Title: Impact of Climate Change on Road Infrastructure
1Impact of Climate Change on Road Infrastructure
- Mark Harvey
- mark.harvey_at_infrastructure.gov.au
- www.bitre.gov.au
2Austroads project published in 2004
- Austroads AP-R243/04 Impact of Climate change
on road infrastucture - Downloadable for free from Austroads website,
with volume of appendices AP-R243/04A - http//www.austroads.com.au
- Also downloadable for free from BITRE website
(main volume only) http/www.bitre.gov.au - http//www.bitre.gov.au/publications/92/Files/clim
ate_change.pdf
3Project aims
- assess likely local effects of climate change for
Australia for the next 100 years, based on the
best scientific assessment currently available - assess the likely impacts on patterns of
demography and industry, and hence on the demand
for road infrastructure - identify the likely effects on existing road
infrastructure and potential adaptation measures
in road construction and maintenance, and - report on policy implications arising from the
findings. - Note The project was not concerned with impacts
of transport emissions on climate change.
4Project structure
- BITRE coordinated the project and prepared the
Executive Summary, Introduction and the Policy
Implications chapters. - The CSIRO Division of Atmospheric Research ran
its global climate change models to produce
forecasts of climate on a grid of about 50
kilometres up to 2100. - The resultant data was passed on to three
consultants to assess its implications.
5Project structure
6Project structure continued
- The Monash University Centre for Population and
Urban Research investigated the likely effects on
population settlement patterns and demographics. - ARRB Group used these population projections to
forecast changes in road transport demand. - calculated changes to an index of climate from
the CSIRO data - road demand and climatic indexes were together
used in pavement deterioration models to predict
the implications for pavement deterioration and
maintenance expenditure needs.
7Project structure continued
- Australian Bureau of Agricultural and Resource
Economics (ABARE) employed its hydrologicaleconom
ic model of the Murray-Darling basin to forecast
implications of climate change for salinity and
agricultural production in the region, and
related this to road infrastructure. - Multi-disciplinary project involving experts from
a range of fields.
8Project structure continued
CSIRO Regional climate change forecasts to 2100
Monash University Centre for Population and Urban
Research Impacts on population projections
ABARE Impacts on salinity and agriculture in
Murray-Darling basin
ARRB Group Impacts on demand for roads
ARRB Group Impacts on road pavements
BITRE report and summary
9Not covered in the study
- Local flooding implications
- requires a catchment hydrological model to
predict flooding heights, durations and water
velocities, and - an area topology model to relate flood heights to
local road infrastructure. - Salinity and impacts of agricultural industries
outside the Murray-Darling Basin - The CSIRO models do not forecast sea level rises
or the likelihood of changes in storm activity.
10Emissions forecasts
- International Panel on Climate Change (IPCC)
emissions scenario selected - A2 scenario
- high scenario chosen to provide strong contrast
with current conditions - predicated on global population of 15 billion in
2100 - rate of CO2 release grows, increasing to nearly
fourfold by 2100.
11IPCC emission scenarios
A2 scenario (red line) used in this study.
12CSIRO Atmospheric-Ocean Global Climate Change
Model
- global circulation model with atmospheric,
oceanic, sea-ice and biospheric submodels - globe divided up into a grid comprised of 300 km
squares - 9 layers of atmosphere, each block having
parameters such as temperature, air pressure,
wind velocity, water vapour content - 12 layers of ocean
- time step of 30 minutes
- run from 1870 to 2100
- suite of properties (temperature, moisture) saved
for6-hourly intervals for the 230 years - took three months on a supercomputer
13CSIRO Conformal-Cubic General Circulation Model
- Results from global model used to nudge more
detailed model for Australia - wind speeds outside Australia adjusted to make
consistent between models - grid of about 50 km squares for Australia and
lower resolution for rest of the world (up to
about 800 km for the other side of the globe)
14Method of deriving detailed forecasts
- outputs monthly means of average, maximum and
minimum temperatures, precipitation, solar
radiation, potential and actual evaporation for
each grid point - converted to
- local temperature change per degree of global
warming for temperature - percent for rainfall, radiation evaporation
change per degree of global warming - used to derive forecast for any IPCC scenario for
any grid point over the next 100 years.
15Key findings temperatures
- average annual temperatures increase by 2 to 6C
by 2100 - Tasmania coastal zones least affected, inland
areas most affected - more extremely hot days and fewer cold days, for
example - average number of summer days over 35C in
Melbourne to increase from 8 at present to 10-20
by 2070 - average number of winter days below 0C in
Canberra to drop from 44 at present to 6-38 by
2070
16Average annual temperature base (2000) and 2100
climate
5 15 17 19 21 23 24 25 26 27 28 29 30 32 34 40
Base (2000) climate
2100 climate
17Temperature changes year 2100 relative to base
climate
18Key findings rainfall and evaporation
- general reduction in rainfall except for the far
north where there will be significant increases - where average rainfall decreases, more droughts
- where average rainfall increases, more extremely
wet years - in the north, more intense tropical cyclones,
more severe oceanic storm surges, more frequent
and heavier downpours - evaporation to increase over most of the country
adding to moisture stress on plants and drought
19Average annual rainfall base (2000) and 2100
climate
10 15 20 25 30 35 40 50 60 70 100 125 200 gt500
Base (2000) climate
2100 climate
20 change in average annual rainfall 2000-2010
134 -9 -12 -14 -25
21Sea level rise
- Not predicted in CSIRO modelling.
- IPCC projects rise of 9 to 88 cm by 2100
- 0.8 to 8.0 cm per decade
22Impact on population and settlement patterns
methodology
- undertaken by Monash University Centre for
Population and Urban Research (Dr Bob Birrell) - population projections developed for Australia as
a whole, States and major metropolises (based on
ABS mid-range projections supplemented by ANU
demographic projection software). - adjustments made to the projections for the eight
major metropolitan regions for climate change - using expert judgement supported by a comfort
index (function of temperature and humidity). A
comfortable climate is a major driver of internal
migration.
23Population base case without climate change
- total fertility rate will fall to 1.6 and net
overseas migration 90,000 per year over the 21st
century - total population 19.1m in 2000 to 27.3m in 2100
- greater concentration in four major metropolises
Sydney, Melbourne, Brisbane and Perth - other growth outside the four cities is in
non-metropolitan Queensland and WA. - significant increase in share of population in
Queensland - for planning purposes, need to take base case,
then adjust for climate change
24Population climate change impacts
- of the eight metropolitan regions assessed, only
Darwin and Melbourne gain population from climate
change - even though hotter, wetter Darwin less
attractive, higher rainfall should promote
agricultural production - but note the contrary view from the recent
Northern Australia Land and Water Taskforce
report lack of suitable soils high evaporation
and lack of dam sites limits water storage - Losers Adelaide (water supply), Cairns (less
attractive climate) and Perth (water and climate) - coastal areas of NSW and Victoria more attractive
climate - hotter, drier climate in inland areas will may
have adverse impact on agriculture
252100 population without and with climate effects
Selected Statistical Division of 2000 population without climate change Adjustment factor with climate change Climate change factors driving population change
Sydney 159 1.00 temps higher but not expected to affect population growth
Melbourne 125 1.15 temperatures higher resulting in more attractive climate
Brisbane 211 0.96 temperatures higher resulting in less attractive climate
Moreton 305 0.98 temperatures higher resulting in less attractive climate
Adelaide 63 0.79 restricted water supply, especially in spring
Perth 195 0.88 less attractive climate restricted water supply
Darwin 275 1.34 temps high but heavy rainfall drives increased agriculture
ACT 93 1.00 temps higher but not expected to affect population growth
Cairns 279 0.83 temperatures higher resulting in less attractive climate
26Note Climate change is not the most important
influence on population patterns.
- range of projections for 2100 compared with 2000
- without climate change -63 Adelaide to 305
Darwin - with climate change -50 Adelaide to 369 Darwin
27Impact on road demand Methodology
- passenger and freight tasks considered separately
- base-case forecasts developed
- cars a function of population, per capita car
ownership - freight a function of population, per capita
freight, average payload (trend to larger
vehicles) - converted to equivalent standard axel loads for
pavement impacts - ARRB used a gravity model to estimate impacts of
climate change on traffic. - If population at A increases by 100a and
population at B by 100b due to climate change,
then traffic between them increases by
100(1a)(1b)-1.
28Impact on road demand 2100 conclusions
- 60 additional traffic (total vehicles passengers
and freight) - dramatic increase in Queensland, moderate in
Syd-Mel corridor, decline around Adelaide,
increase in Perth urban only slight rise in Perth
intercapital traffic - proportion heavy freight vehicles will rise from
12.1 to 13.9 - total road freight to rise by 112 from 2000 to
2100 - average payload to increase by 25, most in next
decade - equivalent standard axles per articulated truck
to double due to higher mass limits - total ESA-kms on National Highway to rise by 230
- due to freight growth, higher mass limits and
payloads
29Impact on pavement performance methodology
- climate represented by Thornthwaite moisture
index - a function of precipitation, temperature and
potential evapo-transpiration. Index varies from
100 on Cape Yorke Peninsula to -50 in central
Australia. - used a National Highway System road database
- pavement models estimate present value of
life-cycle road agency costs (maintenance and
rehabilitation) and road-user costs (travel time
and vehicle operation) - select treatment options and timings to minimise
present value of costs subject to specified
constraints on maximum roughness and annual
agency budgets.
30Pavement Life Cycle Costing (PLCC) model
- 60 year analysis period, 7 real discount rate
- National Highway System split into 60 sections
with similar climate characteristics, traffic
levels, vehicle mixes and pavement
characteristics - pavement deterioration a function of pavement
age, cumulative equivalent standard axle loads,
Thornthwaite index, and average annual
maintenance expenditure.
31HDM4 model
- much more detailed pavement deterioration
algorithm covering roughness, rutting, cracking,
potholing, ravelling, strength etc and
consequently much more detailed data requirements - case studies of 8 road segments analysed in
detail - one segment from each state and territory located
in or near a metropolitan area - data inputs that vary with climate are
site-specific changes in Thornthwaite index,
traffic levels and per cent heavy vehicles
32Other points to note
- Note only trucks cause pavement wear, not cars
- but cars impact on the models because increased
roughness adds to road user costs for cars - Limitations
- effects of floods, severe storms and sea-level
rise not taken into account - no allowance for expansion of lane-kilometres
- design pavement strengths assumed to remain
unchanged - road agencies may not minimise present value of
costs due to budget constraints causing
maintenance to be deferred and higher than
economically warranted maintenance standards in
some areas for social and equity reasons
33Thornthwaite moisture index base (2000) and 2100
climates
-45 -30 -15 0 20 40 60 80 gt100
Base (2000) climate
2100 climate
34Changes in Thornthwaite moisture index 2000 to
2100
35Changes to Thornthwaite index
- tendency to a drier climate overall (negative
change in Thornthwaite Index) - central area of Australia relatively unchanged
- localised areas where the changes are greatest
include - south-west of Western Australia
- north-east Victoria and southern NSW
- south-west Tasmania
- top-end Queensland.
36Optimal road agency costs (PLCC model)
State Optimal Agency Cost (million) Optimal Agency Cost (million) Change
State Base Climate 2100 Climate Change
NSW 72.3 90.1 25
VIC 32 37.6 18
QLD 82 124.2 51
WA 48.3 56.1 16
SA 27.6 23.4 -15
TAS 6.5 6.8 5
NT 17.9 37.3 108
ACT 0.6 0.7 17
Total 287.3 376.1 31
37Comparing optimal road agency costs
- comparison is not with and without climate change
- but 2000 traffic volumes and climate
- with 2100 climate-adjusted traffic volumes and
climate - Northern Territory and Queensland experience
large increases - primarily due to population growth but wetter
climate contributes. - South Australia declines due to smaller
population and drier climate.
38Maintenance rehabilitation funding split
- maintenance routine and periodic maintenance
(pothole patching, kerb and channel cleaning,
surface correction, resealing) - rehabilitation chipseal resheeting, asphalt
overlays, stabilisation, pavement reconstruction - for Australia as a whole, no predicted change in
3565 split - rehabilitation proportion to rise (maintenance
proportion to fall) significantly for Tasmania - converse for WA
- reflects differences in pavement age
distributions and life times
39HDM4 results road agency costs
Base climate 2100 traffic changes only 2100 traffic changes only 2100 climate traffic changes 2100 climate traffic changes
Cost ('000) Cost ('000) Change (3/1) Cost ('000) Change (5/1)
Col number 1 2 3 4 5
ACT 97.8 97.8 0 97.8 0
NSW 46.2 72.7 57 72.8 58
NT 176.6 176.9 0 177.1 0
QLD 83.6 103.1 23 106.1 27
SA 99 96.8 -2 96.8 -2
TAS 140.2 159.5 14 159.4 14
VIC 128.7 175.5 36 177.3 38
WA 205.9 244.5 19 244.1 19
- undiscounted total costs per kilometre over
20-year period - Virtually all the changes are from population
growth leading to traffic increases, not climate
change.
40Impact on salinity in the Murray-Darling Basin
methodology
- ABARE Salinity and Land-use Simulation Analysis
(SALSA) model - network of land management units linked through
overland and ground water flows - hydrological rainfall, evapo-transpiration,
surface water runoff, irrigation, ground water
recharge/discharge rates, salt accumulation in
streams and soil - climate projections incorporated by changing
rainfall and evapo-transpiration - rate of flow of groundwater depends on hydrolic
gradients - very flat in lower parts of the catchment
41Impact on salinity in the Murray-Darling Basin
methodology continued
- land-use allocated to maximise economic return
from use of agricultural land and irrigation
water - relationship between yield loss and salinity for
each agricultural activity - land-use can shift with changes in salinity and
water availability - costs of salinity measured as reduction in
economic returns
42Catchments in the Murray Darling Basin covered by
the SALSA model
43Impact on salinity in the Murray-Darling Basin
Key findings
Units Base scenario Without climate change With climate change
Year 2000 2100 2100
Net production revenue m, npv 3827 3718 3400
Area of high water tables 000 ha 1137 5341 4404
SALT CONCENTRATION
Darling below the Macquarie mg/L 152 277 483
Murray below the Murrumbidgee mg/L 141 181 198
Murray below the Darling mg/L 226 301 343
Murray at Morgan mg/L 313 445 548
SURFACE WATER FLOWS
Darling below the Macquarie confluence GL 7345 7784 6060
Murray below the Murrumbidgee confluence GL 8128 9040 5259
Murray below the Darling GL 6789 7720 4435
Murray at Morgan GL 3827 3718 3400
44Impact on salinity in the Murray-Darling Basin
comparisons
- area affected by high water tables
- base case rise from 1.1m hectares in 2000 to
5.3m hectares in 2100 - climate change rise to 4.4m hectares in 2100
- climate change mitigates salinity problems but
nowhere near sufficient to reverse the rising
trend - net production revenue
- base case falls by 3 due to high water tables,
shift from pasture to cropping - with climate change falls by 11 due to reduced
surface water flows, switching from irrigated to
dryland activities - less demand for road transport
45Impact on salinity in the Murray-Darling Basin
comparisons
- higher water tables are bad for road pavements,
but this is a problem in both the base and
climate change scenarios - slightly less with climate change
- reduced surface water flows make salt
concentrations higher in rivers which reduces
yields from irrigated production - and rusts steel reinforcing in concrete
structures in riverine environments such as
bridges and culverts.
46Summing up uncertainty
- high level of uncertainty about
- IPCC emissions forecasts
- CSIRO estimates of climate impacts
- consultants forecasts
- uncertainties built upon uncertainties
- numerical results are broad indicators that tell
a story
47Summing up demand for roads
- Higher car and truck traffic from population
growth is the main driver of investment and
maintenance needs for roads. - Large changes are forecast without climate
change. - strong growth for SE Queensland, Cairns, Darwin,
Brisbane, Sydney, Melbourne, Perth - decline for Adelaide and inland areas
- Climate change adds to forecasts for Darwin and
Melbourne and reduces forecasts for Adelaide,
Perth and Cairns.
48Summing up road design and maintenance
- less rainfall should slow pavement deterioration
- but effects so small as to have negligible impact
on costs - exception for far northern parts of Australia,
which are forecast to become wetter. Capacities
of culverts and waterways may prove inadequate. - sea-level rise a concern for low-lying roads in
coastal areas - changed and frequencies of floods in some areas
- requires modelling of individual catchments to
forecast impacts
49Overall conclusion
- Changes affecting road infrastructure will occur
regardless of climate change. - Climate change is just another factor in the mix,
and usually not the most important. - The main impacts on road infrastructure may come
from changes in flood heights and frequencies,
and sea-level rise with storm surges, which were
not addressed in detail in the project. - impacts vary greatly between locations
50Subsequent research ARRB Climate change
framework for Queensland Department of Main Roads
in 2008
- report not published, but a summary is available
in a conference paper by Evans, Tsolakis and
Naude http//www.patrec.org/web_docs/atrf/papers/2
009/1737_paper66-Evans.pdf (ATRF Conference 2009) - comprehensive list of potential impacts on road
infrastructure and operations - detailed review of (short- and long-term) climate
change forecasts for Queensland - framework to assess risks, and to assist in the
planning of climate change mitigation and
adaptation responses.
51ARRB Framework
- Four impacts relevant to Queensland
- temperature changes (increases in very hot days)
- rainfall changes (reductions and increases) and
flooding - rising sea levels with storm surges
- increase in cyclone frequency and intensity.
- Phases of framework to identify investment
priorities - identify climate change effects
- geographic scale, certainty, timeframe
- determine impacts on transport
- adaptation strategies
- planning and project evaluation
52Other research underway
- Austroads project Impact of climate change on
road performance, undertaken by ARRB - software to provide climate information from 1960
to 2099 by GPS coordinates based on CSIRO
modelling - minimum and maximum daily temperatures, rainfall,
Thornthwaite moisture index - pre-2007 based on historical meteorological data
- Climate Futures Tasmania Infrastructure project
- World Road Association (PIARC) Technical
Committees C.3 (natural disasters), D.2 (road
pavements), D.3 (bridges), D.4 (geotechnics and
unpaved roads) - all have working groups on adaptation to climate
change