Assessing uncertainty in extreme events: Applications to risk-based decision making in interdependent infrastructure sectors

• Published in: Reliability engineering & system safety Vol. 94; no. 4; pp. 819 - 829
• Main Authors: Barker, Kash, Haimes, Yacov Y.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.04.2009; Elsevier
• Subjects: Applied sciences; Decision theory. Utility theory; Exact sciences and technology; Extreme events; Inoperability input–output model; Multiobjective decision making; Operational research and scientific management; Operational research. Management science; Reliability theory. Replacement problems; Risk management; Risk theory. Actuarial science; Uncertainty analysis; Multiobjective decision making; Risk management; Inoperability input–output model; Uncertainty analysis; Extreme events; Probabilistic approach; Decision support system; Decision making; Multiobjective programming; Natural disaster; Risk analysis; Modeling; Reactive system; Uncertain system; Electrical network; Economic sector; Extreme value; Elicitation; Inoperability input-output model; Input output model
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2008.09.008

Risk-based decision making often relies upon expert probability assessments, particularly in the consequences of disruptive events and when such events are extreme or catastrophic in nature. Naturally, such expert-elicited probability distributions can be fraught with errors, as they describe events which occur very infrequently and for which only sparse data exist. This paper presents a quantitative framework, the extreme event uncertainty sensitivity impact method (EE-USIM), for measuring the sensitivity of extreme event consequences to uncertainties in the parameters of the underlying probability distribution. The EE-USIM is demonstrated with the Inoperability input–output model (IIM), a model with which to evaluate the propagation of inoperability throughout an interdependent set of economic and infrastructure sectors. The EE-USIM also makes use of a two-sided power distribution function generated by expert elicitation of extreme event consequences.