Mignant et al.2014) proposed a generic multi-risk framework based on the sequential Monte Carlo method to allow for a straightforward and flexible implementation of conjoint and cascading events (Fig. 1).The model considers hazard interactions, which are analogous to the ones observed in recent catastrophes, such as the 2005 hurricane Katrina and the 2011 Tohoku earthquake. It also includes time-dependent exposure and time-dependent vulnerability. Validation of the framework was based on the testing of generic data and interaction processes. For presentation of the multi-risk framework to stakeholders (Komendantova et al., 2014), another set of data and interaction processes was used, based on the concept of the Virtual City (Mignan et al., in prep.), which is illustrated in Fig. 2. A virtual city located in a virtual hazardous region provides the baseline for the investigation of hazard interactions in a controlled – yet realistic – environment. Perils and interaction processes are defined heuristically (e.g., earthquakes from simple ground motion prediction equations, floods from water height in a V-basin, storm surge height as a function of wind speed based on the Saffir–Simpson scale, etc.). Risk is also computed from simple considerations (e.g., lognormal distribution as a proxy to various vulnerability curves). By design, the epistemic uncertainties are high, but could be reduced when switching from a virtual scenario to a real one. New applications are investigated in the on-going EU FP7 project STREST (www.strest-eu.org).
Fig.1: Generic multi-risk approach (mignan et al., 2014).a: Sequential Monte Carlo method; b: Concept of harzard correlation matrix (variant of a Markov chain).
Fig.2: Concept of the Virtual City (Komendantova et al., 2014; Mignan et al., in prep.) Perils considered in this example are earthquakes (EQ), volcanic eruptions (VE), fluvial floods (FL), winds (WI) and sea submersion (SS)
Komendantova, N., R. Mrzyglocki, A. Mignan, B. Khazai, F. Wenzel, A. Patt and K. Fleming (2014), Multi-hazard and multi-risk decision-support tools as a part of participatory risk governance: Feedback from civil protection stakeholders, Int. J. Disaster Risk Reduction, 8, 50-67, doi: 10.1016/j.ijdrr.2013.12.006
Mignan, A., S. Wiemer and D. Giardini (2014), The Quantification of Low Probability-High Consequences Events: Part. I. A Generic Multi-Risk Approach, Nat. Haz., in press
Mignan, A., S. Wiemer and D. Giardini (2014), The Quantification of Low Probability-High Consequences Events: Part. II. Guidelines to Multi-Risk Assessment Based on the Virtual City concept, in preparation