Assessment and Management of Natural Hazards Michael Faber - - PowerPoint PPT Presentation

Methodology for Risk Assessment and Management

• f Natural Hazards

COST Action C26 Urban Habitat Constructions under Catastrophic Events International Conference 16-18 September 2010, Naples

Eidgenössische Technische Hochschule Zürich Swiss Federal Institute of Technology Zurich Institute of Structural Engineering Group Risk and Safety

Michael Faber Harikrishna Narasimhan

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Contents of presentation

• Engineering decision making
• System representation in risk assessment
• Risk indicators and quantification
• Decision optimization and life safety
• Large scale risk assessment
• Conclusion

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Engineering decision making

• Development and management of societal infrastructure

is a central task for success of society

• Decision processes involved in this task are subject to

significant uncertainty

• Holistic management of risks in such decision processes is

an overwhelming challenge

Hoover Dam, USA Hong Kong Island, China

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Engineering decision making

Assessment and control of risks due to:

• natural hazards (earthquakes, typhoons, landslides)
• malevolence (terrorism)
• degradation (corrosion, fatigue)
• lack of knowledge (human error, design error)

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Engineering decision making

• Assessment of risk along with evaluation of benefits

achieved from decisions can be related to concept of utility in economic decision theory.

• This provides a methodical framework and theoretical

basis for risk based decision making.

• The development and application of such a framework for

risk based decision making in the field of engineering is described.

• This framework can be used for decision support

concerning risk and safety management for multiple hazards at strategic, normative and operational levels.

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System representation in risk assessment

System System boundary

System modelling from an intergenerational perspective

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System representation in risk assessment

Logical representation of system interrelationships

Exposure events Constituent failure events and direct consequences Follow-up consequences

• Constituents of system could be physical components,

procedural processes or human activities

• Level of detail or scale depends on:
• physical characteristics of the considered problem
• spatial and temporal characteristics of consequences

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System representation in risk assessment

Generation of consequences

Exposures All possible endogenous and exogenous effects with potential to cause consequences

• Suddenly occurring events – accidents, explosions, rock-fall
• Gradually evolving events – deterioration, climate change
• Human errors and malevolence

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System representation in risk assessment

Generation of consequences

Consequences Can be broadly classified into:

• Loss of life and injuries
• Damages to qualities of environment
• Economic losses

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System representation in risk assessment

Generation of consequences

Consequences

• Constituents of system are the first line of defence against

exposure events

• Direct consequences are associated with damage or failure of

individual constituents of the system

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System representation in risk assessment

Generation of consequences

Consequences

• Indirect consequences are associated with the loss of

functionality or failure of the entire system

• They result from combination and interaction of events of

constituent failures

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System representation in risk assessment

Generation of consequences

Consequences

• Indirect consequences are differentiated due to:
• physical system changes
• societal perception of such changes
• This differentiation is important in risk communication and

management

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System representation in risk assessment

Generation of consequences

Vulnerability

• The ratio between the risks due to direct consequences and

the total value of the considered system

• Defined for a specified time frame and by considering all

relevant exposures

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System representation in risk assessment

Generation of consequences

Robustness

• The ratio between the direct risks and the total risks
• Defined for a specified time frame and by considering all

relevant exposure events and all relevant damage states for the constituents of the system

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System representation in risk assessment

System characterization at different scales

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Risk indicators and quantification

Exposure Vulnerability Indirect consequences Direct consequences Robustness Indicators Exposure Vulnerability Indirect consequences Direct consequences Robustness Indicators

Risk indicators

• Any observable or measurable characteristic of the system or

its constituents that contains information about the risk

• For a load bearing structure,
• loading of the structure – exposure
• strength of components of structure – vulnerability
• redundancy, ductility, effectiveness of condition control

and maintenance – robustness

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Risk indicators and quantification

Quantification of risk Direct risks Indirect risks Index of robustness

Exposure Vulnerability Robustness Exposure Vulnerability Robustness

( )

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Risk indicators and quantification

Exposure Vulnerability Indirect consequences Direct consequences Robustness Indicators Exposure Vulnerability Indirect consequences Direct consequences Robustness Indicators

Updating of risks

• Bayesian updating
• Spatial
• Temporal

( ) ( ) ( ) ( ) ( ) ( )(1 ( ))

ij ij ij ij ij ij ij

P e C P C P C e P e C P C P e C P C

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Risk indicators and quantification

Indicators of risk at different levels for a scenario

:

Flood Ship impact Explosion/Fire Earthquake Vehicle impact Wind loads Traffic loads Deicing salt Water Carbon dioxide Yielding Rupture Cracking Fatigue Wear Spalling Erosion Corrosion Loss of functionality partial collapse full collapse Use/functionality Location Environment Design life Societal importance Design codes Design target reliability Age Materials Quality of workmanship Condition Protective measures Ductility Joint characteristics Redundancy Segmentation Condition control/monitoring Emergency preparedness Direct ect con conseq seque uence nces Repair costs Temporary loss or reduced functionality Small number of injuries/fatalities Minor socio-economic losses Minor damages to environment Ind ndirect ect con conseq seque uence nces Repair costs Temporary loss or reduced functionality Mid to large number of injuries/fatalities Moderate to major socio- economic losses Moderate to major damages to environment Exposure Vulnerability Robustness Expo xposure sure Vulne nerab ability Rob

• bustnes

ustness Exposure Vulnerability Robustness Expo xposure sure Vulne nerab ability Rob

• bustnes

ustness Phys hysica cal cha characte acterist stics cs Scen cenario ario rep eprese esentat ntation

• n

Ind ndicator cators Poten ential al con conseq seque uence nces

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Decision optimization and life safety

Feasible, acceptable and optimal decisions

• All decision alternatives are ranked based on their expected

value of utility or benefit

• This should include the expected value of all discounted costs

and incomes resulting from the different decision alternatives

Feasible decisions

Optimal decision

Utility

Decision alternative Acceptable decisions

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Decision optimization and life safety

Risk acceptance and life quality index

• It is useful to differentiate between tangible risks and

intangible risks – i.e. risks which can be easily expressed in monetary terms and which cannot be

• The Life Quality Index (LQI) is a measure that facilitates the

development of risk acceptance criteria for intangible risks

• It is a social indicator derived to reflect the expected length of

“good” life and particularly the enhancement of the quality of life by good health and wealth

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Decision optimization and life safety

Risk acceptance and life quality index

The LQI models the preferences of society with a relationship between:

• Gross Domestic Product (GDP) per capita g
• Life expectancy at birth l
• Proportion of life spent for earning w
• Trade-off between resources available for consumption and

value of time of healthy life r

1

(1 )

r r

L g w

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Decision optimization and life safety

Risk acceptance and life quality index

• Every investment into life safety should lead to an increase in

life-expectancy:

• This leads to the important Societal Willingness To Pay (SWTP)

criterion:

(1 ) g r g r (1 ) g r SWTP g r

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Decision optimization and life safety

Sustainable discounting

• In evaluating the benefit and risk of decision alternatives, the

time of consequences and investments need to be taken into account – by discounting

• Discounting should be based on long term average values, free
• f taxes and inflation
• Private sector discounting – long term investment return
• Public sector discounting – long term rate of economic growth

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Decision optimization and life safety

Risk communication

• Different individuals in society perceive risks in a different way
• Generally risks are perceived more negatively when

stakeholders feel more exposed and have no influence

• Differences also arise as to how adverse events are perceived

before, during and after the occurrence of the event

• This leads to development of risk averse and risk prone

attitudes and may lead to uneven distribution of risks

• To reduce uncertainty associated with risk understanding, it is

necessary to provide transparent information about:

• nature of exposures
• possible precautionary actions
• information on risk management and control
• societal consequences of irrational behaviour

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Large scale risk assessment

Rehabilitation of infrastructure functionality Condition assessment and updating of reliability and risks Optimal allocation of ressources for rebuliding and strengthening Optimal allocation of available ressources for risk reduction

• strengthening
• rebuilding

in regard to possible earth- quakes

Before During After

Damage reduction/Control Emergency help and rescue After quake hazards

Prevention Reduction Recovery

Management of earthquake risks

• It is important to be able to provide decision support in

the situations before, during and after the occurrence of natural hazards

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Large scale risk assessment

Risk Management Risk Management

On-site observations On-site observations Official/insurance data Official/insurance data Airplane observations Airplane observations Satellite Observations Satellite Observations

Real World

Exposure Exposure Vulnerability Vulnerability Robustness Robustness Indicators Indicators Exposure Exposure Vulnerability Vulnerability Robustness Robustness Indicators Indicators

Models of real world

Risk reduction measures Risk reduction measures Risk reduction measures Risk reduction measures

Actions GIS Interface Platform GIS Interface Platform

• A general framework for natural hazards risk

management using Geographical Information Systems (GIS) can be visualized as:

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Large scale risk assessment

Buildings/infrastructure and life lines Soil characteristics Landscape topography Earthquake source locations GIS Data Base Layers

• The GIS database is important as most of the required

data generally are spatially distributed for the considered system (e.g. city or region)

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Large scale risk assessment

Exposure Vulnerability Robustness

• Prob. of

• No. of

• Indicators for exposure (hazards), vulnerability and

robustness (consequences) can efficiently be stored and managed in the GIS data base

• Bayesian Probabilistic Network (BPN) risk models can

then be established and linked to each asset in the considered system

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Large scale risk assessment

• Indicators for exposure (hazards), vulnerability and

robustness (consequences) can efficiently be stored and managed in the GIS data base

• Bayesian Probabilistic Network (BPN) risk models can

then be established and linked to each asset in the considered system

Typical Outputs

DURING AFTER BEFORE BEFORE Generic BPN + structure and site specific information + new data (e.g. aerial photogrammetrical measurements Generic BPN + structure and site specific information + new data + updating models Generic BPN + structure and site specific information

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Large scale risk assessment

Damage State

Fully Operational Life Safety Near Collapse Collapse Operational

• The generic BPN risk models linked with the GIS database

facilitate the efficient risk assessment for large numbers of buildings and other assets

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Large scale risk assessment

• The generic BPN risk models linked with the GIS database

facilitate the efficient risk assessment for large numbers of buildings and other assets

0 – 200’000 200’000 – 400’000 400’000 – 600’000 600’000 – 800’000

Total Risk [$]

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Conclusion

• Engineering decision making is a complex issue due to significant

potential consequences and substantial uncertainties

• Societal development depends on efficient management of risks

and effective communication of the basis of decision making to stakeholders

• A unified framework for risk based decision making has been

presented, which is:

• general enough to accommodate special needs of different

application areas

• specific enough to ensure consistency in modeling and

theoretical basis

• An application of this framework has been illustrated for the

large scale risk assessment and management of earthquake risks

Methodology for Risk Assessment and Management

• f Natural Hazards

COST Action C26 Urban Habitat Constructions under Catastrophic Events International Conference 16-18 September 2010, Naples

Eidgenössische Technische Hochschule Zürich Swiss Federal Institute of Technology Zurich Institute of Structural Engineering Group Risk and Safety

Michael Faber Harikrishna Narasimhan