Decision Support Systems Involving Simulation of Extreme Events

1. Complex Systems Science in Focus 8-10 August 2006 Coogee Bay Hotel, Sydney, NSW Physical Systems Decision Support Systems Involving Simulation of Extreme Events John Mo CSIRO Sustainable Ecosystems

2. Some Thoughts • What are the properties of extreme events and what are the implications of those properties for decision making? • What is the role of decision making in extreme events? • What contextual factors that characterize extreme events are important in decision making? • What is needed to improve extreme event decision making and how to achieve that improvement through research? Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

3. US North East Blackout 2003 Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

4. Melbourne Federation Square Mass Gatherings Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

5. Accidents With Mass Casualties Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

6. Tsunami Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

7. Characteristics of Extreme Events and Implications to Decision Support Requirements • Rare, non repeating • Rapid onset vs. “creeping change” Little opportunity for learning. Relevant experience may be lacking. May or may not be a factor in evolutionary psychology. The decision making implications may be quite different for different events. • High consequence Attention will be focussed on event. Consequence of decisions could be disastrous. • High uncertainty Generally, extreme events are difficult to predict. They often occur with insufficient warning. • Time pressure Limited time for analysis, Stress producing. • Pose complex, ill structured problems This lack of structure may encourage intuitive mode of responding when analytic mode is more appropriate. • Potential to create long-term change In the aftermath of an extreme event, decision makers may face a new environment. • Affect large numbers of people and/or large ecosystems Group decision, leadership, government action, trust, and cooperation/communication among stakeholders are important for implementation of effective decisions. • Under-represented and disenfranchised groups tend to be disproportionately vulnerable Equity should be explicitly considered in decision making Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

8. What Can Science Do? • Evaluate the impact if it happens. The 1-10-100 rule? • Disastrous events must be prevented. • Infer (from scientific base) the unthinkable. • The flow-on consequences of a critical failure • Propagation of failure to other infrastructures • “What if” analysis • Options for investment and other mitigation strategies • Effectiveness of response plans • Prepare to respond swiftly and “correctly” even with dysfunctional systems • Vulnerability assessment • Choke points, single points of failure • Scenarios, including natural disasters and acts of terrorism • Business continuity Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

9. NEMSIM Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

10. National Electricity Network (NEM section) Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

11. Demand Modelling Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

12. Modelling for Blackout Analysis Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

13. Regionaldemand Network constraint NEM demand NEM prices SA Pool prices No. of A/C Wind power Vic-SA Link Murray Link Despatch Capacity Day of week Temper-ature Weather model Geo-spatial Mainten-ance Gen. behaviour Infrastructure Model Elements Yorke Adelaide Mt. Gambia Port Augusta Whyalla Lightning Gust wind Fire Fault Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

14. Simulation of Blackout in South Australia • Specified conditions: • Hot day • Interconnector issues: • Lightning (location, intensity) • Gust wind 120 km/hr • Planned maintenance shutdowns • Multiple generator failures • Policy discrepancy Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

15. 2005 Hurricane Katrina Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

16. The Dennis Mileti Workshop at Emergency Management Australia • Dennis Mileti – Director of the Natural Hazards Research and Applications Information Center of the University of Colorado at Boulder (Invited speaker to the Australian National Emergency Management Committee, EMA, 31 August, 1999) • “The potential complexity … that hazards and risks appear to shift in ways we don’t fully understand. … • Many of our mitigation efforts themselves degrade the environment and contribute to the next disaster • … simply postponing events of even greater ultimate magnitude • …the building of levée banks ... encourage development behind them which increases losses when eventually they fail.” Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

17. Yorke Adelaide Mt. Gambia Port Augusta Whyalla Regionaldemand Network constraint NEM demand NEM prices SA Pool prices No. of A/C Wind power Vic-SA Link Murray Link Despatch Capacity Day of week Temper-ature Weather model Geo-spatial Mainten-ance Gen. behaviour Lightning Gust wind Fire Fault Cascading Events? Multiple interacting systems Evolutionary, changing Management and societal responses Complex Systems Science Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

18. Thank you Questions? John Mo, CSE

19. Major US Blackouts • 1950 June 6 • Widespread outage in the Pacific Northwest from British Columbia and Washington to Oregon, Idaho, and Utah and Montana. • 1965 • January 28th. 6 mid-western states for 2.5 hours. 2 million people affected. • April 11th. A tornado hits in Indiana and blackout extended to St. Louis and Iowa. • November 9th. 8 states fell into darkness for almost a day. Began in Canada Toronto, Rochester, Boston, New York. 4 million homes affected. • December 2nd. A power failure in the El Paso area (Texas, New Mexico, and Mexico) occurred at 8 pm and lasted for 2 hours. • 1977 July 13 & 14 • New York City suffered a massive blackout for 2 days. A number of communities erupted in violence. 3,766 looters arrested and the city suffered an economic blow estimated at more than $300 million. Time magazine called "A Night of Terror." • 2003 August 14 • New York City and much of the Northeast were paralyzed by a sudden blackout for over 24 hours. 50 million people affected. These extreme events do occur but each case is different Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

20. Mercury 05 • Senator Chris Ellison, Minister for Justice and Customs: • “Australia’s largest-ever counter-terrorism exercise, Mercury 05, had met all objectives and reinforced some valuable lessons for more than 4000 participating members of our national security agencies and emergency services” • More than a year of planning and development went into making Mercury 05 as realistic as possible and the response from our police, intelligence, defence, security and emergency services personnel was outstanding • The four-day long exercise included mock bombing attacks or threats in Adelaide, Melbourne and Sydney, a threat to gas facilities in South Australia, a siege following the hijacking of a busload of foreign athletes and the recovery of a foreign vessel with terrorists aboard. Mock events are expensive and tend to repeat the past Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

21. Extreme events • Wide area power outages • Earth quake / Tsunami • Bomb blast / Accident gas explosion • Hurricane • Fire / Bush Fire • Flooding • Traffic blockade • CEO / VIP / politician kidnapped • Extreme weather • Mass gatherings • Stock market crashed • Avian flu / SARS outbreak Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events

22. Types of Infrastructures • Energy • Transport • Communications • Water • Banking and Finance • Food Chain • Health • Emergency Services • Mass Gatherings • Others Complex Systems Science in Focus - Decision Support Systems Involving Simulation of Extreme Events