Optimising climate change adaptation investment
Robert Kinghorn
Principal Economist, Parsons Brinckerhoff
Palisade 2012 Risk Conference, 28-29 May 2012, Sydney
Overview
1. Background
– Study/project brief
– Case study specifics for Narrabeen Lagoon
2. Development of methodology using @Risk
3. Optimisation of solution using RiskOptimizer
4. Outcomes and conclusions
Acknowledgments
• This study was undertaken whilst I was with AECOM
• Model developed with inputs from a wider team of
economists, climate change scientists, engineers and
oceanographers
• Specific acknowledgements to AECOM economics team:
– David Adams
– Katie Feeney
– Matthew Yi (now Deloitte)
• And for guidance/ peer review
– Leo Dobes (Crawford School of Economics & Government, ANU)
• All information sourced from full report
–
http://www.climatechange.gov.au/~/media/publications/adaptation/coastal-flooding-narrabeen-lagoon.pdf
This presentation
• Primarily deals with development of cost-benefit analysis
methodology and use of @Risk/ RiskOptimizer for
analysis
• Less focus on climate change science and specifics of
flood modelling
1. Background
Government Climate Change strategy
• Three pillars of Australian Government’s climate
change strategy:
• mitigation - to reduce Australia’s greenhouse gas emissions.
• global solution - to help shape a collective international
response.
• adaptation - to adapt to unavoidable climate change.
Project brief
• In 2009, the then Department of Climate Change
commissioned AECOM to undertake analysis of the
climate change impacts on infrastructure, and the
economic costs/benefits of adaptation
• AECOM developed a series of case studies, including:
– Low-lying airports/ports (flooding)
– Urban rail (heat impacts)
– Coastal settlements (flooding)
DCC study objectives
• Knowledge of physical impacts of climate change is
growing, but still insufficient for decision makers.
• Infrastructure owners need to what adaptation options
are available, to optimise their investment and minimise
risks.
• We may identify an adaptation measure, but
– When is the best time to implement this?
– What scale should the measure be?
• Invest too early – substantial sunk capex, little immediate
benefit
– (AKA white elephant)
• Leave too late – significant avoidable damage caused
Narrabeen Lagoon – location
Narrabeen Lagoon – the problem
• One of 67 Intermittently Closed & Open Lakes and
Lagoons on NSW coast
• Storms block lagoon entrances by depositing sand
• Flood waters from creeks that feed the lagoon flush
away the sand deposits
• When entrance blocked, lagoon fills like a bathtub,
flooding houses and land around it
• Climate Change expected to increase the frequency and
intensity of storms and rainfall (as well as rising sea
levels)
• BUT – nice place to live!
Narrabeen Lagoon – the bathtub
Source: Dobes, 2010
Narrabeen Lagoon – close-up
Flooding at Narrabeen Lagoon
• Dry days
• After flood
Direct impacts
•
•
•
•
•
Residential & commercial property damage
Damage to roads, bridges, traffic signals
Damage to water and sewerage infrastructure
Damage to gas and electricity infrastructure
Damage to parks and grounds
Indirect impacts
• Indirect flood damage to residences
– Cost of cleaning up (unpaid labour)
– Paying for alternative accommodation
• Commercial properties
– Loss of sales or production down time
• Travel disruption when roads are submerged
– Having to make lengthy detours
• Health:
– In this situation, not flood-borne diseases, but mental health from
trauma due to lost memorabilia (photographs, personal items
etc)
2. Development of methodology
Previous methodologies
• Largely qualitative
• Or average/worst-case scenarios
• Garnaut (2008)
– Used CGE modelling, with ‘shocks’ to economy from CC events
– ?spurious accuracy
• Stern (2006)
– Used CBA but at a macro level
Narrabeen Lagoon approach
• Social cost-benefit analysis
– Future costs and benefits discounted to present values
• Consideration of direct and indirect costs
– Direct damage costs
– Willingness to pay benefits (welfare benefits)
• Costs and benefits assessed over period 2010-2100
• Adaptation investment costs escalate over time at a rate
higher than CPI, and most attract an ongoing
operating/maintenance cost
Issues with discounting
• Standard NSW/Commonwealth of 7% rate too high
– Present value of benefits beyond 2040 would become negligible
– Flood frequencies/probabilities (and hence direct/indirect costs)
become sizable in later years
100%
90%
80%
Discount factor
70%
60%
3%
7%
1.80%
50%
40%
30%
20%
10%
0%
2010
2030
2050
Year
2070
2090
Study design
1. Climate
change
effects on
weather
2. Weather
event
3. Impact on
infrastructure
4. Economic
costs/benefits
of impact
5. Adaptation
options
Lots of uncertainty
• 90 years
– Different combinations of storm frequency/intensity
– Storm events increase in frequency/intensity over time
• 10 climate change scenarios
• 6 adaptation measures
– Different scopes
– Different years of implementation
• @Risk and RiskOptimizer allowed us to assess many
different outcomes
Simulation model framework
Climate change scenario
Iterate
Weather event – year and intensity
(Monte Carlo simulation with @Risk)
•Identify adaptation
options
Calculate costs
(no adaptation)
Calculate costs
(with adaptation)
Calculate NPV of adaptation
Distribution of NPVs of adaptation
Optimisation
(with RiskOptimizer)
Probability distributions of flood intensity
Probability distributions – with climate
change
• Probability of occurrence and intensity progressively
increase over time
Effect of different climate change
scenarios
• Flood probability and height increase from historical
annual exceedance probability (AEP)
Narrabeen Lagoon – close-up
Impacts of flooding
• 1432 residences in floodplain
• 262 commercial properties in floodplain
• Some main roads unpassable when floods reach 2.5m
• Main arterials to Sydney CBD blocked when floods reach
2.8m
Roads closures with 2.8m flood
Damage costs – non-linear
• Example of residential damage cost profile at different
flood heights
– At low floods, damage to carpets.
– At high floods, structural damage to buildings
6 adaptation measures
• 4 infrastructure measures:
– 3 different levees protecting different areas from flooding (varying
heights) (~$150k to $350k)
– Widening of lagoon entrance (varying widths) (~$7m)
• 2 non-infrastructure measures:
– Early-warning system/flood awareness campaign (~$100k)
– Planning controls (~$20k per dwelling)
– Economic benefits mainly due to indirect (willingness-to-pay)
welfare effects
Summary of model process
1. Determine effect of CC scenario on flood risk
2. Select year for implementation of adaptation option
3. Use @Risk to simulate weather event (year and
intensity)
4. Calculate direct and indirect costs with/without
adaptation
5. Discount costs and benefits
6. Calculate NPV of adaptation
7. Repeat thousands of times to generate distribution of
NPVs
3. Optimisation with RiskOptimizer
Optimisation with RiskOptimizer
• Determine best package of measures and timing which
would maximise NPV
• From 6 adaptation measures, there are 12 degrees of
freedom:
– Scope of measure (height or width)
– Year of implementation (or never)
Results
1
Lagoon opening
Scope
Optimal year of
implementation
70m
2035
2.7m
2010
2.5m
>2100
2.3m
>2100
- Increase lagoon outflow
2
Lakeside levee
- Residential protection
3
Prospect Park levee
- Commercial protection
4
Nareen Creek levee
- Residential protection
5
Flood awareness/early warning
2010
6
Planning control
2010
Mean NPV: $25m (discounted to 2009 at 3%)
Optimised NPV
4. Outcomes and conclusions
Outcomes and conclusions
• Non-infrastructure measures have immediate benefit
even with no climate change, since flooding already
occurs
• Most infrastructure measures could be deferred to
medium-/long-term
• Residents willing to pay for preventative measures
(given limited availability of flood insurance)
– E.g. Early-warning system allows them to prepare
Lessons learned and further studies
• Results intuitive
• Provides decision-makers with quantitative information
(costs and timing)
• Methodology could be applied to the other ~70 ICOLLS
in NSW
• Willingness-to-pay data still problematic (no primary data
exists)
• Other applications of this methodology
– Methodology being used in Victoria for similar study looking at
coastal settlements around Port Phillip Bay
– Provision of emergency food in flood-prone north Australia
– Could be used for non-CC infrastructure
Thank you
rkinghorn@pb.com.au