Challenges and Solutions for Exposure...
Transcript of Challenges and Solutions for Exposure...
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2015/FMP/SEM1/019 Session: 7
Challenges and Solutions in Developing Exposure Data: Case of Philippines
Submitted by: AIR Worldwide
Seminar on Disaster Risk Finance – APEC Roadmap for Resilient Economies
Bacolod, Philippines29-30 April 2015
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Challenges and Solutions In
Developing Exposure Data:
Case of Philippines
Apoorv Dabral. Ph.D.
Manager, Research and Modelling- AIR Worldwide, Singapore
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- Categorization of exposure
- Why AIR develops the exposure dataset
- AIR’s approach to developing exposure databases
- Challenges in developing exposure data for
government assets
Agenda
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0
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20 50 100 250 500 1,000
Me
an L
oss
($
B P
HP
)
Mean Return Period (Years)
Philippines Aggregate Combined Loss Curve
Combined Peril Loss
Earthquake Loss
Tropical Cyclone Loss
NTC Precipitation Loss
NOTE:
Results shown are ground-up annual
aggregate Coverage A losses and include
both government assets and private assets.
Based on 10,000-year stochastic event
catalog
Exposure is the Main Input In a Risk Modeling
Framework
0 0.5 1 1.5
MD
R
Sa (0.3s)
Base Damage Functions
Concrete
Masonry
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- Industry Exposure Database (IED)
• Database of the building stock exposed to catastrophe risk are
developed using well established methodology and data gathered from
local agencies and publicly accessible sources
• Database includes building replacement values and other primary
structural characteristics required for catastrophe risk assessment
• Database validated using previous studies conducted in the country
- Government Asset Database
• Database of national government assets which are developed using
data from government agencies and supplemented by publicly
accessible sources
• Replacement values and assets characteristics are required for
catastrophe risk assessment
Exposure For Risk Analysis Can be Divided Into
Two Main Categories
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AIR Has IED’s for More Than 90 Countries as It is a
Critical Component in Model Development
- Methodology adopted for development is similar to that adopted for more than 90countries
- Robust IEDs are critical for• Sovereign (and local) level risk assessment and risk transfer
solutions• Developing and validating models• Providing confidence in loss distributions • Estimating losses for real-time events
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- IEDs are independently developed using data from
government and private vendors
AIR’s IEDs Are Built from the Ground Up to Provide
a Comprehensive Database of All Properties
- Client exposure data
used to validate, rather
than build, the IED
- AIR creates multiple
views of the IED for each
country
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Industry
Exposure
Database
AIR Employs a Robust Approach for Building
Industry Exposure Databases
Rebuild Cost Approach
Replacement
Values
Benchmarking
• National Economic Data
• Insurance PublicationsConstruction
Distribution
Assignment of
construction types to
risks
Disaggregation
High-resolution
spatial mapping of
risks
Spatial Cost
Index
National costs
adjusted for regional
variation
AIR High-Resolution
Attribute Modeling
• Population &
economic censuses
• Housing surveys
Risk Counts
• Occupancy
• Construction & Height
• Floor Area
Risk Attributes
• Costing Manuals
• Construction Indexes
Construction Costs
Data Collection
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Primary Data Sources Used to Develop Risk Counts
Variable Vintage Nationwide Region Municipality
Census of Population
and Housing 2010 X
2007 X
2000 X
Annual Survey of
Philippine Business
and Industry
2012 X
2010 X
2000 X
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Data Disaggregation Improves Spatial Accuracy of
Exposures
Data typically available at low
geographic resolutionActual risk distributions reflect
human settlement patterns
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Various Types of Data Used to Develop
Construction Distributions
GIS Layers
Urbanicity, Hazard
and Location
Census and
Surveys
Height, Wall, Frame
and Year Built
Distributions
Engineering
and Risk
Assessment
Studies
Structural Types
Handbook On Good
Building Design And
Construction In The
Philippines
200720052001
Philippines Wind Zone Philippines Hazard MapPhilippines Seismic Zone
Concrete/Brick/
Stone Wall Type
Distribution from
Census
Wood Wall Type
Distribution from
Census
0-20%
21-40%
41-60%
61-80%
81-100%
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Structural Types Included in the Industry Exposure
Database
Non-engineered
& Wood
• Reinforced Concrete
Shear Wall(With MRF)
• Reinforced Concrete
Shear Wall(Without
MRF)
• Reinforced Concrete
MRF
• Light Metal
• Steel MRF
• Steel Reinforced
Concrete
• Non-engineered
• Wood Frame
Masonry
• Unreinforced
• Reinforced
• Confined
Concrete Steel
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- Spon’s Asia-Pacific Construction Handbook (Davis
Langdon & Seah International)
- Philippines Report, Rider Levett Bucknall
- International Report, Rider Levett Bucknall
- Construction Statistics from Approved Building Permits
(Philippines National Statistics Office)
- Strengthening Natural Hazard Risk in the Philippines
(World Bank)
Replacement Costs Developed From a Variety of
Sources
Wood URM RM Concrete Light Metal Steel
Un
it C
ost
(P
HP
/sq
m) Single Family
Commercial
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Commercial Exposures are Concentrated in Urban
Areas
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Residential Exposures Reflect Population Centers
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National Government Asset
Database
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- Data can be incomplete and inaccurate
- Same data from two sources are sometimes contradicting
- Data often not in a format for use with catastrophe models
- Data sometimes come as a hard copy requiring significant
effort to turn them into a usable electronic database
- Delays in response from some agencies
- General difficulty in acquiring certain exposure datasets
- While it was perceived that a lot of data was available and
easily accessible in the Philippines, the data in general was
difficult to obtain, incomplete, and not at the level that can be
directly or easily used for an exposure database
Data Collection Challenges (from a Catastrophe
Modeling Perspective)
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Different Local Agencies Provides Different Dataset
Abbreviation Agency
BOC Bureau of Corrections
CAAP Civil Aviation Authority of the Philippines
CHED Commission of Higher Education
DepEd Department of Education
DILG Department of Interior and Local Government
DOH Department of Health
DPWH Department of Public Works and Highways
GSIS Government Service Insurance System
LRTA Light Rail Transit Authority
NPC National Power Corporation
NSO National Statistics Office
PNR Philippine National Railway
PPA Philippine Ports Authority
TransCo National Transmission Corporation
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Final Government Asset Database Statistics and
Cost Map
0%
2%
4%
6%
8%
10%
12%
14%
16%
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Government Asset Database
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Spatial Distribution of Some Assets: Ports, Rail, Public Universities,
Public Administration Buildings, Airports, Prisons, Bridges, Etc.
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- AIR has IEDs for the over 90+ countries it models• All IEDs developed from ground up
• IEDs provide comprehensive view of risks and values
- The IED development process leverages the latest technologies and state of the art techniques• Multiple data sources, including remote-sensed data
• Sophisticated algorithms
- A host of data sources coupled with rigorous methodology result in robust high resolution IEDs
- There are several challenges in building a robust national assets exposure database
- There is a need for Government agencies to collect , process and share the data for a more accurate disaster risk assessment.
Summary