Transcript 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.

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 worldwide 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
 Emergency Response Planning
 Exercises
 Public Awareness
 Communication and Information
Management Systems (IMS)
 Technical Emergency Response
Capacity
Institutional Capacity Building

Community Participation
 Legislative Framework
 Training, Education and knowledge
Sharing
 Decentralized Emergency Management
System
 International Cooperation
Risk
Assessment
Risk Mitigation Investments
 Warning and Monitoring Systems
 Hazard Mapping and Land Use Planning
 Code Refinement and Enforcement
 Hazard Specific Risk Mitigation
Catastrophe Risk Financing

Ex-Ante Funding Arrangements
 Catastrophe Insurance Pools
 Reserve Funds
 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
Scale
Indices
National
comparisons of
vulnerability
National
Vulnerability
parameters
Users
Eligibility for
adaptation
funding
Regional
Multiple dimension
profiles of regional
vulnerability
Regional
agencies:
Programme
design
Local
Profiles of vulnerable
situations or syndromes
Local offices:
Project
evaluation
Ecosystems
Water
Other
sectors
Food
Health
At what scale
theneed
do we
vulnerability
to carry out
mapping
the
needs to be
vulnerability
done
mapping
Settlement
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
which an asset would
get damaged or
destroyed in a
hazardous environment
caused by catastrophic
events
the susceptibility of
populations to death and
injuries - the assessment
of which involves
casualty modeling to
compute mortality and
injury rates associated
with various
catastrophic events
• Physical vulnerability
can be for residential
and commercial
buildings, critical
facilities, infrastructure
and agriculture
• Population Data
reflecting the age,
gender, ethnicity and
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
number of census houses by applying the
percentage of residential census houses
computed at district level
-
Building Attribute data available was State level
-
Height data was missing for certain areas
Residential Exposure
in billion rupees
Results: Various loss results including average
Residential exposure at block level in billion rupees
annual losses (AAL), loss costs and probable
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
islands out of a total of 1190 islands completed in a challenging timeframe of
6 months
–
Hazards: Tsunami, Earthquake, Storms,
Floods, and Climate Change
–
Vulnerability: Physical and Social
–
Exposures: Buildings, infrastructure and
agriculture
–
GIS base map developed
–
GIS and CAT risk modeling integration
–
Hazard and risk maps developed
»
Assessments represented on a 5 point
ordinal scale
Historical
data
Exposur
e
Hazard
Assessment
Tsunam
Storm
i
Earthqua
ke
Hazard
zones
SLR
Vulnerability
AnalysisSocial
Physical
Damages/Los
ses
Affected
Population
Risk Profiling
Weights
Individual hazards
hazards and
Individual
multi hazard and
multi hazard
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
[email protected]
www.rmsi.com
Delivering a world of solutions
www.rmsi.com