Natural hazard risk of complex systems – the whole is more than the sum of its parts: I. A holistic modelling approach based on Graph Theory

Abstract

Abstract. Assessing the risk of complex systems to natural hazards is an important and challenging problem. In today’s intricate socio-technological world, characterized by strong urbanization and technological trends, the connections, interdependencies and interactions between exposed elements are crucial. These complex relations 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 of its elements individually. In contrast, a holistic approach considers the whole system as a unique entity of interconnected elements, where those connections are taken into account in order to more thoroughly assess risk. To support this paradigm shift, this paper proposes a new holistic approach to assess the risk in complex systems based on Graph Theory. The paper is organized in two parts: part I describes the proposed approach, and part II presents an application to a pilot study in Mexico City. In part I, we demonstrate that by representing a complex system such as an urban settlement by means of a network (i.e. a graph), it is possible to take advantage of the techniques made available by the branch of mathematics called Graph Theory to analyse its properties. Moreover, it is possible to establish analogies between certain graph metrics (e.g. authority, degree, hub values) and risk variables (exposure, vulnerability and resilience). Leveraging these analogies, one can not only obtain a deeper knowledge of the system (structure, weaknesses, etc.), but also understand its risk mechanisms (how the impacts of a single or multiple natural hazards are propagated, where they are exacerbated), and therefore assess the disaster risk of the system as a whole, including second-order impacts and cascade effects.

Multihazards Scenario Generator: A Network‐Based Simulation of Natural Disasters

“…In fact, the impact of a hazard is a function of the magnitude of the event within a specific area and time interval, and the consequent damage sustained by the exposed elements. Indeed, Arosio, Martina, and Figueiredo (2018a) indicate that the approach to natural risk assessment needs to be holistic as "the whole is more than the sum of its parts." Also, in another recent article, AghaKouchak et al (2018) remind scientists that research gaps on multi-hazards remain to be filled.…”

Are We Missing the Target? A Bias-Variance Perspective on Multi-Hazard Risk Assessment

“…Many current risk studies still consider hazard in isolation, where the risk to exposed elements is sourced from one hazard in isolation also referred to as "single hazard" models (Gill and Malamud, 2014). As mentioned in the Introduction, disaster risk authorities and scientist pointed out the shortcoming of considering the hazards in silos (AghaKouchak et al, 2018;Arosio et al, 2018). In an effort to answer this call, and because of the difficulty inherent in considering interwoven hazards (Liu et al, 2015), current multi-hazard studies largely rely on semi-quantitative studies to assess the risk from multi-hazard (e.g., using indices, indexes) (Kappes et al, 2012).…”

“…But a probabilistic quantification of the multi-hazard risk is often required to provide guidance on the allocation of resources to alleviate the risk. Recent studies are trying to find applicable ways to answer this complex challenge by considering natural hazards as part of an interconnected system (Mignan et al, 2014;Arosio et al, 2018;Dunant et al, 2021a;Dunant et al, 2021b). Few publications actually compare the results of single hazard models and multihazard models to generalise the argument for multi-hazard models.…”

Vulnerability analysis in Complex Networks under a Flood Risk Reduction point of view

“…In this paper, we consider a topological meaning for vulnerability, under a Complex Network approach, as presented in (Yin & Xu (2010); Santos et al (2019)). Interfaces between Complex Systems Science and Disaster Science were discussed in (Arosio et al (2018)), however, the vulnerability index was not presented.…”

“…Due to its generality for representing the system topology (relation among the elements on the system), Network Science approaches have been applied to a huge number of very different areas (Newman, 2010;Estrada, 2011;Barabási, 2016). Recently, Mattsson & Jenelius (2015), Arosio et al (2018) and Santos et al (2019b) discussed interfaces between Complex Systems Science and Disaster Science. However, the first one did not apply its ideas in any real case study, the second one did not analyse the topological vulnerability index, and the third one did not show any susceptibility map, just the topological vulnerability index itself.…”