Probabilistic seismic risk assessment for cities: Counterfactual analysis in a Chilean case study

Abstract. We develop a comprehensive probabilistic seismic risk assessment model and apply it to the coastal city of San Antonio in Chile. We use this model to analyze the implications of various counterfactuals of the exposed building stock, in terms of different risk metrics. We begin by generating a synthetic earthquake catalog via Monte Carlo simulations. We then simulate spatial seismic intensities by using ground motion models, considering correlation parameters specifically estimated for the Chilean subduction zone, to evaluate ground motion intensity measures at each site. Additionally, we develop a high-resolution exposure model that characterizes the building stock and population distribution at the census block level. We use the proposed methodology to obtain risk curves for the current exposed building stock, as well as for four counterfactuals involving changes in building materials and/or design levels. Thus, we quantitatively identify the most effective alternatives for mitigation plans. These alternatives consider not only physical damage but also economic losses and casualties, showing the method's potential for its use as a valuable public policy planning tool for decision-makers. Specifically, we find that changing either the building material or the design level of the predominant building class results in significant reductions in expected annual losses of physical damage, casualties and economic losses.