systematically accounting and assessing disaster losses and impacts

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Systematically accounting and assessingdisaster losses and impacts

Loss Accounting

Risk Modelling

Hazard 1 Hazard 2 Hazard 3 Hazard n

Portfolio 1Assets and people

at risk

Risk retention Risk transferRisk reduction Others…

Monitoring and following-up

Risk Management Strategy 1

Risk Management Strategy 2

Risk Management Strategy 3

Risk Management Strategy n

Portfolio 1Assets and people

at risk

Portfolio 1Assets and people

at risk

Portfolio 1Assets and people

at risk

Tool Kit-Policy options

The overall process

National disaster loss databases: Deconstructing disasters

EM-DAT: Global level of Observation, National level resolution

DatacardsDeathsMissingHouses destroyedHouses demagedVictimsAffectedLosses (runees)Edication center

14715,304

24724,767792,377941,902

12,294,9237,832,749,237

3,703

FatalitiesAffectedDamage

9,84512,628,312

2.5 billion US$

State of Orissa dataset

A detailed picture of historical disaster losses and impacts

• A rich set of indicators

• Coverage of small, medium and large scale disasters.

• Disaggregation of data to usable units (District / Block / Building)

• Collected and validated locally within the country/state

Disaster loss accounting, analysis and reporting

Geographic description and source

Impacts(16 quantitatifs indicatorsand 12 qualitatifs)

Possibility to add options or new indicators

Typical contents of a DesInventar dataset

Informing risk governance and population

UNISDR support to countries building DLDB

8585

European Community Standards

European Community Standards

• Historical Risk Profiles, Baselines and Monitoring• Weather related disasters and CC• Relation to probabilistic models• Economic impact of past disasters• Generation of Empirical Risk Measures• Hybrid (Empirical + Analytical) Risk Models• Validation and Calibration of models

Usage of Disaster Loss Databases

Historical Risk Profiles, Baselines and Monitoring

NEPAL: Historical Risk Profile elements

Mortality due to storm surges

DRR and CCA: Storm surges in Peru (1970 – 2009)

Temporal distribution of storm surge reports

Mortality due to storm surges

Housing sector damage/destruction dueto extreme precipitation events

Mortality due to extreme precipitation events

Frequency of extreme precipitation events

Weather related disasters in S. America (1970 – 2009)

Historical data used to validate Risk/Hazard maps

Comparison of Cyclone/wind reports, deaths, damages and Hazard Atlas - ORISSA

Low

HightNumber of Reports of Cyclone, Winds Houses Damaged or Destroyed due to Cyclone, Winds

Direct Mortality due to Cyclone, Winds

Historical data used to validate Risk/Hazard maps

Number of Flood Reports in Orissa

Comparison of Flood reports, deaths, damages and Hazard Atlas - ORISSA

Low

Hight

Direct Mortality due to Floods in Orissa

Damaged and Destroyed houses due to Floods in Orissa

Probabilistic Risk AssessmentHazard Modeling

Exce

edac

e ra

te

Intensity measure

T = 100 years

T =500 years

= 0.01

= 0.002

= 0.001

Hazard maps for several return periodsHazard Intensity exceedance curve for each computation site

T = 1000 years

Loss Exceedance Curves0.001

0.01

0.1

1

10

100

1,000

10,000

100,0000.00001

0.0001

0.001

0.01

0.1

1

10

100

1,000

0.01 0.1 1 10 100 1,000 10,000 100,000

Retu

rn p

erio

d [y

ears

]

Loss

exc

eeda

nce

rate

[1/y

ear]

Economic loss [Million $USD]

Analytical curve

Risk Pure Premium - RPP

Average Annual Loss - AAL

Probable Maximum Loss - PML

It represents, the annual average of future expected losses, including catastrophic risk (disasters that have not happened yet but may, and eventually will happen).

It is computed as the AAL divided by the portfolio exposed elements. It represents, in relative terms, the amount to be paid annually in order to cover future expected losses.

PML is the anticipated value of the biggest loss that could result from a disaster caused by a “maximum credible event”

Adopting Insurance Industry terms

Extensive Risk Assessment: ‘Empirical ’ Loss Exceedance CurvesExtensive and Intensive Risk Assessment

Proposal of a “Hybrid” Loss Exceedance Curve (Cardona 2010)

Empirical loss exceedance curve and historic risk metrics for Colombia as generated by DesInventar

‘Empirical ’ Loss Exceedance Curve for Albania (losses estimated)

Empirical loss exceedance curve and historic risk metrics for Albania modelled with DesInventar

Revealing risk: integrating analytical and historical views

Frequency 10 times per year

Frequency 1 time every 10

years

Frequency 1 time every

10’000 years

1 million USD 1 billion USD

Extensive

Intensive

High frequency Low severity

Low frequency High severity

Extensive

Intensive

The risk we will have “to live with…”

4

Residual risk

4Residual risk

High frequency Low severity

Low frequency High severity

1

Risk reduction

Risk reduction

1

Corrective: Building retrofitting, mitigation strategies.

2

Risk retention

2 Risk retention

Prospective: Financial reserves, public investment, laws and regulations.

Compensatory: Insurance, contingency funds.

3

Risk transfer

3 Risk transfer

Risk Strategies

Risk retention and transfer structure

Reserve fund

Contingent loan

Insurance and reinsurance

Long term actions (Cat bond, taxes, long term loans, etc)

National governmentIDB / World Bank

Unprotected

RETENTION

TRANSFER

Lower limit

Upper limit AAL

PML

Total exposed value

Deductible

#gar15

Thank you

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