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Journal of Environmental Management (2002) 65, 369±381
doi:10.1006/jema.2002.0562, available online at http://www.idealibrary.com on
1
The effects of large-scale afforestation and
climate change on water allocation in the
Macquarie River catchment, NSW, Australia
Natasha Herron*², Richard Davis³ and Roger Jones§
²
NSW Department of Land and Water Conservation, Suite U101, Level 1, 131±139 Monaro St,
PO Box 189, Queanbeyan NSW 2620, Australia
³
CSIRO Land and Water, GPO Box 1666, ACT 2601, Australia
§
CSIRO Atmospheric Research, Private Bag No.1, Aspendale Victoria 3195 Australia
Received 27 April 2001; accepted 29 January 2002
Widespread afforestation has been proposed as one means of addressing the increasing dryland and stream salinity
problem in Australia. However, modelling results presented here suggest that large-scale tree planting will substantially
reduce river ¯ows and impose costs on downstream water users if planted in areas of high runoff yield. Stream¯ow
reductions in the Macquarie River, NSW, Australia are estimated for a number of tree planting scenarios and global
warming forecasts. The modelling framework includes the Sacramento rainfall-runoff model and IQQM, a stream¯ow
routing tool, as well as various global climate model outputs from which daily rainfall and potential evaporation data ®les
have been generated in OzClim, a climate scenario generator. For a 10% increase in tree cover in the headwaters of the
Macquarie, we estimate a 17% reduction in in¯ows to Burrendong Dam. The drying trend for a mid-range scenario of
regional rainfall and potential evaporation caused by a global warming of 05 C may cause an additional 5% reduction in
2030. These ¯ow reductions will decrease the frequency of bird-breeding events in Macquarie Marshes (a RAMSAR
protected wetland) and reduce the security of supply to irrigation areas downstream. Inter-decadal climate variability is
predicted to have a very signi®cant in¯uence on catchment hydrologic behaviour. A further 20% reduction in ¯ows from
the long-term historical mean is possible, should we move into an extended period of below average rainfall years, such
as occurred in eastern Australia between 1890 and 1948. Because current consumptive water use is largely adapted to
the wetter conditions of post 1949, a return to prolonged dry periods would cause signi®cant environmental stress given
the agricultural and domestic water developments that have been instituted.
Crown Copyright # 2002 Published by Elsevier Science Ltd. All rights reserved.
Keywords: salinity management, water availability, afforestation, integrated assessment.
Introduction
The natural resource base of Australia has been
placed under considerable pressure since European
settlement, 210 years ago. Large tracts of forest
and woodland have been cleared for cropping and
grazing, rivers have been impounded to supply
* Corresponding author. Email: [email protected]. This
work was undertaken while the ®rst author was working at the
Bureau of Rural Sciences, Canberra.
0301±4797/02/$ ± see front matter
water for downstream irrigation and urban use,
and nutrient and sediment loads have increased as
a result of erosion of upland catchments. In recent
years, State and Commonwealth governments have
worked together to institute national policies, aimed
at ameliorating the worst of this environmental
degradation. Many of these policies have identi®ed
a role for the re-establishment of trees within the
landscape. Incentives to encourage greater tree
replanting are currently being evaluated, and
include, in addition to the obvious timber production value, carbon trading, biodiversity and salinity
management schemes.
Crown Copyright # 2002 Published by Elsevier Science Ltd. All rights reserved.
370
N. Herron et al.
In 1997, Commonwealth and state governments
committed themselves to a tripling of plantation
forests by 2020 (Plantation Vision 2020 Implementation Committee, 1997). Although the 2020 policy
was primarily designed to protect remaining areas
of native forest and determine opportunities for
future commercial use, it is also expected to contribute towards biodiversity, salinity management
and carbon sequestration objectives.
Australia has also argued for the use of increases
in vegetation biomass as an allowed mechanism to
meet CO2 emission targets (1990 levels plus 8%) set
by the Kyoto Protocol (Australian Greenhouse
Of®ce, 2000). The vegetation will sequester carbon,
thereby offsetting emissions. Efforts are currently
underway in Australia to develop trading mechanisms to make tree planting economically viable in
sub-commercial areas.
Most recently, natural resource management
policy has been directed towards the management
of dryland salinity. The area affected by dryland
salinisation in the Murray-Darling Basin (MDB),
Australia's most productive agricultural region,
is estimated to rise from about 300 000 hectares
(1996 estimate) to as much as 9 million hectares
(Murray±Darling Basin Commission, 1999), with
related increases in stream salinities and salt loads
(Jolly et al., 2001). In response to this threat,
the Murray±Darling Basin Commission1 (MDBC),
the NSW and South Australian Governments
and the Federal Government have released salinity
strategies for their areas of governance (MDBC,
2000; Department of Land and Water Conservation,
2000; Primary Industries and Resources, South
Australia, 2000a,b). In Victoria, 21 regional salinity
plans have been implemented since the release of
Salt Action: Joint Action in 1988 (Department
of Natural Resources and Environment, 1988).
Tree planting is one of the major responses proposed
within these strategies.
While the re-introduction of trees into the landscape will address many of the environmental
problems that their removal caused, some
negative impacts are also anticipated. These include
economic losses arising from the loss of agricultural
production, possible social impacts (e.g. rural
decline) and reductions in stream¯ow volumes,
which could place further stresses upon water
allocations within catchments. There is suf®cient
1
The MDBC is an autonomous organisation charged with managing the River Murray and the Menindee Lakes system of the
lower Darling River, and advising the Ministerial Council on
matters related to the use of the water, land and other
environmental resources of the MDB.
scienti®c evidence to indicate that a change in
vegetation cover from grasses (or crops) to trees
leads to a reduction in mean annual runoff (Bosch
and Hewlett, 1982; Vertessy, 1999; Zhang et al.,
2001). In a country, where the allocation of
water resources in many catchments is already
over-committed or at capacity, the bene®ts arising
from tree re-planting must be evaluated against
any dis-bene®ts, particularly those arising from
a reduced water supply.
In this paper, we investigate the impact of
a number of tree planting scenarios on stream¯ow
generation in the Macquarie River catchment in
New South Wales, Australia. We also model the
probable impacts of global warming on water availability in this catchment, as climate change is likely
to compound the drying effects of tree establishment in this area, and must be considered in any
long term catchment management planning process. The impact of these ¯ow reductions is assessed
in terms of their impact upon environmental ¯ows
to a RAMSAR listed waterbird breeding area and
to irrigation users in the Macquarie River catchment in New South Wales, Australia.
The Macquarie River catchment
The Macquarie-Bogan catchment covers an area
of about 75 000 km2. It extends from the Great
Australian Divide (east of Sydney) to its junction
with the Barwon River, some 560 km to the northwest (Figure 1). Mean annual rainfall varies from
around 1000 mm in the headwaters to less than
400 mm at the end of the catchment.
Virtually all the Macquarie River ¯ow is generated in the headwater catchments upstream of
Narromine, and is referred to here as the contributing area. Below Narromine, there is a net loss to
stream¯ow due to abstractions for irrigation, evaporation and losses to groundwater. Burrendong
Dam, located upstream of Wellington, is the main
storage in the catchment supplying irrigation
demands downstream to Oxley, as well as supplementing ¯ows to the Macquarie Marshes.
The Macquarie Marshes, located in the lower
reaches of the catchment (Figure 1), are a large
and diverse system of wetlands. They have particular signi®cance as a refuge and breeding area for
waterbirds, and the Macquarie Marshes Nature
Reserve is listed under the Ramsar Convention of
Wetlands of International Importance.
Water allocations are classed as either high
security or general security. High security water is
Climate change on water allocation in NSW, Australia
371
Macquarie River
Bogan River
Figure 1. The Macquarie-Bogan catchment. InsetÐThe Murray-Darling Basin (light grey) and the Macquarie catchment
(dark grey).
a ®xed allocation amount guaranteed in all but the
lowest ¯ow years. Town water supply is a high
security water allocation. General security water is
allocated on the basis of water availability and
most irrigation water is of this type. Every irrigator
is licensed for a ®xed volume of water, but the
proportion of their entitlement that they actually
receive in any year is calculated once dead storage
and high security water allocations have been
deducted from the dam storage volume for that
year. As such, irrigators are more vulnerable to
reductions in catchment runoff than recipients of
high security water, and they often receive less than
100% of their licensed allocation in a water year.
Under the Water Management Plan for the
Macquarie Marshes 1996 (Department of Land
and Water Conservation and National Parks and
Wildlife Service, 1996), 50 GL of high security water
and 75 GL of general security water have been
allocated to the Marshes to ensure their ecological
sustainability. These allocations supplement ¯ows
from tributaries downstream of Burrendong Dam
and dam spills during periods of high runoff. The
Marshes are very sensitive to changes in ¯ow
regime; they have shrunk by more than 40% since
the construction of Burrendong Dam in 1969 and
the regulation of river ¯ows for irrigation
(Kingsford and Thomas, 1995).
Beef cattle, sheep, wool, wheat and cotton are the
major contributors to the agricultural economy.
Wheat dominates the dryland cropping sector; cotton production comprises the majority of revenue
from irrigated summer cropping, and accounts for
approximately 60% of consumptive water use in the
372
N. Herron et al.
Macquarie (Foreman et al., 1998). The area planted
to cotton more than tripled between 1985 and 1995,
and has continued to expand since.
Modelling framework
A modelling system linking a climate scenario generator for Australia with the rainfall-runoff and
stream¯ow management models for the Macquarie
catchment, currently used by the river manager,
has been developed to carry out a risk assessment of
climate change on water resources (Page and Jones,
2001). To assess the added impacts of tree planting,
a tree growth model which had been run for New
South Wales to produce a state-wide forest capability map (ABARE and BRS, 2001) was used to determine the areas suitable for commercial forestry
within the Macquarie catchment, and to guide the
tree replanting scenarios.
runoff for each subcatchment in the Macquarie
is well calibrated with actual stream¯ow data from
gauged stream segments (DLWC, 1995b). The total
contribution to stream¯ow from ungauged stream
sections is estimated at a downstream calibration point and apportioned to the ungauged sections
according to contributing area and the rainfallrunoff pattern of adjacent gauged catchments.
The Sacramento model requires daily rainfall
and potential or A-Class pan evaporation data.
Monthly evaporation coef®cients are speci®ed for
each IQQM sub-catchment to convert point potential evaporation data contained in the input data ®le
to areal potential evaporation. In the Macquarie
catchment, evaporation coef®cients between 07 and
08 have been used for current conditions (DLWC,
1995b). We change these coef®cients to mimic the
effect of changing tree cover for the scenarios
modelled.
The climate model
The stream¯ow routing model
The Integrated Quantity±Quality Model (IQQM) is
a hydrologic modelling tool developed by the New
South Wales Department of Land and Water
Conversation (DLWC) (1995a) for planning and
evaluating water resource management policies.
The model, incorporating the Sacramento rainfallrunoff sub-model, is currently applied to rivers in
NSW to investigate and resolve water-sharing
issues between competing groups, including environmental requirements. Thus it is well known to
NSW water resource managers, and its use here
increases the trustworthiness of the results of the
present study in their eyes.
IQQM operates at a daily time step and can be
used to simulate river system ¯ows for periods up to
hundreds of years. The key component of the model
is the quantity module, which routes water down
a river system subject to tributary in¯ows, losses to
irrigation and other extractions. Water allocation
rules are built into the model and are catchment
speci®c. IQQM also uses the Sacramento rainfallrunoff model to generate daily stream¯ows in each
of the tributary subcatchments.
The rainfall-runoff model
The Sacramento model (Burnash et al., 1984) is a
lumped parameter rainfall-runoff model. Modelled
To model the impact of global warming induced
climate changes on stream¯ow, new rainfall and
potential evaporation ®les were generated for
input into Sacramento model by coupling the
Australian climate scenario generator, OzClim
(CSIRO, 1996) to IQQM (Page and Jones, 2001).
This linking of a climate forecasting model with
a water resource management tool represents a
new and powerful development in water resource
management. OzClim contains ten model patterns that can be used to explore a comprehensive range of climate scenarios, and is the ®rst
model used for down-scaling potential evaporation sequences.
Precipitation and potential evaporation were
generated from eight global circulation model
(GCM) simulations of the enhanced greenhouse
effect. These eight models were evaluated for their
ability in simulating climate in the Australian
region by the Commonwealth Scienti®c and
Industrial Research Organisation (CSIRO, 2001).
Three are reported in this project:
Max-Planck ECHAM4/OPYC3 1860-2099 simulation forced by the IS92a emission scenario
after 1990 (DKRZ Model User Support Group,
1992; Oberhuber, 1992);
CSIRO DARLAM 125 km 1960±2100 simulation,
IS92a emissions from 1990 (McGregor and
Katzfey, 1997); and
Hadley Centre HADCM3 1861±2100 simulation
1% CO2 p.a. from 1990 (Johns et al., 1997).
Climate change on water allocation in NSW, Australia
All models simulate historical CO2 before 1990.
The Max Planck GCM output simulates the wettest
regional climate change for the Macquarie catchment, while the Hadley Centre GCM simulates the
driest (Jones et al., 2001). A thirdÐthe DARLAM
regional climate modelÐwas also included to represent a mid-range climate projection.
Climate patterns for each GCM were calculated
by regressing local change against annual average
global warming for the whole run to produce
a measure of local change per degree of global
warming. This is done by linearly regressing local
monthly seasonal mean rainfall (or potential evaporation) against global average temperature and
taking the slope of the relationship as the estimated
local response to global warming (e.g. Hennessy
et al., 1998). A standardised pattern of regional
climate change is produced that can be re-scaled by
new values of global warming, derived from simple
climate models, to generate a range of climate
change scenarios for regional impact analysis
(IPCC-TGCIA, 1999). Using this method, OzClim
produces monthly values of change for regional
rainfall and evaporation for different levels of global
Figure 2.
373
warming based on the regional patterns of a given
GCM. These values are used to alter the historical
rainfall and potential evaporation data input
®les providing climate change scenarios for
input into the Sacramento Model (Jones et al.,
2001). Improvements in both GCMs and scaling
techniques have produced a more robust range of
projections for seasonal changes in rainfall and
evaporation than were available for an earlier
study of the Macquarie catchment produced by
Whetton et al. (1998). The regional patterns of
change which tend towards rainfall increases in
summer-autumn period and towards decreases
in the winter-spring are consistent throughout
southern Australia in most of the climate models
(CSIRO, 2001).
The tree growth model
Tree planting scenarios were constructed from
a forest capability map of the Macquarie catchment
(Figure 2), generated using a spatial version of
the Physiological Principles in Predicting Growth
Forest capability map of the Macquarie catchment, produced using the 3-PG model.
374
N. Herron et al.
(3-PG) model (Landsberg and Waring, 1997). 3PGSPATIAL has been modi®ed to work in a GIS
framework for assessing forest growth potential
over varying spatial scales (Tickle et al., 2000).
Gross primary production is calculated from climate, site factors and initial conditions and a set
of parameters characterising the performance of
the trees to be grown. This model had previously
been run for New South Wales to produce a statewide forest capability map (ABARE and BRS, 2001)
and these data were used simply to determine the
areas suitable for commercial forestry within the
Macquarie catchment, and to guide the tree replanting scenarios. Because 3-PG had been used for
this earlier government policy work, its use here
increased the acceptability of the current project to
water resource managers.
Figure 2 shows forest capability in terms of
biomass production potential for a generic hardwood timber. Commercially viable production
potential (12 m3/ha/yr) is associated with the higher
rainfall areas in the southeast of the catchment.
Yields become increasingly marginal towards the
northwest. Tree planting in areas of lower production potential might be pursued for salinity
management, carbon sequestration or biodiversity
reasons should markets develop for these products
or subsidies be made available.
Scenarios and forecasts
The tree planting scenarios
In the work described here, we choose three scenarios that re¯ect high, medium and low levels of tree
planting, including both commercially viable and
sub-commercial plantings.
Scenario 1Ðhigh-level adoptionÐassumes that all
land that is currently classed as commercially
capable will be planted to trees by 2030. In the
headwater areas around Oberon, Bathurst and
Orange, this means relatively high proportions of
the sub-catchments will be forested. There are low
to no increases in tree cover in sub-catchments
further downstream. Overall, this scenario corresponds to a further 10% of the contributing area
planted to trees.
Scenario 2Ðlow-level adoptionÐassumes that
only 20% of the commercially viable land is
planted. Again plantings are focussed in the upper
catchment. This represents only a 2% increase in
the area planted to trees.
Scenario 3Ðmoderate level adoptionÐincludes
the 20% of commercially viable land in Scenario 2,
plus 10% of the more marginal 8±12 m3/ha/y
biomass production class being planted. The
inclusion of trees in the more marginal production
areas represents tree planting for salinity management, carbon sequestration targets and/or
biodiversity reasons. The 10% level of adoption in
these marginal areas is consistent with observations over the last 7 years in the mid-Macquarie of
the willingness of farmers to shift from cropping/
grazing into tree production (Alan Nicholson,
Department of Land and Water Conservation,
pers. comm.). Under this scenario, 5% of the
contributing area is planted to trees.
Vegetation-runoff relationships
The impact of tree planting on runoff was calculated using the empirical relationship of Zhang
et al. (2001) which relates mean annual evapotranspiration (ET) to mean annual precipitation
(P) and the proportion of forest and grass cover
within a catchment using a world-wide, 295 catchment data set.
ET ˆ P
1 ‡ w…Ez =P†
1 ‡ w…Ez =P†‡ P=Ez
…1†
where w is the plant available water coef®cient and
Ez is the potential evaporation parameter. For
forested areas, Zhang et al. (2001) estimate w to be
2 and Ez to be 1410; for grassed areas, w is 05 and
Ez is 1100. The relationship assumes that at an
annual time-step there is no change in soil water
storage. Recharge is also assumed to be negligible.
The Zhang curves (Figure 3) predict that for the
same mean annual precipitation, more runoff is
generated from a grassland than a forest. The
difference in runoff increases with increasing
mean annual precipitation, such that increasing
tree cover in a high rainfall area will cause a bigger
loss in runoff than planting in a low rainfall area.
There is a signi®cant difference between the two
curves, as shown by the 95% con®dence bands in
Figure 3.
The Zhang curves were incorporated into a GIS
to estimate mean annual evapotranspiration for
sub-catchments in the Macquarie catchment,
using the approach of Vertessy and Bessard
(1999), but excluding their adjustment for elevation.
Areas not covered by trees were assumed to be
Climate change on water allocation in NSW, Australia
became less reliable with decreasing annual rainfall.
Since the IQQM-Sacramento model is calibrated for
the Macquarie catchment under current conditions
(DLWC, 1995b) and this calibration needs to be
retained, the IQQM stream¯ow volumes under
current condition were scaled by the ratio of the
Zhang runoff estimate for each tree planting scenario to the Zhang runoff estimate under current
conditions, to obtain predicted IQQM stream¯ow,
as follows:
1800
Mean Annual Streamflow (mm)
1600
1400
Grass
1200
1000
800
600
QIQQM …predicted†
QZhang (predicted)
QIQQM …current†
ˆ
QZhang …current†
Trees
400
200
0
0
500
1000
1500
2000
2500
Mean Annual Precipitation (mm)
Figure 3. Stream¯ow as predicted from Zhang et al.
(2001), with 95% con®dence limits shown for each curve.
These curves describe the empirical relationship between
stream¯ow and mean annual precipitation for forested and
grassed catchments. It is assumed that on an annual timestep, there is no change in soil water storage, such that the
catchment water balance can be described by Q ˆ PÿET.
grassland. For the current condition, the proportion
of each sub-catchment area under trees was determined from the current land use map. The additional area of each sub-catchment under trees for
each of the three scenarios was based upon the
forest capability for that sub-catchment as determined by the 3-PG model. Mean ET for each grid
cell within a sub-catchment could then be calculated
for each scenario using Eq (1): for forested cells, 1ÿf
is zero and the second term on the RHS of the
equation drops out, while for grassed cells, f is 0
and the ®rst term drops out.
Given the assumptions of no deep recharge and
negligible soil water storage on an annual basis,
mean annual runoff could be calculated for each
grid cell from
Q ˆ P ÿ ET
375
…2†
A total mean annual runoff for each subcatchment was determined for current conditions,
and for each of the 3 scenarios, by summing the
runoff from all grid cells within each subcatchment. When compared to their corresponding
calibrated IQQM mean annual stream¯ow volumes,
runoff estimates for current conditions based on the
Zhang formula were mostly over-estimated, and
…3†
The Zhang approach is based on long-term mean
annual catchment responses and is, therefore, not
appropriate for analysis of intra-annual behaviour.
Analysis of the IQQM ¯ow data at daily, monthly
and annual time-steps indicates signi®cant differences in the ¯ow distributions for tree and grass
cover at the daily and, to a lesser extent, monthly
time-steps. These differences are attributed to the
in¯uence of antecedent soil moisture on runoff
generation over relatively short time-scales. At the
annual time-step, ¯ow distributions were not
found to differ signi®cantly between forested and
grassed catchments. Therefore, despite the use of a
daily time-step model (IQQM) to quantify changes
in stream¯ow with changes in vegetation cover, only
annual stream¯ow totals and inter-annual comparisons are reported in the results.
The monthly evaporation coef®cients within each
sub-catchment systems ®le in the Sacramento
model were changed until the ¯ow generated by
the model yielded runoff volumes approximating
the predicted stream¯ows for each scenario in that
sub-catchment. IQQM was run with these new
tributary in¯ows for the upper catchment to route
the water through Burrendong Dam and through
the lower part of the catchment.
Climate scenarios
Global warming was simulated by modifying the
input climate ®les to the Sacramento model.
Global temperatures were assumed to rise by
05 C by 2030, the median estimate from the
Inter-governmental Panel on Climate Change
(IPCC, 1996) and the low estimate from IPCC
(2001). Three climate scenarios were produced by
scaling changes per degree of global warming from
376
N. Herron et al.
the Max-Planck, Hadley Centre and DARLAM
GCMs described above by 05 C.
To evaluate the in¯uence of episodic shifts in
climate regime on stream¯ow in the Macquarie
catchment, the 107 year stream¯ow record was
divided into two periodsÐa relatively dry period between 1890 and 1948 and a wetter regime between
1949 and 1996, roughly re¯ecting the drought
dominated regime (DDR) and the ¯ood dominated
regime (FDR) as de®ned by Warner (1987).
predicted to decrease by between 3% (40 GL) and
30% (390 GL), depending on the planting scenario
and the GCM used.
The results change signi®cantly when the
drought and ¯ood dominated periods (DDR and
FDR) are considered separately (Figure 5). For
conditions resembling the FDR, ¯ows are likely to
be greater than the long-term average in all but the
N o C limate
C hange
M ax Planck
D AR LAM
H adle y
C e ntre
10
Results
UpstreamÐdam in¯ows
Figure 4 shows the estimated reductions in in¯ows
to Burrendong Dam for each of the tree planting
scenarios and climate forecasts. Under current
conditions, the mean annual in¯ow to the dam is
approximately 1080 GL/year. The ®rst column of
points represents the impact of the tree planting
scenarios with no global warming. Tree planting
leads to reductions in mean annual in¯ows of 17%
(182 GL) for Scenario 1, 4% (45 GL) for Scenario 2
and 7% (75 GL) for Scenario 3. Changes in in¯ows to
Burrendong Dam arising from global warming with
no tree planting (^) range from ‡1 and ÿ16% of
current ¯ow, depending on the GCM used. When
both tree planting and global warming are combined, ¯ows in the upper Macquarie River are
% C h ange in Streamflow
0
–10
–20
–30
No tree replanting
A ll c om m erc ially capable land
–40
20% c om m erc ially capable land
20% c om m erc ially capable + 10%
m arginal
–50
Figure 4. % Change from current long term annual
average in¯ow to Burrendong Dam for tree planting and
global warming scenarios.
Drought Dominated Period
%Change from Current Longterm Average
NoClimate
Change
Max Planck
DARLAM
Flood Dominated Period
Hadley
Centre
No Climate
Change
30
30
20
20
10
10
0
0
-10
-10
-20
-20
-30
-30
-40
-40
-50
-50
-60
-60
Max Planck
DARLAM
No tree replanting
20% commercially capable land
All commercially capable land
20% commercially capable + 10% marginal
Hadley
Centre
Figure 5. % Change from current long term annual average in¯ow to Burrendong Dam when ¯ow record is separated into
¯ood and drought dominated regimes.
Climate change on water allocation in NSW, Australia
largest tree-planting scenario modelled (i.e.
Scenario 1). That is, the increase in ¯ows from
increased precipitation more than outweighs
the reduced runoff from the trees and global warming. With no tree planting and the wettest GCM
projection, ¯ows will increase by as much as 29%
over the current long-term average.
If DDR conditions were to develop again, reductions in stream¯ow are likely to be considerably
greater than suggested from the 107-year record in
Figure 4. In the absence of global warming and tree
planting and using 1890 to 1948 rainfall records,
average ¯ows were 22% lower than the longer 107year average. When global warming and tree plantings are included in the predictions, reductions in
¯ow of as much as 46% are estimated.
DownstreamÐirrigation water
and the middle GCM projection with tree planting
Scenario 3 (mid-range forecast). Allocation reliability varies signi®cantly with scenario.
The most pessimistic forecast for irrigators is
that the frequency with which they can expect
their full allocation will drop from the current 43%
of the time to about 21% of the time. Under these
drier conditions, irrigators are predicted to have
an allocation of less than 42% of their current
total entitlement 50% of the time. On average,
allocations will tend to be 27% less than under
current conditions under this pessimistic forecast,
with the greatest differences in allocation reliability
occurring in the 30±60% probability range.
The most optimistic outcome, the wettest GCM
and no tree planting, indicates a very minor reduction in the frequency of full allocations, with the
overall distribution not differing signi®cantly from
current allocation reliability. The mid-range outcome (middle GCM and tree planting Scenario 3)
indicates that irrigators can expect their full allocation 32% of the time (compared to 43% of the time at
present), and greater than 65% of their allocation
50% of the time (490% at present).
When DDR and FDR periods are separated out
(Figure 7), a return to an extended below-average
precipitation period would compromise irrigation
enterprises further. For the most optimistic outcome, an 18% reduction from the long-term mean
annual allocation is predicted; for the most pessimistic outcome the reduction from the current longterm average is close to 30%. Under a wetter regime,
a 30% increase on the current long-term average
allocation is estimated for the most optimistic
scenario, and a 13% reduction for the most pessimistic outcome.
100
100
90
90
80
80
70
70
% of Allocation
% of Allocation
These reductions in stream¯ow into Burrendong
Dam have signi®cant effects on downstream water
users, particularly those that rely on general security water. Except for very low ¯ow years when the
allocation of general security water is less than or
equal to 10%, town water supply will receive its full
allocation. However, the frequency of low ¯ow years
is expected to increase, such that town water supply
may be at risk 5% more often.
Irrigators in the catchment are expected to
experience more signi®cant impacts. Figure 6
shows allocation reliability for the wettest GCM
projection with no tree planting (the most optimistic
forecast), the driest GCM projection with tree
planting scenario 1 (the most pessimistic forecast)
60
50
40
30
Current
(i)
(ii)
(iii)
20
10
377
60
50
40
30
Longterm - Current
(i) fdr
(i) ddr
(ii) fdr
(ii) ddr
20
10
0
0
0
10
20
30
40
50
60
70
80
90
100
% Time Flow Exceeds
Figure 6. Allocation reliability for (i) the wettest GCM
prediction with no tree planting, (ii) the driest GCM
prediction with tree planting Scenario 1 and (iii) the middle
GCM prediction with tree planting Scenario 3. Current
allocation reliability is also shown.
0
10
20
30
40
50
60
70
80
90
100
% Time Allocation Exceeds
Figure 7. Allocation reliability when ¯ow record is
separated into ¯ood and drought dominated regimes for
(i) the wettest GCM prediction with no tree planting and
(ii) the driest GCM prediction with tree planting Scenario 1.
Current allocation reliability is also shown.
378
N. Herron et al.
DownstreamÐMacquarie Marshes
Large ¯ows of water in the Macquarie are the key to
the extensive breeding of ibis, herons, egrets and
spoonbills in the Marshes (Kingsford and Johnson,
1998; Johnson, 1998). The quantity of water determines the extent of the habitat created for breeding;
breeding populations are proportional to the area
¯ooded. For these colonially nesting water birds, a
minimum annual ¯ow of about 200 GL is required
before bird breeding will occur, although greater
reliability of breeding comes with annual ¯ows of
4250 GL. For large-scale breeding (450 000 pairs),
annual ¯ows exceeding 350 GL are needed
(Johnson, 1998). The high security and general
security water allocated to the Marshes under the
Macquarie Marshes Water Management Plan is still
well below the quantity required for bird breeding.
10000000
Flow to Macquarie Marshes (ML)
Current
(i)
(ii)
Large scale bird breeding: >350 GL/y
(iii)
1000000
Small to moderate bird breeding
100000
No bird breeding
10000
0
10
20
30
40
50
60
70
80
90
100
% Time Flow Exceeds
Figure 8. Impact of ¯ow reductions on bird breeding
events in the Macquarie Marshes for (i) the wettest GCM
prediction with no tree planting, (ii) the driest GCM
prediction with tree planting Scenario 1 and (iii) the middle
GCM prediction with tree planting Scenario 3. Current
allocation reliability is also shown.
Drought-dominated
Flood-dominated period
Trees + Global warming
Global warming
Trees
–50
–40
–30
–20
–10
0
Current
10
20
Unregulated ¯ows from tributaries downstream
of Burrendong Dam are needed to bring total ¯ows
up to threshold volumes for bird breeding.
The impacts of ¯ow reductions to the Macquarie
Marshes are illustrated in Figure 8. The probability
of receiving 200 GL decreases from 084 to 066 and
08 for the driest and mid-range predictions,
respectively. For large-scale bird breeding events,
reductions of a similar magnitude occur, with the
probability of ¯ows 4350 GL decreasing from 054
to 032 and 044, respectively. Overall there is
a 18% reduction in mean annual ¯ows to the
Marshes for the driest scenario and an 12% reduction for the mid-range predictions, in spite of the
Marshes receiving some of their allocation as high
security water.
The results presented above are summarised in
Figure 9. Reductions of between 4 and 17% of the
current long-term average in¯ows to Burrendong
Dam were simulated for the three tree planting
scenarios modelled here. Since the trees are planted
preferentially in the highest forest capability land,
the effect of planting is `magni®ed' in the river
¯ows. Thus, for example, a 10% increase in trees in
the upper catchment will result in approximately
17% less river ¯ow.
Reductions in stream¯ow arising from global
warming, including the driest outcome, were
found to be comparable to the reductions arising
from tree planting Scenario 1. If we ignore secondary effects of higher temperatures and CO2 levels
on forest productivity, the impacts of both
changed land use and global warming are additive.
Stream¯ow is predicted to be reduced by 30% of
the current long term mean for Scenario 1, using
the Hadley Centre climate projections. Jones et al.
(2001) estimate changes in mean annual ¯ow
based on the entire range of climate change in
2030 taken from IPCC (1996) of 04±08 C as ranging from ‡1 to ÿ21%. The recent IPCC projections
of 05±13 C in 2030 (IPCC, 2001) increase this
range to ‡1 to ÿ30%, although the most likely
range is 0 to ÿ15% (Jones and Page, 2001). While
there is considerable uncertainty about the exact
magnitude of the stream¯ow changes likely to
arise from global warming and extensive tree planting, the combined effects will certainly reduce
stream¯ow.
30
% Change in streamflow from current conditions
Figure 9. Summary of results, showing relative signi®cance of tree planting, global warming and climate
variability scenarios on ¯ow reductions in the Macquarie
catchment.
Discussion
With only general security allocations, the irrigators
are particularly sensitive to long term stream¯ow
Climate change on water allocation in NSW, Australia
reductions in the Macquarie River. A reduction in
mean annual stream¯ow translates to a reduction
in the fraction of their entitlement received by
irrigators. This, in turn, translates to a reduction
in the sustainable crop area (de®ned as the area
harvested) and/or a change in crop mix. We have
not modelled the economic implications of these
reduced allocations because we do not have information on the likely changes in crop mix. However,
we estimate that, in the most extreme scenario,
irrigators will receive their full entitlements as
much as 50% less often than at present.
The high security water allocation means that
the Marshes are less vulnerable than irrigators to
long term ¯ow reductions. Nevertheless, the ecological functioning of the Marshes will be threatened should there be a long-term reduction in
stream¯ow. Impacts on the frequency of bird breeding events may be even larger than indicated by
Figure 8 because the duration and magnitude of
¯ows over shorter periods within the year are more
critical determinants of bird breeding events than
the total annual ¯ow (Department of Land and
Water Conservation and National Parks and
Wildlife Sevice, 1996). It is likely that bird breeding
is determined by the ¯ow during a 5±7 month period
surrounding the median breeding period in
October.
Water availability in the Macquarie River is
more vulnerable to shifts in the rainfall regime
over periods lasting several decades than it is to
either tree planting or global warming by 2030. By
2070, however, Jones et al. (2001) show that the
impacts of global warming on water availability
could outweigh the in¯uence of decadal shifts in
rainfall regime. Decadal variability can decrease
stream¯ow by as much as 20% or increase it by as
much as 25% from the long-term historical average.
Given that the water supply infrastructure has
been developed under the relatively favourable
rainfall of an FDR, a return to below average
rainfall would signi®cantly stress the system based
on its current operating rules. Thus, all but the
most optimistic water resources managers need to
plan for a period of greater competition for more
limited water resources over the next 30 years.
Of the three changes modelled here, one (global
warming) will almost certainly occur (IPCC, 2001),
one (inter-decadal climate shifts) is a stochastic
event whose occurrence cannot be predicted and
the third (tree planting) is a societal choice and
may or may not occur. The decision whether to
permit tree planting depends on the balance
between costs and bene®ts to both private and
public consumers. A parallel study (Heaney et al.,
379
2000; Heaney and Beare, 2000) predicts that
widespread forestation in the headwater areas
would provide only modest, if any, long term
reductions in stream salinities, yet impose a large
net cost from lower returns from irrigated agriculture and forest based land uses. The potential
bene®ts from carbon sequestration, local salinity
control and improved biodiversity were not included in these calculations.
This paper illustrates some of the complexities
associated with implementing government policies.
The promotion of salinity management, forestry
supply and improved biodiversity through tree
planting will be at the expense of reduced river
¯ows. If the objectives of the environmental ¯ow
policies of the Australian Commonwealth and State
governments are also to be met, this implies less
water for irrigation and other consumptive uses.
The analysis in this paper needs to be supplemented
with an assessment of dryland agriculture, carbon
sequestration, biodiversity improvements and
opportunities for enhancing water use ef®ciencies
in irrigated areas to gain an improved understanding of the costs and bene®ts from tree planting in
this catchment.
Acknowledgments
The authors wish to thank Cher Page at CSIRO
Atmospheric Research for running the combined global
warming and tree planting scenarios; Rob O'Neill from
the Department of Land and Water Conservation in
NSW who guided and advised us in running IQQM and
supplied much needed information about water allocation
procedures in the Macquarie catchment; Adrian Bugg
from the Bureau of Rural Sciences who provided the forest
capability assessment for the Macquarie catchment; Peter
Hairsine from CSIRO Land and Water and Tom Aldred
from the Natural Resource Management Policy Division
in the Department of Agriculture, Fisheries and Forestry,
Australia, for their incisive reviews of this paper; and the
Rural Industry Research and Development Corporation
who provided funding for the development of the OzClimIQQM modelling system.
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