Empirical Framework for Characterizing Infrastructure Failure Interdependencies

This paper develops an analytical framework with empirical applications to characterize infrastructure failure interdependencies (IFIs). It uses major electrical power outages as the context for understanding how extreme events (within or external to the power system) lead to failures of other infrastructure systems, given a major electrical power outage. The paper takes an empirical approach by examining the patterns of IFIs that occurred in three kinds of events: the August 2003 northeastern North American blackout, the 1998 Quebec ice storm, and a set of three 2004 Florida hurricanes. Data sources include media reports and official ex post assessments of the events. The results characterize IFIs in terms of the sectors affected, and the consequences for society. We developed scales to characterize the consequences of IFIs in terms of impact and extent indices. A comparison is provided of IFIs arising in all five events discussed in the paper, as a basis for considering priorities for risk mitigation. The most significant IFIs in all five events included effects on HVAC in buildings; effects on water systems; effects on health systems, including hospitals and public health efforts, and effects on road transportation systems.

[1]  Rachel A. Davidson,et al.  Electric Power Distribution System Performance in Carolina Hurricanes , 2003 .

[2]  Mitchell J. Small,et al.  Risk Analysis and Society: Contributors , 2003 .

[3]  Jaewook Park,et al.  Context and Resiliency: Influences on Electric Utility Lifeline Performance , 2006 .

[4]  Hiroyuki Kameda,et al.  Cross-Impact Analysis for Lifeline Interactions , 1991 .

[5]  Robert S. Germain,et al.  Large Scale Systems , 1996 .

[6]  B Fischhoff,et al.  A Deliberative Method for Ranking Risks (I): Overview and Test Bed Development , 2001, Risk analysis : an official publication of the Society for Risk Analysis.

[7]  Ralph L. Keeney,et al.  Eliciting probabilities from experts in complex technical problems , 1991 .

[8]  Sandip Roy,et al.  The influence model , 2001 .

[9]  P. Slovic.  Trust, Emotion, Sex, Politics, and Science: Surveying the Risk‐Assessment Battlefield , 1999, Risk analysis : an official publication of the Society for Risk Analysis.

[10]  Masanobu Shinozuka,et al.  Evaluating the Disaster Resilience of Power Networks and Grids , 2004 .

[11]  James H. Lambert,et al.  Risk Analysis and Society: Risk of Extreme and Rare Events: Lessons from a Selection of Approaches , 2003 .

[12]  Ralph L. Keeney,et al.  On the uses of expert judgment on complex technical problems , 1989 .

[13]  Stephanie E. Chang,et al.  Infrastructure failure interdependencies in extreme events: power outage consequences in the 1998 Ice Storm , 2007 .

[14]  Yacov Y. Haimes,et al.  Risk modeling, assessment, and management , 1998 .

[15]  Ralph L. Keeney,et al.  Feature Article - Decision Analysis: An Overview , 1982, Oper. Res..

[16]  James H. Lambert,et al.  PRIORITIZATION OF SCHEDULE DEPENDENCIES IN HURRICANE RECOVERY OF TRANSPORTATION AGENCY , 2002 .

[17]  P. Slovic.  Perception of risk. , 1987, Science.

[18]  Stephanie E. Chang,et al.  The Regional Economic Impact of an Earthquake: Direct and Indirect Effects of Electricity Lifeline Disruptions , 1997 .

[19]  Barry M. Horowitz,et al.  Modeling interdependent infrastructures for sustainable counterterrorism , 2004 .

[20]  H. Fineberg,et al.  Understanding Risk: Informing Decisions in a Democratic Society , 1996 .

[21]  Mitchell J. Small,et al.  Risk Analysis and Society , 2004 .

[22]  James P. Peerenboom,et al.  Identifying, understanding, and analyzing critical infrastructure interdependencies , 2001 .

[23]  S. Kaplan,et al.  On The Quantitative Definition of Risk , 1981 .

[24]  John V. Farr,et al.  Infrastructure Risk Analysis Model , 2000 .