Enhancing Knowledge and capacity for the management of disaster risks for a resilient future in Asia and the Pacific Ex Ante Tool for Risk Sensitive Development Planning: Probabilistic Catastrophic Hazard Risk Assessment Regional Conference on Strategies and Tools for Integrating Disaster Risk Reduction into Development Planning and Financing 16-18 February 2015, Bangkok, Thailand
Probabilistic hazard risk assessments for risk sensitive development planning Target 1. Identifying the potential economic losses, despite insufficient historical data for analyzing Target 2. The ex-ante assessment tool to support the analysis of the future impact from the natural hazards Target 3. Creating powerful incentives for countries to develop planning options and tools to cope with risk Target 4. Contributing well-structured resource allocations to reduce those potential damage and safeguard development Target 5. Achieving mainstreaming Disaster Risk Reduction
Ex-Ante: Probabilistic Risk Assessment Perspectives in the modelling Vulnerability data Hazard data Risk data AND exposure data Hazards, Vulnerability, Exposure and Risk Data Reference: Piers Blaikie, Terry Cannon, Ian Davis, Ben Wisner, 2011, At Risk
Ex-Ante: Probabilistic Risk Assessment Principle modules in probabilistic earthquake risk model Hazard Module Exposure Module Vulnerability Module Set of Scenarios Damage and Loss Module Risk Transfer and Retention Module Cost-Benefit Analysis (CBA) Module Reference: (Cardona et al., 2008) Statistics Risk curve: Expected loss or loss occurrence probability
A concept of Probable Maximum Losses AEL: Annual Expected Losses = Single loss expectancy annual rate of occurrence PML: Probable Maximum Losses Estimates the maximum potential damage the value of the largest loss that could result from a disaster Losses Reference and source: European Environment Agency (2008), http://www.eea.europa.eu/data-and-maps/figures/example-of-the-adjustment-of-lossdistribution-as-a-consequence-of-changing-risk
Millions US$ 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2,000 - Probable Maximum Losses (100-200 yrs) in South East Asia EQ and Typhoon Probabilistic Models Phillippines Indonesia Vietnam Thailand Malaysia Cambodia Lao PDR Singapore % of GDP 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0-100 years 200 years Phillippines Indonesia Vietnam Thailand Malaysia Cambodia Lao PDR Singapore 100 years 200 years Reference and source: World Bank, GFDRR, ASEAN and UNISDR (2011), Advancing Disaster Risk Financing and Insurance un ASEAN Countries
Introduction of Probabilistic Catastrophic Hazard Risk Assessment for Development Planners Case Study : Nepal
Probabilistic risk assessment model - Development Planners Perspectives Perspective 1. Identifying insufficient data and capacity for each country for conducting probabilistic risk assessment Perspective 2. Easy to access and manage with insufficient data in the analysis Perspective 3. Developing less complicated and easyunderstanding applications Perspective 4. More concentrates on Macro-level economic losses: Using GDP and actively working population Perspective 5. Approach to sectorial analysis
A comparative study of probabilistic risk assessment models CAPRA OpenSHA OpenQuake Hazus MH 2.1 Selena 2.0 B E N E F I T S Multi-hazard risk assessment tool Detailed process and well-structured theoretical framework Supported by World Bank, UNISDR and the Inter-American Development Bank Being developed by CIMNE in Polytechnic University of Catalonia Specialized to earthquake Graph-based outcome are supported Collecting all possible ruptures and provide more accurate probability of occurrence Open Source risk assessment package Verified testing with same results Outcome calculate automatically Working with GIS application Well-structured application theoretical framework and manual Various base data for vulnerability and exposure analysis Open Source risk assessment package All theoretical framework from Hazus MH 2.1 Understandable manual Easy to customize: depends on types of data and disasters User-friendly interface L I M I T A T I O N S Numerous data are complementally required Need several trainings to run the application, data sorting and coding Annual average loss and other losses are manually calculated Do not have loss and damage function Only used for creating a set of scenarios and finding a probability of occurrence Should work with Hazus MH 2.1 or other applications those have loss and damage function Hard to understand the manual and need to know computer languages to run the application Only for an earthquake risk assessment The application should be worked with ArcGIS (ArcGIS 10 with SP2) Open Source package, but it is hard to customize Only US based data can be used Still not open to the rest of World Only for an earthquake risk assessment Not GIS based application Numerical base outcome will be shown in Excel file: not support for graphs and sorted table
Probabilistic Catastrophic seismic risk assessment proto-type application A modified SELENA 2.0 is being developed by UNESCAP (SEismic Loss EstimatioN uisng a logic tree Approach: SELENA) Developed by NORSAR and Universidad de Alicante Hazard data: Location (longitude, latitude, magnitudes of earthquakes, PGA (Peak Ground Acceleration), types of soil and Depth Based on these data, using random variables and creating scenarios (Ground shaking or shaking map) Vulnerability data: types of building, type of occupants, length of road Exposure data: GDP per Capita, Population and Economically active population These data will be applied in to a logic tree scheme which is the most critical part of SELENA 2.0. For the macro level analysis, the modified logic tree scheme was implemented.
Probabilistic Catastrophic seismic risk assessment prototype application A modified SELENA Input interfaces
Nepal Accumulated Seismic Risk The entire country lies in a high earthquake hazard area and thus the entire country is prone to earthquake hazards (GRIP and NSET, 2011). Between 1970 and 2007, Far Western and Eastern Regions recorded the highest levels of accumulated losses having faced the occurrence of a significant number of earthquakes Earthquake-prone areas in Nepal Reference: GRIP and NSET, 2011
Case study: Nepal 8 Earthquake histocial data in Nepal 7 6 5 4 3 2 1 0 Total earthquake occurrences: 94 events recorded in DesInventar Total number of death: Over 9,000 reported in EM-DAT Total number of affect people: Around 730,000 recorder in EM-DAT Total damages and losses in US$: Over 300 million US$ recorded in EM-DAT
Historical data for earthquakes in Nepal (http://earthquaketrack.com/) Near Kathmandu Date Date Time Time M Focal Depth Location Latitute Longitude Type of Magnitude 1988 20-Aug 21-Aug 23:09 6:09 6.8 13 km Lahan 26.755 86.616 mb 2011 18-Sep 19-Sep 12:40 19:40 6.9 63 km Gangtok, Sikkim, India 27.719 88.137 mb 2008 25-Aug 25-Aug 13:21 20:21 6.7 293 km Baglung 30.901 83.52 mb 1993 20-Mar 20-Mar 14:51 21:51 6.2 191 km Khandbari 29.084 87.333 mb 1980 29-Jul 29-Jul 14:58 21:58 6.6 84 km Pithoragarh, Uttarakhand, India 29.598 81.092 mb 2005 7-Apr 8-Apr 20:04 3:04 6.3 247 km Baglung 30.491 83.662 mb 1974 24-Mar 24-Mar 14:16 21:16 5.7 59 km Banepa 27.727 86.11 mb 2004 11-Jul 11-Jul 23:08:00 6:08 6.2 270 km Baglung 30.694 83.672 mb 1980 19-Nov 20-Nov 19:00 2:00 6.1 14 km Gangtok, Sikkim, India 27.394 88.752 mb 1974 27-Sep 27-Sep 5:26 12:26 5.6 99 km Kathmandu 27.85 86.941 mb 1998 3-Sep 4-Sep 18:15 1:15 5.6 60 km Khandbari 27.85 86.941 mb 1997 3-Nov 3-Nov 2:29 9:29 5.5 151 km Kathmandu 29.078 85.383 mb 2010 26-Feb 26-Feb 4:42 11:42 5.5 128 km Khandbari 28.436 86.726 mb 1988 29-Oct 29-Oct 9:10 16:10 5.4 29 km Banepa 27.871 85.648 mb 1975 31-Jan 31-Jan 12:38 19:38 5.4 54 km Bharatpur 28.1 84.729 mb 1988 20-Apr 20-Apr 6:40 1:40 5.4 41 km Lahan 27.042 86.694 mb 1986 10-Jan 10-Jan 3:46 10:46 5.4 150 km Banepa 28.648 86.527 mb 2009 7-Nov 8-Nov 20:08 3:08 5.5 208 km Kathmandu 29.49 86.008 mb 1997 31-Jan 1-Feb 20:02 3:02 5.2 31 km Kathmandu 27.946 85.127 mb 1978 4-Oct 4-Oct 13:53 20:53 5.2 49 km Banepa 27.834 85.963 mb Near Xizang Nepal Border Date Date Time Time M Focal Depth Location Latitute Longitude 1974 27-Sep 27-Sep 5:26 12:26 5.6 99 km Kathmandu 28.596 85.496 mb 1987 9-Aug 10-Aug 21:15 4:15 5.6 138 km Baglung 29.502 83.714 mb 1997 3-Nov 3-Nov 2:29 9:29 5.5 151 km Kathmandu 29.078 85.383 mb 1975 31-Jan 31-Jan 12:38 7:38 5.4 54 km Bharatpur 28.1 84.729 mb 1984 18-Nov 19-Nov 22:04 5:04 5.3 63 km Pokhara 28.799 84.073 mb 1978 10-Feb 11-Feb 17:29 12:29 5.2 48 km Bharatpur 28.072 84.644 mb 2014 3-Aug 3-Aug 5:57 12:57 5.2 179 km Kathmandu 29.307 85.588 mb 1987 19-Jan 19-Jan 7:46 2:46 5.2 15 km Baglung 28.458 83.343 mb Near Nepal India Border Date Date Time Time M Focal Depth Location Latitute Longitude 1980 29-Jul 29-Jul 12:23 19:23 5.7 93 km Tikapur 29.331 81.258 mb 1981 18-May 18-May 4:28 11:28 5.6 139 km Tikapur 29.577 81.869 mb 2001 27-Nov 27-Nov 7:31 2:31 5.5 137 km Tikapur 29.606 81.752 mb 2001 27-Nov 27-Nov 8:53 3:53 5.4 131 km Tikapur 29.543 81.632 mb 1991 9-Dec 9-Dec 1:02 8:02 5.4 125 km Tikapur 29.543 81.632 mb 2011 4-Apr 4-Apr 11:31 18:31 5.3 53 km Pithoragarh, Uttarakhand, India 29.698 80.754 mb 1976 10-May 11-May 18:43 1:43 5.2 92 km Tikapur 29.284 81.46 mb 1993 20-Mar 21-Mar 21:26 4:26 5.2 182 km Khandbari 28.994 87.383 mb 1992 2-Jun 3-Jun 22:07 5:07 5.2 93 km Tikapur 28.984 81.913 mb
Probabilistic Catastrophic seismic risk assessment Proto-type application for Nepal Input data (Nepal Planning Commission 2011 Census, Output data Set of scenarios Macro level Outcome: damage in GDP per capita Macro level data: GDP per capita Hazard data (Historic) Vulnerability data: Micro level NPC 2011 Census data Exposure data Causalities output Loss and Damage in Physical assets or causalities (Micro level outcomes)
Probabilistic Catastrophic seismic risk assessment proto-type application Period Probable Maximum Losses >8 magnitude (4-5) magnitude GDP per Capita Losses Period GDP per Capita Losses 10 years 8926 10 years 115783 25 years 21340 25 years 39058 50 years 39615 50 years 2773 100 years 68261 100 years 7 200 years 101334 200 years 0
Far western Mountain Far western Hill Mid western Mountain Probabilistic risk assessment outcomes: *Magnitude 5-4 and within 10 years* Far western Tarai Mid western Hill Western Mountain Mid western Tarai Western Hill Western Tarai Central Hill Central Mountain Eastern Mountain Region Exposed Damage in GDP per Capita Central Hills 76573 11940 Eastern Mountain 57228 11515 Central mountain 43747 8427 Eastern Hills 44901 8050 Far Western Tarai 38070 5501 Central Tarai Eastern Hill Eastern Tarai Nepal Rupee (GDP per Capita), 2011 Census data in Nepal
Far western Mountain Far western Hill Mid western Mountain Probabilistic risk assessment outcomes: *Magnitude greater than 8 and within 200 years* Far western Tarai Mid western Hill Western Mountain Mid western Tarai Western Hill Western Tarai Central Hill Central Mountain Eastern Mountain Region Exposed Damage in GDP per Capita Central Hills 76573 10450 Eastern Mountain 57228 10078 Central mountain 43747 7376 Eastern Hills 44901 7046 Far Western Tarai 38070 4814 Central Tarai Eastern Hill Eastern Tarai Nepal Rupee (GDP per Capita), 2011 Census data in Nepal
Probabilistic Catastrophic seismic risk assessment A proto-type Ex Ante Tool for Risk Sensitive Development Planning 4 Take away messages It s easy to customize for development planner, easy to adapt It s based on macro level data that is easier to access and collect than micro level data on vulnerability and exposure May be adapted for provincial or district level analysis for land management and land use planning, regional development planning or large engineering projects It may be used for ex-ante analysis for risk assessment before conducting more detailed analysis
Enhancing Knowledge and capacity for the management of disaster risks for a resilient future in Asia and the Pacific Contributors Jonghyo Nam, Economist ESCAP Consultant D Das, Analyst, RIMES Indrajit Pal, Seismologist, AIT Sung Eun, Economist ESCAP Staff Member Sanjay Srivastava, Chief Disaster Risk Reduction Section, ESCAP