Exploring the impact of spatial correlations of earthquake ground motions in the catastrophe modelling process : a case study for Italy

Schiappapietra, E. and Stripajová, S. and Pažák, P. and Douglas, J. and Trendafiloski, G. (2022) Exploring the impact of spatial correlations of earthquake ground motions in the catastrophe modelling process : a case study for Italy. Bulletin of Earthquake Engineering, 20 (11). pp. 5747-5773. ISSN 1573-1456 (https://doi.org/10.1007/s10518-022-01413-z)

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Abstract

Catastrophe models are important tools to provide proper assessment and financial management of earthquake-related emergencies, which still create the largest protection gap across all perils. Earthquake catastrophe models include three main components, namely: (1) the earthquake hazard model, (2) the exposure model and, (3) the vulnerability model. Simulating spatially distributed ground motion fields within either deterministic or probabilistic seismic hazard assessments poses a major challenge when site-related financial protection products are required. In this framework, we develop ad hoc correlation models for different Italian regions (specifically northern, central and southern Italy) and thereafter we perform both deterministic scenario-based and probabilistic event-based hazard and risk assessments in order to advance the understanding of spatial correlations within the catastrophe modelling process. We employ the OpenQuake engine for our calculations. This is an open-source tool suitable for accounting for the spatial correlation of earthquake ground-motion residuals. Our outcomes, albeit preliminary, demonstrate the importance of considering not only the spatial correlation of ground motions, but also its associated uncertainty in risk analyses. Although loss exceedance probability curves for the return periods of interest for the (re)insurance industry show similar trends, both hazard and risk footprints in terms of average annual losses feature less noisy and more realistic patterns if spatial correlation is taken into account. Such results will have implications for (re)insurance companies evaluating the risk to high-value civil engineering infrastructures.

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