A simplified framework for probabilistic earthquake loss estimation

Earthquake loss estimation procedures exhibit aleatory and epistemic uncertainty imbedded in their various components; i.e. seismic hazard, structural fragility, and inventory data. Since these uncertainties significantly affect decision-making, they have to be considered in loss estimation to inform decision-and policymakers and to ensure a balanced view of the various threats to which society may be subjected. This paper reviews the uncertainties that affect earthquake loss estimation and proposes a simple framework for probabilistic uncertainty assessment suitable for use after obtaining impact results from existing software, such as HAZUS-MH. To avoid the extensive calculations required for Monte Carlo simulation-based approaches, this study develops an approximate method for uncertainty propagation based on modifying the quantile arithmetic methodology, which allows for acceptable uncertainty estimates with limited computational effort. A verification example shows that the results by the approximation approach are in good agreement with the equivalent Monte Carlo simulation outcome. Finally, the paper demonstrates the proposed procedure for probabilistic loss assessment through a comparison with HAZUS-MH results. It is confirmed that the proposed procedure consistently gives reasonable estimates.