A review of quantification methodologies for multi-hazard interrelationships

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Globally and yearly, individual hazards and hazard interrelations have the potential to result in socio-economic losses. Here, in this critical review, we use grey- and peer-review literature to identify and compare current research available for the quantification of hazard interrelations, focussing on 14 different natural hazards. We first provide a historical context for quantitative single hazard and multi-hazard assessment. We then construct a literature database with 146 references related to multi-hazard interrelations. We use our literature database to identify trends for hazard interrelation and multi-hazard and from these group hazard interrelations into five types: triggering, change condition, compound, independence and mutually exclusive. Our critical review identifies 19 different modelling methods to quantify natural hazard interrelationships which we cluster into three broad modelling approaches: stochastic, empirical, and mechanistic. We then synthesize results of our classification of quantification methods for hazard interrelationships and using two matrices illustrate this in practice for 24 different interrelations between 14 natural hazards, one for cascading hazards (temporal order in the multi-hazard event) and one for compound hazards (two or more hazards acting together). Finally, we provide examples of applications for each the three quantitative modelling approaches defined. We believe that this review will lead to a better understanding of quantification methodologies for hazard interrelations between different sub-disciplines that focus on natural hazards, thus aiding cross-disciplinary approaches for better understanding potential risk related to multi-hazard events.




Tilloy, A., Malamud, B. D., Winter, H., & Joly-Laugel, A. (2019, September 1). A review of quantification methodologies for multi-hazard interrelationships. Earth-Science Reviews. Elsevier B.V. https://doi.org/10.1016/j.earscirev.2019.102881

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