2015 Global Risk Assessment. Sahar Safaie Program Officer, UNISDR Risk Knowledge Section

Transcription

1 2015 Global Risk Assessment Sahar Safaie Program Officer, UNISDR Risk Knowledge Section

2 Outline Global Assessment Report (GAR) evolution Global Risk Assessment for GAR15 Objective Scope Audience/Users Challenges faced in conducting the global risk assessment

3 2015 Global Assessment Report

4 Main Objective: Awareness and Advocacy 2015 To focus international attention on the extent of disaster risk at global, regional, and national level and encourage political and economic support for disaster risk reduction.

5 12 Technical partners with direct contributions 6 Hazards are covered: flood, earthquake, cyclone wind and storm surge, tsunami, volcanic eruption, drought Probabilistic Hazard modeling of 5 hazards at global scale Probabilistic risk modeling using CAPRA software Datasets and results including national risk profiles will be openly available

6 Probabilistic Risk Modeling Hazard Exposed assets Damage Loss exceedance Economic Human Vulnerability

7 Global Exposure Database The Global Exposure Database provides the distribution of the value of the urban, mid urban, and rural built environment A 5Km x 5 Km grid globally and 1kmx1km grid along the coasts Physical areas defined using BUREF producing a global reference layer of built-up by integrating population and remote sensing data Uses socioeconomic indicators (GDP, population(landscan), income level)

8 Global cyclone hazard assessment Probabilistic cyclonic wind developed using the open source program ERN-Hurricane ( Topography (SRTM), terrain roughness (SEDAC), Bathymetry (GEBCO-08) 2,534 scenarios were created Climate change scenario in Atlantic basin (up to 2055)

9 Global seismic hazard assessment Probabilistic Earthquake Hazard model, developed using the open source program CRISIS2014 ( Using the seismic catalogue by the ISC-GEM Initiative (to complement the existent USGS-NEIC catalogue) and GEM GMPE More than 1 million scenarios were created No site condition

10 Global tsunami hazard assessment Global probabilistic Tsunami hazard model Probabilistic Tsunami Hazard Assessment (PTHA) calculates a set of synthetic earthquakes to obtain a distribution of possible run-up heights

11 Global flood hazard assessment Global probabilistic flood hazard model Flood discharges associated to different return periods, in each of the world s major river basins, from information from 7,552 gauging stations worldwide SRTM digital elevation model used Defended flood model

12 Global Volcano Model Global evaluation of volcanic hazard threat to population Global probabilistic volcanic ash fall hazard model Asia Pacific probabilistic risk model of volcanic ash fall Source: Geoscience Australia

13 Vulnerability functions Asia pacific region specific vulnerability functions for most hazards Latin America and Europe region specific vulnerability functions Hazus vulnerability curve is the basis for most of the regions

14 Probabilistic Risk Modelling Output: Loss exceedance curve Using CAPRA risk modeling software Annual Average Losses (AAL) Probable Maximum Loss

15 Drought Hazard and Risk Agricultural drought hazard and Land degradation for Africa and the Mediterranean, and South America Regions (using Satellite imagery from ) Probabilistic assessment of crop losses for Malawi, Senegal, Mali, Niger, and Kenya including Climate change scenario ( )

16 Results of Global Risk Assessment

17 Component Technical Partners Exposure model at global scale United Nations Environment Programme Global Resource Information Database (UNEP-GRID) University of Geneva World Agency for Planetary Monitoring and Earthquake Risk Reduction (WAPMERR) Joint Research Center (JRC) Kokusai Kogyo, Beijing Normal University Earthquake hazard model at global scale International Center for Numerical Methods in Engineering (CIMNE) and INGENIAR Ltd. Cyclone wind and storm surge hazard model at global scale International Center for Numerical Methods in Engineering (CIMNE) and INGENIAR Ltd. Tsunami hazard model at global scale Norwegian Geolotechnical Institute (NGI) Flood hazard model at global scale Centro Internazionale in Monitoraggio Ambientale (CIMA) Foundation Volcano hazard and risk evaluation Including a global probabilistic volcanic ash fall hazard model and Asia Pacific volcanic ash fall probabilistic risk model Global Volcano Model (GVM) Geoscience Australia Vulnerability model for each region International Center for Numerical Methods in Engineering (CIMNE) and INGENIAR Ltd. (Latin America, Europe, Africa), Asia) Geoscience Australia (for Asia Pacific) Hazus (North America) Probabilistic risk model of all earthquake, cyclone wind and storm surge, flood, tsunami, and volcanic ash fall (Asia Pacific) Agricultural drought hazard and land degradation assessment of Africa and Middle East Climate change impact on agricultural drought in three African countries International Center for Numerical Methods in Engineering (CIMNE) and INGENIAR Ltd. Arab Centre for the Studies of Arid Zones and Drylands (ACSAD) Famine Early Warning Systems Network (FEWS NET) Others: World Meteorological Organization (WMO) coordinated and conducted peer review of the hydrometeorological hazard models UNESCO coordinated and conducted peer review of the geo hazard models and vulnerability model Global Earthquake Model (GEM): (a) earthquake catalogue and ground motion equations were adopted in UNISDR earthquake hazard model, (b) a task group of GEM governing board peer-reviewed UNISDR earthquake exposure, hazard and vulnerability model

18 Challenges faced in the process of implementing global scale multi-hazard risk assessment Faced by UNISDR Modeling methodologies and global datasets for each hazard that are identified as best available per consensus of international scientific community Communication and transparency in pros/cons/shortcoming of various models, data sets, tools Interdisciplinary Collaboration between risk modeling community and economists/social scientists and public policy experts Technical capacity at national level in developing countries

19 Challenges faced in the process of implementing global scale multi-hazard risk assessment Faced by Technical partners in various components Lack of quality data and open data at global scale (i.e. DEM, census data) Low level of research and data available specially in developing countries (i.e. structural vulnerability) Methodologies and tools to deal with the lack of quality data and open data challenge

20 Gap between supply of risk information and use of it by decision makers in DRM A WCDRR Working Session Based on preliminary discussions, six elements have been identified Political will and legitimacy The purpose and context Data availability and open data Technical capacity of the user Actionable risk assessment Communication of concepts and results

21 Thank you