TURNkey Report D4.8 - Report on procedures for rapid mapping of earthquake losses

This report details the procedures that have been applied, developed or improved in Task 4.5 for the rapid estimation of damages and losses after an earthquake event. The report revolves around several actions and technical results, which are organized as follows: • Section 3 summarizes the state-of-the-art of current rapid response algorithms and systems, based on a review by Guérin-Marthe et al. (2021). The SELENA and Armargedom software, coupled with shake-map estimates from WP3, are put forward as one of the technical solutions to be implemented in the TURNkey platform. • Section 4 conducts a benchmark study of two damage estimation methods, namely SELENA (Molina et al., 2010), using fragility functions, and Armagedom (Sedan et al., 2013), using semi-empirical vulnerability indices. Both methods are applied on two case-study areas (Luchon area in TB-2 and Alicante area) and the damage distributions are compared. • Section 5 investigates the impact of various factors (resolution of soil amplification maps and building exposure datasets, influence of ground-motion variability) on the accuracy of the damage estimates when applying earthquake scenarios over built areas. Two case studies are considered, namely the Luchon area (TB-2) and the town of Hveragerði (TB3). • Section 6 introduces a probabilistic framework for near real-time seismic damage assessment that exploits heterogeneous sources of information about the seismic input and the structural response to the earthquake. The value of information provided by various combinations of observations and measurements is quantified. The approach is applied to an arbitrary roadway bridge near Patras (TB-4). • Section 7 introduces a sampling-based Bayesian updating method in order to refine damage and loss estimates from field observations. The method is applicable to large real-world systems, such as extended built areas or real-world infrastructure systems. It is applied to the Luchon area (TB-2), where the damage distribution of common buildings and the connectivity loss of the road network system are estimated in a rapid response context. The Bayesian approach for the updating of damage and loss estimated has been implemented in a R/Matlab code, which is briefly described in the companion Deliverable D4.9.