The Role of Climate Change in Urban The Role of Climate Change in Urban

Flood Risk Management TodayFlood Risk Management Today

Nicola Ranger & Ana Lopez

Grantham Research Institute on Climate Change and the Environment

Centre for Climate Change Economics and Policy

Contents

� Brief overview of climate change and urban flood risk

� Uncertainties in future flood hazard projections

� Implications for urban flood management planning

� Principles for dealing with uncertainty

Climate change and urban flood risk

� Increased mean and/or heavy rainfall:

� Already evidence of increases in heavy rainfall events in many regions

� In some areas, this could lead to an increase in flood risk, in particularly in urban areas – flash flooding.

� Global sea level rise and changes in storm surge risks

� Mean sea levels will increase across most of the globe.

� In some areas, this will be aggravated by increases in storm surge risk.

� Climate change could aggravate other risk factors, such as aging infrastructure, encroachment on drainage canals, reduced natural drainage (urbanisation)

Min et al. 2011

Hansen et al. 2011

Top 20 Cities in terms of Exposed

Population to Storm Surge 2070s

Observed Trends in 5-day consecutive rainfall (1951-99)

Encroachment in Mumbai

Uncertainties

� However uncertainties in

climate change projections are large:

� Model dependent

� Non-robust

� Unknown unknowns

� Similar problems are faced when

estimating flood probabilities for

extreme events (even without

anthropogenic climate change):

� Lack of data

� Non-stationary system

� Extrapolation

Reconstructed AMJ precipitation and JJA temperature Source: Bungten et al (2011) Science

A climate of deep uncertainty

Knowledge of the Space

of Possible OutcomesKnowledge of

Likelihood HIGH LOW

HIGH

LOW

‘Risk’ (known

probabilities)

‘Ambiguity’(some

information,

but gaps and

uncertainty)

‘Ignorance’(unknown

probabilities)

Global Mean

Temperature

Hurricane

Activity in the

Atlantic

Sea Level Rise

Local Water

Stress

Today

2100

~2030-2050

Local Flood

Hazard

� Planners can no longer rely

on history as a guide to

future levels of risk

� Traditional tools of decision

making under risk (e.g.

expected utility analysis)

become less relevant

� Risk assessment and

decision making must shift

from a backward-looking

paradigm to one based upon

forecasting current and

future levels of risk

� A challenge is that it is

impossible to predict future

conditions with certaintyn.b. not just uncertainties linked with

climate change, also other long-term

trends, such as increasing exposure,

urbanisation and land-use change

Maladaptation

� If climate change is not considered upfront in planning there is a risk of locking-in future impacts, risks to life, unnecessary costs and wasted investments

� Types of Maladaptation:

� Over-adaptation: where adjustments are proven to be unnecessary given the climate realised, e.g. a sea defence built to withstand 4m of sea level rise that never emerges.

� Inaction/under-adaptation: a failure to act or where adjustments do not achieve the maximum potential reduction in losses for the realised climate, or in some cases, actually increase impacts above what they could have been given improved ex-ante adaptation.

� Incorrect adaptation: where adjustments are made, but are later found to be either not adaptive or counter-adaptive.

Which decisions are sensitive to climate change?

Characteristics of decisions that could be sensitive to

climate change:

� Decisions involving systems that are sensitive to current

climate variability (e.g. ecosystems, hydrological

systems)

� Decisions involving measures that are:

� Anticipatory measures

� Long-lived (e.g. more than roughly 10 years)

� Long lead times

� Focussed on reducing risk from single hazard, or reducing general vulnerability

� Irreversibility (sunk-costs)

� Benefits/design varies with climate conditions

Large-scale infrastructure projects

Dealing with Uncertainty in Decision Making

� In many cases a range of ‘no-regrets’ options are

available and will have immediate benefits and can

enhance long-term flexibility to cope with climate

change and other risk drivers;

� Measures to better cope with current climate variability (such as

well-maintained drainage systems and early warning systems)

� Measures to manage non-climate drivers of risk (such as limiting

building in exposed areas, managing erosion and increasing

permeability of urban areas)

� Measures to reduce systemic vulnerability or resilience to shocks

(insurance systems, emergency response planning)

� Some measures with strong co-benefits (such as natural

ecosystem flood storage systems, regenerating mangrove areas,

green urban spaces)

Robustness to Climate Change Uncertainties

Cost-to-

Benefit

Ratio**

Lower

Benefits

relative to

Costs

Based on Findings for:

Guyana (CWF, 2009)

Mozambique (World Bank, 2010)

UK (Ranger et al. 2010)

Robustness to Uncertainties*

Resettlement

to Lower Risk

Zones

Rebuilding

natural

ecosystems

LowHigh

Insurance

Upgrade

Drainage

Systems

Building

Codes Flood

Defences

Early Warning

SystemsHigher

Benefits

relative to

Costs

Urban

Development

Controls

Erosion

Control

Benefits ~= Costs for the Scenarios/Case Studies Considered

Reduced social

vulnerability

n.b. Economic

cost/benefit and

robustness will depend

on the case…

Principles for dealing with uncertainty

� For potential ‘high-regrets’ projects, one approach to reducing the

chance of maladaptation is to make a decision more flexible to deal with

climate change uncertainties; through:

� Use measures that are suitable over a range of climates

� Build in an option to adjust the adaptation measure if required

� Build flexibility into the decision process itself by incorporating sequencing,

waiting and learning over time (take no-regrets options now and wait for

more information before taking more inflexible options)

� Strategies that reduce flexibility (such as building in exposed areas) can

limit robustness

� But there are trade-offs: building in flexibility can often incur a additional

cost or productivity trade-off

RobustnessOptimalityTrade-off zone

RobustnessOptimalityTrade-off zone

The Thames 2100 Project: decision pathways approach

The Thames 2100 Project: thresholds & decision points

Conclusions

� Climate change is likely to have implications for urban flood risk management

decisions today; but is one of many drivers that must be considered (e.g.

urbanisation, aging infrastructure, population growth etc.)

� Failure to adequately treat climate change in decision making today could lead

to future unnecessary costs, wasted investments and risks to life.

� Long-term infrastructure is an area where planning decisions are likely to be

sensitive to assumptions about future climate conditions.

� There are some general principles for making urban flood risk management

investments/decisions more robust to climate change:

� Focus on identifying ‘no-regrets’ options that provide benefits under any climate

scenario; such options reduce risk today and can help to build long-term flexibility

into flood risk management plans (e.g. Thames Barrier case).

� For potentially ‘high-regrets’ decisions, such as long-term infrastructure, look for

options to build flexibility into planning processes and investment decisions.

� Where the choice between different options is more subtle (e.g. the Thames

Barrier case), a range of tools are available to support decision making

EXTRA SLIDES

Sensitivity of Adaptation to Climate PDFs

Option 1: Repair Existing Infrastructure

Option 2: Upgrade by x% Existing Infrastructure

Option 3: Major Reengineering of Infrastructure & Home Resilience

Option 5: Major Reengineering of Infrastructure & Home Resilience & Retreat from some areas

For illustration only…

Traditional Approach: Apply

Expected Utility Analysis to

Optimise the Costs versus Benefits

of Action under Known Uncertainty

“Improper consideration of

residual uncertainties of probabilistic climate

information (which is always incomplete and conditional) in

optimisation exercises could lead to mal-

adaptation and be far from optimal” Dessai et al. 2009 based on Hall 2007

Decision methods

Can I assume that

probabilities are known?

Can I assume that

probabilities are known?

Am I facing an irreversible

decision, and do I expect

to learn more about risks

in the future?

Am I facing an irreversible

decision, and do I expect

to learn more about risks

in the future?

Yes

Yes

Am I averse to risk, or

concerned with how outcomes

are distributed across different

individuals?

Am I averse to risk, or

concerned with how outcomes

are distributed across different

individuals?

No

Real options and

Quasi-option

value

Real options and

Quasi-option

value

Expected UtilityExpected Utility Expected ValueExpected Value

Do I have conflicting or incomplete*

probabilities (Ambiguity)?

Or do I have no (trustworthy)

probabilities at all (Ignorance)?

Do I have conflicting or incomplete*

probabilities (Ambiguity)?

Or do I have no (trustworthy)

probabilities at all (Ignorance)?

No

Do I have weights on

alternative plausible

probability distributions?

Do I have weights on

alternative plausible

probability distributions?

Smooth ambiguity

model

Smooth ambiguity

modelMaximin expected

utility

Maximin expected

utility

Yes

No

Do I have a model

of system

behavior?

Do I have a model

of system

behavior?

IgnoranceAmbiguity

Robust decision

theory or Info-gap

Robust decision

theory or Info-gap

Can I measure the strength of my

preferences over outcomes?

Can I measure the strength of my

preferences over outcomes?

Yes

No

MaximinMaximinMinimax Regret

or αααα-Maxmin

Minimax Regret

or αααα-Maxmin

I can only

rank outcomes

I can measure

how

much better one

outcome

is than another

Yes

No

The role of climate change in planning today

Return Period

50yr 200yr 500yr

Flood Depth at

Location

+10 years+10 years

+10 years+10 years

+50 years+50 years

+50 years+50 years