholars suggested other possible
drivers of escalation such as NaTech events, which considers that up to 5 per cent of industrial
accidents are caused by natural triggers that involve hazardous facilities (Krausmann et al.,
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2011). In both cases, gaps have been found in the existing legislative frameworks, where it is
necessary to integrate different levels of risk and critical infrastructure mapping to increase
the effectiveness of mitigation strategies for multiple-scale events (Nones and Pescaroli,
2016). Secondly, in order to increase the effectiveness of deployment and the organization of
procurement in disaster relief, new datasets are needed. The analysis of different case studies
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suggests that the disruption of critical infrastructure can impact the logistics of emergency
relief (Berariu et al., 2015). It also has the potential to orient international aid in order to rectify
a shortfall of emergency goods and expertise caused by the disruption (Pescaroli and Kelman,
2017). Finally, it has been pointed out that cascading risk may require a change in methods
of scenario building and contingency planning. Our previous work suggested that flexibility of
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response can be increased by considering possible escalation paths that are common to
different categories of triggering event (Pescaroli and Alexander, 2016; Pescaroli et al., 2018).
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This approach is complementary to the perspective of broad impact-tree analysis (Macfarlane,
2015). Shifting from a focus on hazards to one on vulnerability assessment enables one to
recognise the sensitive nodes that may cause secondary events to escalate. On the one hand,
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tipping points, or thresholds, can be associated with an increased demand for products and
services during events such as blackouts. This drives the prioritization of recovery actions and
introduces new questions and issues regarding coordination between public and private
stakeholders(Münzberg and Schultmann, 2017). On the other hand, in order to consider the
different components of risk in relation to one another, it is essential to introduce good
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practices into emergency planning and scenario building (Alexander, 2016; Pescaroli et al.,
2018). The next section will propose a holistic framework that may be used by scholars and
practitioners as the basis for improved work in this field.
5. A holistic framework for compound, interconnected, interacting and
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cascading risk
In order to identify complementarities and minimise the duplication of efforts in research,
policies, and practices, this paper has given a brief overview of compound, interacting,
interconnected and cascading risks. However,more discussion is needed to increase our
385
understanding of areas in which the concepts overlap.
Despite the presence of a very clear definition released by the IPCC, some literature on
compound risk associates or uses it interchangeably with the concepts of 'interconnected' and
'cascading' risks. Prior to the work of IPCC, Perry and Quarantelli (2005) referred to compound
dynamics as the combination of different losses or vulnerabilities, for which the background
390
conditions are coupled with changes in society and the built environment. In the work of
Kawata (2011), compound disasters were reported as a form of amplification of sequential
events, such as the 1923 great Kanto Earthquake and fire, and the collapse one year later
during a typhoon of some levees damaged by the earthquake. This approach was integrated
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by other authors to describe possible compounding features, including multiple, coincidental
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and simultaneous or near simultaneous events, sequential and progressive events, random
and related hazards, and infrastructure failures (Eisner, 2014). Although some parts of this
description are in line with the IPCC approach on compounding risk, other elements tend to
overlap with cascading and interacting risk, including their operational tools in terms of multi-
hazard assessment, safety standards and the redundancy of lifelines. Other literature (Liu and
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Huang, 2014) has used both approaches (Eisner, 2014; Kawata, 2011) in order to show that
compound disasters could be a “subset of cases” in which extensive losses are associated
with a compounding process that includes both physical and human factors. According to this
perspective, the critical challenge for emergency management and strategic preparedness
policies lies in defining the interaction between the components (Liu and Huang, 2014).
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However, in this case, compound risk has been associated with the linkages between natural
hazards and technology without taking into account other studies, such as those that refer to
technological disasters triggered by natural hazards (NATECH) (Santella et al., 2011) .
Interacting and interconnected risks tend to overlap with cascading risk. First, interactions
among hazards have been associated with the physical and environmental domains, by which
410
we mean a chain of hazardous events in which one manifestation triggers another, as when
a storm causes a flood(Gill and Malamud, 2014; Liu et al., 2016). This is clearly different from
the use of the “toppling dominos metaphor” in the chemical industry process explained earlier
(Khan and Abbasi, 1998; Abdolhamidzadeh et al., 2011; Cruz et al., 2004; May, 2007),
increasing the confusion. Secondly, interconnected and interacting risks can be seen as
415
precursors of the appearance of cascading effects and disasters (Helbing, 2013; Helbing et
al., 2006; World Economic Forum, 2016). In interactive complex systems, the speed of
cascading events (meaning their capacity to influence other components) can be the measure
or manifestation of 'tight coupling' (Perrow, 1999). In studies of the interdependency between
critical infrastructure and the built environment, cascading risks can be seen as one of the
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possible categories of failure that are part of the infrastructure interdependency dimension
(Rinaldi et al., 2001). In other words, cascading effects can be seen as caused by
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dependencies and interdependencies associated with infrastructure domain (Luiijf et al., 2009;
Luiijf and Klaver, 2013). In the literature on risk and resilience, this aspect has been
developed for infrastructure systems and disruptions that spread out from one network to
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others through the many components of systems (Buldyrev et al., 2010; Galbusera et al.,
2016; Guikema et al., 2015).
The overlapping areas in the centre of Figure 2 reflect the descriptions reported in this paper
and have the following attributes:-
- They include a reference to the built environment. The vagueness in the early use of
430
concepts could be associated with duplication of efforts, for example extending the area
of interest of a certain risk (Intergovernmental Panel on Climate Change, 2012), and a
common lack of inter-agency agreements (May, 2007). It is clear that standard definitions
should be more widely adopted in order to help increase the effectiveness of research and
practice, and to avoid confusion and duplication of effort in the analysis of the built
435
environment.
- They include elements of interdependencies. On the one hand, this leads to problems
such as the oversimplifying of ideas such as the “toppling dominoes” metaphor (Pescaroli
and Alexander, 2015). On the other, it makes some progress towards integrating multi-
disciplinary research on the anthropogenic dimension of disasters (Alexander, 1993;
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Helbing et al., 2006; Perry and Quarantelli, 2005; Weichselgartner, 2001).
- They point to the existence of an amplification process that that could be associated with
the higher complexity of the system and the wider impacts of possible disasters (Helbing,
2013; Pescaroli and Alexander, 2016; Sornette, 2009). The identification of amplification
dynamics may reflect the cross-disciplinary manifestation of increased complexity at the
445
system level.
They are complex risks which maintain high potential for surprise and non-linear evolution,
and this has to be considered in the assessment process. They include different levels of
consequence and uncertainty (Aven and Kristensen, 2005). Due to their level of complexity,
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the quantification of risk and probabilistic assessment have a large degree of arbitrarieness,
450
where important drivers could have been ignored, underestimated, or are not available in the
form of datasets, which would require the integration of qualitative data (Aven, 2010).These
relationships are shown in Figure 2, which is intended to be a synthetic framework for use in
future studies.
Figure 2 derives the following characteristics for each risk:-
455
• Compound risk can refer to the environmental domain, or to the concurrence of
natural events. Eventually it can be correlated with different patterns of extreme
impacts caused by climate change. Institutional definitions tend to focus more
narrowly on the hazard component of disaster risk.
460
• Interacting risk refers to the domain of physical relations developed in the natural
environment and to its and casual chains. They focus on the area in which hazard
interacts with vulnerability to create disaster risk. The study of interacting risk may
be the focus of disciplines such as geophysics and physical geography, while
giving space to multiple risk assessment tools and strategies For example, the
465
study of the dynamics of interacting risk may can be translated into simulations
and models for the energy industry, thus defining better hazard maps .
• Interconnected risk tends to be used more often in network science and in studies
of global inter-linkages It can include the complex interactions between human,
environment, and technological systems, which can be translated, for example,
470
into coherent multiple risk assessments or network analysis. Interconnected risk
may be referred to as the physical interdependencies that allows societal
interactions, and thus a pre-condition for cascading risk.
• Cascading risk is associated mostly with the anthropogenic domain and the
vulnerability component of risk. This results in a disaster escalation process. In
475
other words, it focuses mainly on the management of social and infrastructure
19
nodes. With respect to triggering events, while interconnected risk can be seen as
one of the preconditions for the manifestation of cascades, compound and
interacting dynamics can influence its magnitude.
480
Figure 2. A framework for compound, interacting, interconnected and cascading risks
In the analysis of case studies, some examples will help to clarify the approach to
cross-risk interaction and how to apply the framework shown in Figure 1. This has been
developed bearing in mind the needs of the SFDRR (United Nations Strategy for Disaster Risk
485
Reduction, 2015) and the methodologies of decision support for emergency and crisis
management, such as scenario building (Macfarlane, 2015). The first event to consider is the
eruption of the Icelandic volcano Eyjafjallajökull in April 2010. It demonstrates how recurrent
compounding processes can have extensive impacts on the interconnected system, spreading
its cascading effects to the wider cross-border scale (Alexander, 2013; Pescaroli and
490
Alexander, 2016). The volcanic hazard itself became a problem because it was “coincident
with north to north-westerly air flow between Iceland and North West Europe, which prevails
for only 6 per cent of the time” (Sammonds et., 2011). In other words, together with the
20
eruption, the other determining factor was weather conditions, thus creating compound risk
(which was atypical but not entirely unusual). In contrast to other cases in which the impact
495
was limited, in 2010 the ash spread out over an area with a high concentration of essential
transportation system nodes. It affected global networks that are highly dependent on aviation,
thus creating interconnected risk. Although the direct physical damage was limited, disruption
of the infrastructure and its cascading effects on society were subject to non-linear escalation
and became the primary source of crisis that needed to be managed (i.e., cascading risk).
500
The second example is the triple disaster that struck Japan on the 11th March 2011. In
two different ways it explains how interacting and interconnected features can overlap with
social vulnerabilities and thus contribute to the cascading escalation of the event (Pescaroli
and Alexander, 2015; National Diet of Japan, 2012). First, an earthquake that triggered a
tsunami represented an interacting hazard, which affected highly coupled infrastructure
505
(interconnected risk), and provoked a wide range of non-linear secondary emergencies, such
as the extensive loss of vital services and the creation of NaTech events (cascading risk).
Secondly, the earthquake triggered a small and localised landslide (interacting risk) that cut
off the Fukushima power plant from the main electric grid (interconnected risk), exacerbated
existing vulnerabilities at the site and led to a full-blown nuclear meltdown (cascading risk). In
510
both cases, the disruption of critical infrastructure orientated the progress of emergency relief
towards mitigating the escalation of secondary emergencies (Pescaroli and Kelman, 2017),
while the meltdown of the Fukushima Dai'ichi plant was regarded as a man-made disaster that
could have been predicted and avoided were it not for the prevalence of negligence (National
Diet of Japan, 2012).
515
Hurricane Sandy, also known as Super-Storm Sandy, is our last case. It encompasses
all the possible joint effects of compounding, interacting, interconnected and cascading risks
(Kunz et al., 2013; Pescaroli and Alexander, 2016). Its relevance mainly lies in climate change
scenarios, in which the primary nature of the event triggers may be subject to intensification.
Hurricane Sandy made landfall in the United States on 29th October 2012. The storm winds
520
not only wreaked direct damage, but also contributed to the generation of a storm surge that
21
caused flood damages (interacting risk), while concurrent cold air flowing from the Arctic
intensified cold weather and caused snow storms inland (compounding risk). Sandy impacted
a geographical area of strategic importance to the US economy. It has a dense population and
a high concentration of industrial plants and financial networks, such as the New York Stock
525
Exchange (interconnected risk).
The composite nature of the hazard and the loss of highly-ranked critical infrastructure
triggered a wide range of secondary crises that escalated in a non-linear manner. While the
emergency responders had to tackle leaks from refineries and chemical plants, or fires in
houses, the President of the USA made a new declaration of emergency regarding the
530
prolonged power outages and the damage to the production and distribution chain of gasoline
and distillates (cascading risk). An official report (Blake et. al., 2013) attributed around 50
deaths to the joint effect of extended power outages and cold weather (interaction of
compounding and cascading risk).
However, this clarification is simply not enough to translate the conceptual framework into a
535
tool that can be used to understand, manage and predict events. Taking back the conceptual
equation used for the definition of risk, and the complementary works cited in the introduction,
it may be useful to subject Figure 3 to further discussion.
Our review shows that the compound, interacting, interconnected, and cascading risk tend to
be different component of hazards and vulnerabilities. While compound risk can be mostly
540
associated with the physical dimension of hazards, interacting and interconnected risk
gradually increase the focus on the vulnerability component. Thus they become the centre of
cascading risk. The analysis of root causes and consequences use different tools. On the one
hand the work mostly involves physical modelling and forecasting. On the other hand it
focuses on network analysis and resilience assessment in the broader sense. Those tools are
545
complementary and can be used together, while common areas of interaction and overlapping
can be indentified in the build environment and in mechanisms such as early warning systems.
As noted, in all of these cases, there is a common background of wide uncertainties in the
environmental, physical, technological and social dimensions, that can challenge risk
22
assessment and management with the existence of weak background knowledge. This
550
influence the tools that are needed, but it also affects the assessment process and the possible
policy outcomes, as there may be different emphases on hazards and vulnerabilities. In order
to maximise the efficiency of the process of risk analysis and risk assessment, it is essential
to understand the differences and complementarities inherent in compound, interacting,
interconnected and cascading events. .
555
Figure 3- Overview of the relations of Compound, interacting, interconnected, and cascading risk with
hazard, vulnerability, uncertainties and analytical tools.
6. Conclusion
560
This paper has developed a common framework for compound, interacting, interconnected
and cascading risk, which aims to support a better visualization and understanding of high-
impact events. It develops these ideas in line with the SDFF, and characterizes complex
events in a way that should support a more highly focused analysis (Aven, 2016; Linkov et al.
565
2014; Greenberg et., 2011; Pescaroli and Alexander, 2016). This is in line with the perceived
23
need for new strategies designed to integrate systemic risks in research, policies and
management that has been frequently highlighted in the literature (Aitsi-Selmi et al., 2016;
Helbing, 2013;Linkov et al 2014; Mileti, 1999;Helbing 2015;Alexander 2016).
Despite a general perception of overlap between the four concepts dealt with in this paper, we
570
have shown that very specific issues have been addressed in compound, cascading,
interacting and interconnected risk. These have not always been assimilated in research and
management, and this requires better coordination in order to improve the complementarities
of forecasting tools, the flexibility of mitigation measures, and the ability to adapt to emergency
response.
575
We have defined boundaries that can help to produce more focused risk estimations and
better tools, which will, we trust, help stakholders and academics to improve description,
visualization and communication, as suggested in some of the literature and in the SFDRR
itself (UNISDR, 2015; Aven 2016). There are significant limitations to this perspective that
must be considered. First the readers, should note that this article does not pretend to be an
580
exhaustive review of all the literature in the field.Instead, it provides a synthetic framework and
guidelines for those readers who are interested in the topic. Although we have tried to define
as much as possible the boundaries of each category, futher work is needed in order to define
the specific boundaries and their significance as “tipping points” for risk assessment. Future
research should better consider qualitative implications for practical management of such
585
situations in terms of scenario building and the broadening of impact trees, which must be
complementary to the methodologies and tools that have already been identified in the
literature (Aven, 2016: Helbing, 2013; Linkov et al., 2014; Pescaroli and Alexander, 2016). In
other words, new research should be developed on how to predict and address
interdependencies, together with advice on what actions should be taken once
590
interdependencies are triggered. The translation of theoretical frameworks into practice is one
of the most important challenges that need to be addressed in the furtherance of disaster risk
reduction.
24
7. Acknowledgements
595
This work has been carried out under the aegis of the EC FP7 FORTRESS project.
FORTRESS is funded by the European Commission within FP7- Area 10.4.1 Preparedness,
prevention, mitigation and planning, TOPIC SEC-2013.4.1-2 SEC-2013.2.1-2, Grant 607579.
The authors gratefully acknowledge Igor Linkov (USACE), Dirk Helbing (ETHZ), Georgios
Giannopulos (JRC) and Luca Galbusera (JRC) for their precious questions, feedbacks and
600
suggestions during our workshops.
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