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In disaster-prone regions such as Chile, catastrophe models help (re)insurers to understand and quantify the risks facing their businesses. The 2010 (M8.8) Maule (Chile) earthquake highlighted the need for quantifying losses not only from primary perils (in this case earthquake) but also from secondary perils such as tsunamis, which contribute to the overall event losses but are not often modelled. This paper presents a new catastrophe model for Chile developed by Impact Forecasting (IF) in collaboration with Aon Benfield Research partners. The model has the capability to model losses due to earthquake (ground-shaking) and induced tsunamis along the Chilean coast in a probabilistic manner, and also for historical scenarios. The model is implemented in the IF catastrophe modelling platform, ELEMENTS. Criteria for selecting tsunamigenic events are proposed which take into consideration earthquake location, depth and the resulting seabed vertical displacement and tsunami inundation depths at the coast. More than 3,600 events were selected for tsunami simulations. Deep and shallow water wave propagation is modelled using state-of-the-art modelling suite, Delft3D (from Deltares). The Delft3D-FLOW module is used in 2-dimensional hydrodynamic simulation settings with non-steady flow. Static seabed vertical displacement resulting from earthquake slip is used as an input boundary condition to the model. Use of the SRTM digital elevation model determines the spatial grid-cell resolution of approximately 90m. The modelled inundation extent for the 2010 event is validated through comparison with real observations. The vulnerability component consists of an extensive damage curves database, including curves for buildings, contents and business interruption for 21 occupancies, 24 structural types and 2 secondary modifiers such as building height and period of construction. The Chile earthquake and tsunami model is validated through comparison of the modelled and observed losses for client portfolios for the 2010 event.


Session R40, Assessment, Prediction, and Management of Flood Events II



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