A simplified framework for probabilistic earthquake loss estimation

Young Sun Choun, Amr S. Elnashai

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)355-364
Number of pages10
JournalProbabilistic Engineering Mechanics
Issue number4
StatePublished - Oct 2010

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Civil and Structural Engineering
  • Nuclear Energy and Engineering
  • Condensed Matter Physics
  • Aerospace Engineering
  • Ocean Engineering
  • Mechanical Engineering


Dive into the research topics of 'A simplified framework for probabilistic earthquake loss estimation'. Together they form a unique fingerprint.

Cite this