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www.rmsi.com
Delivering a world of solutions
Quantifying the Catastrophe Exposures from
Cyclones, Floods and Earthquakes in 4 Indian States
Adityam KrovvidiHead & General ManagerRisk Management Group, RMSI
June 3, 2003
Delivering a world of solutions
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Delivering a world of solutions
Application Software Development
Modeling Framework
Stochastic Module
Hazard Module
Vulnerability Module
Financial Module
Results & Discussion
Limitations
Introduction
Presentation outline
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Introduction
A World Bank initiative
RMSI study objectives – Risk assessment
– Inputs for decision-making
Scope
– Four states: AP, OR, GJ, MH
– Three perils: Cyclone, Earthquake, Flood
– Assets: Housing, Educational & Medical Buildings, Roads & Bridges
Model resolution: Block
Results
– Exposure databases
– Hazard & risk mapping
– Potential costs of disasters
Deliverables: A detailed report
Introduction
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Definition of Block
Introduction
Andhra Pradesh Andhra Pradesh district mapdistrict map
(23)(23)
Block map Block map (1134)(1134)
Average AP block
– 242 sq. km (95 sq. mi)
– 1.5 times Florida zip
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Application Software Development
Introduction
Modeling Framework
Stochastic Module
Hazard Module
Vulnerability Module
Financial Module
Results & Discussion
Limitations
Modeling Framework
Presentation outline
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Modeling Framework
Probabilistic analysis for loss estimation
Modeling framework
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Application Software Development
Introduction
Modeling Framework
Stochastic Module
Hazard Module
Vulnerability Module
Financial Module
Results & Discussion
Limitations
Stochastic Module
Presentation outline
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Historical Cyclones Catalog
Past in-house study
Catalog compilation
– Major source: IMD
– Track data: 1891-2000
– Parametric data: 1950-2000» Central pressure
» Forward velocity
» Radius to max wind
Intensity scale
– Modified Saffir-Simpson
– Categories 0 to 5
Stochastic module
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Cyclone Activity in Andhra Pradesh
Landfall rate = 73 in 110 years
Catastrophic events
– 1977 Chirala - CAT5
– 1979 Ongole - CAT4
– 1984 Srihari Kota - CAT1
– 1989 Kavali - CAT4
– 1990 Machalipatnam - CAT3
– 1996 Kakinada - CAT1
Stochastic module
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Stochastic Events Generation
Coastline segmentation
– The 50 nmi gates capture the complex orientations
Simulation of events on each gate
– Develop CDFs for cyclone parameters» Central pressure
» Forward velocity
» Angle of landfall
– Stratified sampling of CDFs
– Events defined by random matching of parameters
– Pattern matching with historical tracks
4800
Stochastic events
Stochastic module
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Application Software Development
Introduction
Modeling Framework
Stochastic Module
Hazard Module
Vulnerability Module
Financial Module
Results & Discussion
Limitations
Hazard Module
Presentation outline
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Windfield modeling
Georgiou’s (1985) model adopted
Model parameters
– Pressure drop
– Forward velocity
– Track angle with site
– Radius to max wind
– Distance to site
Calibration of coefficients
– Historical storms reconstruction
Directional roughness
Peak gust wind speed at site
Validation
Hazard module
Site
R
Cyclone Track
(, P, VT, Rmax)
§
§
§
§
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Rainfall modeling
Model parameters
– Hourly precipitation rate
– Translational speed
– Size of cyclone
Hourly precipitation rate
– Jayanti (1987)
– Depends on:» Intensity of storm
» Sector & radius to site
– Modified for higher CATs
Significant size = 300 km radius
Integration at block centroid
Validation
Hazard module
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Storm Surge modeling
Nomogram based model
– Ghosh (1977, 1983)
Model parameters
– Central pressure
– Radius of max wind
– Forward velocity
– Angle of track to coastline
– Bathymetry
Profiles along and across the coast
Flood depth computations
– 100 m x 100 m DEM used
Surge tide at important towns on coast
Validation
Hazard module
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Cyclone Hazard Mapping
Hazard module
Wind speed
Rainfall
Storm surge
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Application Software Development
Introduction
Modeling Framework
Stochastic Module
Hazard Module
Vulnerability Module
Financial Module
Results & Discussion
Limitations
Vulnerability Module
Presentation outline
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Assets Inventory
Housing inventory in Andhra Pradesh
Vulnerability module
Buildings: residential, education & medical
– Source: Census 1991 projected to 2001
Roads & bridges: NH, SH, MDR, ODR, VR
– Source: Remote sensing images
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Vulnerability Functions – Overall Approach
Vulnerability module
Benchmark Benchmark curvescurves
(Intl. experience)(Intl. experience)
Reported loss Reported loss datadata
Damage data Damage data fromfrom
Event recon.Event recon.
Domestic Domestic Published Published Research Research
Base Base vulnerability vulnerability
Function Function (composite)(composite)
Engineering Engineering reviewreview
(Vul. Atlas, IS (Vul. Atlas, IS codes)codes)
InventoryInventory
++
+
Vulnerability Vulnerability FunctionsFunctions
Peakgust
MD
R (
%)
+
+
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Vulnerability Functions – Key Features
Considered
– Independent effects of wind, rainfall & storm surge
– Occupancy type: residential, educational & medical
– Building type based on wall+roof material
– Road type » Major- NH, SH, & MDR
» Minor- ODR & VR
Explicitly not considered
– Building age & height
Vulnerability module
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Application Software Development
Introduction
Modeling Framework
Stochastic Module
Hazard Module
Vulnerability Module
Financial Module
Results & Discussion
Limitations
Financial Module
Presentation outline
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Exposure
Modeled assets
– Housing
– Public infrastructure» Roads & bridges
» Educational institutions
» Medical facilities
Valuation at 2001 prices
Financial module
Exposure is the total value or replacement cost of assets that is at risk
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AAL at district level in Andhra Pradesh
Model Validation - Detailed
Financial module
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-
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
1977 Chirala 1979 Ongole 1990Machilipatinam
1999 Orissa
Modeled Loss (Crore Rs.)
Observed Loss (Crore Rs.)
Model Validation - Aggregated
Financial module
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Average Annual Loss (AAL)
Financial module
AAL is the expected loss per year when averaged over a very long period
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Exceeding Probability (EP) Curve
Financial module
EP curves are cumulative distributions that show the probability that losses will exceed a certain amount
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Application Software Development
Introduction
Modeling Framework
Stochastic Module
Hazard Module
Vulnerability Module
Financial Module
Results & Discussion
Limitations
Results & Discussion
Presentation outline
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Exposure Summary
45% of housing exposure in coastal districts of AP & OR
OR has lowest exposure due to poor economic status
Housing contributes about two-thirds in total exposure
Results & Discussion
0
10,000
20,000
30,000
40,000
50,000
60,000
ANDHRA PRADESH GUJARAT MAHARASHTRA ORISSA
Housing
Roads &Bridges
Education
Medical
Million $
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AAL Summary
AAL as % of exposure
– AP = 0.2%
– GJ = 0.1%
– MR = 0%
– OR = 0.3%
The long-term average losses are driven by Cyclones in AP, GJ & OR
AP has highest Cat risk and MR has least
0
10
20
30
40
50
60
70
80
90
Millions
AP GJ MR OR
EQ
FL
CY
Results & Discussion
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Loss Cost Summary
Risk modelers consider loss cost as AAL per thousand dollars of exposed value. The major advantage of loss cost over AAL is that it can be compared across perils, coverages, geographies, etc.
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
AP GJ MR OR
CY
EQ
FL
FL JP AP GJ OR
Cyclone 1.56 0.27 1.55 0.76 3.22
CA JP GJ MR
Earthquake 2.51 1.67 0.52 0.05 Housing damage potential
compared globally
OR cyclones have damage potential double that of Florida hurricanes
AP cyclones have the same potential as Florida and GJ’s potential is one-half of AP
GJ earthquakes have damage potential 10 times more than that of Maharashtra. However, it is 3 and 5 times lower than Japan and California
Results & Discussion
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EP Curves Summary
0.0%
5.0%
10.0%
15.0%
20.0%
- 500 1,000 1,500 2,000 2,500 3,000
Aggregate Loss (Million USD)
An
nu
al E
xcee
din
g P
rob
abili
ty
Andhra Pradesh Gujarat
Orissa Maharashtra
Loss return periods of historical events
– 2001 GJ earthquake, M7.9: 195 years ($1183 mn)
– 1999 OR cyclone, CAT5: 123 years ($1074 mn)
– 1993 MR earthquake, M6.3: 474 years ($127 mn)
– 1990 AP cyclone, CAT4: 37 years ($502 mn)
Results & Discussion
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Probable Maximum Loss (PML) Summary
There is no common approach or unified definition to evaluate PML. Since developing economies cannot afford to plan for a high risk tolerance a 150 year PML is suggested
0
200
400
600
800
1,000
1,200
Millions
AP GJ MR OR
Combined
Housing
Infrastructure
PML as % of exposure
– AP = 2.1%
– GJ = 2.1%
– MR = 0.1%
– OR = 3.2%
GJ needs $1 billion for Cat risk preparedness, closely followed by AP
Results & Discussion
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Financial Impact on States
Maharashtra is comfortably placed
Cat losses are unbearable given the debt and fiscal deficit position
PML has a significant impact on state GDP
States have no capacity to absorb PML shock
Orissa is the worst affected
StateAAL
(million $) %GDP %Tax rev%Fiscaldeficit
PML(million $) %GDP %Tax rev
%Fiscaldeficit
AP 83 0.3% 2.6% 5.5% 921 3.3% 28.7% 61.5%
GJ 65 0.3% 2.8% 2.1% 1,009 4.4% 43.7% 32.8%
MR 3 0.0% 0.1% 0.1% 59 0.1% 1.1% 2.7%
OR 43 0.6% 3.8% 1.8% 479 6.5% 41.9% 19.9%
Results & Discussion
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Application Software Development
Introduction
Modeling Framework
Stochastic Module
Hazard Module
Vulnerability Module
Financial Module
Results & Discussion
Limitations Limitations
Presentation outline
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Limitations of the Study
Limitations
Limitations are driven by the resource constraints and objectives
Census 2001 data was not available at the time of study
No detailed inventory – floor area, age, height, etc.
No boundary data below the block, say post code
Uncertainty not quantified
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