Quantifying Disaster Risk: measuring progress in the path towards resilience

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1 Quantifying Disaster Risk: measuring progress in the path towards resilience Sujit Mohanty UNISDR -ROAP Expert Group Meeting (EGM) on Improving Disaster Data to Build Resilience in Asia and the Pacific, 30 September to 1 October 2013, Sendai, Japan

2 Escalating losses Total economic losses ( ) in million US$ for selected countries Source: GAR 2013

3 Our collective aim Substantial reduction of disaster losses, in lives and in the social, economic and environmental assets of communities and countries Expected outcome of the Hyogo Framework for Action : Building the Resilience of Nations and Communities to Disasters (Hyogo Framework)

4 The challenge of understanding Resilience A society resilient to natural hazards: that can absorb hazardous events impact; [capacity] that can distribute the risk among the different stakeholders; that can adapt to the changes in frequency and severity of hazards, as well as the continuous increase of assets, and continue to prevent disaster to happen; [adaptive capacity] Resilience assumes effective risk management and risk management requires measurements of hazard exposure and losses.

5 Risk can not be Managed or Reduced if it can not be Measured One starting point of understanding Disaster Risk Reduction and the path towards Resilience could be by :- Measuring Losses over time

6 Country perspective: Why governments need to understand/ measure risk and resilience? It can not be managed or reduced if it is not measured Optimizing Investment in disaster risk reduction no one has unlimited resources

7 Country perspective: Investment decisions Hazard, Exposure, Vulnerability Disaster losses (past) Future Risk (Probability of losses or Annual Average Loss) Can you avoid the risk? Yes Prospective DRM (Risk Avoidance) No Can you mitigate the risk? Yes Prospective DRM (Risk Mitigation) Risk Reduction No Can you transfer the risk? Yes Risk Transfer Cost and benefit No Risk Retaining Risk Finance

8 What is currently being done in Quantifying Risk?

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10 Source: Recording Disaster Losses: Recommendations for a European approach, 2013

11 Hazard Vulnerability Exposure Socio economic data/ Social statistics Spatial/ GIS data Climate data

12 Loss accounting (Global) EM-DAT(CRED): The first global database at national resolution with public access NatCat SERVICE (Munich RE): a global database at national resolution with no public access Sigma CatNet Service (Swiss RE) DesInventar: a national based accounting system (with implementation in large number (>45) of countries this is becoming a global dataset)

13 National level losses DesInventar (>45 ) Spatial Hazard Event and Loss Database for the US (SHELDUS) The Canadian Disaster Database: a national database for Canada, province/territory resolution with public access, with records from Emergency Management Australia Disasters Database: a national database for Australia, regional resolution with public access, with records from Disaster Incidence Database of Bangladesh (DIDB): a national database for Bangladesh, district resolution. Calamidat Disaster Event Database of Philippines: a national database of Philippines.. More

14 Disaster Forensic (Event specific loss assessment) PDNA / DALA: Damage and Needs Assessment Reports from Yr Countries PDNA Year Type of Disaster Seychelles 2013 Flood, Fiji 2013 Cyclone, Somoa 2012 Cyclone, Malawi 2012 Flood, Bhutan 2011 Earthquake, Pakistan 2011 Flood, Thailand 2011 Flood, Djibouti 2011 Drought, Kenya 2011 Drought, Lao PDR 2011 Typhoon, Lesotho 2011 Flood, Uganda Drought, Benin 2010 Flood, Guatemala 2010 Tropical Storm, Togo 2010 Flood, Pakistan 2010 Flood, Moldova 2010 Flood, Haiti 2010 Earthquake, El Salvador 2010 Tropical Storm, Cambodia 2009 Cyclone, Lao PDR 2009 Cyclone, Indonesia 2009 Earthquake, Samoa 2009 Tsunami, Philippines 2009 Cyclone, Bhutan 2009 Earthquake, Burkina Faso 2009 Flood, Senegal 2009 Flood, Central African Republic 2009 Flood, Namibia 2009 Flood, Yemen 2008 Tropical Storm, Haiti 2008 Hurricane, India 2008 Flood, Myanmar 2008 Cyclone, Bolivia 2008 Flood, Madagascar 2008 Cyclone, Bangladesh 2007 Cyclone, Indonesia 2006 Earthquake, Pakistan 2005 Earthquake, India 2005 Tsunami, Maldives 2005 Tsunami, Sri Lanka, 2005 Tsunami, Indonesia, 2005 Tsunami, Guyana, 2005 Floods, Grenada, 2004 Hurricane, Gujarat, India, 2001 Earthquake, El Salvador 2001 Earthquake, Belize 2000 Hurricane, Mozambique 2000 Flood, Turkey 1999 Earthquake 50 large scale events Source: The World Bank

15 Global hazard specific and multi-hazard datasets Earthquakes: US Geological Survey (USGS) Floods: Dartmouth Flood Observatory (DFO) Tropical cyclones: NOAA archives Tsunamis: NOAA/WDS Global Historical Tsunami Database Global Disaster Identifier Number (GLIDE)

16 Risk Modeling Comprehensive Probabilistic Risk Assessment (CAPRA)- open source tool combining hazard, Exposure and vulnerability (social and economical) data [ CAPRA Risk data viewer - Global Risk Data Platform- data on past hazardous events, human & economical hazard exposure and risk from natural hazards (including socio economic data). It covers tropical cyclones and related storm surges, drought, earthquakes, biomass fires, floods, landslides, tsunamis and volcanic eruptions. GAR/ UNISDR/ UNEP-GRID [ Global Earthquake model (GEM).more

17 Global Earthquake Model (GEM)

18 Current practice : Challenges What are the bottlenecks?

19 Current practices : Challenges No common Vocabulary for disaster data Data rich vs data poor countries Distinction in approach, purpose, scale and scope between global (EM-DAT, NatCat SERVICE, Sigma CatNet) and national databases (e.g. DesInventar) Less systematic loss data in Hazard centric databases Varied internal data collection processes of governments

20 Options/ suggestions A common vocabulary or a Standard set of Minimum required data Framework for Asia Pacific methodology that should to be standardized at local level Guidance to member states in their choice of implementation Starting point : Standardization of loss accounting (hazard event identification, affected elements, and loss indicators describing damage/loss of affected elements) Data standardization and more rigor in data collection/ analysis/ use in Future DRR framework (HFA2)

21 Update on upcoming global and regional processes

22 Hyogo Framework for Action ( ) Hyogo Framework for Action 2 (2015 -??)

23 Opportunities to change

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25 Thank You