Towards near-real-time damage estimation using a CSM-Based tool for seismic risk assessment

Loss estimation studies have traditionally been using individual scenario earthquakes as the basis for planning and decision making. Existing knowledge of regional geology and seismology have, in the same context, been used to generate maps with estimated intensities or ground-motion parameters (e. g., accelerations). In combination with other factors (e. g., composition and structural characteristics of the building stock), these parameters allow a direct estimation of the damage to structures and lifelines and of the impacts on the population (e. g., number of injured and fatalities). Nowadays, the advent of high-speed computing, satellite telemetry, and Geographic Information Systems (GIS) has made it possible to generate rapid loss estimates for multiple earthquake scenarios, and to provide a greatly improved mapping capability. Perhaps most importantly, it is now within reach to derive damage and loss estimates for an earthquake in near real-time solely based on the source parameters of an event, with magnitude and location as a minimum. We have investigated the capabilities and efficiency of the seismic risk and loss assessment tool SELENA [Molina et al., 2007] for such a near real-time application. One of the main features of this tool consists of taking into account epistemic uncertainties in all types of input data by a logic-tree computation scheme. Therefore, the influence of the number of logic-tree branches on the computation time is examined in order to evaluate its applicability for near-real-time damage assessment. The SELENA software tool is tested in a near-real-time context for the Arenella district in Naples ( Italy), one of the test cities within the EC-SAFER project. The risk and loss assessment studies depend on real-time shake map estimates along with the building stock inventory facilitated by the University of Naples as well as structural capacity curves and vulnerability functions developed for the predominant building types by Polese et al. [2008].