Population

Document Sample
Population Powered By Docstoc
					          Disaster Management Framework for Preparedness



        Inderjit Claire
        Vice President
        RMSI

        October, 2007




Delivering a world of solutions
Delivering a world of solutions

                                                    www.rmsi.com
                  Need for Mainstreaming Pre-hazard Risks Management

          Frequency and magnitude of
           losses from natural disasters have
           been constantly increasing
          Losses from recent natural
           disasters have been a great deal
           higher than those that occurred
           earlier in time
          This trend is expected to continue
           because of an increasing higher
           concentration of population and
           property in areas susceptible to
           natural hazards
                                                Losses from major natural disasters world-
                                                  wide from 1950-2006 (in 2006 $ values)
                                                (Courtesy: NatCatSERVICE, Geo Risks Research, Munich
                                                                        Re)




Delivering a world of solutions

                                                                                          www.rmsi.com
                                    Hazards



                                   Earthquakes
                                   Tsunami
                                   Landslides
                                   Cyclones
                                   Floods
                                   Fire




Delivering a world of solutions

                                                  www.rmsi.com
                                  Hazard Risk Management Framework
           Emergency Preparedness                       Institutional Capacity Building
              Emergency Response Planning                      
                                                                Community Participation
                       Exercises                              Legislative Framework
                    Public Awareness                     Training, Education and knowledge
              Communication and Information                             Sharing
                 Management Systems (IMS)                Decentralized Emergency Management
              Technical Emergency Response                              System
                          Capacity                           International Cooperation


                                              Risk
                                           Assessment
           Risk Mitigation Investments                  Catastrophe Risk Financing
             Warning and Monitoring Systems                  Ex-Ante Funding Arrangements
          Hazard Mapping and Land Use Planning               Catastrophe Insurance Pools
            Code Refinement and Enforcement                        Reserve Funds
              Hazard Specific Risk Mitigation                 Contingent Capital Facility




Delivering a world of solutions

                                                                                    www.rmsi.com
       Scenario Based Vulnerability Mapping – Earthquake Example
                       Starts with scenarios, then defines the hazard, then estimates the
                        vulnerability, calculates what is the exposure and finally estimates
                        probable total damage




Delivering a world of solutions

                                                                                               www.rmsi.com
                                  Disaster Risk Modeling Process

                                           Calculating the hazard coefficients for
                                           stochastic events generated.


                                           • Stochastic Module generates random
                                           events from the characteristics of historical
                                           events that have occurred in the region.

                                           • Hazard Module analyses the hazard
                                           coefficients for each geographic region based
                                           on various identified perils applicable in the
                                           region.




Delivering a world of solutions

                                                                                    www.rmsi.com
                                  Disaster Risk Modeling Process

                                           Calculating the vulnerability and
                                           exposure of the area against
                                           disasters.
                                           • Vulnerability Module focuses on
                                           assessment of physical vulnerability of
                                           buildings and infrastructure to ground shaking
                                           and collateral hazards and social vulnerability
                                           of affected population.

                                           • Exposure Module involves the tasks of
                                           classification and quantification of the
                                           exposures at locality, sector, county,
                                           community and city levels.



Delivering a world of solutions

                                                                                   www.rmsi.com
                                  Disaster Risk Modeling Process

                                           Calculating the loss from disasters



                                           • Damage/Loss Module: Finally, the damage
                                           ratio from the vulnerability module is multiplied
                                           by the value of the exposed risk at a location to
                                           calculate an estimated monetary loss.




Delivering a world of solutions

                                                                                    www.rmsi.com
                                  Vulnerability




                                                  At what scale
                                                        the
                                                   do we need
                                                  vulnerability
                                                   to carry out
                                                     mapping
                                                        the
                                                   needs to be
                                                  vulnerability
                                                       done
                                                     mapping



  Vulnerability
  parameters




Delivering a world of solutions

                                                  www.rmsi.com
                                   Vulnerability has a Spatial Component


                Which places are more vulnerable to a hazard?
                        –     Which geographical region, socio-economic class etc.
                Who are the vulnerable people?
                        –     Relative vulnerability among households and
                              individuals
                What should be done?
                        –     Link to intervention/ adaptation




Delivering a world of solutions

                                                                                     www.rmsi.com
                                                        Social Vulnerability
                                     Coping Ability
                                       –   Resistance
                                       –   Resilience
                                     Social Environment
                                       –   Age
                                       –   Gender
                                       –   Ethnicity
                                       –   Household type
                                     Economic Environment
                                       –   Income and Assets
                                       –   Insurance
                                       –   Debts
                                     Overlay environmental hazard maps with vulnerability maps to
                                      determine areas vulnerable to hazards
                                     Add values, weights, factors for each variable in each layer to
                                      represent “Total Vulnerability”



Delivering a world of solutions

                                                                                                        www.rmsi.com
                     Vulnerability Module – Statistical Data Requirements

                             Physical Vulnerability        Social Vulnerability


                            • Physical vulnerability     • Social vulnerability is
                            refers to the degree to      the susceptibility of
                            which an asset would         populations to death and
                            get damaged or               injuries - the assessment
                            destroyed in a               of which involves
                            hazardous environment        casualty modeling to
                            caused by catastrophic       compute mortality and
                            events                       injury rates associated
                                                         with various
                            • Physical vulnerability     catastrophic events
                            can be for residential
                            and commercial               • Population Data
                            buildings, critical          reflecting the age,
                            facilities, infrastructure   gender, ethnicity and
                            and agriculture              household type
Delivering a world of solutions

                                                                                 www.rmsi.com
                                  Exposure Module: Use of Statistical Data

           • Building Use – Residential, Commercial, Industrial
           • Type of Buildings
                    • Type of Construction – Steel, Concrete, Masonry
                    • Category/Building class
                    • Building Height, No. of floors
                    • Building age
                    • Built up floor area of the buildings
           • Occupancy Details – Population density



                            Exposure Module calculates how much of the population and
                                   buildings are ‘exposed’ to the natural hazard
Delivering a world of solutions

                                                                                   www.rmsi.com
                                      Case Study – India Earthquake Model

                                                                        Objective of the Project: The risk modeling
                                                                        involved historical catalog compilation, hazard assessment,
                                                                        vulnerability evaluation, exposure development, and loss
                                                                        analysis.

                                                                        Data Available:
                                                                        -    Census Houses data (Block level)
                                                                        -    Occupancy wise Census data (District level)
                                                                        -     For each block/town total number of residential
                                                                             census houses is calculated from the total
                                                 Residential Exposure
                                                                             number of census houses by applying the
                                                   in billion rupees
                                                                             percentage of residential census houses
                                                                             computed at district level
                                                                        -    Building Attribute data available was State level
                                                                        -    Height data was missing for certain areas
                                                                        Results: Various loss results including average
                                                                             annual losses (AAL), loss costs and probable
    Residential exposure at block level in billion rupees
                                                                             maximum losses (PML)
                                                                        Alternatives used: Remote Sensing techniques
                                                                             were used to generate the unavailable data


Delivering a world of solutions

                                                                                                                        www.rmsi.com
                                  Case Study – Romania Earthquake Model

                                                      Objective of the Project: Design and
                                                      customization (where appropriate) of a model for
                                                      damage computation following an earthquake in
                                                      Romania.

                                                      Data Available:
                                                      -   Census Houses data (Commune level)
                                                      -   Occupancy wise Census data
                                                          (Commune level)
                                                      -   Building Attribute (County level)
                                                      -   Height data (Commune level)
                                                      Results: Various loss results including
                                                          average annual losses (AAL), loss costs
                                                          and probable maximum losses (PML)
                                                      Use of spectral intensity approach which
                                                      is different for different heights of the
                                                      buildings.


Delivering a world of solutions

                                                                                               www.rmsi.com
           Case Study: Developing a Disaster Risk Profile for Maldives

                 Business need
                     –     Maldives was among the most severely
                           affected countries hit by the Asian
                           Tsunami on December 26, 2004
                     –     UNDP initiated a study to analyze
                           Maldives’ high level of vulnerability and to
                           avoid the present scale of losses and
                           damage in the future
                     –     Recovery and development planning to be
                           based on Disaster Risk Management
                           (DRM) strategy




Delivering a world of solutions

                                                                          www.rmsi.com
            Case Study: Developing a Disaster Risk Profile for Maldives

              Solution
                 –     Countrywide study: 200 inhabited                                       Hazard
                       islands out of a total of 1190 islands -          Historical        Assessment
                                                                                        Tsunam     Storm
                       completed in a challenging timeframe of             data             i
                       6 months                                                         Earthqua        SLR
                                                                                           ke
                                                                                               Hazard
                 –     Hazards: Tsunami, Earthquake, Storms,                                    zones
                       Floods, and Climate Change
                 –     Vulnerability: Physical and Social                                  Vulnerability
                                                                         Exposur
                                                                                              Analysis
                                                                                        Physical     Social
                                                                            e
                 –     Exposures: Buildings, infrastructure and
                       agriculture
                                                                                      Damages/Los     Affected
                 –     GIS base map developed                                            ses         Population

                 –     GIS and CAT risk modeling integration                               Risk Profiling
                                                                          Weights
                 –     Hazard and risk maps developed                                    Individual hazards and
                                                                                         Individual hazards and
                                                                                               multi hazard
                                                                                              multi hazard
                           »      Assessments represented on a 5 point
                                  ordinal scale

                                                                                            Risk indices by
                                                                                                island


Delivering a world of solutions

                                                                                                        www.rmsi.com
           Case Study: Developing a Disaster Risk Profile for Maldives

                Benefits
                   –     Comprehensive report and base
                         maps generated
                   –     Government of Maldives used
                         the report as a key input for
                         planning developmental
                         strategies to mitigate future
                         disasters
                   –     First GIS base map of Maldives
                         developed




                                  3-D view of bathymetry of Maldives (depth
                                                  in meters)
Delivering a world of solutions

                                                                              www.rmsi.com
                                                  Data Sources


                   Public records data
                    county, city departments
                           –      Census Data


                   Other sources
                           –      Satellite imagery, aerial
                                  photos
                           –      Administrative boundary
                                  maps
                           –      Land use/ Land cover maps




Delivering a world of solutions

                                                                 www.rmsi.com
                        Analysis: Land Use wise Distribution of Population




                                                                    Flood Extent




Delivering a world of solutions

                                                                               www.rmsi.com
                                  Delivering a world of solutions




                                         info@rmsi.com

                                         www.rmsi.com




Delivering a world of solutions

                                                                    www.rmsi.com

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:3
posted:11/10/2011
language:English
pages:21