EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Investigating the effect of spatial correlation on loss estimation in catastrophe models – a case study for Italy 

Svetlana Stripajova1, Erika Schiappapietra2, Peter Pazak1, John Douglas2, and Goran Trendafiloski1
Svetlana Stripajova et al.
  • 1Aon, Impact Forecasting (
  • 2Department of Civil and Environmental Engineering, University of Strathclyde, Glasgow, UK

Catastrophe models are very important tool to provide proper assessment and financial management of earthquake-related emergencies, which still create the largest protection gap across all other perils. Earthquake catastrophe models contain three main components: earthquake hazard, vulnerability and exposure. 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. Several authors have demonstrated that the spatial correlation of earthquake ground-motion is period-, regionally- and scenario-dependent, so that the implementation of a unique correlation model may represent an oversimplification.

In this framework, we have established a joint research project between the University of Strathclyde and Impact Forecasting, Aon’s catastrophe model development centre of excellence, in order to advance the understanding of spatial correlations within the catastrophe modelling process. We developed correlation models for northern, central and southern Italian regions using both ad hoc and existing ground-motion models calibrated on different databases. Thereafter, we performed both deterministic scenario and event-based probabilistic hazard and risk assessments for Italy using the 2020 European Seismic Hazard and Risk Models. We employed the OpenQuake-engine for our calculations, which is an open-source tool suitable for accounting for the spatial correlation of earthquake ground-motion residuals. The results demonstrate the importance of considering not only the ground-motion spatial correlation, but also its associated uncertainty in risk analyses. Our findings have implications for (re)insurance companies evaluating the risk to high-value civil engineering infrastructures.

How to cite: Stripajova, S., Schiappapietra, E., Pazak, P., Douglas, J., and Trendafiloski, G.: Investigating the effect of spatial correlation on loss estimation in catastrophe models – a case study for Italy , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4950,, 2022.