climate change and its impacts on water supply and demand in sydney

8/12/2019 Climate change and its impacts on water supply and demand in Sydney

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Climate change and its impacts on water supply and

demand in Sydney

Summary report


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Acknowledgements

Chapter 1:

Authors: Wenju Cai (CSIRO), Raj Mehrotra (UNSW),

Contributors: Colette Grigg (NSW Office of Water), Jason Martin (SCA), Yue-Cong Wang (Sydney

Water)

Chapter 2:

Authors: Wenju Cai (CSIRO), Jason Martin (SCA)

Contributors: Tim Cowan (CSIRO), Arnold Sullivan (CSIRO), Dewi Kirono (CSIRO), Ian Macadam,

(CSIRO) Mahes Maheswaran (SCA), Golam Kibria (SCA)

Chapter 3:

Authors: Ashish Sharma (UNSW), Raj Mehrotra (UNSW)

Chapter 4:

Authors: Jason Martin (SCA), Golam Kibria (SCA), Mahes Maheswaran (SCA)

Chapter 5:

Authors: Yue-Cong Wang (Sydney Water), Barry Abrams (Sydney Water)

Contributors: Frank Spaninks (Sydney Water), Katherine Beatty (Sydney Water), Matthew Inman

(CSIRO), Andrew Grant (CSIRO), Magnus Moglia (CSIRO)

Chapter 6:

Authors: Colette Grigg (NSW Office of Water)

Contributors: Greg Allen (Sydney Water), Mahes Maheswaran (SCA)

Project Coordination: NSW Office of Water

Editorial:

Karen Pearce (Bloom Communications), Alison White (NSW Office of Water), Katy Brady (NSW Office

of Water), Colette Grigg (NSW Office of Water), Donna Siemsen (SCA) and Cathy OToole (SCA)

A NSW and Australian Government sponsored research project conducted in collaboration between

the Commonwealth Scientific and Industrial Research Organisation, the Australian Government

Department of Climate Change and Energy Efficiency, the NSW Department of Environment, Climate

Change and Water, the NSW Office of Water, Sydney Catchment Authority, Sydney Water and the

University of NSW.


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Contents

Execut ive summary ...........................................................................................................................91. Introducti on ..................................................................................................................................17

Investigating climate change and its impacts on water supply and demand in Sydney..............17Sydneys surface water supply ..................................................................................................17

Catchment area...............................................................................................................17Reservoir and supply system...........................................................................................18Sydney Waters delivery and distribution area .................................................................18

Modelling an uncertain future.....................................................................................................18Global climate modelling..................................................................................................19Uncertainty and limitations of climate modelling ..............................................................19

About this study.........................................................................................................................21Study area.......................................................................................................................21Current climate and climate change projection timeframes..............................................22Climate modelling and downscaling methods ..................................................................22Emission scenarios..........................................................................................................23Climate variables .............................................................................................................23Water availability and supply ...........................................................................................24Water demand .................................................................................................................25

2. Understanding Sydneys climate................................................................................................26Current climate observations for Sydney ...................................................................................26

Temperature....................................................................................................................26Rainfall ............................................................................................................................27Inflows ............................................................................................................................29Evaporation .....................................................................................................................30

Major influences on climate variability for Sydney......................................................................32Natural influences............................................................................................................32Human influences on climate...........................................................................................34Inflows and synoptic classifications .................................................................................35

Implications for run-off and inflows ............................................................................................363. Climate change project ions for Sydneys catchments .............................................................37

About these projections .............................................................................................................37Temperature ..............................................................................................................................37

Projected warming for 2030.............................................................................................37Projected warming for 2070.............................................................................................37Extreme temperature: hot days, hot spells and cold spells ..............................................39

Rainfall ......................................................................................................................................39Projected rainfall changes for 2030 .................................................................................40Projected rainfall changes for 2070 .................................................................................40Rainfall intensity, extreme rainfall, wet and dry spells......................................................41

Evaporation ...............................................................................................................................434. Impacts on water availabili ty ......................................................................................................46


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Estimating the impacts on water availability...............................................................................46Catchment-scale rainfall, evaporation and inflow projections.....................................................47

Rainfall ............................................................................................................................47Evaporation .....................................................................................................................48Inflows ............................................................................................................................49Summary of impacts on rainfall and inflow.......................................................................51

Impacts of climate change on water supply ...............................................................................52Changes to water supply system performance ................................................................52

5. Implications for demand .............................................................................................................53Factors influencing demand.......................................................................................................53Weather conditions and water use.............................................................................................53Projected demand for water without climate change..................................................................54Determining climate demand .....................................................................................................54

Water use, weather and customers .................................................................................55Demand difference from current climate..........................................................................55

Modelled changes in water demand due to climate ...................................................................55Annual average demand..................................................................................................56Demand variability ...........................................................................................................57

Water conservation programs....................................................................................................576. Impl icat ions for supply and demand planning ..........................................................................58

The challenge of water resource planning in the Sydney context ..............................................58The Metropolitan Water Plan and adaptive management ..........................................................58Implications for Sydneys water supply systems ........................................................................59Implications for Sydneys urban water demand..........................................................................60

7. Future research needs ................................................................................................................62References .......................................................................................................................................63Appendix 1: Variable convergence score for global cl imate models ..........................................65Appendix 2: SRES scenarios ..........................................................................................................66Appendix 3: Maps o f the study area...............................................................................................67Appendix 4: High resolu tion cl imate change pro jections ............................................................69Appendix 5: Future changes for annual average rainfall ..............................................................91Appendix 6: Sydney Catchment Author itys water supply planning and assessment ..............92


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Appendix 7: Assumed system configurat ion in 2010 for water supply .......................................93Appendix 8: Water supply zones and weather stat ions used to determine climate

demand in thi s s tudy ...............................................................................................................94Appendix 9: Annual demand increases (GL/year) due to c limate change under the A2

scenario , by customer sector by supply zone ......................................................................95

Appendix 10: Related projects ........................................................................................................96Tables

Table 3.1: Projected changes to average seasonal and annual daily maximum temperature(DMT) (C) for 2030 and 2070, relative to the current climate. Best estimate

(median) change is given, with range of uncertainty (5th and 95th percentile

values) in brackets.........................................................................................................38Table 3.2: Projected changes in the average number of hot days (daily maximum

temperature (DMT)>35C), hot spells (DMT>27C for 4-7 consecutive days) andcold spells (DMT40 mm/day) in 2030 and 2070 under the A1B and A2 scenarios, relative to

the current climate. Best estimate (median) percentage changes are given, with

range of uncertainty (5th and 95th percentile values) in brackets. .................................42Table 3.7: Projected changes in the number of wet spells (>7 days) and the rainfall amount

in them for 2030 and 2070. Best estimate (median) percent changes in both the

number of days and rainfall totals are given, with range of uncertainty (5th and

95th percentile values) in brackets. ...............................................................................43Table 3.8: Projected changes to pan evaporation (PE) for 2030 and 2070 under the A1B

and A2 scenarios, relative to the current climate. Best estimate (median)

percent changes are given, with range of uncertainty (5th and 95th percentile

values) in brackets.........................................................................................................43Table 3.9: Projected average number of occurrences in a year when pan evaporation (PE)

is (a) greater than 9 mm; (b) less than 5 mm for 15 or more consecutive days


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and; (c) greater than 7 mm for 7 or more consecutive days. Best estimate

(median) values are given, with range of uncertainty (5th and 95th percentile

values) in brackets.........................................................................................................45Table 4.1: Changes in annual rainfall (mm/year) for current climate and future climate

changes under A1B and A2 emission scenarios for 2030 and 2070..............................47Table 4.2: Annual evaporation (mm/year) for current climate, and A1B and A2 emission

scenarios for 2030 and 2070 .........................................................................................49Table 4.3: Changes in annual inflow (GL/year) for current climate and future climate

change under the A2 emissions scenario. .....................................................................50Table 4.4: Changes in annual inflow (GL/year) for current climate and future climate

changes under A1B and A2 emission scenarios for 2030 and 2070. .............................51Table 4.5: Annual average changes in rainfall (mm/year) and inflow (GL/year) (% change

compared to current climate) for A1B and A2 emission scenarios for 2030 and

2070 ..............................................................................................................................52Table 5.1: Average annual demand increases due to climate changes for different

scenarios. The increase is measured against the current water demand withoutclimate change impacts, i.e. 567 GL/year for 2030 and 639 GL/year for 2070...............56

Table 5.2: Annual demand increases (GL/year) due to climate change under the A2scenario, by customer sector. Figures are the total demand increases totalled

across the 14 supply zones. ..........................................................................................56Table 5.3: Projected annual demand variability for 2030 and 2070 for different climate

scenarios.......................................................................................................................57

Figures

Figure 2.1: Annual mean temperature anomalies (C) for Sydney (33.86oS, 151.21oE)between 1950 and 2009. There is a clear warming trend from around 1970 and

a particularly rapid increase in temperatures since 2000. The black line

represents the 11-year moving average (middle year) of the measurements. ...............26Figure 2.2: Observed annual total rainfall trend in terms of percentage of climatological

rainfall based on the rainfall data over 19502009. Blue colour shows rainfall

increase and red indicates rainfall reduction..................................................................27Figure 2.3: Total annual rainfall anomaly (mm) for the Sydney region (33.86oS, 151.21oE).

The black line represents the 11-year moving (middle year) average of the

measurements...............................................................................................................28Figure 2.4: Sequences of Sydney rainfall for summer, winter, autumn and spring seasons.

Dry conditions similar to the recent drought (20002007) were observed

previously (e.g. 19391945 for summer and 19351942 for autumn). The zero

level indicates the long-term average over 19611990, which is used by the

IPCC as the baseline to define the present day climate.................................................28 Figure 2.5: Observed and modelled annual inflows (GL/year) for Warragamba Dam, the five

metropolitan dams (Cataract, Cordeaux, Avon, Nepean, Woronora) and Tallowa

Dam...............................................................................................................................30


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Figure 2.6: Annual evaporation (mm/year) at Prospect Reservoir from 1909. After a clearincrease in evaporation beginning in 1970 there is an apparent reduction from

1979 until recent years (20042007) where an increase is observed. ...........................31Figure 2.7: Distribution of annual pan evaporation at sites across Sydneys catchments

from 1960 to 2002. ........................................................................................................32Figure 2.8: Time series of the IPO index. Positive values indicate an anomalous warming in

the equatorial Pacific Ocean representing an El Nio-like pattern, and negative

values a La Nia-like pattern. ........................................................................................33Figure 2.9: Large-scale annual mean rainfall changes by the year 2070 (mm/day) from an

average ensemble of four climate model experiments (two with the A2 emission

scenario, one with A1B, and one with B1). ....................................................................35Figure 3.1: Best estimates (median values) of annual changes in daily maximum

temperature (C) for 2030 and 2070 under the A1B and A2 scenarios, relative to

the current climate. ........................................................................................................38Figure 3.2: Best estimates (50th percentiles) of changes in annual pan evaporation (%) for

2030 and 2070 under the A1B and A2 scenarios, relative to the current climate.

Blue indicates a higher percentage change in evaporation............................................44 Figure 5.1: Weather conditions and water use, January 2000 and 2001 .........................................53Figure 5.2: Projected potable water demand (GL/year) 2010 to 2070..............................................54


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Executive summary

The characteristics of variable inflow patterns over the last 120 years are taken into account in the

investigation, analysis, design and operation of Sydneys water supply system. Sydney and its

catchment area are subject to infrequent but severe droughts, such as the severe droughts in the

1890s, the 193040s and the recent drought of 20012007. While there have been periods of low

inflows, there have also been numerous large inflow events where storages filled quickly, even when

levels were low. In response to these conditions, Sydney has one of the largest per capita storages in

the world.

Sydneys rainfall is much more variable than many other parts of Australia. The recent drought has

highlighted the importance of improving our understanding of the implications of climate variability and

climate change for the water supply/demand balance of Australias largest city. Enhancing our

knowledge and capacity to respond to climate variability and climate change will be crucial to

sustaining the economic, environmental and social wellbeing of greater Sydney over the long term.

The Climate change and its impacts on supply and demand in Sydney study provides important

insights into the potential impacts of climate change on Sydneys predominantly rain-fed water supply

system, and on Sydneys future demand for urban water by:

investigating if the recent climate fluctuations in Sydney fall within the instrumental record of

natural climate variability or whether they can be attributed to the effects of climate change

downscaling climate change projections to the regional scale for use in hydrological modelling,

and to assess the changes in the rainfall, temperature and evaporation that are likely to occur

under a range of future greenhouse gas emission scenarios.

using regional climate change projections to estimate climate change impacts on inflows, and

water availability and supply under a range of future greenhouse gas emission scenarios

determining the likely urban water demand for Sydney under a range of emission scenarios,

improving knowledge of the link between key climate variables and understanding the potential

impact on future drought response initiatives.

The study also discusses the impacts of natural climate variability on current climate drivers for theSydney region and their potential impact on water supply and demand. However, it is well-recognised

that further research is required before we will better understand what influence climate variability will

have on Sydneys water supply and demand in the future.

The study is a collaboration between the Commonwealth Scientific and Industrial Research

Organisation (CSIRO), the Australian Government Department of Climate Change and Energy

Efficiency, the NSW Department of Environment, Climate Change and Water, the NSW Office of

Water, Sydney Catchment Authority (SCA), Sydney Water and the University of NSW (UNSW).

Current climate observations for Sydney

Climate observations for Sydney show that:

since 1950, annual mean temperature has increased by about 0.7C with warming more

marked in the inland areas

annual total rainfall is decreasing, mostly as a result of reduced winter rainfall in recent years

relative to the very wet years of the early 1950s, 1960s and 1970s. However this trend is

within the natural range of climate variability.

In the Sydney catchment area pan evaporation data is only available for a limited number of locations.

These data are for a shorter period than the period for rainfall data, however Prospect Reservoir has


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maintained accurate pan evaporation records since 1909. These records show significant multi-

decadal variability over the past 100 years with a marked increase in evaporation rates after 1970 to

1979. After 1979 evaporation rates started to decrease, until recent years (20042007) where rates

increase.

Evaporation across Sydneys catchments is largely dependent on geography and wind. Observed

records from the past 40 years show annual pan evaporation varying from 9001900 mm/year,

demonstrating the high degree of variability of this climate indicator.

Natural climate drivers have varying impacts on Sydneys climate. These include, the El Nio-Southern Oscillation (ENSO), Interdecadal Pacific Oscillation (IPO), Southern Annular Mode (SAM)

and Indian Ocean Dipole (IOD). Human climate influences, such as carbon dioxide, ozone depletion

and northern hemisphere aerosols, also have varying impacts on Sydneys climate (see chapter two

for definitions of the climate drivers).

The dry conditions of the recent drought were in part due to the extended period of time the Pacific

Ocean has spent in an El Niolike state and a shift of the IPO from a negative to positive phase,

which has intensified since the 1990s. A synoptic (large scale weather patterns) study (Pepler et al.

2009)of the Sydney region also confirmed that a majority of the summer low flow (19602008) events

occurred during El Nio years and 80 percent of the low flow events occurred when the Southern

Oscillation Index (SOI, see chapter two) was negative.

The synoptic study also concluded that east coast lows (strong cyclonic systems of the east coast ofNSW) have the single most significant impact on dam levels. They were responsible for 66 percent of

high flow days, including both major dam-filling events since 1992.

About this s tudy

This study focused on determining the impacts of climate change on both water supply and urban

water demand at the regional or catchment level. At its commencement in June 2006 the study was

the first to investigate climate change impacts on both water supply and demand.

The scientific methodologies used and developed in this study were based on the best available

information in Australia, at the time. The outcomes have provided a good basis for investigating

climate change impacts on water supply and demand and as the science and modelling capabilities

improve, so too will the information available for assessing these impacts.

Area

The study area extends over both Sydneys drinking water catchments and the urban areas of Sydney

where the vast majority of drinking water is consumed (Sydney Waters area of operations). This area

is more than 20,000 km2 in size and includes the Hawkesbury Nepean, Shoalhaven and Georges

River basins.

Timeframes and research approach

The climate period for 19602002 is used as the baseline in this study as it is representative (at the

time of commencing this study) of the recent average climate in the Sydney region. It is referred to as

the current climate1. The climate change projections estimate the average climate for two 20-yearwindows, 20212040 (referred to as 2030) and 20612080 (referred to as 2070). Comparison of the

future climate change impacts in 2070 and 2030 are made against the current climate.

1 The baseline current climate (1960-2002) does not include the recent drought of 2001-2007 as the study commenced before

the drought ended.


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Runs of the CSIRO Mark 3.0 (Mk3) global climate model (GCM) are used in this study because it was

the only readily available model which produces continuous daily data of dynamically consistent

predictors for both present day and future climates. CSIRO Mk3 has also been found to be one of the

best models in simulating Australias climate and associated large-scale climate drivers.

Outputs from CSIRO Mk3 GCM runs for three greenhouse gas emission scenariosrepresenting low,

mid and high emission futures (B1, A1B, and A2 respectively) were downscaled to the local/regional

level using statistical techniques developed by UNSW. To project the impacts of climate change on

water supply, the downscaled data was put into the SCAs rainfall/run-off model, Hydrological

Simulation Program-FORTAN (HSPF) to generate the run-off data. This data was fed into the SCAs

water supply system simulation model, Water Headwork Network (WATHNET) to estimate the impacts

of climate change on water supply availability under future climate scenarios.

Although three emission scenarios were modelled in this study, the findings presented in this report

focus primarily on the higher emission A2 scenario as it is now considered more realistic than the low

and mid-range scenarios (B1 and A1B).

The possible impact of climate change on urban water demand was estimated by calculating the

difference of demand under current climate conditions compared to the demand under future emission

scenarios for 2030 and 2070. Population and dwelling projections, water savings (from conservation

programs) and downscaled climate conditions from the three emission scenarios were put into a

demand model developed by Sydney Water to produce monthly demands under climate change

conditions for each demand sector in each of Sydney Waters water supply zones.

Limitations

While GCMs are the most advanced tools for investigating the causes of observed climate change and

projecting future climate change, they are limited in their capacity to model important features, such as

the impact of clouds and aerosols. Additionally GCMs do not simulate key forcing parameters, such as

solar radiation and volcanic activity, into the future. It is believed that these forcing parameters heavily

influence the persistence of low-flow sequences (such as drought).

Another area of uncertainty is that it is not yet possible to estimate future atmospheric greenhouse gas

concentrations with great certainty, since this depends on both economic growth rates and the extent

that mitigation strategies are adopted internationally. While downscaling provides a better

representation of climate impacts at a regional or local level, there are still some major challenges to

address in regard to uncertainties and bias associated with GCMs.

However local/regional simulations are still an important part of planning for climate change impacts

as long as their limitations are understood and communicated. Nationally and internationally,

researchers are working to improve the capabilities of global climate models, and further work has

been indentified which will improve our understanding of potential climate change impacts in the

Sydney region.

Climate change projections for Sydneys catchments

Sydney's daily maximum temperature is projected to increase by 0.3C to 0.7C (with a best estimate

of 0.5C) in 2030 and 1.3

C to 1.6

C (with a best estimate of 1.5

C) in 2070. Hot days, where the daily

maximum temperature is above 35C, are projected to increase to around four days each summer in

2030 and seven days each summer in 2070 (up from the current average of three days each

summer). The frequency of hot spells (periods when four to seven consecutive days each have a daily

maximum temperature greater than 27C) is projected to increase from around twice every summer to

around three times every summer in 2070. The frequency of cold spells (periods of four to five

consecutive days when the daily maximum temperature is less than 10C) will decrease from around

once every two winters to once every five winters in 2070.


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The number of wet days in the Sydney region is projected to change very litt le in both 2030 and 2070,

while the annual rainfall amount is projected to decrease slightly by two percent under both A1B and

A2 emission scenarios.

Under the A2 emission scenario, in 2070, the number of extreme rainfall days, where more than 40

mm falls, is likely to increase annually, with a maximum increase of about 18 percent in summer and a

decrease of about seven percent in winter. Increased instances of wet spells of seven days or more

are likely, mainly in autumn and summer. Rainfall amounts in these longer wet spells are likely to

increase in all seasons. Longer dry spells (of 15 days or more) could increase in 2030 and 2070. By

2070 the Sydney region is likely to see longer dry spells interrupted by heavier rainfall events.

Evaporation is projected to increase by two percent in 2030, and 10 percent in 2070. In the Sydney

region there are currently 10.4 days in a year where pan evaporation is greater than 9 mm. In a

warmer climate, this number is expected to increase to 11.5 in 2030 and 17.4 in 2070. The western

part of the study area shows greater sensitivity to the projected climate changes.

The increase in temperature, evaporation and summer rainfall and decrease in winter rainfall under

the A2 emission scenario is consistent with the recent findings from the NSW Climate Impact Profile

study (DECCW 2010).

Climate change impacts on water availability and supply

The total operating storage of the Sydney dams is about 2,600 gigalitres (GL). The Warragambacatchment is responsible for around 80 percent of the total inflows into Sydneys water supply, with the

dam having a capacity of around 2,027 GL. The majority of the other 20 percent of the inflows come

from the Upper Nepean, Woronora and Blue Mountains catchments. Recent changes to the water

supply system will see this balance shift to 6070 percent and 4030 percent. The contribution of the

Shoalhaven catchment varies depending on when pumping occurs. The Blue Mountains Catchment

was excluded from the study area for the water availability and supply modelling because its flows

represent less than one percent of Warragambas inflow.

In general, projections suggest that inland regions (the majority of the Warragamba and Shoalhaven

catchments) may get drier, while coastal regions (Upper Nepean, Wingecarribee, eastern section of

Warragamba and parts of the Shoalhaven catchments) may tend to be slightly wetter.

The majority of impacts to inflow, under A2 emission scenario, are projected to occur by 2030.

Projections under the A2 emissions scenario for 2030 suggest reduced rainfall and inflows in

Warragamba and the Shoalhaven, but increases in the region surrounding the four Upper Nepean

dams (Cataract, Cordeaux, Avon and Nepean) and Woronora. Projections also indicate evaporation

could increase by around three percent at Warragamba, Nepean, and Wingecarribee dams and

around seven percent at Goulburn. Warragamba, Nepean and Wingecarribee provide representation

of evaporation at major storages and near coastal catchments, while Goulburn provides an indication

of the evaporation changes to the inland catchments.

Under the A2 scenario, in 2070 rainfall and inflows may reduce for Warragamba and Shoalhaven and

increase for the catchments of the Upper Nepean dams. Evaporation is projected to increase for

Warragamba, Nepean, and Wingecarribee dams by around 10 percent and at Goulburn by around

22 percent. Overall for 2030 and 2070 there is a projected decrease in inflows from the downscaledcurrent climate by around 25 percent for Warragamba and Shoalhaven dams and a five percent

increase for the Upper Nepean dams.

Sydneys water supply system is designed to ensure that the annual volume of water supplied does

not compromise system security or trigger an unacceptable frequency of water restrictions. Currently

the maximum volume of water that can be safely drawn from the system (known as the system yield)

is 570 GL/year.


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The water supply system yield (based on the assumed system configuration for 2010) is projected to

reduce by around eight percent per year in 2030 and by around 11 percent per year in 2070 under the

A2 scenario. This means that we may experience an increase in the frequency of droughts and

imposition of restrictions compared to the current conditions. However, further work is needed to

improve our understanding of how future climate conditions will impact on periods of low inflows (a key

factor in estimating system yield and managing security of supply). While GCMs can replicate low

inflow periods that have occurred in the past, they are not presently able to model such periods in the

future, and further work is required before we can more confidently project impacts on future droughts.

Climate change impacts on demand

Household water uses accounts for about 72 percent (50 percent single residential and 22 percent

multi-unit) of water used in Sydney. The other 28 percent is used by commercial (10.5 percent),

industrial (9.5 percent) and government and other sectors (including agriculture) (eight percent).

Under the A2 scenario the majority of the increase in annual demand is from the residential and

commercial sectors. Within the residential sector, single residential dwellings show the largest

increase, since the climate impact is mainly from outdoor water uses. Temperature and evaporationincreases also impact the use of air conditioners and outdoor water use in the commercial sector.

In general, annual demand increases due to climate change are more severe in 2070 than in 2030 in

all sectors. In systems such as Orchard Hills, Prospect North and Macarthur, the annual demand

increase in the residential sector is highest for the single residential sector. This is because most of

the dwelling growth in these systems is single residential dwellings in the greenfield areas. On the

other hand, in Potts Hill water supply system the increase is higher for the multi-residential sector as

the majority of growth in this system is multi-dwellings.

The highest increase in average annual demand due to climate change (from the current climate

demand of 639GL/year) is about 25 GL/year in 2070, under the A2 emission scenario. This is much

less than the estimated range for the variability in annual demand (52 GL/year in 2030 and 73 GL/year

in 2070). That is, the increase in water demand for Sydney will be influenced more by natural climatevariability than human induced climate change impacts.

Given that the impact of climate change on total demand is around four percent, or 25 GL/year, in

2070, it is difficult to estimate any significant impact on demand hardening2, or the impact of drought

2Demand hardening the reduction in effectiveness of measures designed to reduce water consumption in drought periods,

due to the uptake overtime of programs/appliances/fittings to improve water efficiency and substitute mains water with

alternatives, such as rainwater tanks.

Drinking water consumption by sector


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restrictions on water use. Importantly, peoples attitude to water use, including both their indoor and

outdoor water use, will directly impact on the reduction in demand achieved when drought restrictions

are implemented. It will therefore be important to monitor peoples attitude to water use and drought

restrictions.

Climate change will also result in a slight increase in the savings from water conservation programs

targeting outdoor use. This would partly offset the increase in water demand due to climate change. It

is difficult to quantify this effect since there is no data available to establish the relationship between

the savings and key climate variables. However, as the increase is very small it should be interpreted

that climate change impacts would not significantly affect the savings achieved by demandmanagement programs.

Implications for supply and demand planning

There is still significant uncertainty regarding the climate in Sydneys drinking water catchments in the

future. However, planning for variable rainfall in the short and longer term is a continuing theme for the

Metropolitan Water Plan for greater Sydney.

The findings from this study provide some guidance to key water agencies to understand and plan for

the impacts of climate change on Sydneys dam storage system. The projected decrease in rainfall

and inflows to the inland areas of the catchment, and slight increase in rainfall and inflows to the

coastal areas, may provide opportunities for future enhancement to the configuration and performance

of the storage system.

While there may be slight changes to inter-seasonal variability for rainfall, there is a balance between

increasing temperature and evaporation, which may result in little change to the overall variability

between seasons in terms of dam inflows.

Increasing summer rainfall intensity could result in increased runoff and associated stream

sedimentation and turbidity, while prolonged drought periods may increase the propensity for algal

blooms. However, in the short term, there are no foreseen management issues for coping with these

projected changes as the Sydney Catchment Authority has the necessary response framework

already in place.

Although there may not be a significant increase in urban water demand due to climate change it is

still important to have contingency measures in place. The 2010 Metropolitan Water Plan outlines a

new, simpler regime of drought restrictions, and measures that could be deployed in extreme drought

if needed.

Inter-seasonal variability has been identified as a potential issue for urban water demand, however

Sydney Water is already assessing implications through their current climate change and risk

assessment adaptation programs. The true impacts are difficult to quantify because of the current

limitations in the results.

As a result of the projected increase in extreme rainfall events, Sydney Water has started looking at

the potential impacts of increased flows on stormwater infrastructure. Another issue is the long-term

coupling of sea-level rise and extreme events on low-lying stormwater assets. Sydney Water has

begun looking at the broader issues of potential climate change impacts on its infrastructure andoperations with a view to identifying future adaptation options that might be required.

The outcomes of this study were considered in the review of the 2006 Metropolitan Water Plan.

However, while the research indicates potential changes to supply and demand under future climate

conditions, the relatively low impact of these changes and the lack of certainty in the findings mean

that, for the short term, the research has not fundamentally changed water management planning for

Sydney.


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The 2010 Metropolitan Water Plan adopts an adaptive management approach to water planning. This

means that, while there is no immediate need to change current management practices to cope with

the projected impacts of climate change, the Plan is flexible enough to allow measures to be adjusted

in the medium and long-term future, if needed. Through this adaptive management approach the 2010

Plan, has the capacity to:

manage risk by having the appropriate buffer between supply and demand

understand the likely pressure points on the supply and demand balances in the future

respond to changing conditions due to both climate change and climate variability

continue to improve our knowledge of climate change impacts on greater Sydneys water

supply

incorporate this knowledge into future strategies.

Future research

This study was undertaken to better understand the impacts of climate change on Sydneys water

supply system and future urban water demand. It broke new ground in modelling climate change

impacts at the regional level and has helped identify the next quantum of research needed to improve

the confidence of modelling at the regional scale.

There will always be uncertainty associated with climate change projections, due to uncertaintiesabout future levels of greenhouse gas emissions, the lack of consistent climate data and limitations of

global climate models. It is not possible to develop absolutely precise projections of future climate

change. However, by adopting a flexible, adaptive approach we can still plan for future water supply

even in the absence of perfect information.

One of the elements of adaptive management is to continually review and update the information

base. A number of areas of further research have been identified to improve the methods that were

used in this study and to the increase the level of confidence in results projecting the impacts of

climate change on water supply and demand systems at the regional/local level. These include the

need to:

improve the representation of severe climatic extremes in all aspects of current climate

modelling understand why GCMs are unable to simulate sustained anomalies, such as drought (low

frequency variability) in future simulations, with the aim of removing this bias

develop a means by which GCM simulations can be dynamically downscaled3to enhance

their representation of low frequency variability

understand how dynamically downscaled climate simulations can be used to develop

stochastic (random) downscaling procedures for climate variables such as rainfall,

temperature and evaporation, to give accurate representation of drought and high flows in

future climate simulations

model future simulations using at least two GCMs and the more pessimistic A1FI greenhouse

gas emission scenario

finalise the current study of palaeological information to better understand natural climate

variability (wet and dry cycles) and to assess how representative the past 100 years is of thelong-term historical hydrological patterns

understand the climate change impact on the synoptic (large scale weather patterns)

classifications driving extremely high and low inflows to the Sydney catchments

3Dynamical downscaling uses regional climate models, driven by GCM outputs, to produce higher resolution results for a small

geographic region. This improves the accuracy and spatial patterns of climate variables compared to the GCM but the quality of

the results depends on the biases inherited from the GCMs (e.g. the models tendency to produce wet or dry results).


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make use of advances in climate science and improved climate modelling that will be included

in the Intergovernmental Panel for Climate Changes (IPCC) fifth assessment report.


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CHAPTER 1

Introduction

Investigating cl imate change and its impacts on water supply

and demand in Sydney

Sydneys rainfall is much more variable than rainfall in many other parts of Australia. Inflows to theSydney water supply system are three times more variable than inflows to the Melbourne system

(Sydney Water 2007). The recent drought has highlighted the importance of better understanding the

implications of climate variability and climate change for the water supply/demand balance of

Australias largest city. Enhancing our knowledge and capacity to respond to climate variability and

climate change will be crucial to sustain the economic, environmental and social wellbeing of greater

Sydney over the long term.

This study seeks to provide important insights into the potential impacts of climate change on

Sydneys predominantly rain-fed water supply system, and on Sydneys future demand for water, by:

investigating if the recent climate fluctuations in Sydney fall within the instrumental record of

natural climate variability or whether they can be attributed to the effects of climate change

downscaling climate change projections to the regional scale for use in hydrological modelling,

and to assess the changes in the rainfall, temperature and evaporation that are likely to occur

under a range of future greenhouse gas emission scenarios (emission scenarios)

using regional climate change projections to estimate climate change impacts on inflows, and

water availability and supply under a range of future emission scenarios

determining the likely urban water demand for Sydney under a range of emission scenarios,

improving knowledge of the link between key climate variables, and understanding the potential

impact on future drought response initiatives.

The study also discusses the impact of natural climate variability on current climate drivers for the

Sydney region and the potential impact that this variability has on water supply and urban waterdemand. It is well-recognised, however, that further research is required before we will understand

what influence climate variability will have on Sydneys water supply and demand in the future.

The study is a collaboration between the Commonwealth Scientific and Industrial Research

Organisation (CSIRO), the Australian Government Department of Climate Change and Energy

Efficiency, the NSW Department of Environment, Climate Change and Water, the NSW Office of

Water, Sydney Catchment Authority (SCA), Sydney Water and the University of NSW (UNSW).

Sydneys surface water supply

Catchment area

Sydneys catchment area covers 16,000 km, extending from the headwaters of the Coxs River nearLithgow to the headwaters of the Shoalhaven River near Cooma. It consists of five main river systems:

Warragamba Catchment this catchment accounts for 80 percent of total inflows into

Sydneys water supply and, with a capacity of 2,027 GL. The other 20 percent of total inflows

come from the Upper Nepean, Shoalhaven, Woronora and Blue Mountains catchments.

Recent changes to the water supply system will see this balance shift to 6070 percent and

4030 percent. Warragamba Dam is one of the largest domestic water supply dams in the

world.


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Upper Nepean Catchment this catchment lies in one of the highest rainfall regions in NSW.

The dams of the Upper Nepean collect water from the catchments of the Cataract, Cordeaux,

Avon and Nepean rivers, which are tributaries of the Upper HawkesburyNepean River. The

combined storage capacity of the dams is 375 GL. These systems supply water to the

Macarthur and Illawarra regions, the Wollondilly Shire, and metropolitan Sydney.

Shoalhaven Catchment - water from Tallowa Dam, and Fitzroy Falls and Wingecarribee

reservoirs, is used to supply local communities and supplement supply to Sydney and the

Illawarra storages during drought.

Woronora Catchment - Woronora Dam has a storage capacity of 72 GL. It collects water from

the catchment of the Woronora River, which drains into the dam and then to Botany Bay. The

dam supplies water to residents within the Sutherland Shire in Sydney's south.

Blue Mountains Catchment the Blue Mountains system comprises two small catchment

areas feeding five dams, which provide water for about 41,000 people living in the Blue

Mountains region. Water for the Blue Mountains is also sourced from the Fish River Scheme,

which originates in Oberon.

Reservoir and supply system

The Sydney Catchment Authority is responsible for delivering a reliable and safe bulk water supply. It

manages a total of 21 storage dams (11 of these are defined as major dams) and associated

infrastructure that supply raw water to the Sydney Water for treatment and distribution to the Sydney

metropolitan area, as well as to two local government areas outside the Sydney Water area ofoperation. The total operating storage of the dams is about 2,600 GL.

The map in the executive summary shows locations of Sydney Catchment Authoritys water supply

infrastructure and drinking water catchments and Sydney Waters delivery and distribution systems.

See Appendix 3 for a more detail representation of the drinking water catchment and delivery and

distribution system.

Sydney Waters delivery and d istr ibution area

Sydney Water provides drinking water, recycled water, wastewater and some stormwater services to

over 4.3 million people in Sydney, the Illawarra and the Blue Mountains. This area of operations

covers 12,700 km. Sydney Waters delivery system covers about 3,200 km.

Modelling an uncertain futureThe most important information for policy makers in planning for future climate change is to

understand the impacts at the local or regional level. This is particularly important for the Sydney

region which has a highly variable rainfall and experiences variations in rainfall and run-off across the

coastal and inland regions. It is important to understand how climate change may impact on rainfall

patterns so that water planners can adjust the system operations or augment supply to adapt to the

projected changes.

To project climate change impacts at a broad scale climate scientists use global climate models

(GCMs). These models represent physical processes in the global atmosphere, oceans, ice sheets

and on the land surface. They also take into account man-made impacts on climate, such as

greenhouse gas emissions and aerosols, as well as natural climate influences, such as solar variability

and gases from volcanic eruptions.

The broad scale resolution of GCMs is too coarse for driving hydrological models to project changes in

rainfall patterns, as local features and dynamics are not well represented at this scale. Therefore, to

obtain the finer resolution required for hydrological models, the coarser data outputs from GCMs are

downscaled.

This study adopted a statistical downscaling technique to gain a better understanding of climate

change on water supply and demand at the local/regional level. When this study began (June 2006) it


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was the first time this methodology had been applied to project climate change impacts on water

supply and demand at the local level.

While downscaling provides a better representation of climate impacts at a local level, it is very difficult

to project these impacts with a high level of confidence due to the uncertainties associated with global

climate modelling. However local/regional simulations are still an important part of planning for climate

change impacts as long as their limitations are understood and communicated.

Global climate modelling

GCMs are the most advanced tools for investigating the causes of observed climate change and

projecting future climate change. A GCM is a complex mathematical representation of the earths

climate system. It relies on the solution of fluid motion and energy algorithms to reflect changes in

climatic variables such as wind, temperature, humidity and rainfall. GCMs typically provide outputs at

a resolution of around 200 km x 200 km. Worldwide, there are 23 GCMs that attempt to predict the

changes in climate under different carbon emission scenarios.

Climate models are able to reproduce the significant features of the observed climate very well

(Randall et al. 2007), and there is a high level of confidence in their ability to provide credible

quantitative estimates of future climate change, particularly at a broader continental scale and above.

The highest confidence is attached to results analysed at the coarsest spatial and temporal scales,

such as global or hemispheric annual means. Confidence decreases with finer scales, such as sub-

continental or regional daily variability.

Modelling climate change impacts at the local or regional level using GCM outputs is less certain. At

finer scales the magnitude of natural climate variability increases and regional climate signals, such as

the El Nio-Southern Oscillation and Southern Annular Mode are easily masked. Furthermore, local

influences on climate (such as regional topography or processes) become more important at finer

spatial scales (CSIRO and Bureau of Meteorology 2007, p. 41).

Uncertainty and limitations of climate modelling

Climate modelling is characterised by uncertainty at three levels:

1. Emission scenarios: It is not possible to estimate future atmospheric greenhouse gas

concentrations with great certainty since this depends both on economic growth rates and theextent of mitigation strategies adopted internationally.

2. GCM performance: There remain significant limits in the capability of GCMs to model

important features such as the impact of clouds and aerosols. Additionally, key forcing

parameters such as solar radiation and volcanic activity cannot be predicted into the future.

3. Downscaling limitations: There remain significant limits in the capability of downscaling

methods to estimate climate impacts at the local or regional level.

Emission scenarios

It is not possible to estimate with certainty what the level of greenhouse gases will be at a particular

time in the future as this will be determined by rates of economic growth and global mitigation actions.

Recognising this uncertainty around future emissions growth and global atmospheric concentrations of

greenhouse gases (GHG), the Intergovernmental Panel on Climate Change (IPCC) developed a range

of potential GHG emission scenarios for their Special Report on Emissions Scenarios (SRES 2000).

The SRES scenarios are grouped into four scenario families (A1, A2, B1 and B2) that explore different

development pathways, covering a wide range of demographic, economic and technological driving

forces and resulting GHG emissions (see Appendix 2 for more detail on the scenarios). The emission

projections are widely used in the assessment of future climate change, and their underlying


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assumptions with respect to socio-economic, demographic and technological change serve as inputs

to many recent climate change vulnerability and impact assessments.

In 2008, the Garnaut Climate Change Review(Garnaut 2008) concluded that all the IPCCs emission

scenarios may underestimate the future growth in emissions in the early 21st century, with recent

science indicating that the A2 scenario may now be seen as a realistic/optimistic scenario rather than

pessimistic. Some climate scientists even claim that the A1FI emission scenario is a more realistic

scenario than A2, as it is based on more rapid growth in emissions (in line with recent observed

emissions growth) and higher GHG concentrations in 2030 and particularly in 2070. Recent analysis of

global mean surface temperature also shows that the rate of warming is in the upper range of the

IPCCs climate projections (A1FI).

The A1FI scenario is now being used in Queensland to model potential climate change impacts (see

the Urban Water Security Research Alliance project discussed in Appendix 10).

GCM performance

There is some uncertainty in the GCM representation of climate, as we still have much to learn about

climate processes and how they are translated in a climate model. Model representations of cloud

physics, anthropogenic aerosol effects, chemical ozone and its interactions with climate, and carbon

cycles are areas in which significant uncertainty exists. As a consequence the response from one

model to another varies vastly, even for the same climate change emission scenario, and it is difficult

to place a higher confidence in a particular model.

To help address this issue, UNSW developed the variable convergence score (skill score) for climate

variables across a number of GCMs (Appendix 1).A higher score indicates higher consistency of that

climate variable across GCMs, and with that, a higher confidence in the use of that variable in

downscaling for future climates. The study carried out by UNSW suggests that future rainfall is

considerably more difficult to simulate compared to variables such as air pressure or temperature, i.e.

rainfall is simulated less consistently than pressure or temperature for future climate by a range of

GCMs.

This skill score is an important step in trying to evaluate the accuracy of GCM model outputs for their

use in projects aiming to assess future climate change impacts at a regional level.

Climate modellers often use a multi-model ensemble to helpaddress uncertainties associated withGCM output. In a multi-model ensemble many independent models are run for a given set of climate

conditions and their results aggregated. Use of a multi-model ensemble cancels out model biases of

opposing natures. Further, because each model has its own variability, when aggregated over many

models, the variability component is reduced, leaving only the climate change response.

GCMs continue to improve in their ability to reproduce the observed climate and to separate out the

impacts of human-induced and natural variability factors. Recently the Program for Climate Model

Diagnosis and Intercomparison (PCMDI), an international climate change research group, produced a

database of experiments using the 23 available GCMs (see ). This

database represents state-of-the-art climate modelling and includes more sophisticated

representations of physical and dynamical processes at a finer spatial resolution than has been used

in the past.

However, climate models still have some limitations and it is virtually impossible to predict exactly how

climate statistics will evolve over the 21st century. Hence our knowledge of relevant processes and

deficiencies in our data, methods and models is likely to remain imperfect for the foreseeable future

and thus will be an ongoing source of uncertainty (Jones 2000; Visser et al. 2000).

A common methodology in trying to assess the impacts of climate change on water supply is to

generate rainfall, evaporation and flows for future climates under assumed greenhouse gas emission

scenarios (the approach used in this project). While frequently used, this approach assumes that


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climate model simulations are unbiased both in a distributional sense (such as means and variance

percentiles) as well as in their representation of the sustained anomalies (such as droughts) that

define water resource system reliability and security. There is growing evidence to suggest that

regional model simulations, over a historical timeframe, misrepresent distributional attributes and low-

frequency variability (including drought and high inflows) that characterise long-term persistence in the

climate.

A possible reason for this is that the GCM representations for historical climate contain key forcing

parameters, including solar radiation and volcanic activity. The GCM runs for future time periods do

not contain all these forcing parameters. It is believed that the forcing parameters heavily influence the

persistence of flow sequences i.e. low-flow persistence is present in the GCM representation for the

historical climate but not for the future GCM representations. To address this issue, statistical

techniques were developed in this study to reproduce the historical persistence in the downscaled flow

sequences. However, this methodology may also reduce the confidence in the projected impacts of

climate change on water supply in the Sydney region.

Future research needed to address the key limitations of using climate modelling to project climate

change impacts on water supply at the regional level, is discussed in chapter seven.

Downscaling

Finer resolution outputs to project climate change impacts at the local/regional level are achieved by

downscaling GCM outputs. There are three general classes of downscaling techniques: perturbation(daily scaling), statistical and dynamical (physically-based).

Perturbation is the simplest downscaling method. Historical daily rainfall data series are scaled or

modified by applying rainfall and evaporation values derived from a GCM. This is done to produce a

future daily rainfall series that preserves the historical rainfall pattern (i.e. the temporal sequence of

wet days and the frequency/length of wet and dry spells). With this method it is not possible to model

droughts longer than those that have been observed. This is an issue for future projections as current

science indicates that future droughts may be longer than those experienced in the past.

Statistical downscaling (which was the method applied to this project) relates synoptic (large-scale)

atmospheric predictors (e.g. humidity, wind speed, sea-level and other atmospheric pressures, air

temperature, and previous days rainfall) and local climate variables (predictands, e.g. at-site rainfall

and temperature) over a specified period, based on analysis of historical data. This relationship (in the

form of a series of mathematical models) is then used to downscale atmospheric predictors simulated

by a GCM to obtain point rainfall and other local variables.

Dynamical downscaling uses regional climate models, driven by GCM outputs, to produce higher

resolution results for a small geographic region. This improves the accuracy and spatial patterns of

climate variables compared to the GCM, however the quality of the results depends on the biases

inherited from the host GCM/s (e.g. the models tendency to produce wet or dry results).

The performance of downscaling methods varies across seasons, locations and GCMs, and depends

strongly on biases inherited from the driving GCM and the presence and strength of regional features

(such as topography, land use and vegetation cover). In general, statistical downscaling methods are

more appropriate where point values of extremes are needed for impact studies.

About th is study

Study area

The study area extends over both Sydneys drinking water catchments (Sydney Catchment Authoritys

area of operations, excluding the Blue Mountains) and the urban areas of Sydney where the vast

majority of drinking water is consumed (Sydney Waters area of operations). This area is more than

20,000 km2 in size and includes the Hawkesbury-Nepean, Shoalhaven and Georges River basins.


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Maps of the drinking water catchment and delivery and distribution systems are attached at Appendix

3.

The Blue Mountains Catchment was excluded from the study area for the water supply modelling as it

is generally regarded to be implicitly modelled as part of the Orchard Hill demand, especially in terms

of a broad scale impact assessment. Its flow represents approximately 0.3 percent of Warragambas

inflow. The Blue Mountains area was included in the demand modelling.

Current climate and climate change projection timeframes

The climate period for 19602002 is used as the baseline in this study as it is representative (at the

time of commencing this study) of the recent average climate in the Sydney region. It is referred to as

the current climate. High quality data on all major climatological variables are readily available for this

period. Comparison of future climate change impacts are made against this baseline.

The simulations for the GCM emission scenarios are undertaken for close to 100 years, with

increasing greenhouse gas emissions throughout. The climate change projections estimate the

average climate for two 20-year windows, 20212040 (referred to as 2030) and 20612080 (referred

to as 2070). The results for individual years will show some variation from the average for these time

slices.

This baseline and 20-year time slices were also used for the hydrological assessments in the study.

However, as is discussed later in this chapter, 20-year time slices do not provide an adequate low flowsequence to accurately assess the impacts of drought on future water supply.

Throughout the report there is also reference made to the timeframe of 19611990, which is the IPCC

baseline to define current climate. This baseline was used when discussing current climate trends for

NSW in chapter two.

Climate modelling and downscaling methods

GCM and downscaling

Runs of the CSIRO Mark 3 (Mk3) GCM are used in this study. The statistical downscaling models are

calibrated using reanalysis atmospheric data (spatial and temporal interpolation data between actual

observations) and observed daily rainfall/evaporation/daily maximum temperature records at ground

locations. This information is then validated using current climate (19602002) GCM data.

CSIRO Mk3 was chosen because it was the only readily available model which produces continuous

daily data of dynamically consistent predictors for both the present day and future climate. It is also

one of the models used in the IPCCs fourth assessment report, and it has been extensively examined

in terms of its performance. It has been found to be one of the best models in simulating Australian

climate and associated large-scale climate drivers.

Ideally, additional GCMs would have been used to reduce uncertainty in the projections, but these

were not readily available in the timeframe of the study. However, the sensitivity of CSIRO Mk3 to

climate change forcing is close to the multi-model ensemble average, in terms of future rainfall change

and the seasonality of the change. In addition, multiple emission scenarios were used to take into

account uncertainties arising from varying levels of greenhouse gas emissions, and multi-decadal

long-term averages were used to allow for the uncertainty associated with climate variability.

Downscaling techniques were used by UNSW to transform the coarse resolution GCM outputs from

CSIRO Mk3 to a finer spatial scale (around 5km x 5km, or at point locations). The statistical

downscaling framework developed by UNSW (Mehrotra and Sharma 2010) consisted of daily

mathematical models for rainfall occurrences, rainfall amounts (volume), temperature and pan

evaporation based on daily atmospheric variable outputs from the CSIRO Mk3 model. As the skill


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levels of GCMs for rainfall prediction are low, the downscaling method for this study used variables

(other than rainfall) that are predicted well by GCMs, such as temperature and surface pressure.

The downscaled rainfall and evaporation data was put into the SCAs rainfall/run-off model,

Hydrological Simulation Program-FORTAN (HSPF), to generate the run-off data. The run-off and

evaporation data was then fed into SCAs water supply system simulation model, Water Headwork

Network (WATHNET), to estimate the impacts of climate change on water supply availability under

future climate scenarios.

The downscaled data was also used by Sydney Water in their demand model to determine futureclimate change impacts on urban water demand.

Catchment based rainfall/run-off models

HSPF was used to estimate streamflow from rainfall and evaporation. The model allows for rainfall

distribution within the catchment including soil infiltration rates, vegetation holding capacity, root depth

and transpiration rates, return of flows to streams (base-flow) and flows to the deeper groundwater

aquifers. Soil moisture accounting in a continuous timescale is of paramount importance for the

prediction of inflow changes during periods of drought.

The SCA developed and calibrated four HSPF models to represent the main water supply catchments.

Each of these models has sub-catchments within them to allow adequate representation of the spatial

variation in meteorological, geological and topographical conditions. A time series of rainfall andevaporation provides the temporal variation.

Demand model

The demand model was built using the relationship between key climate variables and the water

demand of individual sectors (single residential, multi-residential, industrial, commercial, primary

produce, government and others) developed in this study. To capture the spatial variation of climate

the demand model was divided into 14 water supply zones.

The population forecast for the demand modelling is based on the NSW median population forecast of

just over five million in 2030 and over six million in 2070 (NSW Department of Planning, 2008, with

adjustments made by Sydney Water to reflect the catchment area modelled in this study). This

forecast has increased slightly since the 2008 figures, however as the difference between thedemands with and without climate change are modelled, the slight increase in population forecasts

does not impact on the overall model results.

Emission scenarios

This study used the B1, A1B and A2 emission scenarios, representing low, mid and high emission

futures. At the beginning of this study (June 2006) it was considered that the B1, A1B and A2

scenarios would provide an adequate spread of possible futures, ranging from optimistic (B1) through

to pessimistic (A2).

However, recent thinking on emission scenarios (as discussed earlier in this chapter) suggests that the

A1FI scenario may be the more realistic scenario for future conditions. In consideration of this the

report only presents outcomes for the A1B and A2 scenarios. Results for B1 are available in Appendix4 and associated technical papers (Mehrotra and Sharma 2010; Sydney Catchment Authority 2009

and Sydney Water 2009).

Climate variables

Rainfall frequency and intensity, temperature and evaporation are the key climate variables influencing

inflows into Sydneys catchments (and driving possible changes in water supply demands). In addition

to its impact on evaporative losses from water storages, evaporation affects soil moisture and thus the

volume of run-off and inflows generated by a rainfall event. Rainfall, temperature and evaporation are


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also the key climate variables influencing urban water demand. As such they are the key climate

variables that are assessed in this study.

Water availabilit y and supply

Sydneys water supply system is designed to ensure that the annual volume of water supplied does

not compromise system security or tr igger an unacceptable frequency of water restrictions. Currently,

the dam system has sufficient capacity to store approximately four years of current unrestricted

demand (assuming no further inflows during this period). This indicates that the system is able to

withstand severe drought conditions (based on drought periods from the historical record).

The maximum volume of water that can be supplied from the system, defined as the system yield, is

determined using 200,000 years of synthetically generated flow, based on 100 years of inflow records

(19092008), thereby ensuring that the system meets the design and performance criteria of security,

reliability and robustness (see Appendix 6 for more detail). The water supply simulation model

(WATHNET) is used to represent the complex set of system constraints, environmental and regulatory

releases and operating rules.

To determine the impacts of climate change, a system configuration (detailed at Appendix 7)

representing conditions for 2010 is used. The system configuration represents a range of government

policy decisions and planned infrastructure, allowing reference to other key planning analyses that

have occurred prior to and in parallel with this study. Two key limitations in this study are the shorter

analysis timeframe of 43 years (compared to the 100 years timeframe used to determine the current

system yield) and the lack of persistence in the climate change projections.

Persistenceis the accurate representation of multiple years of low inflow sequences. For Sydney, the

worst droughts on record are in the order of f ive to seven years in length, between 1934 and 1942 and

the most recent drought between 2001 and 2007 (in mid-2009, drought restrictions were lifted and the

Water Wise Rules took effect). In the historical analysis of the annual flow records for Sydney, the lag-

1 annual correlation is significant, but there is no significant correlation between the current years flow

and that of two years earlier.

The key factor in making a robust assessment of Sydneys water supply system is being able to

accurately represent multiple years of low flow (drought) sequences. This persistence of low flow

sequences is statistically measured as a correlation between each years flow and the flow from

previous years. In the historical analysis of the annual flow records for Sydney, there is significant

correlation between the current and previous years flow (defined as a lag-1 annual correlation).

During the development of the adopted methodology it became clear that there was a lack of

persistence in multi-year flow periods for the climate change projection scenarios. The possible reason

for this (as discussed in the section on GCM performance earlier in this chapter) is that the key forcing

parameters present in the current climate GCM runs are absent in future runs.

To enable an analysis of the impacts of climate change (and maintain the historical persistence) the

average flow between the current climate and the climate projections was applied to the historical

observation of inflows between 1960 and 2002. However, further research is required to understandthe climate change impacts on future drought sequences.

To determine the impact of the reduced assessment period, a comparison between the longer 100-

year period and the shorter 43-year period was made. As performance of the system was assessed

using 2,000 replicates of annual inflows generated using historical records at each site for a 43-year

period, the yield assessment in this study must be considered as a modified system yield and will be

referred to as the system output. This system output was produced specifically for this research and is

for comparative purposes only.


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Water demand

The water demand forecast for future scenarios strongly relies on future climate conditions, dwelling

and population forecasts, saving estimates of water conservation programs, and the relationship

between demand and key climate variables.

The uncertainties of the future climate conditions still remain. Any limitations from the statistical

downscaling model will carry through and affect the demand results.

There is no data available to determine the relationship between savings from water conservationprograms and key climate variables (such as rainfall and temperature).

Forecasts for non-residential (commercial, industrial, government and others) are not available. As

such a simple regression equation was used to estimate the future projections in this study. A better

approach could be to improve the forecast of non-residential dwellings and produce a more robust

estimate of the total impact from these customer sectors.

The only aspect of demand that can be adequately projected is that component which is influenced by

climate. Any other influences, such as behaviour, new appliances or users coming on-line/off-line are

not accounted for. This means sectors that are highly dependent on these influences, such as the

industrial sector, have models that poorly represent consumption. The industrial sector is likely to be

influenced by major users coming on-line or going off-line. Similarly, the commercial sector is likely to

be influenced by economic conditions. These factors have not been included in the regression model.Despite this, the regression model is adequate to predict the relative increase of demand due to

climate change.


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CHAPTER 2

Understanding Sydneys climate

Current climate observations for Sydney

Reliable observational climate records have been kept in Australia since 1910. However, the highest

quality data and data reflecting human-induced climate changes are only available from 1950. This

study focuses on changes since 1900s for rainfall, inflows and evaporation and changes since 1950s

for temperature (as the Bureau of Meteorology does not provide data for the Sydney region before

1950). This chapter outlines how Sydneys climate has changed in recent times and what factors have

driven these changes.

The baseline for current climate commonly used by the Intergovernmental Panel for Climate Change

(IPCC) to compare future climate conditions is 19611990 (referred to in this chapter, for temperature

and rainfall). As discussed in chapter one, the current climate baseline for comparing future climate

impacts under this study is 19602002.

Temperature

Since 1950 Sydneys annual mean temperature has increased by about 0.7C. Warming is more

marked in inland areas: averaged across NSW, the annual mean temperature has risen by about1.1C since 1950 (Figure 2.1).For 11 consecutive years (19972007) the annual mean temperature

across NSW has been above the 19611990 average, with 2007 being the hottest year (averaged

across NSW). This persistent warming is unprecedented during the period of record.

Figure 2.1: Annual mean temperature anomalies (C) for Sydney (33.86oS, 151.21

oE) between 1950 and

2009. There is a clear warming t rend from around 1970 and a particularly rapid increase in

temperatures si nce 2000. The black line represents the 11-year moving average (middle year)

of the measurements.

Note that 11-year moving averages are commonly used to indicate inter-decadal signals.


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Rainfall

Although Australian rainfall is highly variable, long-term changes in rainfall trends have emerged.

Since the 1950s, rainfall has been decreasing over eastern and southern Australia. In contrast, there

has been a significant increasing trend over north-west Australia (Figure 2.2).

Figure 2.2: Observed annual total rainfall trend in terms of percentage of climato logical rainfall based on

the rainfall data over 19502009. Blue colour show s rainfall inc rease and red indicates rainfall

reduction.

In the Sydney region the average annual rainfall for the past 120 years has been 865 mm in the

Warragamba Catchment, 816 mm in the Shoalhaven Catchment, and 1,130 mm in the Upper Nepean

Catchment. Since the 1950s there has been an observed decreasing trend in Sydneys annual rainfall

(Figure 2.3). This trend is mostly the result of reduced winter rainfall in recent years relative to the very

wet years of the early 1950s. A relatively smaller contribution to the annual rainfall reduction comes

from the declining trend in summer rainfall (Figure 2.4). The observed long-term data shows that there

is virtually no long-term trend in autumn and spring.


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Figure 2.3: Total annual rainfall anomaly (mm) for the Sydney region (33.86oS, 151.21

oE). The black l ine

represents the 11-year moving (mid dle year) average of the measurements.

Figure 2.4: Sequences of Sydney rainfall for summer, winter, autumn and spring seasons.

Dry condi tions sim ilar to the recent drought (20002007) were observed previously (e.g.

19391945 for summer and 19351942 for autumn). The zero level i ndicates the long-term

average over 19611990, which is used by t he IPCC as the baseline to define the p resent day

climate.

Sydney seasonal rainfall anomaly (mm)

Sydney total annual rainfall anomaly (mm)


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Inflows

As discussed in the previous section, the rainfall in Sydneys catchments is unusually variable.

Consequently the inflows to Sydneys catchments vary widely. In fact, the coefficient of variability for

Sydney is three times that for Melbourne (Sydney Water 2007). This is reason the storage capacity

was built to last around seven years without rain. It has since reduced to four and a half years due to

population growth and water demand. As a comparison, the storage capacity for London would last

around 11 weeks without rain.

The volume of inflows is affected by the frequency and intensity of rainfall events and by soil moisture,which in turn are affected by temperature and evaporation. The current estimates of inflows are

derived from a combination of daily inflow observations at gauged locations (where observed data was

available) and monthly mass balances at each dam.

Annual inflows to each of the dams in the three major catchments are shown in Figure 2.5. As the

figure shows, inflows into Sydneys major dams were dominated by high flows in the 1950s, 1960s

and 1970s. It should be noted that the inflow data for Tallowa Dam has been derived from models

based on the rainfall records, since this dam was only constructed in 1977.

8/12/2019 Climate change and its impact

climate change and its impacts on water supply and demand in sydney

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