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The effects of large-scale afforestation and climate change on water allocation in the Macquarie River catchment, NSW, Australia
Journal of Environmental Management (2002) 65, 369±381 doi:10.1006/jema.2002.0562, available online at http://www.idealibrary.com on
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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.
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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
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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
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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.
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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.
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(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 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
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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 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 P ÿ ET
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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
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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
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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
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H adle y C e ntre
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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
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No tree replanting A ll c om m erc ially capable land
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20% c om m erc ially capable land 20% c om m erc ially capable + 10% m arginal
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Figure 4. % Change from current long term annual average in¯ow to Burrendong Dam for tree planting and global warming scenarios.
Drought Dominated Period
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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.
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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)
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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.
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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.
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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)
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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
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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.,
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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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L. G., Callander, B. A., Harris, N., Kattenberg, A. and Maskell, K. (eds), Climate Change 1995: The Science of Climate Change, Contribution of Working Group I to the second assessment report of the IPCC, pp. 9±49. Cambridge University Press, Cambridge. Intergovernmental Panel on Climate Change (2001). Summary for Policymakers. In Climate Change 2001: The Scienti®c Basis (J. T. Houghton, Y. Ding, D. J. Griggs, M. Noguer, P. van der Linden and D. Xiaosu, eds.) pp. 1±20. Cambridge. Cambridge University Press (http://www.unep.ch/ipcc/pub/spm22-01.pdf) IPCC-TGCIA (1999). Guidelines on the Use of Scenario Data for Climate Impact and Adaptation Assessment. Version 1. Prepared by Carter, T. R., Hulme, M. and Lal, M., 69 pp. IPCC Task Group on Scenarios for Climate Impact Assessment. Johns, T. C., Carnell, R. E., Crossley, J. F., Gregory, J. M., Mitchell, J. F. B., Senior, C. A., Tett, S. F. B. and Wood, R. A. (1997). The second Hadley Centre coupled ocean-atmosphere GCM: model description, spinup and validation, Climate Dynamics 13, 103±134. Johnson, W. (1998). Consequences for the Macquarie Marshes. In Climate Change Scenarios and Managing the Scarce Water Resources of the Macquarie River (Hassall and Associates, ed.), pp. 61±75. Report prepared for the Australian Greenhouse Of®ce, Canberra. Jolly, I. D., Williamson, D R., Gilfedder, M., Walker, G. R., Robinson, G., Jones, H., Zhang, L., Dowling, T. I., Dyce, P., Nathan, R. J., Nandakumar, N., Clarke, R. and McNeill, V. (2001). Historical stream salinity trends and catchment salt balances in the MurrayDarling Basin, Australia, Marine and Freshwater Research 52, 53±63. Jones, R. N., Page, C. M., Herron, N. F., Davis, R. J., O'Neill, R., Bennett, D. and McClintock, D. (2001). Climate change and the risk to long-term water supply in the Murray-Darling Basin, AWA 19th ConventionÐA Water Odyssey, Canberra, 2±4 April, 2001. Australian Water Australia, Paper 198. Kingsford, R. T. and Johnson, W. (1998). Impact of water diversions on colonially-nesting waterbirds in the Macquarie Marshes of arid Australia, Colonial Waterbirds 21, 159±170. Kingsford, R. T. and Thomas, R. F. (1995). The Macquarie Marshes in arid Australia and their waterbirds: a 50 year history of decline. Environmental Management 19, 867±878. Landsberg, J. J. and Waring, R. H. (1997). A generalised model of forest productivity using simpli®ed concepts of radiation-use ef®ciency, carbon balance, and partitioning. Forest Ecology and Management 95, 209±228. McGregor, J. L. and Katzfey, J. J. (1997). Climate modelling for the Australian region using DARLAM, Proceedings of the International Workshop on Regional Modeling of the `General Monsoon System' in Asia, Beijing, China (TEACOM Report, 4), pp. 13±18. START Regional Centre for Temperate East Asia. Murray-Darling Basin Commission (2000). Draft Basin Salinity Management Strategy 2001±2015, 36 pp. MDB Ministerial Council, September 2000, Canberra. Murray-Darling Basin Commission (1999). The Salinity Audit of the Murray-Darling BasinÐA 100 Year Perspective, 39 pp. MDBC, Canberra. Oberhuber, J. M. (1992). The OPYC Ocean General Circulation Model, Report No. 7, Deutsches
Climate change on water allocation in NSW, Australia Klimarechenzentrum, Hamburg. (http://www.dkrz.de/ forschung/reports/ReportNo.7.ps) Page, C. M. and Jones, R. N. (2001). OzClim: The development of a climate scenario generator for Australia. In MODSIM 2001: International Congress on Modelling and Simulation: Proceedings, 10±13 December 2001, Canberra, ACT (F. Ghassemi, H. Whetton, R. Little and M. Littleboy, eds.) pp. 667± 671. Canberra: Modelling and Simulation Society of Australia and New Zealand. Plantation Vision 2020 Implementation Committee (1997). Plantations for Australia: The 2020 Vision, Department of Primary Industries and Energy, Canberra ACT. (http://www.affa.gov.au/docs/forestry/ plantations/vision.html) Primary Industries and Resources South Australia (2000a). Draft State Dryland Salinity Strategy, 43 pp. Prepared by the Primary Industries and Resources South Australia for the Soil Conservation Council of South Australia, October 2000. Primary Industries and Resources South Australia (2000b). Draft State South Australian River Murray Salinity Strategy, 27 pp. Prepared by the Primary Industries and Resources South Australia for the Soil Conservation Council of South Australia, October 2000. Tickle, P. K., Coops, N. C., Hafner, S. D. and The Bago Science Team (2000). Assessing forest productivity at local scales across a native eucalypt forest using a
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process model, 3PG-SPATIAL, Forest Ecology and Management 5366, 1±17. Vertessy, R. A. (1999). The impacts of forestry on stream¯ows: A review, In Forest Management for Water Quality and Quantity (J. Croke and P. Lane, eds), pp. 93±109. Research Centre for Catchment Hydrology, Report 99/6, Canberra. Vertessy, R. A. and Bessard, Y. (1999). Anticipating the negative hydrologic effects of plantation expansion: Results from a GIS-based analysis on the Murrumbidgee Basin. In Forest Management for Water Quality and Quantity (J. Croke and P. Lane, eds), pp. 69±73. Cooperative Research Centre for Catchment Hydrology, Report 99/6, Canberra. Warner, R. F. (1987). The impacts of alternating ¯ood-and drought-dominated regimes on channel morphology at Penrith, New South Wales, Australia, International Association of Hydrological Sciences Publication 68, 327±338. Whetton, P., Jones, R. and Pittock, B. (1998). Climate Change Methodology and Results. In Climate Change Scenarios and Managing the Scarce Water Resources of the Macquarie River (Hassall and Associates, eds), pp. 18±26. Report prepared for the Australian Greenhouse Of®ce, Canberra. Zhang, L., Dawes, W.R. and Walker, G.R. (2001). The response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resources Research 37, 701±708.
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.
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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
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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
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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.
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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.
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(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 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 QZhang current
Trees 400 200 0
0
500
1000
1500
2000
2500
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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 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 P ÿ ET
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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
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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
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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
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Figure 4. % Change from current long term annual average in¯ow to Burrendong Dam for tree planting and global warming scenarios.
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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.
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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)
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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.
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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.
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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)
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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
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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
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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.,
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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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