Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Building Resilience in an Urban World


Published on

  • Login to see the comments

  • Be the first to like this

Building Resilience in an Urban World

  1. 1. Building Resilience in an Urban World Abhas K. Jha Program Leader, Disaster Risk Management East Asia Pacific The World Bank Santa Fe Institute Trustee and Business Network Symposium, November 2, 2012
  2. 2. I am going to talk about 3 things today….1. The rising trend in disasters and what are the key drivers behind it.2. How is the World Bank addressing this issue.3. Some emerging future directions.
  3. 3. 3 Main Messages1. The growth of people and assets in harm’s way, due to rapid urbanization will be, by far, the biggest driver of disaster risk over the next few decades.2. The deep uncertainties from climate change implies the need for “robust” solutions-that work (“good enough”)across a wide range of scenarios.3. The risks of disasters cannot be completely eliminated: a) Preparing for “graceful” failure b) Getting the balance right between structural and non-structural measures
  4. 4. 1. Trends
  5. 5. Rome Wasn’t Built in Day..China Does it in Two Weeks!
  6. 6. Where is this urbanization happening?
  7. 7. Africa, Indian Sub-Continent and China 15% 25% 25%
  8. 8. Small and Medium TownsGrowth in population by city scales. Source: based on Population Division of the Department of Economic and Social Affairs of the UnitedNations Secretariat, World Population Prospects: The 2008 Revision and World Urbanization Prospects: The 2009 Revision.
  9. 9. Increasing Trend of Disasters Source: MunichRe
  10. 10. The Major Takeaway from the IPCC SREX “Long-term trends in normalized losses have not been attributed to natural or anthropogenic climate change” -IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation
  11. 11. Source: Pielke and Landsea
  12. 12. Source: Ranger and Garbett-Shiels, 2011
  13. 13. Cascading failures, fragile networks“Networks that are efficientare often notresilient, because resilientnetworks have inefficientredundancies. Resilience is apublic good, created by theright kind of redundancy.” -Michael Spence
  14. 14. Complex, Cascading, Non-linear The major disaster area in : National population Tohoku share 4.5% (Iwate, Miyagi and National GDP share Fukushima) 4%Japanese mining and manufacturing production inMarch: -15.5% (the biggest drop in history)Japanese export in April: -12% Source: Prof. Masahisa Fujita
  15. 15. March 11, 2011:The Headline You Did Not Read Prevention pays but designsystems that “fail gracefully”.
  16. 16. Risk Tolerance= F (Affordability) ALARP Principle ALARP Principle
  17. 17. 2. Examples
  18. 18. A Quick Word on the World Bank
  19. 19. Macroeconomic Planning & Disaster Risk Financing Integration of ClimateRapid Disaster Impact Change projections Estimation PACIFIC RISK INFORMATION SYSTEM Professional and Urban Planning and Institutional Infrastructure Design Capacity Development Source SOPAC
  20. 20. Satellite Administrative Population Agriculturalimagery Boundaries Census Census TopographicSurface Geology Surface soil Bathymetry maps Geodetic and Infrastructure References Fault Data Source: SOPAC
  21. 21. Creating Robust Risk Information 145° E 150° E 155° E 0 100 200 400 Kilometers 5° S 5° S Lae Port Moresby 10° S 10° SHazard Papua New Guinea AAL / Asset Value Exposure/Vulnerability 0% - 0.05% 0.05% - 0.1% 0.1% - 0.15% 0.15% - 0.2% 0.2% - 0.3% 0.3% - 0.4% 0.4% - 0.5% 0.5% - 1.15% 145° E 150° E 155° E RiskPacific Catastrophe Risk Assessment and Risk Financing in association with SPC/SOPAC and the ADB
  22. 22. Risk Assessment Event IntensityGeneration Calculation Damage Estimation Limit Loss Calculation Exposure Information Deductible Mitigation / Policy Policy Conditions Conditions Source: SOPAC
  23. 23. Country risk profilesAn Illustration with Solomon Islands
  24. 24. Acting collectively for cost-effectivefinancial solutions against major disasters Adding more countries increases risk diversification benefits Adding more perils increases risk diversification benefits Note: Impact of risk diversification on 150yr loss
  25. 25. Geonodes: Sharing Information for Resilience
  26. 26. Participatory Mapping: OpenStreetMapDKI Jakarta:100% coverageOver 6000structuresdigitized2,658 RWmapped
  27. 27. InaSAFE Impact analysis PDF Click
  28. 28. Jakarta flood prone areas and hospitalslo
  29. 29. Exact location of potentially flooded hospitals
  30. 30. Building the Open Source CommunitySAFE CodeSprint: Pavia Italy. November 12-16, 2012
  31. 31. Metro Manila and Can Tho:Getting the Balance Right Between ‘Structural and Non-structural MeasuresKeeping the water away from Keeping the people awaythe people from the waterHard engineered Increased preparedness • Awareness campaigns• Flood conveyance • Urban management• Flood storage Flood avoidance• Urban drainage systems • Land use planning• Ground water management • Resettlement• Flood resilient building design Emergency planning & management• Flood defenses • Early warning systems and evacuationEco-system management • Critical infrastructure• Utilizing wetlands Speeding up recovery• Creating environmental buffers • Building back smarter • Risk insurance
  32. 32. Ho Chi Minh City Developing an Integrated Flood Risk Management Strategy Urban growth in the periphery of the city had as a result newly-urbanized districts arising in sites at flood risk. Hard engineering or structural measures to minimize flood risk might be unsustainable under large hydrological, land subsidence and urbanization uncertainties.Components:• Protection to an appropriate return frequency, determined by predictions using historical data and non-stationary analysis• Adaptation to cope with extreme events that surpasses design criteria• Retreat, which means restoring space for water to adapt to long-term climate changes. Ho Long Phi Robust Decision Making (RDM) Helps Inform Good Decisions Without Reliable Predictions
  33. 33. Robust Decision Making (RDM) Helps Inform Good Decisions Without Reliable Predictions RDM follows “Deliberation with Analysis” decision support process Participatory Scoping 1.Define Goals, Uncertainties, and StrategiesKey idea: 2.Choose Candidate Strategy• Start with strategy• Use analytics to identify Tradeoff Analysis Case Generation scenarios where strategy fail to 5.Display and Evaluate 3.Estimate Performance of meet its goals Tradeoffs Among Strategy in Many Futures Strateg(ies)• Use these scenarios to identify and evaluate responses Scenario Exploration and Discovery 4.Characterize Strategy’s Vulnerabilities Deliberation Analysis Robust Strategy Vulnerabilities Source: Rob Lempert, RAND Deliberation with Analysis
  34. 34. Factors Potentially Considered in Our AnalysisX: Exogenous uncertainties L: Policy levers• Extreme precipitation (X mm/3 hrs) • System described in 2001 JICA Master Plan• Mean sea level • Adaptation options include:• Subsidence rate • Elevating buildings• Infrastructure performance • Small scale pumps• Delays in implementing flood control plans • Public awareness• Rate and patterns of economic and • Retreat options include: population growth • Restrictions/appropriate land use• Effectiveness of policies • Adaptive decision strategies• Costs of implementing policies • Signposts • ResponsesR: Relationships M: Measures of merit• SWMM Model • RI: Risk exposure (population/housing)• ArcGIS for calculating RI and DI • DI: Damage exposure (economic) Source: Rob Lempert, RAND
  35. 35. Risk Layering: A Balance-Sheet Approach to Risk Finance • Catastrophe Bonds100 Parametric insurance • • Traditional Insurance Probable Maximum 90 Loss 80 70 Transfer 60Contingent lines of credit • • Loans (Standard or Emergency) 50Budget reallocations • 40 Retention 30• Reserves/Calamity funds 20 10 0 1980 1985 1990 1995 2000 2005
  36. 36. 3. Emerging Directions
  37. 37. Emerging Directions1. Recognizing, measuring and responding to complexity (CCN for networks?).2. Cognitive limitations, Communicating uncertainty3. Beyond cost-benefit (fat tails), evidence based DRM, Value-for-Money4. The economics (and politics!) of open data for resilience.5. Decision-making in data-scarce environments, Big data, Simulations, Serious Gaming
  38. 38. Ultimately it boils down to….• INVESTMENTS: What concrete actions can we take to build resilience into our program?• INSTRUMENTS: What instruments do we need to support our clients to mainstream resilience ? (Data, metrics, analytical work etc.)• INCENTIVES: Institutionally why is this not happening, even for events that we know that are bound to take place? (Changing incentives)
  40. 40. Thank you!Abhas K.