Water Availability in the Warrego A report to the Australian Government from the CSIRO Murray-Darling Basin Sustainable Yields Project
September 2007 Murray-Darling Basin Sustainable Yields Project acknowledgments
The Murray-Darling Basin Sustainable Yields project is being undertaken by CSIRO under the Australian Government's Raising National Water Standards Program, administered by the National Water Commission. Important aspects of the work were undertaken by Sinclair Knight Merz; Resource, Environmental Management Pty Ltd; Department of Water and Energy (New South Wales); Department of Natural Resources and Water (Queensland); Murray-Darling Basin Commission; Department of Water Land and Biodiversity Conservation (South Australia); Bureau of Rural Sciences; Salient Solutions Australia Pty Ltd; eWater Cooperative Research Centre; University of Melbourne; Webb, McKeown and Associates Pty Ltd; and several individual sub-contractors.
Murray-Darling Basin Sustainable Yields Project disclaimers
Derived from or contains data and/or software provided by the Organisations. The Organisations give no warranty in relation to the data and/or software they provided (including accuracy, reliability, completeness, currency or suitability) and accept no liability (including without limitation, liability in negligence) for any loss, damage or costs (including consequential damage) relating to any use or reliance on that data or software including any material derived from that data and software. Data must not be used for direct marketing or be used in breach of the privacy laws. Organisations include: Department of Water Land and Biodiversity Conservation (South Australia), Department of Sustainability and Environment (Victoria), Department of Water and Energy (New South Wales), Department of Natural Resources and Water (Queensland), Murray-Darling Basin Commission.
CSIRO advises that the information contained in this publication comprises general statements based on scientific research. The reader is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, CSIRO (including its employees and consultants) excludes all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole) and any information or material contained in it. Data is assumed to be correct as received from the Organisations.
Citation
CSIRO (2007). Water availability in the Warrego. A report to the Australian Government from the CSIRO Murray-Darling Basin Sustainable Yields Project. CSIRO, Australia. 89pp.
Publication Details
Published by CSIRO © 2007 all rights reserved. This work is copyright. Apart from any use as permitted under the Copyright Act 1968, no part may be reproduced by any process without prior written permission from CSIRO.
ISSN 1835-095X
Photos on cover courtesy of the Queensland Department of Natural Resources and Water Director’s Foreword
Following the November 2006 Summit on the Southern Murray-Darling Basin, the Prime Minister and Murray-Darling Basin state Premiers commissioned CSIRO to report on sustainable yields of surface and groundwater systems within the Murray-Darling Basin. This report from the CSIRO Murray-Darling Basin Sustainable Yields Project details the assessments for one of 18 regions that encompass the Basin.
The CSIRO Murray-Darling Basin Sustainable Yields Project is providing critical information on current and likely future water availability. This information will help governments, industry and communities consider the environmental, social and economic aspects of the sustainable use and management of the precious water assets of the Murray-Darling Basin.
The project is the first rigorous attempt worldwide to estimate the impacts of catchment development, changing groundwater extraction, climate variability and anticipated climate change, on water resources at a basin-scale, explicitly considering the connectivity of surface and groundwater systems. To do this, we are undertaking the most comprehensive hydrologic modelling ever attempted for the entire Basin, using rainfall-runoff models, groundwater recharge models, river system models and groundwater models, and considering all upstream-downstream and surface- subsurface connections. We are complementing this work with detailed surface water accounting across the Basin – never before has surface water accounting been done in such detail in Australia, over such a large area, and integrating so many different data sources.
To deliver on the project CSIRO is drawing on the scientific leadership and technical expertise of national and state government agencies in Queensland, New South Wales, Victoria, the Australian Capital Territory and South Australia, as well as the Murray-Darling Basin Commission and Australia’s leading industry consultants. The project is dependent on the cooperative participation of over 15 government and private sector organisations contributing over 100 individuals. The project has established a comprehensive but efficient process of internal and external quality assurance on all the work performed and all the results delivered, including advice from senior academic, industry and government experts.
The project is led by the Water for a Healthy Country Flagship, a CSIRO-led research initiative which was set up to deliver the science required for sustainable management of water resources in Australia. The Flagship goal is to achieve a tenfold increase in the social, economic and environmental benefits from water by 2025. By building the capacity and capability required to deliver on this ambitious goal, the Flagship is ideally positioned to accept the challenge presented by this complex integrative project.
CSIRO has given the Murray-Darling Basin Sustainable Yields Project its highest priority. It is in that context that I am very pleased and proud to commend this report to the Australian Government.
Dr Tom Hatton
Director, Water for a Healthy Country
National Research Flagships
CSIRO
Executive Summary
The CSIRO Murray-Darling Sustainable Yields Project is providing governments with a robust, basin-wide estimate of water availability on an individual catchment and aquifer basis, taking into account climate change and other risks. This report describes the assessments undertaken for the Warrego region. While key aspects of the assessment and modelling methods used in the project are contained in this report, fuller methodological descriptions will be provided in a series of project technical reports.
The Warrego region of Queensland and New South Wales is based around the Warrego River and includes the towns of Charleville (pop. ~3500) and Cunnamulla (pop. ~1500) and several nationally important wetlands.
The region reported on here ends at Fords Bridge 87 km upstream of the junction with the Darling River. As defined the y region represents seven percent of the Murray-Darling Basin’s area but has less than one percent of the Basin’s total water resource. Rainfall and runoff are highly variable between years and streamflow mostly occurs as large infrequent floods. The region contributes less than one percent of the inflows to the Darling River. Water diversions are low – there are no major dams and only about 300 hectares of irrigation.
Rainfall and runoff for 1997–2006 are not significantly different to the long-term historical averages. There are no commercial forestry plantations in the region and relatively few farm dams. This situation is not predicted to change and thus such developments do not present a risk to future water availability.
Executive Summar Water use from shallow aquifers is very low, has little impact on streamflow and is unlikely to increase because these aquifers are generally difficult to access and their water quality is only suitable for stock and domestic use. Greater use is made of water from the aquifers of the Great Artesian Basin but these aquifers are not connected to the shallow aquifers or to the river and have very little surface recharge.
The best estimate 2030 climate scenario indicates a six percent reduction in river inflows leading to a seven percent reduction in total end-of-system flows. However, because water use is low, even assuming maximum permissible use the average impact on diversions is only a three percent reduction. This reduction is mainly associated with un- supplemented water access in Queensland downstream of Wyandra. There is however, a wide uncertainty range around the best estimate 2030 climate predictions with changes in river inflows ranging from a 44 percent increase to a 28 percent decrease.
The Water Resource Plan that relates to the Queensland portion of the Warrego requires that at least 89 percent of the average flow into New South Wales is maintained. This implies that a maximum of 11 percent of the average ’without development’ flow at the border may be diverted in Queensland for use. Given current surface water entitlements in Queensland this requirement is being met. Changes in inflows under future climate would alter the percentage diverted for use. Under the ‘best’ estimate (median) 2030 climate current Queensland entitlements would represent 12 percent of the ‘without development’ flow at the border. The range for the 2030 climate is from seven percent (wet extreme) to 15 percent (dry extreme). The predicted impact of 2030 climate change on the frequency with which flow ceases at the major end-of-system points is considerably smaller than the impact to-date due to water resource development.
The frequency of beneficial small floods reaching the 37,000 ha Yantabulla Swamp has not been affected by water resource development nor has the frequency of important high flows for the Warrego River Waterholes. The best estimate 2030 climate would reduce the frequency of these beneficial flows by ten percent and nine percent respectively and would be likely to have adverse effects on waterbird breeding and fish populations. The wet and dry 2030 climate extremes would have large environmental consequences.
Meteorological and hydrological data are sparse for the Warrego, rainfall and streamflow are highly variable and natural water losses are high. For these reasons the hydrologic modelling of the Warrego is less robust that for less variable and data-rich parts of the Basin. The most uncertain results are for low flows in the lower reaches of the river. This may limit the ability to assess the environmental impacts of development in the lower reaches of the river. The modelling is however, adequate for assessing the potential relative impacts of climate change on the moderate to high flows that are important for most diversions and for wetland inundation. The largest sources of uncertainty in the assessments of future water availability are the climate changes projections (global warming level) and the predicted implications of global warming on rainfall.
Water availability in the Warrego September 2007 © CSIRO 2007 Table of Contents
1 Introduction ...... 1 1.1 Background ...... 1 1.2 Project methodological framework ...... 3 1.3 Climate and development scenarios ...... 4 1.4 Rainfall-runoff modelling ...... 5 1.5 River system modelling...... 6 1.6 Monthly water accounts ...... 8 1.7 Groundwater modelling...... 10 1.8 Environmental assessment...... 11 1.9 References...... 12 2 Overview of the region...... 13 2.1 The region ...... 13 2.2 Environmental description...... 15 2.3 Surface water resources ...... 16 2.4 Groundwater ...... 18 2.5 References...... 20 3 Rainfall-runoff modelling...... 21 3.1 Summary...... 21 3.2 Modelling approach...... 22 3.3 Modelling results ...... 24 3.4 Discussion of key findings...... 30 3.5 References...... 30 4 River system modelling ...... 31 4.1 Summary...... 31 4.2 Modelling approach...... 33 4.3 Modelling results ...... 37 4.4 Discussion of key findings...... 47 5 Uncertainty in surface water modelling results ...... 49 5.1 Summary...... 49 5.2 Approach...... 50 5.3 Results ...... 54 5.4 Discussion of key findings...... 61 5.5 References...... 62 6 Groundwater assessment ...... 64 6.1 Summary...... 64 6.2 Groundwater management units – hydrogeology and connectivity ...... 64 6.3 References...... 66 7 Environment...... 67 7.1 Summary...... 67 7.2 Approach...... 68 7.3 Results ...... 72 7.4 Discussion of key findings...... 73 7.5 References...... 73 Appendix A Rainfall-runoff results for selected subcatchments...... 75 Appendix B River water modelling reach mass balances ...... 77 Appendix C River system model uncertainty assessment by reach ...... 84 Tables
Table 1-1. River system models in the Murray-Darling Basin...... 7 Table 2-1. Summary of land use within the Warrego region...... 14 Table 2-2. Summary of surface water sharing arrangements in the Queensland portion of the Warrego...... 17 Table 2-3. Categorisation of GMUs, including annual extraction, entitlement and recharge details in New South Wales ...... 19 Table 2-4. Groundwater sharing arrangements within the New South Wales portion of the Warrego region ...... 20 Table 3-1. Summary results from the 45 Scenario C simulations (numbers show percentage change in mean annual rainfall and runoff for Scenario C relative to Scenario A) ...... 27 Table 3-2. Water balance over the entire region by scenario ...... 29 Table 4-1. Storages in the river model...... 35 Table 4-2.Modelled water use configuration...... 35 Table 4-3. Model water management ...... 35 Table 4-4. Model setup information ...... 36 Table 4-5. Rainfall, evaporation and flow factors for model robustness test ...... 37 Table 4-6. River system model average annual water balance under scenarios O, A and C ...... 38 Table 4-7. Details of weir behaviour ...... 39 Table 4-8. Change in annual irrigation diversions in each calibration reach relative to Scenario A ...... 40 Table 4-9. Cease-to-flow percentiles for scenarios P, A and C ...... 42 Table 4-10. Annual water availability under Scenario C relative to Scenario A...... 43 Table 4-11. Relative level of development under scenarios A and C ...... 44 Table 4-12. Indicators of level of use under Scenarios A and C...... 44 Table 4-13. Relative level of available water not diverted for use under Scenarios A and C ...... 44 Table 4-14. Change in cross border flows under scenarios A and C ...... 44 Table 4-15. Average reliability indicators under Scenarios A and C...... 47 Table 4-16. Average difference between allocated and diverted medium security usage...... 47 Table 5-1. Possible framework for considering implications of assessed uncertainties ...... 51 Table 5-2. Comparison of water accounting reaches with reach codes used in the river model (QDNR, 2004)...... 52 Table 5-3. Some characteristics of the gauging network of the Warrego region (76,615 km2) compared with the entire Murray- Darling Basin (1,062,443 km2)...... 55 Table 5-4. Details of stream flow rating uncertainty, calibration and validation periods, number of years between 1895 and 2006 (112 years) with annual rainfall less than the driest and more than the wettest year in the calibration period, respectively, and prior assessment of the models performance (source: QDNR, 2004, with exception of the climate range information)...... 57 Table 5-5. Regional water balance modelled and estimated on the basis of water accounting ...... 59 Table 6-1. Categorisation of groundwater management units including annual extraction, entitlement and recharge details in New South Wales...... 66 Table 7-1. Definition of environmental indicators...... 72 Table 7-2. Values of environmental indicators for scenarios P and A, and percentage changes from Scenario A for the remaining scenarios...... 72
Figures
Figure 1-1. Region by region map of the Murray-Darling Basin ...... 2 Figure 1-2. Methodological framework for the Murray-Darling Basin Sustainable Yields Project...... 3 Figure 1-3. Timeline of groundwater use and resultant impact on river...... 8 Figure 2-1. 1895–2006 annual and monthly rainfall averaged over the Warrego region (based on the Bureau of Meteorology’s SILO database). The curve on the annual graph shows the low frequency variability...... 13 Figure 2-2. Map of dominant land uses of the region with insert showing the location of the Warrego within the Murray-Darling Basin ...... 15 Figure 2-3. History of surface water diversions in the Queensland portion of the region ...... 18 Figure 3-1. Map of the modelling subcatchments and calibration catchments ...... 23 Figure 3-2. Modelled and observed monthly runoff and daily flow duration curve for the calibration catchments...... 24 Figure 3-3. Spatial distribution of mean annual rainfall and modelled runoff averaged over 1895–2006...... 25 Figure 3-4. 1895–2006 annual rainfall and modelled runoff series averaged over the region. The curve shows the low frequency variability...... 25 Figure 3-5. Mean monthly rainfall and modelled runoff (averaged over 1895–2006 for the region)...... 25 Figure 3-6. Percentage change in mean annual runoff from the 45 Scenario C simulations (15 GCMs and three global warming scenarios) relative to Scenario A runoff...... 26 Figure 3-7. Mean annual rainfall and modelled runoff for Scenarios A, Cdry, Cmid and Cwet ...... 28 Figure 3-8. Mean monthly rainfall and modelled runoff for scenarios A and C averaged over 1895–2006 across the region ...... 29 Figure 3-9. Daily flow duration curves for Scenarios A and C averaged over the region ...... 30 Figure 4-1. Map showing IQQM subcatchments (with and without inflows), major storages, and model nodes and links...... 34 Figure 4-2 Allan Tannock Weir behaviour over the maximum days between spills under (a) Scenario A, (b) Scenario Cwet, (c) Scenario Cmid, and (d) Scenario Cdry ...... 39 Figure 4-3. Total average diversions under scenarios A and C from upstream to downstream...... 40 Figure 4-4. (a) Total water use under Scenario A; (b) difference between total water use under scenarios A and Cwet; (c) difference between total water use under scenarios A and Cmid; (d) difference between total use water use under scenarios A and Cdry ...... 41 Figure 4-5. Daily flow duration curves under scenarios A, C and P for lower end of flows for each end of system flow gauge - (a) Fords Bridge; (b) Cuttaburra Ck and (c) Norooma & Widgeegoara Ck ...... 41 Figure 4-6. Transect of total river flow under scenarios P, A and C ...... 42 Figure 4-7. Scenario A water availability...... 43 Figure 4-8. Water availability under Scenario C relative to Scenario A ...... 43 Figure 4-9. Comparison of diverted and non-diverted shares of water under Scenarios P, A and C ...... 45 Figure 4-10. Reliability of diversions under general security licences - by water product for scenarios (a) A; (b) Cdry; (c) Cmid; and (d) Cwet(a) ...... 46 Figure 4-11. Reliability of unsupplemented access water for (a) QLD and (b) NSW irrigators for each scenario...... 46 Figure 5-1. Map showing the subcatchments used in modelling, with the reaches for which river water accounts were developed (‘accounting reach’) and tributary catchments with gauged inflows (‘contributing catchment’). Shaded areas (‘floodplain and wetlands’) were classified as subject to periodic inundation; small irrigation areas are located inside and just outside subcatchment 4232021. Black dots and lines are nodes and links in the river model respectively...... 53 Figure 5-2. Map showing the rainfall, stream flow and evaporation observation network along with the subcatchments used in modelling...... 56 Figure 5-3. Patterns along the length of the river (expressed as the cumulative contributing catchment area) of indicators of the fraction of inflows/gains, outflows/losses and the total of water balance components that is (a) gauged or (b) could be attributed in the water accounts...... 58 Figure 5-4. Changes in the model efficiency (the relative performance of the river model in explaining observed streamflow patterns) along the length of the river (expressed as the cumulative contributing catchment area)...... 60 Figure 5-5. Pattern along the river (expressed as cumulative river catchment area) of the ratio of the projected change over the river model uncertainty for the different scenarios modelled for (a) monthly and (b) annual flows...... 61 Figure 6-1. Map of groundwater management units...... 65 Figure 7-1. Location map of environmental assets...... 69 Figure 7-2. Satellite image of Yantabulla Swamp (Cuttaburra Basin) ...... 70 Figure 7-3. Satellite image of Warrego River Waterholes Charleville-Wyandra ...... 71 1 Introduction
1.1 Background
Australia is the driest inhabited continent on Earth, and in many parts of the country – including the Murray-Darling Basin – water resources water for rural and urban use are comparatively scarce. Into the future, climate change and other risks (including catchment development) are likely to exacerbate this situation and hence improved water resource data, understanding and planning and management are of high priority for Australian communities, industries and governments.
On 7 November, 2006, the Prime Minister of Australia met with the First Ministers of Victoria, New South Wales, South 1 Introduction Australia and Queensland at a water summit focussed primarily on the future of the Murray-Darling Basin (MDB). As an outcome of the Summit on the Southern Murray-Darling Basin, a joint communiqué called for “CSIRO to report progressively by the end of 2007 on sustainable yields of surface and groundwater systems within the MDB, including an examination of assumptions about sustainable yield in light of changes in climate and other issues.”
The subsequent Terms of Reference for what became the Murray-Darling Basin Sustainable Yields Project specifically asked CSIRO to
x estimate current and likely future water availability in each catchment and aquifer in the MDB considering: o climate change and other risks; o surface-groundwater interactions; and x compare the estimated current and future water availability to that required to meet the current levels of extractive use.
The MDB Sustainable Yields Project is reporting progressively on each of 18 contiguous regions that comprise the entire MDB. These regions are primarily the drainage basins of the Murray and the Darling rivers – Australia’s longest inland rivers, and their tributaries. The Darling flows southwards from southern Queensland into New South Wales west of the Great Dividing Range into the Murray River in southern New South Wales. At the South Australian border the Murray turns south-westerly eventually winding to the mouth below the Lower Lakes and the Coorong. The regions for which the project assessments are being undertaken and reported are the Paroo, Warrego, Condamine-Balonne, Moonie, Border Rivers, Gwydir, Namoi, Macquarie-Castlereagh, Barwon-Darling, Lachlan, Murrumbidgee, Murray, Ovens, Goulburn- Broken, Campaspe, Loddon-Avoca, Wimmera and East Mount Lofty Ranges (see Figure 1-1).
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 1 1 Introduction 1 Introduction
Figure 1-1. Region by region map of the Murray-Darling Basin
The MDB Sustainable Yields Project will be the most comprehensive Basin-wide assessment of water availability undertaken to-date. For the first time:
x daily rainfall-runoff modelling has been undertaken at high spatial resolution for a range of climate change and development scenarios in a consistent manner for the entire Basin, x the hydrologic subcatchments required for detailed modelling have been precisely defined across the entire Basin, x the hydrologic implications for water users and the environment by 2030 of the latest Intergovernmental Panel on Climate Change climate projections, the likely increases in farm dams and commercial forestry plantations and the expected increases in groundwater extraction have been assessed in detail (using all existing river system and groundwater models as well new models developed within the project), x river system modelling has included full consideration of the downstream implications of upstream changes between multiple models and between different States, and quantification of the volumes of surface- groundwater exchange, and
2 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 x detailed analyses of monthly water balances for the last ten to twenty years have been undertaken using available streamflow and diversion data together with additional modelling including estimates of wetland evapotranspiration and irrigation water use based on remote sensing imagery (to provide an independent cross- check on the performance of river system models).
The successful completion of these outcomes, among many others, relies heavily on a focussed collaborative and team- oriented approach between CSIRO, State government natural resource management agencies, the Murray-Darling Basin Commission, the Bureau of Rural Sciences, and leading consulting firms – each bringing their specialist knowledge and expertise on the Murray-Darling Basin to the project.
1.2 Project methodological framework
The methodological framework for the project is shown in Figure 1-2. This also indicates in which chapters of this report 1 Introduction the different aspects of the project assessments and results are presented.
Figure 1-2. Methodological framework for the Murray-Darling Basin Sustainable Yields Project
The first steps in the sequence of Figure 1-2 are definition of the reporting regions and their composite sub-catchments, and definition of the climate and development scenarios to be assessed (including generation of the time series of climate data that describe these scenarios). The second steps are rainfall-runoff modelling and rainfall-recharge modelling for which the inputs are the climate data for the different scenarios. Catchment development scenarios for farm dams and commercial forestry plantations are modifiers of the modelled runoff time series.
Next, the runoff implications propagated are through river system models and the recharge implications propagated through groundwater models – for the major groundwater resources – or considered in simpler assessments for minor groundwater resources. The connectivity of surface and groundwater is assessed and the actual volumes of surface- groundwater exchange under current and likely future groundwater extraction are quantified. Uncertainty levels of the river system models are then assessed based on monthly water accounting.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 3 The results of scenario outputs from the river system model are used to make limited hydrological assessments of ecological relevance to key environmental assets. Finally, the implications of the scenarios for water availability and water use under current water sharing arrangements are assessed, synthesised and reported.
1.3 Climate and development scenarios
The project is assessing the following four scenarios of historical and future climate and current and future development, all of which are defined by daily time series of climate variables based on different scalings of the 1895–2006 climate:
1. historical climate and current development
2. recent climate and current development
3. future climate and current development
4. future climate and future development
These scenarios are described in some detail below with full details provided in Chiew et al. (2007a).
1.3.1 Historical climate and current development 1 Introduction 1 Introduction
Historical climate and current development – referred to as “Scenario A” – is the baseline against which other climate and development scenarios are compared.
The historical daily rainfall time series data that are used are taken from the Australian Bureau of Meteorology’s SILO database which provides data for a 0.05o x 0.05o (5 km x 5 km) grid across the continent (Jeffrey et al., 2001; and www.nrm.qld.gov.au/silo). Areal potential evapotranspiration (PET) data are calculated from the SILO climate surface using Morton’s wet environment evapotranspiration algorithms (www.bom.gov.au/climate/averages; and Chiew and Leahy, 2003).
Current development for the rainfall-runoff modelling is the average of 1975 to 2005 land use and small farm dam conditions. Current development for the river system modelling is the dams, weirs and license entitlements in the latest State agency models, updated to 2005 levels of large farm dams. Current development for groundwater models is 2004– 2005 levels of license entitlements. Surface–groundwater exchanges in the river and groundwater models represent an equilibrium condition for the above levels of surface and groundwater development.
1.3.2 Recent climate and current development
Recent climate and current development – referred to as “Scenario B” – is used for assessing future water availability should the climate in the future prove to be similar to that of the last ten years. Climate data for 1997–2006 is used to generate stochastic replicates of 112-year daily climate sequences. The replicate which best produces a mean annual runoff values closest to the mean annual runoff for the period 1997–2006 is selected to define Scenario B.
1.3.3 Future climate and current development
Future climate and current development – referred to as “Scenario C” – is used to assess the range of likely climate conditions around the year 2030. Three global warming scenarios are analysed in 15 global climate models (GCM) to provide a spectrum of 45 climate variants for the 2030. The scenario variants are derived from the latest modelling for the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC, 2007).
Two types of uncertainties in climate change projections are therefore taken into account: uncertainty in global warming mainly due to projections of greenhouse gas emissions and global climate sensitivity to the projections; and uncertainty in GCM modelling of climate over the MDB. Results from each GCM are analysed separately to estimate the change per degree global warming in rainfall and other climate variables required to calculate PET. The change per degree global warming is then scaled by a high, medium and low global warming by 2030 relative to 1990 to obtain the changes in the climate variables for the high, medium and low global warming scenarios. The Scenario C considerations are therefore
4 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 for 112-year rainfall and PET series for a greenhouse enhanced climate around 2030 relative to 1990 and not for a forecast climate at 2030.
The method used to obtain the Scenario C climate series also takes into account different changes in each of the four seasons as well as changes in the daily rainfall distribution. The consideration of changes in the daily rainfall distribution is important because many GCMs indicate that extreme rainfall in an enhanced greenhouse climate is likely to be more intense, even in some regions where projections indicate a decrease in mean seasonal or annual rainfall. As the high rainfall events generate large runoff, the use of traditional methods that assumes the entire rainfall distribution to change in the same way will lead to an underestimation of mean annual runoff in regions where there is an increase, and an overestimation of the decrease in mean annual runoff where there is a decrease (Chiew, 2006).
All 45 Scenario C variants are used in rainfall-runoff modelling; however, three variants – a ‘dry’, a ‘mid’ (best estimate – median) and a ‘wet’ variant – are presented in more detail and are used in river and groundwater modelling. 1 Introduction 1.3.4 Future climate and future development
Future climate and future development – referred to as ‘Scenario D’ – considers the ‘dry, ‘mid’ and ‘wet’ climate variants from Scenario C together with likely expansions in farm dams and commercial forestry plantations and the changes in groundwater extractions anticipated under existing groundwater plans.
Farm dams here refer only to dams with their own water supply catchment, not those that store water diverted from a nearby river, as the latter require licenses and are usually already included within existing river system models. A 2030 farm dam development scenario for the MDB has been developed by considering current distribution and policy controls and trends in farm dam expansion. The increase in farm dams in each subcatchment is estimated using simple regression models that consider current farm dam distribution, trends in farm dam (Agrecon, 2005) or population growth (Australian Bureau of Statistics, 2004; and Victoria DSE, 2004) and current policy controls (Queensland Water Act, 2000; New South Wales Water Management Act, 2000; Victoria Water Act, 1989; South Australia Natural Resources Management Act, 2004). Data on the current extent of farm dams is taken from the 2007 Geosciences Australia “Man- made Hydrology” GIS coverage and from the 2006 VicMap 1:25,000 topographic GIS coverage. The former covers the eastern region of Queensland MDB and the north-eastern and southern regions of the New South Wales MDB. The latter data covers the entire Victorian MDB.
A 2030 scenario for commercial forestry plantations for the MDB has been developed using regional projections from the Bureau of Rural Sciences which takes into account trends, policies and industry feedbacks. The increase in commercial forestry plantations is then distributed to areas adjacent to existing plantations (which are not natural forest land use) with the highest biomass productivity estimated from the PROMOD model (Battaglia and Sands, 1997).
Growth in groundwater extractions has been considered in the context of existing groundwater planning and sharing arrangements and in consultation with State agencies. For groundwater the following issues have been considered:
x growth in groundwater extraction rates up to full allocation, x improvements in water use efficiency due to on-farm changes and lining of channels, and x water buy-backs.
1.4 Rainfall-runoff modelling
The adopted approach provides a consistent way of modelling historical runoff across the MDB and assessing the potential impacts of climate change and development on future runoff.
The lumped conceptual daily rainfall-runoff model, SIMHYD, with a Muskingum routing method (Chiew et al., 2002; Tan et al., 2005), is used to estimate daily runoff at 0.05o grids (~ 5 km x 5 km) across the entire MDB for the four scenarios.
The model is calibrated against 1975–2006 streamflow data from about 200 unregulated catchments of 50–2000 km2 across the MDB (calibration catchments). Although unregulated, streamflow in these catchments for the calibration period may reflect low levels of water diversion and the effects of historical land use change. The calibration period is a compromise between a shorter period that would better represent current development and a longer period that would better account for climatic variability. In the model calibration, the six parameters in SIMHYD are optimised to maximise
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 5 an objective function that incorporates the Nash-Sutcliffe efficiency (Nash and Sutcliffe, 1970) of monthly runoff and daily flow duration curve, together with a constraint to ensure that the total modelled runoff over the calibration period is within five percent of the total recorded runoff. The resulting optimised model parameters are therefore identical for all cells within a calibration catchment.
The runoff for non-calibration catchments is modelled using optimised parameter values from the geographically closest calibration catchment, provided there is a calibration point with 250 km. Once again the parameter values for each grid cell within a non-calibration catchment are identical. For catchments more than 250 km from a calibration point the parameter values used are taken from the whole-of-Basin modelling run (identical parameters across the entire Basin) which best matched observed flows at calibration points. The places these ‘default’ values are used are all areas of very low runoff.
As the parameter values come from calibration against streamflow from 50–2000 km2 catchments, the runoff defined here is different, and can be much higher, than streamflow recorded over very large catchments where there can be significant transmission losses (particularly in the western and north-western parts of the MDB). Almost all of the catchments available for model calibration are in the higher runoff areas in the eastern and southern parts of the MDB. Runoff estimates are therefore generally good in the eastern and southern parts of the MDB and are comparatively poor elsewhere.
The same model parameter values are used for all the simulations. The Scenario C simulations therefore do not take into 1 Introduction 1 Introduction account the effect on forest water use of global warming and enhanced atmospheric CO2 concentrations. There are compensating positive and negative global warming impacts on forest water use, and it is difficult to estimate the net effect because of the complex climate-biosphere-atmosphere interactions and feedbacks. This is discussed in Marcar et al. (2006) and in Chiew et al. (2007b).
Bushfire frequency is also likely to increase in Scenario C. In local areas where bushfires occur, runoff would reduce significantly as forests regrow. However, the impact on runoff averaged over an entire reporting region is unlikely to be significant (see Chiew et al., 2007b).
For Scenario D (future climate and future development) the impact of additional farm dams on runoff is modelled using the CHEAT model (Nathan et al., 2005) which takes into account rainfall, evaporation, demands, inflows and spills. The impact of additional plantations on runoff is modelled using the FCFC model (Forest Cover Flow Change; Brown et al. (2006) and www.toolkit.net.au/fcfc).
The modelling approach and results (model calibration, cross-verification, regionalisation and climate change impact simulation with the SIMHYD and Sacramento rainfall-runoff models, and Scenario D modelling) across the MDB are described in detail in Chiew et al. (2007b).
1.5 River system modelling
The project is using river system models that encapsulate descriptions of current infrastructure, water demands, and water management and sharing rules to assess the implications of the changes in inflows described above on the reliability of water supply to users. Given the time constraints of the project and the need to link the assessments to State water planning processes, it is necessary to use the river system models currently used by State agencies, the Murray- Darling Basin Commission and Snowy Hydro Ltd. The main models in use are IQQM, REALM, MSM-Bigmod, WaterCress and a model of the Snowy Mountains Hydro-electric Scheme.
The modelled runoff series from SIMHYD are not used directly as subcatchment inflows in these river system models because this would violate the calibrations of the river system models already undertaken by State agencies to different runoff series. Instead, the relative differences between the daily flow duration curves of Scenario A and Scenarios B, C and D respectively are used to modify the existing inflows series in the river system models. The Scenarios B, C and D inflow series for the river system modelling therefore have the same daily sequences – but different amounts – as the Scenario A river system modelling series.
6 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Table 1-1. River system models in the Murray-Darling Basin
Model Description Rivers modelled
IQQM Integrated Quantity-Quality Model: hydrologic modelling tool Paroo, Warrego, Condamine-Balonne (Upper, Mid, developed by the NSW Government for use in planning and Lower), Nebine, Moonie, Border Rivers, Gwydir, Peel, evaluating water resource management policies. Namoi, Castlereagh, Macquarie, Marthaguy, Bogan, Lachlan, Murrumbidgee, Barwon-Darling
REALM Resource Allocation Model: water supply system simulation Ovens (Upper, Lower), Goulburn, Wimmera, Avoca, tool package for modelling water supply systems configured ACT water supply. as a network of nodes and carriers representing reservoirs, demand centres, waterways, pipes, etc.
MSM-BigMod Murray Simulation Model and the daily forecasting model Murray BigMod: purpose-built by the Murray-Darling Basin
Commission to manage the Murray River system. MSM is a 1 Introduction monthly model that includes the complex Murray accounting rules. The outputs from MSM form the inputs to BigMod, which is the daily routing engine that simulates the movement of water.
WaterCress Water Community Resource Evaluation and Simulation Eastern Mt Lofty Ranges (six separate catchments) System: PC-based water management platform incorporating generic and specific hydrological models and functionalities for use in assessing water resources and designing and evaluating water management systems.
SMHS Snowy Mountains Hydro-electric Scheme model: purpose Snowy Mountains Hydro-electric Scheme built by Snowy Hydro Ltd to guide the planning and operation of the SMHS.
A few areas of the MDB have not previously been modelled and hence some new IQQM or REALM models have been implemented. In some cases ancillary models are used to estimate aspects of water demands of use in the river system model. An example is the PRIDE model used to estimate irrigation for Victorian REALM models.
River systems that do not receive inflows or transfers from upstream or adjacent river systems are modelled independently. This is the case for most of the river systems in the Basin and for these rivers the modelling steps are:
x model configuration x model warm-up to set initial values for all storages in the model, including public and private dams and tanks, river reaches and soil moisture in irrigation areas x using scenario climate and inflow time series, run the river model for all climate and development scenarios x where relevant, extract initial estimates of surface-groundwater exchanges and provide this to the groundwater model x where relevant, use revised estimates of surface-groundwater exchanges from groundwater models and re-run the river model for all scenarios.
For river systems that receive inflows or transfers from upstream or adjacent river systems, model inputs for each scenario were taken from the upstream models. In a few cases several iterations were required between upstream and downstream models because of the complexities of the water management arrangements. An example is the connections between the Murray, Murrumbidgee and Goulburn regions and the Snowy Mountains Hydro-electric Scheme.
1.5.1 Surface-groundwater interactions
The project is explicitly considering and quantifying the water exchanges between rivers and groundwater systems. The approaches used are described below.
The river models used by State agencies have in turn typically been calibrated by State agencies to achieve mass balance within calibration reaches over relatively short time periods. When the models are run for extended periods the relationships derived during calibration are assumed to hold for full the modelling period. In many cases however, the
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 7 calibration period is a period of changing groundwater extraction and a period of changing impact of this extraction on the river system. That is, the calibration period is often one of changing hydrologic relationships, a period where the river and groundwater systems have not fully adjusted to the current level of groundwater development. To provide a consistent equilibrium basis for scenario comparisons it is necessary to determine the equilibrium conditions of surface and groundwater systems considering their interactions and the considerable lag times involved in reaching equilibrium.
Figure 1-3 shows an indicative timeline of groundwater use, impact on river, and how this has typically been treated in river model calibration, and what the actual equilibrium impact on the river would be. By running the groundwater models until a ‘dynamic equilibrium’ is reached, a reasonable estimate of the ultimate impact on the river of current groundwater use is obtained. A similar approach is used to determine the ultimate impact of future groundwater use. 1 Introduction 1 Introduction
Figure 1-3. Timeline of groundwater use and resultant impact on river
For some groundwater management units – particularly fractured rock aquifers – there is significant groundwater extraction but no model available for assessment. In these cases there is the potential for considerable impacts on streamflow. At equilibrium, the volume of water extracted must equal the inflows to the aquifer from diffuse recharge, lateral flows and flows from overlying rivers. The fraction that comes from the overlying rivers is determined using a ‘connectivity factor’ that is estimated from the difference in levels between the groundwater adjacent to the river and the river itself, the conductance between the groundwater pump and the river, and the hydrogeological setting. Given the errors inherent in this method, significant impacts are deemed to be those about 2 GL/yr for a subcatchment, which given typical connectivity factors translates to groundwater extraction rates of around 4 GL/yr for a subcatchment.
1.6 Monthly water accounts
Monthly water accounts provide an independent set of the different water balance components by river reach and by month. The water accounting differs from the river modelling in a number of key aspects:
x The period of accounting extends to 2006 where possible, which is typically more recent than the calibration and evaluation periods of the river models assessed. This means that a comparison can produce new insights about the performance and assumptions in the river model, as for example associated with recent water resources development or the recent drought in parts of the MDB. x The accounting is specifically intended to estimate, as best as possible, historical water balance patterns, and used observed rather than modelled data wherever possible (including recorded diversions, dam releases and other operations). This reduces the uncertainty associated with error propagation and assumptions in the river
8 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 model that were not necessarily intended to reproduce historical patterns (e.g. differences in actual historical and potential future degree of entitlement use). x The accounting uses independent, additional observations and estimates on water balance components not used before such as actual water use estimates derived from remote sensing observations and SIMHYD estimates of local runoff generation. This can help to constrain the water balance with greater certainty.
Despite these advantages, it is emphasised that the water accounting methodology invokes models and indirect estimates of water balance components where direct measurements are not available. Because of this, these water accounts are not an absolute point of truth. Rather, they provide an estimate of the degree to which the river water balance is understood and gauged, and a comparison between river model and water account water balances provides one of several lines of evidence to inform our (inevitably partially subjective) assessment of model uncertainty and its implications for the confidence in our findings. The methods for water accounting are based on those used by Kirby et al. (2006) and Van Dijk et al. (2007) and are described in detail in Kirby et al. (2007). 1 Introduction 1.6.1 Wetland and irrigation water use
An important component of the accounting is estimate of actual water use based on remote sensing observations. Spatial time series of monthly net water use from irrigation areas, rivers and wetlands were estimated using interpolated station observations of rainfall and climate combined with remote sensing observations of surface wetness, greenness and temperature. Net water use of surface water resources was calculated as the difference between monthly rainfall and monthly actual evapotranspiration (AET).
AET estimates are based on a combination of two methods. The first method uses surface temperature remotely sensed by the AVHRR series of satellite instruments for the period 1990-2006 and combines this with spatially interpolated climate variables to estimate AET from the surface energy balance (McVicar and Jupp, 2002). The second method loosely follows the FAO56 ‘crop factor’ approach and scales interpolated potential evaporation (PET) estimates using observations of surface greenness and wetness by the MODIS satellite instrument (Van Dijk et al., 2007). The two methods were constrained using direct on-ground AET measurements at seven study sites and catchment stream flow observations from more than 200 catchments across Australia. Both methods provide AET estimates at 1 km resolution.
The spatial estimates of net water use were aggregated for each reach and separately for all areas classified as either irrigation area or floodplains and wetlands. The following digital data sources were used:
x land use grids for 2000/2001 and 2001/02 from the Bureau of Rural Sciences (adl.brs.gov.au/mapserv/landuse/) x NSW wetlands maps from the NSW Department of Environment and Conservation (NSW DEC) x hydrography maps, including various types of water bodies and periodically inundated areas, from Geoscience Australia (GA maps; Topo250K Series 3) x long-term rainfall and AET grids derived as outlined above x LANDSAT satellite imagery for the years 1998 to 2004.
The reach-by-reach estimates of net water use from irrigation areas and from floodplains and wetlands are subject to the following limitations:
x Partial validation of the estimates suggested an average accuracy in AET estimation within 15 percent, but probably decreasing with the area over which estimates are averaged. Uncertainty in spatial estimates originates from the interpolated climate and rainfall data as well as from the satellite observations and the method applied. x Errors in classification of irrigation and floodplain/wetland areas will have added an unknown uncertainty to the overall estimates, particularly where subcatchment definition was uncertain or wetland and irrigation areas were difficult to discern. x Estimated net water use cannot be assumed to have been derived from surface water in all cases as vegetation may also have access to groundwater use, either directly or through groundwater pumping. x Estimated net water use can be considered as an estimate of water demand that apparently is met over the long-term. Storage processes, both in irrigation storages and wetlands, need to simulated to translate these estimates in monthly (net) losses from the river main stem.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 9 Therefore, the AET and net water use estimates are used internally to conceptual water balance models of wetland and irrigation water use that include a simulated storage as considered appropriate based on ancillary information.
1.6.2 Calculation and attribution of apparent ungauged gains and losses
In a river reach, ungauged gains or losses are the difference between the sum of gauged main stem and tributary inflows, and the sum of main stem and distributary outflows and diversions. This would be equal to measured main stem outflows and water accounting could occur with absolute certainty. The net sum of all gauged gains and losses provides an estimate of ungauged apparent gains and losses. There may be differences between apparent and real gains and losses for the following reasons:
x Apparent ungauged gains and losses will also include any error in discharge data that may originate from errors in stage gauging or from the rating curves associated to convert stage height to discharge. x Ungauged gains and losses can be compensating and so appear smaller than in reality. This is more likely to occur at longer time scales. For this reason water accounting was done on a monthly time scale. x Changes in water storage in the river reach, connected reservoirs, or wetlands, can lead to apparent gains and losses that become more important as the time scale of analysis decreases. A monthly time scale has been chosen to reduce storage change effects, but they can still occur. 1 Introduction 1 Introduction The monthly pattern of apparent ungauged gains and losses for each reach was evaluated in an attempt to attribute them to real components of water gain or loss. The following techniques were used in sequence:
x Analysis of normal (parametric) and ranked (non-parametric) correlation between apparent ungauged gains and losses on one hand, and gauged and estimated water balance components on the other hand. Estimated components included SIMHYD estimates of monthly local inflows and remote sensing-based estimates of wetland and irrigation net water use. x Visual data exploration: assessment of temporal correlations in apparent ungauged gains and losses to assess trends or storage effects, and comparison of apparent ungauged gains and losses and a comparison with time series of estimated water balance components.
Based on the above information, apparent gains and losses were attributed to the most likely process, and an appropriate method was chosen to estimate the ungauged gain or loss using gauged or estimated data. The water accounting model includes the following components:
x A conceptual floodplain and wetland running a water balance model that estimates net gains and losses as a function of remote sensing-based estimates of net water use and main stem discharge observations. x A conceptual irrigation area running a water balance model that estimates (net) total diversions as a function of any recorded diversions, remote sensing-based estimates of irrigated area and net crop water use, and estimates of direct evaporation from storages and channels. x A routing model that allows for the effect of temporary water storage in the river system and its associated water bodies and direct open water evaporation. x A local runoff model that transforms SIMHYD estimates of local runoff to match ungauged gains.
These model components will be described in greater detail in Kirby et al. (2007) and were only used where the data or ancillary information suggested their relevance. Each component has a small number of unconstrained or partially constrained parameters that need to be estimated. A combination of direct estimation as well as step-wise or simultaneous automated optimisation was used, with the goal to attribute the largest possible fraction of apparent ungauged gains and losses. Any large residual losses and gains suggest error in the model or its input data.
1.7 Groundwater modelling
Groundwater assessment, including groundwater recharge modelling, was undertaken to assess the implications of the climate and development scenarios on groundwater management units (GMUs) across the Basin. A range of methods
10 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 were used appropriate to the size and importance of different GMUs. There are over 100 GMUs in the Murray-Darling Basin, and the choice of methods was based on an objective classification of the GMUs as high, medium or low priority.
Rainfall-recharge modelling was undertaken for all GMUs. For dryland areas, daily recharge was assessed using a model that considered plant physiology, water use and soil physics to determine vertical water flow in the unsaturated zone of the soil profile at a single location. This model has been run at multiple locations across the MDB in considering the range of soil types and land uses to determine scaling factors for different soil and land use conditions. These scaling factors have then been used to scale recharge for given changes in rainfall for all GMUs according to local soil types and land uses.
For many of the higher priority GMUs, recharge is largely from irrigation seepage. In New South Wales this recharge has been embedded in the groundwater models as a percentage of the applied water. For irrigation recharge, information has been collated for different crop types, irrigation systems and soil types, and has been used for the scenario modelling.
For high priority GMUs numerical groundwater models are being used. In most cases these already exist but often 1 Introduction require improvement. In some cases new models were developed. Although the groundwater models have seen less effort invested in their calibration than the existing river model, the project has invested considerable effort in model calibration and various cross-checks to increase the level of confidence in their modelling.
For each groundwater model, each scenario is run using river heights as provided from the appropriate river system model. For recent and future climate scenarios, adjusted recharge values are also used, and for future development the 2030 groundwater extractions levels are used. The models are run for two consecutive 111-year periods. The average surface-groundwater flux values for the second 111-year period are passed back to the river models as the equilibrium flux. The model outputs are used to assess indicators of groundwater use and reliability.
For lower priority GMUs no models were available and the assessments were limited to simple estimates of recharge, estimates of current and future extraction, allocation based on State data, and estimates of the current and future impacts of extraction on streamflow where important.
1.8 Environmental assessment
Environmental assessments on a region by region basis consider the environmental assets already identified by State governments or the Australian Government that are listed in the Directory of Important Wetlands in Australia (Environment Australia, 2001) or the updated on-line database of the directory. From this directory, environmental assets are selected for which there exists sufficient publicly available information on hydrological indicators (such as commence- to-fill levels) which relate to ecological responses such as bird breeding events.
Information sources include published research papers and reports, accessible unpublished technical reports, or advice from experts currently conducting research on specific environmental assets. In all cases the source of the information on the hydrological indicators used in each assessment is cited. The selection of the assets for assessment and hydrologic indicators was undertaken in consultation with State governments and the Australian Government through direct discussions and through reviews by the formal internal governance and guidance structures of the project.
The Directory of Important Wetlands in Australia (Environment Australia, 2001) lists over 200 wetlands in the Murray- Darling Basin. Information on hydrological indicators of ecological response adequate for assessing scenario changes only exists for around one tenth of these. More comprehensive environmental assessments are beyond the terms of reference for the project. The Australian Department of Environment and Water Resources has separately commissioned a compilation of all available information on the water requirements of wetlands in the Basin that are listed in the Directory of Important Wetlands in Australia.
For regions where the above selection criteria identify no environmental assets, the river channel itself is considered as an asset and ecologically-relevant hydrologic assessments are reported for the channel. The locations for which these assessments are provided are guided by prior studies. In the Victorian regions for example, detailed environmental flow studies have been undertaken which have identified environmental assets at multiple river locations with associated hydrological indicators. In these cases a reduced set of locations and indicators has been selected in direct consultation with the Victorian Department of Sustainability and Environment. In regions where less information is available,
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 11 hydrological indicators may be limited to those that report on the water sharing targets that are identified in water planning policy or legislation.
Because the environmental assessments are a relatively small component of the project, a minimal set of hydrological indicators are used in assessments. In most cases this minimum set includes change in the average period between events and change in the maximum period between events as defined by the indicator.
A quality assurance process is applied to the results for the indicators obtained from the river system models which includes checking the consistency of the results with other river system model results, comparing the results to other published data and with the asset descriptions, and ensuring that the river system model is providing realistic estimates of the flows required to evaluate the particular indicators.
1.9 References
Agrecon (2005) Agricultural Reconnaissance Technologies Pty Ltd Hillside Farm Dams Investigation. MDBC Project 04/4677DO. Australian Bureau of Statistics (2004) Population projections for Statistical Local Areas 2002 to 2022. Available at: www.abs.gov.au. Battaglia M and Sands P (1997) Modelling site productivity of Eucalyptus globulus in response to climatic and site factors. Australian Journal of Plant Physiology 24, 831–850. Brown AE, Podger PM, Davidson AJ, Dowling TI and Zhang L (2006) A methodology to predict the impact of changes in forest cover on
1 Introduction 1 Introduction flow duration curves. CSIRO Land and Water Science Report 8/06. CSIRO, Canberra. Chiew et al. (2007a) Climate data for hydrologic scenario modelling across the Murray-Darling Basin. A report to the Australian Government from the CSIRO Murray-Darling Basin Sustainable Yields Project. CSIRO, Australia. In prep. Chiew et al. (2007b) Rainfall-runoff modelling across the Murray-Darling Basin. A report to the Australian Government from the CSIRO Murray-Darling Basin Sustainable Yields Project. CSIRO, Australia. In prep. Chiew FHS (2006) An overview of methods for estimating climate change impact on runoff. Paper prepared for the 30th Hydrology and Water Resources Symposium, December 2006, Launceston. Chiew FHS and Leahy C (2003) Comparison of evapotranspiration variables in Evapotranspiration Maps of Australia with commonly used evapotranspiration variables. Australian Journal of Water Resources 7, 1–11. Chiew FHS, Peel MC and Western AW (2002) Application and testing of the simple rainfall-runoff model SIMHYD. In: Singh VP and Frevert DK (Ed.s), Mathematical Models of Small Watershed Hydrology and Application. Littleton, Colorado, pp335–367. Environment Australia (2001) A Directory of Important Wetlands in Australia. Available at: http://www.environment.gov.au/water/publications/environmental/wetlands/pubs/directory.pdf IPCC (2007) Climate Change 2007: The Physical Science Basis. Contributions of Working Group 1 to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. Jeffrey SJ, Carter JO, Moodie KB and Beswick AR (2001) Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environmental Modelling and Software 16, 309–330. Kirby M, Mainuddin M, Podger G and Zhang L (2006) In: Sethaputra S and Promma K (Eds) Basin water use accounting method with application to the Mekong Basin. Paper prepared for the IHP International Symposium on Managing Water Supply for Growing Demand, October 2006, Bangkok. Available at: www.riversymposium.com/index.php?element=06KIRBYMac Kirby et al. (2007) Uncertainty assessments for scenario modelling. A report to the Australian Government from the CSIRO Murray- Darling Basin Sustainable Yields Project, CSIRO Australia. In prep. Marcar NE, Benyon RG, Polglase PJ, Paul KI, Theiveyanathan S and Zhang L (2006) Predicting the Hydrological Impacts of Bushfire and Climate Change in Forested Catchments of the River Murray Uplands: A Review. CSIRO Water for a Healthy Country. McVicar TR and Jupp DLB (2002) Using covariates to spatially interpolate moisture availability in the Murray-Darling Basin. Remote Sensing of Environment 79, 199–212. Nash JE and Sutcliffe JV (1970) River flow forecasting through conceptual models 1: A discussion of principles. Journal of Hydrology 10, 282–290. Nathan RJ, Jordan PW and Morden R (2005) Assessing the impact of farm dams on streamflows 1: Development of simulation tools. Australian Journal of Water Resources 9, 1–12. New South Wales Government (2000) Water Management Act 2000 No 92. Queensland Government (2000) Water Act 2000. South Australia Government (2004) Natural Resources Management Act 2004. Tan KS, Chiew FHS, Grayson RB, Scanlon PJ and Siriwardena L (2005) Calibration of a daily rainfall-runoff model to estimate high daily flows. Paper prepared for the Congress on Modelling and Simulation (MODSIM 2005), December 2005. Melbourne, Australia. pp2960–2966. Van Dijk A et al. (2007) Reach-level water accounting for 1990-2006 across the Murray-Darling Basin. A report to the Australian Government from the CSIRO Murray-Darling Basin Sustainable Yields Project. CSIRO, Australia. In prep. DSE (2004) Victoria in Future 2004 – Population projections. Department of Sustainability and Environment, Victoria. Available at: www.dse.vic.gov.au. Victoria Government (1989) Water Act 1989, Act Number 80/1989.
12 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 2 Overview of the region
This chapter summarises the region’s biophysical features including rainfall, topography, land use and the environmental assets of significance. It outlines the institutional arrangements for the region’s natural resources and presents key features of the surface and groundwater resources of the region including historic water use.
The Warrego region covers seven percent of the MDB, has less than one percent of the Basin’s population, uses less than one percent of the surface water diverted for irrigation and less than 0.1% of the Basin’s share of the groundwater resource. The major river is the Warrego River which includes a number of wetlands of national significance, including the Warrego River Waterholes and the Yantabulla Swamp. Annual water use is strongly influenced by seasonal rainfall patterns with the capacity of the river storage being less than one tenth of the long term extraction limit. The major land uses are dryland cattle, sheep grazing, and approximately 300 ha of irrigated cotton and horticulture. There is no re the of 2 Overview commercial plantation forestry in the region – although some native forests are logged – and there are relatively few farm dams.
2.1 The region
The Warrego region is predominantly in Queensland. It covers 76,615 km2 or seven percent of the MDB. It is bounded to the east by the Condamine-Balonne region, to the west by the Paroo region, and forms the northern edge of the MDB. g ion The southern boundary of the region is at Fords Bridge on the Warrego River 87 km upstream of the junction with the Darling River (Figure 2-2). The region is generally flat with a gentle southwards gradient. The upper catchment of the Warrego River includes the Warrego and Chesterton ranges. As this region is partly defined in terms of the area considered by the IQQM river system model, it is different to the extent of the full Warrego catchment that would normally be considered to continue to the Darling River junction.
Major water resources in the Warrego region include the Warrego River, the Great Artesian Basin, alluvial aquifers, wetlands and water storages. Associated with these water resources are both private and public infrastructure, including the Allan Tannock Weir near Cunnamulla and on-farm water storages. Mean annual rainfall is 422 mm varying from 650 mm in the north to less than 250 mm in the south. The rainfall, runoff and runoff coefficients for the Warrego region are amongst the lowest in the MDB. Most of the rainfall and runoff occur in summer and early autumn. Rainfall varies substantially between years, with long periods that are considerably wetter or drier than the others (Figure 2-1). Despite this variability, the region’s average annual rainfall has remained relatively consistent over the past 111 years. The mean annual rainfall over 1997–2006 (427 mm) is not statistically different to the long term mean.
80 1000
800 60
600 40 400 20 200 Annual rainfall (mm)
0 Mean monthly rainfall (mm) 0 1895 1915 1935 1955 1975 1995 JFMAMJ JASOND
Figure 2-1. 1895–2006 annual and monthly rainfall averaged over the Warrego region (based on the Bureau of Meteorology’s SILO database). The curve on the annual graph shows the low frequency variability.
The region’s population is approximately 7100, which is 0.4% of the MDB. The main towns are Charleville (pop. ~3500) and Cunnamulla (pop. ~1500). The predominant land use is low-intensity grazing of sheep and cattle. The river's flow is generally too erratic for irrigated cropping, however small areas of cotton and horticulture have been established in
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 13 recent times using water stored in the weir near Cunnamulla and in on-farm storages. Currently there is a total of approximately 300 ha of irrigated cropping (Table 2-1). There is no commercial plantation forestry in the region – although some native forests are logged – and relatively few farm dams.
The Warrego region has the second most sparse stream gauging network in the Murray-Darling Basin, after the Paroo region. The rainfall gauging network is about three times less dense than the basin average and the stream flow measurement network about ten times less dense. See Section 5.3 for more information about the gauging network in the Warrego region.
A Regional Natural Resource Management Plan (NRM Plan) (QMDC and SWNRM, 2004) has been prepared for all the catchments in the MDB region of southern Queensland. The South West Natural Resource Management Group Inc. (SWNRM) is the designated regional body responsible for development and the implementation of the NRM Plan in the Warrego.
The NRM Plan is a framework to guide coordinated and holistic planning and on-ground action to improve the management and condition of the natural resources in the region, and identifies resource condition targets and prioritises ion innovative management strategies to improve catchment health and protect regional assets. The aspirational resource g condition and management action targets in the NRM Plan for water have been primarily based on the principles in the water resource plans for the major river systems. The NRM Regional Plan is not a statutory plan and hence its targets for water use and management are aspirational only. The aspirational targets for water are:
x water to be efficiently used by 2035, x groundwater to be sustainability managed for long term environmental, production and social values by 2035, x surface water to be sustainability managed for long term environmental, production and social values by 2035.
The statutory responsibility for the development of water resource plans in the Queensland section of the Warrego sits 2 Overview of the re with the Queensland Department of Natural Resources and Water. In developing the Water Resource Plan for the region which includes the Warrego, the Department engaged a range of stakeholders in the plan area including the South West NRM Group.
The resource condition targets seek to incorporate the objectives from the Strategic Management Plan for the Great Artesian Basin (GABCC, 2000) and the objectives from the Water Resource Plan (Department of Natural Resources and Mines, 2003). Cross-border coordination and identification of common issues has been initiated as part of the NRM Plan for the western intersecting streams including the Warrego River (QMDC and SWNRM, 2004).
Table 2-1. Summary of land use within the Warrego region
Land use Area (%) Area (ha) Dryland crops 0.2 18,700 Dryland grazing 89.5 6,852,200 Irrigated crops <0.1 300 Cotton 33.3 100 Horticulture 66.7 200 National parks and state forests 10.0 763,200 Urban <0.1 1,200 Water 0.2 16,900 Total 100.0 7,652,500 Source: BRS (2000).
14 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 vriwo h re the of 2 Overview g ion
Figure 2-2. Map of dominant land uses of the region with insert showing the location of the Warrego within the Murray-Darling Basin
2.2 Environmental description
The vegetation of the Warrego region is largely determined by soil type, climate and flooding patterns. Native grasslands occur on the more fertile clay soils and saltbush shrubland on saltier floodplain alluvium, and mulga woodlands and shrublands are dominant on the extensive red earths. Mixed woodlands of cypress pine, brigalow and eucalypts occur on
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 15 upland sedimentary slopes. The extent of the remnant vegetation coverage was estimated to be 75 percent in 1999 for the Warrego River catchment (QMDC and SWNRM, 2004).
The clay soils of the Warrego alluvia contain very high levels of salts at relatively shallow depths. The low salinity in the Warrego River, the extent of native vegetation retention, and the low rainfall and high evaporation indicate that there is a relatively low risk of rising shallow groundwater levels in the catchment. Water quality in the shallow alluvial aquifers along the Warrego River ranges from <1000 μS/cm in the immediate vicinity of Charleville and upstream but becomes more saline downstream. Stream salinity in the Warrego River is low with the annual median salinity of 108 μS/cm at Cunnamulla.
There are many wetlands of National Importance in the Warrego region. Studies on the extent and nature of wetlands in the Warrego (QMDC and SWNRM, 2004) found the wetlands to be in generally good condition, although some have been affected by grazing and by sedimentation. The following descriptions of some of these areas are from Environment Australia (2001):
x Warrego River Waterholes, a string of large, permanent and intermittent waterholes and billabongs covering ion some 500 ha along the Warrego River channel in Queensland between Charleville to the south of Wyandra. g x Warrego Distributary Wetlands which covers 12,000 ha along the river from near Cunnamulla to the New South Wales border. The area consists of many distributary channels – streams that branch off and flow away from the main stream – and associated smaller watercourses and floodplain swamps. x The Cuttaburra Basin is a complex of braided streams and channels, temporary lakes, swamps and basins connecting the Paroo and Warrego regions through a main distributary stream (Cuttaburra Creek) that branches from the western bank of the Warrego River south of Cunnamulla. Cuttaburra Creek then flows through Yantabulla Swamp. The swamp is a mosaic of channels, floodways and wetlands and covers 37,000 ha and floods every few years on average, receiving water from the Paroo overflow as well as a number of creeks 2 Overview of the re which flow from the Warrego River.
2.3 Surface water resources
2.3.1 Rivers and storages
The major river, the Warrego, flows roughly southward from its headwaters in the Carnarvon National Park north of Augathella. The upper Warrego consists of a number of tributary rivers including the Nive, Ward and Langlo Rivers which join the main stream above and below Charleville. In the mid-basin the large distributary Cuttaburra creek takes flows to the Yantabulla Swamp and into the Cuttaburra Channels and Kulkyne Creek joining the Paroo River. Further south, a series of distributary creeks, including the Irana, Kerribree and Green creeks, leave the Warrego River. These creeks inundate floodplains and fill lakes while the main channel of the Warrego eventually reaches the Darling River.
The Warrego is an ephemeral river and only in wet years does substantial flow reach the Darling River. Most of the river flows occur as small to moderate floods following large relatively infrequent rainfall events. Monthly flows are extremely variable with peak flows exceeding the median by 3000 times. Major flooding however, requires a heavy rainfall over most or the entire Warrego region. As a guide, minor flooding requires at least 75 mm of rainfall in 24 hours over isolated areas, with lesser rains of 50 mm over more extensive areas; with rain also in the previous 24–72 hours then moderate to major flooding may occur (Bureau of Meteorology, 2005).
The Warrego River has no major dams, however the Allan Tannock Weir near Cunnamulla provides an active storage capacity of 4.27 GL and supplies the town of Cunnamulla and local irrigation. There are approximately a further 6 GL of storage in other weirs and up to an estimated 19 GL of storage in farm dams. This latter estimate, however, may not be reliable (Webb, McKeown and Associates, 2007). There are also a number of natural waterholes and wetlands that hold water for an extended period of time.
16 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 2.3.2 Surface water management institutional arrangements
Water resources within Queensland are managed under the Water Act 2000. The two tier planning regime involves development of a Water Resource Plan, which sets the strategic rules for water management in a catchment and a Resource Operations Plan which sets the operational rules.
The Water Resource (Warrego, Paroo, Bulloo and Nebine) Plan 2003 (Department of Natural Resources and Mines, 2003) covers the entirety of the Queensland portion of the Warrego region. The Warrego, Paroo, Bulloo and Nebine Resource Operations Plan 2006 (Department of Natural Resources and Mines, 2006) describes the practical implementation of the objectives and outcomes specified in the Water Resource (Warrego, Paroo, Bulloo and Nebine) Plan 2003. The intent of these plans is to provide enhanced certainty and security for water users and the environment.
The objectives for the Water Resource Plan include objectives for environmental flow and water allocation security. The environmental flow objective includes a provision that the flows of the Warrego and its distributary streams that cross the vriwo h re the of 2 Overview border from Queensland into New South Wales be at least 89 percent of the pre–development flow pattern (assessed over a specified period using a river system model).
Future allocation decisions affecting water allocation groups are limited to include:
x the annual volume probability for a water allocation group be not less than the annual volume probability for the group immediately before the decision is made x the 45 percent annual volume probability for a water allocation group be not less than the 45 percent annual volume probability for the group immediately before the decision is made. g ion Macro Water Sharing Plans are proposed for the New South Wales portion of the Warrego Region. Water management rules for this area have not been formalised at this time.
2.3.3 Water products and use
Water allocated for the Warrego region is detailed in Table 2-2. There is 2,612 ML of regulated water supply allocated to irrigation and town use from the Cunnamulla Water Supply Scheme. This water has a Medium priority rating (Resource Operations Plan). A further 40,003 ML of unsupplemented water allocation is available from unregulated water harvesting. An upper volumetric limit of 90,880 ML of unsupplemented water may be accessed by licence holders in any one year.
Unsupplemented water may be available in times of high flow. Extraction rate-limits govern water use. The provisions under which water may be accessed are detailed on the individual water allocation and include an annual volumetric limit, a maximum daily rate of take, commence-to-pump conditions and cease-to-pump conditions.
Table 2-2. Summary of surface water sharing arrangements in the Queensland portion of the Warrego
Water Products Priority of Access Allocated Entitlement (ML) Total Licensed (Long Term) Extraction Limit 42,615 Annual Volumetric Extraction Limit 93,492 Supplemented Access High 0 Supplemented Access Medium 2,612 - Local Water Utilities Medium 124 - Agricultural Use Medium 2488 Domestic and Stock 0* Unallocated 8,100 Unsupplemented Access Low 40,003 Environmental Provisions **
* Domestic and Stock allocations have been converted to nominal allocations ** Environmental Provisions are taken into consideration when setting the conditions of extraction on the entitlement to ensure there is a volume of water available for the environment. Source: Warrego, Paroo, Bulloo and Nebine Resource Operations Plan 2006
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 17 An additional volume of 8100 ML has been reserved as unallocated water for future use. This is made up of 4000 ML available for release in the Upper Warrego Water Management Area for taking water from a watercourse or a water licence for taking overland flow water, 4000 ML of unallocated water for release in the Lower Warrego Water Management Area for taking water from a watercourse, or a water licence for taking overland flow water and 100 ML for future town water supply needs. This water is scheduled for auction in September 2007 and allocations planned for issue by late 2007.
Queensland Water Resource Plans do not establish specific environmental water allocations; rather, environmental water is protected via the water access rules.
While water sharing arrangements for the New South Wales portion of the Warrego have not yet been formalised, there are unrestricted licences in the New South Wales portion of the region which allow access to unregulated flows. In the river system model (see Chapter 4) these are modelled as having a combined pump-capacity limit of 191 ML/day.
Surface water use is strongly influenced by the seasonal rainfall patterns which dictate runoff and stream flow; use varied ion g between about 2 GL to11 GL per year between 1993 and 2005. This represents less than one percent of the surface water use in the MDB. In years without floodplain harvesting the total diversion was in the order of 3 GL, whereas in years with significant floodplain harvesting it was between 7 and 11 GL. Domestic water use (urban and rural) accounts for less than two percent of use. As the Allan Tannock Weir near Cunnamulla has an active storage capacity of around one tenth of the average long term extraction limit, water users are dependent on the opportunity to capture unsupplemented water from overland flow or high river flows for irrigation.
15 2 Overview of the re
10
5 Annual waterAnnual use (GL)
0 1980 1985 1990 1995 2000 2005
Figure 2-3. History of surface water diversions in the Queensland portion of the region
Cotton and horticulture are the major irrigated industries within the Warrego region. The areas of production are small – only 300 ha – compared to most other regions within the MDB. Two-thirds of the irrigated land use is horticulture production, however, approximately two-thirds of the irrigated water use is for cotton production.
2.4 Groundwater
2.4.1 Groundwater management units – the hydrogeology and connectivity
The groundwater management units (GMUs) in the Warrego have been assessed as very low priority in the context of the overall project on the basis of the size of the aquifers, the level of development and the assumed degree of connectivity with the surface water system.
The Warrego region is underlain by consolidated sandstones, shales and mudstones that constitute the multi-layered aquifers of the Great Artesian Basin (GAB). The GAB is overlain with alluvial sediments up to 30 m thick. There are no GMUs in the Queensland portion of the region. The GMUs of the New South Wales portion of the region are the GAB GMU, an Upper Darling Alluvium GMU and a GAB Alluvial GMU (Table 6-1; Figure 6-1).
18 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Apart from some minor stream infiltration to the very north of the Queensland portion of the region (where GAB aquifers outcrop) and direct infiltration of GAB recharge beds in the headwaters of the Warrego River, there is no rainfall recharge to GAB aquifers within this region. In the New South Wales part of the region the aquifers are artesian to sub-artesian and rainfall will not infiltrate (DLWC, 2000). The GAB groundwater systems are considered to be unconnected to the shallow aquifers and the river, and hence there is very little impact on streamflow. The freshwater, semi-permanent Warrego River Waterholes and Yantabulla Swamp are generally believed to be replenished by floodwater, and existing information makes no reference to the role of groundwater in their hydrology (NSW Department of Environment and Conservation).
The northernmost GAB aquifers show variable water levels and good quality groundwater (Skelt et al., 2004). The water in the shallow alluvial aquifers (at 6 –10 m below ground level) is believed to be mostly saline to brackish – although data is limited.
Table 2-3. Categorisation of GMUs, including annual extraction, entitlement and recharge details in New South Wales vriwo h re the of 2 Overview
Code Priority Name Extraction 2004– Entitlement Long term average Recharge ranking 2005 extraction limit GL/y N601 very low GAB unknown 1 na* na* N63 very low GAB Alluvium unknown 0.02 1.3 2.1 N46 very low Upper Darling Alluvium unknown 0.2 1.7 3.4
* not available g ion
2.4.2 Water management institutional arrangements
The water resources within the Queensland GAB aquifers are administered by the Water Resource (Great Artesian Basin) Plan 2006. This plan provides a framework for sustainably allocating and managing water in the GAB. A Resource Operations Plan (GABBC, 2006) details the arrangements for implementing the water resource plan.
The water resources within the New South Wales GAB aquifers are controlled by the Water Sharing Plan for the New South Wales Great Artesian Basin Groundwater Resources 2007. The vision for this plan is to achieve equitable, viable and sustainable management of the Great Artesian Basin in New South Wales for the benefit of the community and the biodiversity of the region.
Excluding areas of the GAB covered by the Water Sharing Plan for the New South Wales GAB, groundwater extraction in the New South Wales portion of the reporting region will soon be controlled by a Macro Water Plan (DWE, In prep) which will provide an extraction limit and environmental provisions. Extraction records for the macro plan regions are generally poor. This plan is being prepared under the New South Wales Water Management Act 2000 and will provide an extraction limit and environmental provisions for the groundwater system. The annual extraction limit is set as a proportion of ‘recharge’ to the system. The macro planning process does not discount the extraction limit for salinity. As such the limits reflect availability in quantity terms only. The environmental provisions are 30–50 percent of the rainfall recharge.
2.4.3 Water products and use
The shallow groundwater is generally unsuitable for irrigation purposes due to poor quality and low yields. A total volume of 1164 ML of groundwater has been allocated for use under the New South Wales water sharing arrangements for groundwater within the Warrego region (Table 2-4). This includes a volume of 964 ML for the two zones of the GAB Groundwater Management Plan (Water Sharing Plan for the NSW Great Artesian Basin Groundwater Sources 2007, In prep) and 200 ML for the three GMU Macro Water Plans (2007, in prep).
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 19 Table 2-4. Groundwater sharing arrangements within the New South Wales portion of the Warrego region
Summary of groundwater sharing arrangements Name of plan Groundwater Macro Plan Year of Plan 2007 Basic rights Domestic and stock rights 0.877 GL/yr Native Title None Access licenses Urban 0.152 GL/yr Planned Share 0.135 GL/yr Announced Allocation None Environmental Provisions ion Planned share 30–50% of rainfall recharge g Supplementary provisions
Annual groundwater use has been historically low and similar between years. This reflects the use of the water for domestic and stock purposes. Water use from the alluvial and shallow sandstone aquifers represents less than 0.1% of the total groundwater use in the MDB.
Around 1300 bores draw from the Queensland GAB aquifers and provide the bulk of stock and domestic water, but water 2 Overview of the re quality from this source is also generally inadequate for irrigation due to poor quality. As an indication of the level of GAB use, the combined Warrego-Paroo-Nebine region of western Queensland Murray-Darling Basin (QMDB) is allocated only one percent of the total QMDB groundwater allocation, of which approximately 74 percent is to Great Artesian Basin bores, 23 percent is to shallower sandstone aquifers and only three percent is to the alluvial systems. Overall, groundwater use in the Warrego is minor and has not led to declining groundwater levels.
2.5 References
BRS (2000) Land use data. Available at: http://adl.brs.gov.au/mapserv/landuse/. Bureau of Meteorology (2005) Flood Warning System for the Warrego River, Available at: http://www.bom.gov.au/hydro/flood/qld/brochures/warrego/warrego.shtml. Department of Natural Resources and Mines (2003) Water Resource (Warrego, Paroo, Bulloo and Nebine) Plan 2003. Department of Natural Resources and Mines (2006) Warrego, Paroo, Bulloo and Nebine Resource Operations Plan 2006. DLWC (2000) Warrego NSW Macro-Groundwater Sharing Plans. Department of Water and Energy. DWE (In prep) NSW Macro-Groundwater Sharing Plans, Department of Water and Energy. Environment Australia (2001) A Directory of Important Wetlands in Australia. Third Edition. Environment Australia, Canberra. Available at: http://www.environment.gov.au/water/publications/environmental/wetlands/pubs/directory.pdf. GABBC (2006) Great Artesian Basin Resource Operations Plan 2006. QMDC and SWNRM (2004) Regional Natural Resource Management Plan 2004 (NRM), Queensland Murray Darling Committee Inc. and South West Natural Resource Management Group Inc. NSW Department of Environment and Conservation. Warrego River. Available at: http://wiserivers.nationalparks.nsw.gov.au/Multimedia/vBlob.jsp?id=668#top. Skelt K, Ife D and Hillier J (2004) Murray Darling-Basin Groundwater Status 1990–2000 Catchment Report: Warrego-Paroo Catchment. Murray Darling Basin Commission, Canberra. Water Resource (Great Artesian Basin) Plan 2006. Water Sharing Plan for the NSW Great Artesian Basin Groundwater Sources 2007. Webb, McKeown and Associates (2007) State of the Darling. Interim Hydrology Report to the Murray-Darling Basin Commission. ISBN 1 921 257 17 2.
20 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 3 Rainfall-runoff modelling
This section includes information on the climate scenario and rainfall-runoff modelling done for the Warrego region. It has four sub-sections:
x a summary x an explanation of the regional modelling approach x a presentation and description of the modelling results, and x a discussion of key findings.
3.1 Summary analrnf modellin 3 Rainfall-runoff
3.1.1 Issues and observations
x Recent climate (Scenario B) modelling is not carried out for the Warrego region because the mean annual rainfall and runoff for 1997–2006 are similar to the long-term 1895–2006 means. x Future development (Scenario D) modelling is not carried out for the Warrego region because of the little to no increase in commercial forestry plantations and farm dams in the region would have a negligible impact on runoff over the region. x The impact of future bushfires on runoff averaged over the entire Warrego region has been broadly assessed to g be negligible (Chiew et al 2007a).
3.1.2 Key messages
x The mean annual rainfall and modelled runoff averaged over the Warrego region are 422 mm and 7.2 mm respectively. Most of the rainfall and runoff occurs in summer and early autumn. River flows are intermittent, with most of the runoff coming from infrequent flood events. x Rainfall, runoff and the runoff coefficient (proportion of rainfall that becomes runoff) in the Warrego are amongst the lowest in the Murray-Darling Basin. x Rainfall and runoff can vary considerably from year to year. The mean annual rainfall and runoff over the past ten years (1997–2006) are not statistically significantly different from the long-term means. x The best estimate (median) from climate change impact modelling is a six percent reduction in mean annual runoff by ~2030 relative to ~1990 (with extreme estimates ranging from -25 percent to +46 percent). x There are no commercial forestry plantations in the region and relatively few farm dams. This situation is unlikely to change and therefore commercial forestry and farm dams are unlikely to significantly impact future runoff.
3.1.3 Uncertainty
x Scenario A – historical climate and current development. The runoff estimates in the Warrego region (and the western and north-western parts of the MDB are relatively poor compared to the eastern and southern parts of the MDB. It is considerably more difficult to model runoff in the western and north-western parts of the MDB because the region is drier, less of the rainfall becomes runoff, river flows are intermittent with most of the runoff occurring as infrequent floods, there are far fewer rainfall stations and there are no gauging stations recording streamflow over small catchment areas. Although there is large uncertainty in the runoff estimates for the Warrego region, the modelling results for Scenario C relative to Scenario A can be used to realistically assess the impact on climate change on runoff.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 21 x Scenario C – future climate and current development. The biggest uncertainty in Scenario C modelling is in the climate change projections. The uncertainty in the rainfall-runoff modelling of climate change impact on runoff is small compared to the climate change projections. This project takes into account the current uncertainty in climate change projections explicitly by considering results from 15 global climate models and the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC, 2007) global warming projections. The results are then presented as a median estimate of climate change impact on runoff and the range of the extreme estimates.
3.2 Modelling approach
3.2.1 Rainfall-runoff modelling – general approach g The general rainfall-runoff modelling approach is described more fully in Chapter 1 and in detail in Chiew et al. (2007a) including details of model calibration, cross-verification, regionalisation and climate change impact simulation with the SIMHYD model and for comparison the Sacramento rainfall-runoff model. A brief summary is given below.
The rainfall-runoff modelling provides a consistent way of modelling historical runoff across regions of the Murray-Darling Basin and assessing the potential impacts of climate change and development on future runoff. Daily rainfall runoff is estimated using the SIMHYD hydrology model, with a Muskingum routing method.
The rainfall-runoff modelling uses 5 km x 5 km grids (0.05 degrees) across each region for the four scenarios to provide spatial patterns and gradients in runoff. The rainfall-runoff models are calibrated against 1975–2006 streamflow from small unregulated catchments. In the model calibration, the six parameters of SIMHYD are optimised to maximise an 3 Rainfall-runoff modellin objective function that incorporates the Nash-Sutcliffe efficiency of monthly runoff and the daily flow duration curve, together with a constraint to ensure that the total modelled runoff over the calibration period is within five percent of the total recorded runoff. The runoff for single grid cell in a subcatchment in the reporting region is modelled using optimised parameter values for a calibration catchment closest to the subcatchment.
3.2.2 Rainfall-runoff modelling for the Warrego reporting region
The rainfall-runoff modelling is carried out to estimate runoff in 0.05 degrees grid cells in nine subcatchments as defined for the river system modelling in Section 4 for the Warrego region (Figure 3-1). As there is no streamflow gauging station in the Warrego region with a catchment area of 50–2000 km2, a different approach is used to obtain model parameter values for the Warrego region (and several other regions in the western and north-western parts of the Murray-Darling Basin). For the Warrego, the model is calibrated against streamflow data from Gauging Stations 423204 (8747 km2) and 423203 (42,888 km2) (Figure 3-1). The optimised parameter values for Gauging Station 423204 are used to model runoff in Subcatchment 4232040, and the optimised parameter values for Gauging Station 423203 are used to model runoff in all the other Warrego sub-catchments.
Scenario B modelling is not carried out for the Warrego region because the mean annual rainfall and modelled runoff for 1997–2006 are not significantly different (at statistical significance level of Į = 0.2 with the Student-t and Rank-Sum tests) from the long-term 1895–1996 means (see Section 3.3.1).
Scenario D modelling is not carried out for the Warrego region because commercial forestry plantations and farm dams are unlikely to impact significantly on runoff. This is because there are no commercial forestry plantations in the region and relatively few farm dams and this situation is unlikely to change.
22 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 analrnf modellin 3 Rainfall-runoff g
.
Figure 3-1. Map of the modelling subcatchments and calibration catchments
3.2.3 Model calibration
Figure 3-2 compares the modelled and observed monthly runoff and the modelled and observed daily flow duration curve at the two calibration catchments. The results indicate that the SIMHYD calibration can reproduce satisfactorily the observed monthly runoff series (Nash-Sutcliffe E values of 0.78 and 0.94) and the daily flow duration characteristic (Nash
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 23 Sutcliffe E values of 0.86 and 0.93). The results were also cross-checked against the existing runoff modelling results of Young et al. (2006).
However, despite the satisfactory model calibration, the runoff estimates for the Warrego region are poor compared to the runoff estimates for the eastern and southern parts of the MDB.
This is because, compared to the eastern and southern parts of the MDB, there are far fewer rainfall stations in the Warrego, there are no streamflow gauging stations for 50 km2 to 2000 km2 catchments, river flows are intermittent with most of the runoff occurring as infrequent floods, and the runoff coefficient (proportion of rainfall that becomes runoff) is low. g 3 Rainfall-runoff modellin
Figure 3-2. Modelled and observed monthly runoff and daily flow duration curve for the calibration catchments
3.3 Modelling results
3.3.1 Scenario A – historical climate and current development
Figure 3-3 shows the spatial distribution of mean annual rainfall and modelled runoff for 1895–2006 across the Warrego region, Figure 3-4 shows the 1895–2006 annual rainfall and modelled runoff series averaged over the region, and Figure 3-5 shows the mean monthly rainfall and runoff averaged over the region for 1895–2006.
The mean annual rainfall and modelled runoff averaged over the Warrego region are 422 mm and 7.2 mm respectively. There is a clear north-south gradient in both rainfall and runoff, with mean annual rainfall ranging from about 650 mm in the north to less than 300 mm in the south and mean annual runoff ranging from about 20 mm in the north to less than five mm in the south (Figure 3-4). The rainfall, runoff and runoff coefficient in the Warrego are amongst the lowest in the MDB. Most of the rainfall occurs from late spring to early autumn, and most of the runoff occurs in summer and early autumn (Figure 3-5).
24 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Rainfall and runoff can vary considerably from year to year (the coefficients of variation of annual rainfall and runoff are 0.35 and 1.19 respectively) with long periods over several years or decades that are considerably wetter or drier than others (Figure 3-4).
The mean annual rainfall and modelled runoff over the past ten years (1997–2006) are one percent higher and eight percent lower respectively than the 1895–2006 long-term means. However the 1997–2006 rainfall and runoff means are not statistically significantly different to the long-term 1895–1996 means (at significance level Į = 0.2 with the Student-t and Rank-Sum tests). 3 Rainfall-runoff modelling
Figure 3-3. Spatial distribution of mean annual rainfall and modelled runoff averaged over 1895–2006
1000 60
800 40 600
400 20 200 Annual runoff (mm) runoff Annual Annual rainfall (mm) rainfall Annual 0 0 1895 1915 1935 1955 1975 1995 1895 1915 1935 1955 1975 1995
Figure 3-4. 1895–2006 annual rainfall and modelled runoff series averaged over the region. The curve shows the low frequency variability.
80 3
60 2
40
1 20 Mean monthly runoff (mm)
Mean monthly rainfall (mm) 0 0 JFMAMJJASOND JFMAMJ JASOND
Figure 3-5. Mean monthly rainfall and modelled runoff (averaged over 1895–2006 for the region)
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 25 3.3.2 Scenario C – future climate and current development
Figure 3-6 shows the percentage change in the modelled mean annual runoff averaged over the Warrego region for Scenario C relative to Scenario A for the 45 scenarios (15 GCMs for each of the high, medium and low global warming scenarios). The percentage change in the mean annual runoff and the percentage change in mean annual rainfall from the corresponding GCMs are also tabulated in Table 3-1 (Chiew et al, 2007b) technical report for description of the GCMs and detailed discussion of method used to obtain Scenario C climate series).
The plot and table indicates that the potential impact of climate change on runoff can be very significant. However, there is considerable uncertainty in the estimates, with results from 60 percent of the GCMs showing a reduction in mean annual runoff and 40 percent of the GCMs showing an increase in mean annual runoff. These results are different to the southern parts of the Murray-Darling Basin where the majority of GCMs indicate that rainfall would decrease.
Because of the large variation between GCM simulations and the method used to obtain the climate change scenarios g (see Section 3.1.3), the biggest increase and biggest decrease in runoff come from the high global warming scenario. For the high global warming scenario, rainfall-runoff modelling with climate change projections from 40 percent of the GCMs indicates a decrease in mean annual runoff greater than ten percent, and rainfall-runoff modelling with climate change projections from one-third of the GCMs indicates an increase in mean annual runoff greater than ten percent.
In subsequent reporting here and in other Sections, only results from an extreme ‘dry’, ‘mid’ and extreme ‘wet’ variant are shown (referred to as Cdry, Cmid and Cwet). For the Cdry scenario, results from the second highest reduction in mean annual runoff from the high global warming scenario are used. For the Cwet scenario, results from the second highest increase in mean annual runoff from the high global warming scenario are used. For the Cmid scenario, the median mean annual runoff results from the medium global warming scenario are used (shown in bold in Table 3-1).
3 Rainfall-runoff modellin Figure 3-7 shows the mean annual runoff across the Warrego region for Scenario A and for the Cdry, Cmid and Cwet scenarios.
60 High global w arming
40 Medium global w arming
Low global w arming 20
0
-20
-40 % change in mean annualinrunoff mean % change
-60 iap mri ipsl mpi gfdl miub csiro cnrm miroc inmcm giss_aom ncar_pcm cccma_t47 cccma_t63 ncar_ccsm
Figure 3-6. Percentage change in mean annual runoff from the 45 Scenario C simulations (15 GCMs and three global warming scenarios) relative to Scenario A runoff
26 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Table 3-1. Summary results from the 45 Scenario C simulations (numbers show percentage change in mean annual rainfall and runoff for Scenario C relative to Scenario A)
High global warming Medium global warming Low global warming GCM Rainfall Runoff GCM Rainfall Runoff GCM Rainfall Runoff ipsl -11 -34 ipsl -7 -24 Ipsl -3 -12 mpi -8 -25 mpi -5 -17 mpi -2 -8
csiro -8 -23 csiro -5 -16 csiro -2 -7 cnrm -10 -17 cnrm -6 -12 cnrm -3 -6 iap -4 -15 mri -5 -10 Mri -2 -5 mri -7 -13 iap -3 -10 iap -1 -4 gfdl -5 -7 giss_aom -7 -7 giss_aom -3 -4 analrnf modellin 3 Rainfall-runoff giss_aom -10 -4 gfdl -4 -6 gfdl -2 -3
inmcm -2 -1 inmcm -1 -1 inmcm -1 -1 ncar_ccsm 2 10 ncar_ccsm 1 6 ncar_ccsm 1 2 ncar_pcm 8 26 ncar_pcm 5 16 cccma_t47 3 6 cccma_t47 10 27 cccma_t47 6 16 ncar_pcm 2 7 cccma_t63 6 27 cccma_t63 4 17 cccma_t63 2 7 miub 11 46 miub 7 27 miub 3 11
miroc 15 60 miroc 10 35 miroc 4 14 g
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 27 g 3 Rainfall-runoff modellin
Figure 3-7. Mean annual rainfall and modelled runoff for Scenarios A, Cdry, Cmid and Cwet
28 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 3.3.3 Summary of results for all modelling scenarios
Table 3-2 shows the mean annual rainfall, modelled runoff and actual evapotranspiration (rainfall minus runoff) for Scenario A (averaged over the Warrego region), and the percentage changes in the rainfall, runoff and actual evapotranspiration in Scenario C relative to Scenario A. Figure 3-8 shows the mean monthly rainfall and modelled runoff for Scenarios A and C averaged over 1895-2006 for the Warrego. Figure 3-9 shows the daily rainfall and flow duration curves for Scenarios A and C averaged over the region. The modelling results for the nine subcatchments in the Warrego are summarised in Appendix A.
As explained earlier, Scenario B (recent climate and current development) modelling is not carried out for the Warrego because the mean annual rainfall and modelled runoff for 1997-2006 is not statistically significantly different to the long- term means. The Scenario B results would therefore be essentially the same as the Scenario A results.
The modelling results indicate a median estimate of -6% change in mean annual runoff by ~2030 (Scenario C). However, 3 Rainfall-runoff modelling there is considerable uncertainty in the results with extreme estimates ranging from -25% to +46%.
As explained earlier, Scenario D (future climate and future development) modelling is not carried out for the Warrego because commercial forestry plantations and farm dams are unlikely to significantly impact future runoff. The Scenario D results would therefore be essentially the same as the Scenario C results.
Table 3-2. Water balance over the entire region by scenario
Scenario Rainfall Runoff Evapotranspiration (mm) (mm) (mm) A 422 7.2 415 (% change) B – – – Cdry -8 -25 -8 Cmid -4 -6 -3 Cwet 11 46 10 Ddry – – – Dmid – – – Dwet – – –
80 3 Scenario C range Scenario C range Scenario A 60 Scenario A Scenario Cmid 2 Scenario Cmid
40
1 20
Mean monthly rainfall (mm) 0 Mean monthlyrunoff (mm) 0 JFMAMJJASOND JFMAMJJASOND
Figure 3-8. Mean monthly rainfall and modelled runoff for scenarios A and C averaged over 1895–2006 across the region
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 29 g
Figure 3-9. Daily flow duration curves for Scenarios A and C averaged over the region
3.4 Discussion of key findings
The mean annual rainfall and modelled runoff averaged over the Warrego region are 422 mm and 7.2 mm respectively. There is a clear north-south gradient in both rainfall and runoff, with mean annual rainfall ranging from about 650 mm in the north to less than 300 mm in the south and mean annual runoff ranging from about 20 mm in the north to less than 3 Rainfall-runoff modellin five mm in the south. Most of the rainfall and runoff occurs in summer and early autumn. The rainfall, runoff and runoff coefficient (proportion of rainfall that becomes runoff) in the Warrego are amongst the lowest in the MDB.
Rainfall and runoff can vary considerably from year to year with coefficients of variation of annual rainfall and runoff of 0.35 and 1.19 respectively. The mean annual rainfall and runoff over the ten-year period 1997 to 2006 are 427 mm and 6.6 mm respectively, and they are not statistically significantly different from the long term means.
The runoff estimates in the Warrego region (and the western and north-western parts of the MDB) are relatively poor compared to the eastern and southern parts of the MDB. It is considerably more difficult to model runoff in the western and north-western parts of the MDB because the region is drier, less of the rainfall becomes runoff, river flows are intermittent with most of the runoff occurring as infrequent floods, there are far fewer rainfall stations and there are no gauging stations recording streamflow over small catchment areas.
The climate change impact modelling show a median estimate of -6% change in mean annual runoff by ~2030 relative to ~1990. There is considerable uncertainty in the modelling results with extreme estimates ranging from -25% to +46%. The main sources of uncertainty are in the global warming projections and the global climate modelling of local rainfall response to the global warming. The uncertainty in the rainfall-runoff modelling of climate change impact on runoff is small compared to the climate change projections.
There are no commercial forestry plantations in the Warrego and relatively few farm dams. This situation is unlikely to change and therefore commercial forestry and farm dams are unlikely to impact future runoff.
3.5 References
Chiew et al (2007b) Rainfall-Runoff Modelling Across the Murray-Darling Basin. A report to the Australian Government from the CSIRO Murray-Darling Basin Sustainable Yields Project. CSIRO, Australia. IPCC (2007) Climate Change 2007: The Physical Science Basis. Contributions of Working Group 1 to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. Young W, Brandis K and Kingsford R (2006) Modelling monthly streamflows in two Australian dryland rivers: Matching complexity to spatial scale and data availability. Journal of Hydrology 331, 242–256.
30 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 4 River system modelling
This chapter includes information on river system modelling done for the Warrego region. It has four sub-sections:
x a summary x an explanation of the regional modelling approach x a presentation and description of results x a discussion of key findings.
The information in this chapter is derived from the Queensland Department of Natural Resources and Water’s (QDNRW) calibrated IQQM for the Warrego river system. ie s 4 River 4.1 Summary y 4.1.1 Issues and observations modellin stem
River system modelling for the Warrego reporting region considers six modelling scenarios:
1. Scenario O: This represents the original river system model configuration that was used for planning purposes in QDNRW. It is run over the original modelling period that QDNRW used for planning. g 2. Scenario A is based on the Scenario O model but is run for a common historic climate period (1 June 1895 to 30 June 2006) and represents current levels of development. This scenario is the baseline scenario that all other scenarios are compared against.
3. Scenario P is based on the Scenario A model and is run for the common historic climate period. Current levels of development such as public storages and demand nodes are removed from the model to represent pre- development conditions. Note natural water bodies, fixed diversion structures and existing catchment runoff characteristics are not adjusted.
4. Scenarios Cwet, Cmid and Cdry: These scenarios represent a range of future climate conditions that are derived by adjusting the historic climate and flow inputs used in Scenario A, which is described in Chapter 2. The level of development is the same as Scenario A, i.e. current level of development.
Future development scenarios were not modelled in the Warrego analysis as there was not significant development of commercial plantation forestry, farm dams or groundwater. Consequently results for future development scenarios will be similar to the C scenarios.
The Warrego river system model:
x Is configured to represent the full utilisation of licences. Consequently the demands generated represent what could be diverted if licenses were fully utilised. The observed history of use is considerably smaller than what is reflected in this configuration of the model.
x Irrigation demands are modelled using a soil moisture accounting model that is configured with large areas and large on-farm storages that ensure all available water is utilised. Consequently the demands do not reflect the variation in demands due to climatic influences.
x Modelled crop areas are fixed and do not reflect any change in irrigated area as a function of available water resources.
x Includes the 8.1 GL of unallocated water to be auctioned in September 2007.
x Represents unsupplemented access as water extracted from the main river and modelled distributaries. The beneficial flooding in the lower part of the system is not explicitly modelled and consequently this is not assessed.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 31 x Analysis of the pre-development flows along the Warrego River indicates that it changes from a gaining to a losing stream (point of maximum average annual flow) at the Wyandra gauge (423203). The pre-development average annual flow over the modelling period is 423 GL/year.
The Queensland Water Resource Operations Plan is based on results for the original model (Scenario O) that runs over a different climatic period to the common modelling period used in this study. Despite the difference in modelling period the percentage of long term average flow to NSW is identical at 89 percent.
4.1.2 Key messages
x The current level of development (maximum permissible use) in the Warrego is low: 12 percent of the long-term average flow is able to be diverted for use.
x The best estimate 2030 climate scenario indicates a 6 percent reduction in river inflows, leading to a seven g percent reduction in both total surface water availability for the region and in total end of system flows. However, because water use is low, even assuming maximum permissible use the average impact on diversions is only a three percent reduction. This reduction is mainly associated with un-supplemented water access in Queensland.
x The climate extremes for 2030 indicate:
stem modellin o Under a wet extreme 2030 climate increases in total inflows (44 percent), water availability (47 y
s percent), diversions assuming current maximum permissible use (13 percent) and end of system flows r (51 percent).
o Under a dry extreme 2030 climate decreases in inflows (28 percent), water availability (30 percent), 4 Rive diversions assuming current maximum permissible use (12 percent) and end of system flows (32 percent).
x Neither the supplemented nor the unsupplemented access upstream of Wyandra varies significantly under the climate change scenarios.
x The Water Resource Plan that relates to the Queensland portion of the Warrego requires that at least 89 percent of the average flow into New South Wales is maintained; this implies that a maximum of 11 percent of the average ‘without development’ flow at the border may be diverted in Queensland for use. Given current surface water entitlements in Queensland this requirement is being met. Changes in inflows under future climate would alter the percentage diverted for use. Under the best estimate 2030 climate current Queensland entitlements would represent 12 percent of the ‘without development’ flow at the border. The range for the 2030 climate extremes is from seven percent ((wet extreme) to 15 percent (dry extreme).
x The predicted impact of future climate change on the frequency with which flow ceases at the two major end-of- system points is considerably smaller than the level of impact that has already occurred due to water resource development.
4.1.3 Robustness
The model was run for an extreme climate scenario to assess how robustly it would behave. During this test scenario allocations were zero and Allan Tannock Weir was drawn below dead storage. The model behaved robustly during this extreme test.
The model response to increases and decreases in inflow was reasonable with the change in diversions and end of systems flows consistent with the change in inflow. Mass balance over the modelling period was maintained with 0.1 percent for all scenarios.
32 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 4.2 Modelling approach
The following section provides a summary of the generic river modelling approach, a description of the Warrego river system model and how the river model was developed. Refer to Chapter 1 for more contexts on the overall project methodology.
4.2.1 General
River system models that encapsulate descriptions of current infrastructure, water demands, and water management and sharing rules are used to assess the implications of the changes in inflows described above in this chapter on the reliability of water supply to users. Given the time constraints of the project, and the need to link the assessments to State water planning processes, it is necessary to use the river system models currently used by State agencies and the ie s 4 River Murray-Darling Basin Commission. The main models in use are IQQM, REALM, MSM-Bigmod, WaterCress and a model of the Snowy Mountains Hydro-electric Scheme.
A few areas of the Basin have not previously been modelled, and hence some new IQQM or REALM models have been y implemented. In some cases ancillary models are used to estimate aspects of water demands of use in the river system modellin stem model. A key example is the Pride model used to estimate irrigation for Victorian REALM models.
River systems that do not receive inflows or transfers from upstream or adjacent river systems are modelled independently. This is the case for most of the river systems in the Basin, and for these rivers the modelling steps are:
(i) Model configuration. g (ii) Model warm-up to set initial values for all storages in the model, including public and private dams and tanks, river reaches and soil moisture in irrigation areas.
(iii) Using scenario climate and inflow time series, run river model for all scenarios (historical, recent and future climate as well as future development).
(iv) Where relevant, extract initial estimates of surface-groundwater exchanges and provide to groundwater model.
(v) Where relevant, use revised estimates of surface-groundwater exchanges from groundwater models and re-run river model for all scenarios.
For river systems that receive inflows or transfer from upstream or adjacent river systems, model inputs for each scenario are taken from the ‘upstream’ model(s). In a few cases several iterations are required between upstream and downstream models because of the complexities of the water management arrangements. An example is the connections between the Murray, Murrumbidgee and Goulburn regions and the Snowy Mountains Hydro-electric Scheme.
4.2.2 Description of river model for the Warrego region
The Warrego region is described by the Warrego river systems model (Figure 4-1).
The model is an IQQM V6.73.4 representation of the Warrego River system from the Augathella gauge (423204) to three terminal points: Fords Bridge gauge (423001), Cuttaburra Creek and Widgeegoara-Noorama Creeks. The model does extend past the Fords Bridge gauge to the Darling River but this is not calibrated or reported herein. The outflows from Fords Bridge, Cuttaburra Creek and Widgeegoara-Noorama Creeks are inflows, respectively, into the Darling, Paroo and Nebine river systems. The impacts of these inflows for each of the scenarios will be considered in the respective reporting regions.
The model represents the Warrego River system with 276 links and 277 nodes arranged into 31 river sections. The natural pools and water bodies along the length of the Warrego River are modelled by 44 storage nodes. Allan Tannock Weir is the only regulated storage in the model (Table 4-1). The model assumes that inflows into Allan Tannock Weir up to 300 ML/day will bypass the weir.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 33 The irrigation water use is modelled by 74 nodes, and stock and domestic demands are modelled by seven nodes (Table 4-2). There is a regulated water supply from Allan Tannock Weir to two irrigation nodes. The water is shared to these users via an annual accounting system. g stem modellin y s r 4 Rive
Figure 4-1. Map showing IQQM subcatchments (with and without inflows), major storages, and model nodes and links
34 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Table 4-1. Storages in the river model
Active storage Average annual Average annual Average annual Degree of Inflow release net evaporation regulation GL GL/y Major supply reservoirs Allan Tannock Weir 4.27 317.9 2.8 2.3 0.02 Natural water bodies Warrego system to Fords 38.07 Bridge Region totals 42.34 317.9 2.8 2.3 0.02
Table 4-2.Modelled water use configuration ie s 4 River
Number of Medium security Licence Pump Model notes nodes water product constraints
GL/y ML/day y Irrigation Soil moisture accounting single store for modellin stem combined crops. Regulated 2 2.608 1050 On farm storage at some nodes. Qld unsupplemented 70 90.88 3451 Nodes configured with large areas and OFS volumes to consume all available water. NSW unregulated 4 unrestricted 191
Sub-total 76 4692 g Stock and domestic 7 0 0.1 80 Fixed demand Number of Medium security Licence Pump Model notes nodes water product constraints
Table 4-3. Model water management
Bypass flow Allan Tannock Weir Up to 300 ML/day of inflow
Accounting system Allan Tannock Weir Annual accounting
4.2.3 Model setup
The original Warrego River model and associated IQQM V6.73.4 executable code were obtained from QDNRW. This model was run for the original period of 1 January 1889 to 31 December 1999 and validated against previous results. The time series rainfall, evaporation and flow inputs to this model were extended to 30 June 2006.
A pre-development version of this model was created by removing Allan Tannock Weir, all irrigators and fixed stock and domestic demands. Natural water storages were not changed as they represent the pre-development physical characteristics of the system.
The Warrego River system contains a significant amount of total storage relative to inflows. The initial state of these storages can influence the results obtained. As the Warrego model starts with a warm up period from 1 January 1895 to 30 June 1895 the initial state of Allan Tannock Weir and all natural water body storages needs to be determined. To do this the model was started with all of these storages empty and run up to 31 May 1895 and the final storage volumes were recorded. This was repeated with all of the storages initially full. The results of this analysis are presented in Table 4-4 and show that under both cases the storages converged to a similar result. Each storage was subsequently configured with this initial storage volume.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 35 Table 4-4. Model setup information
Original models Version Start date End date Warrego IQQM 6.73.4 01/01/1889 31/12/1999 Connection Fords Bridge Warrego outflows to Darling Cuttaburra Ck Cuttaburra outflows to Paroo Norooma & Widgeegoara CK Norooma & Widgeegoara Creek to Nebine
Baseline models Warm up period 01/06/1895 30/06/1895 Modelling period IQQM 6.73.4 01/06/1895 30/6/2006
g Connection Fords Bridge Warrego outflows to Darling Cuttaburra Ck Cuttaburra outflows to Paroo Norooma & Widgeegoara CK Norooma & Widgeegoara Creek to Nebine
stem modellin Modifications Warrego y
s Data Extend to 30/06/2006 r Inflows No adjustment required Groundwater loss nodes None 4 Rive Initial storage volume Allan Tannock Weir 4.77 Warm up test results Setting initial storage volumes Storages commence empty Storages commence Difference % of Full full Volume
GL % Allan Tannock Weir storage volume 4.77 4.77 0 0 31/05/1895 Natural water bodies storage volume 38.07 38.07 0 0 31/05/1895
Storage volume 30 May (1895-2006) Mean Median GL GL Allan Tannock Weir 3.8 4.1 Natural water bodies 43.4 42.9 Robustness test results Minimum allocation Allan Tannock Weir (%) 0 Minimum storage volume (ML) Cunnamulla 136
The model was configured for an extreme dry climate scenario by applying seasonal factors to rainfall, evaporation and inflows (Table 4-5). The model was run and behaved robustly even when Allan Tannock Weir went below dead storage volume and allocations were at zero percent. The results of the model setup are summarised in Table 4-4.
36 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Table 4-5. Rainfall, evaporation and flow factors for model robustness test
Season Rainfall Evaporation Flow DJF 0.97 1.67 0.90 MAM 0.33 1.07 0.80 JJA 0.73 1.07 0.30 SON 0.88 1.03 0.69
4.3 Modelling results
4.3.1 River system water balance ie s 4 River
The mass balance table (Table 4-6) shows the net fluxes for the Warrego River system. Scenario O (the original model scenario) fluxes and Scenario A fluxes are displayed as GL/year, while all other scenarios are presented as a percentage
change from Scenario A. Note the averaging period for Scenario O differs from Scenario A. y tmmodellin stem The directly gauged inflows represent the inflows into the model that are based on a river gauge. The indirectly gauged inflows represent the inflows that are derived to achieve mass balance between mainstream gauges. Diversions are listed based on the different water products in the reporting region. End of system flows are shown for the three end-of- system gauges and net evaporation is displayed for Allan Tannock Weir and all the natural water storages. The change in storage between 30 June 1895 and 30 June 2006 averaged over the 111 year period is also included. g Appendix B contains mass balance tables for the eight subcatchments in the model. The mass balance of each of these river reaches and the overall mass balance was checked by taking the difference between total inflows and outflows of the system. In all cases the mass balance error was less than 0.1 percent.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 37 Table 4-6. River system model average annual water balance under scenarios O, A and C
O A Cwet Cmid Cdry Model start date 01/01/1889 01/07/1895 Model end date 31/12/1999 30/6/2006 GL/y % change from Scenario A
Storage volume
Change over period -0.5 -0.1 -15% 14% 32%
Inflows Sub-catchments Directly gauged 55.5 52.0 51% -11% -27% Indirectly gauged 596.5 552.5 43% -6% -28% g Sub-total 652.1 604.5 44% -6% -28%
Diversions Licenced private diversions Medium security (nominal volume 2.612 GL/y) 2.5 2.5 0% 0% -1% QLD unsupplemented access (volumetric limit 90.88 GL/y) 44.6 42.0 15% -3% -15% stem modellin y s r NSW unregulated access 6.9 6.9 2% -1% -3% Sub-total 54.1 51.5 13% -3% -12%
4 Rive Stock and domestic QLD unsupplemented access 0.1 0.1 0% 0% 0% Sub-total 54.2 51.5 13% -3% -12%
Outflows End of system outflow to Fords Bridge 62.0 57.2 47% -7% -27% Cuttaburra Creek 92.2 82.6 53% -7% -35% Norooma & Widgeegoara Creek 3.4 3.5 78% -14% -44% Sub-total 157.6 143.3 51% -7% -32% Net evaporation* Allan Tannock Weir 2.3 2.3 3% 4% 4% Natural water bodies 61.8 59.3 16% -2% -11% Sub-total 64.2 61.6 16% -1% -11% Sub-total 221.8 204.9 41% -5% -26%
Unattributed fluxes Total 376.7 348.2 50% -7% -31%
* Evaporation from private licensed storages (GL/y) is not included as it is already accounted in diversions
4.3.2 Storage behaviour
The modelled behaviour of major public storages gives an indication of the level of regulation of a system as well as how reliable the storage is during extended periods of low or no inflows. Table 4-7 provides indicators that show the lowest recorded storage volume and the corresponding date for each of the scenarios. The average and maximum years between spills is also provided. The period between spills commences when the storage exceeds full supply volume and ends when the storage falls below 90 percent of full supply volume. The end condition is applied to remove the periods when the dam is close to full and oscillates between spilling and just below full which distorts the analysis.
38 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 The time series of storage behaviour for the maximum period between spills for each of the scenarios is shown in Figure 4-2.
Table 4-7. Details of weir behaviour
Allan Tannock Weir A Cwet Cmid Cdry Minimum storage volume (ML) 136 124 120 99 Minimum storage date 9/6/1916 9/6/1916 9/6/1916 22/6/1916 Average years between spills 0.3 0.3 0.3 0.3 Maximum years between spills 1.4 1.4 1.4 1.5
(a) (b) ie s 4 River 6000 6000
5000 5000
4000 4000 y tmmodellin stem 3000 3000
2000 2000 Volume (ML) Volume (ML) 1000 1000
0 0 g Dec 1914 Jun 1915 Dec 1915 Jun 1916 Dec 1916 Dec 1914 Jun 1915 Dec 1915 Jun 1916 Dec 1916
(c) (d)
6000 6000
5000 5000
4000 4000
3000 3000
2000 2000 Volume (ML) Volume (ML) 1000 1000
0 0 Dec 1914 Jun 1915 Dec 1915 Jun 1916 Dec 1916 Jan 1979 Jul 1979 Jan 1980 Jul 1980 Jan 1981
Figure 4-2 Allan Tannock Weir behaviour over the maximum days between spills under (a) Scenario A, (b) Scenario Cwet, (c) Scenario Cmid, and (d) Scenario Cdry
4.3.3 Diversions
Table 4-8 shows the total average annual diversions for each reach for Scenario A and the percentage change of all other scenarios compared to Scenario A. Figure 4-3 shows total average annual diversions for all scenarios from upstream to downstream. Note the three downstream distributary catchments have been combined for the end of the system.
Figure 4-4(a) shows the annual time series of total diversions for Scenario A and Figure 4-4 (b)-(d) show the difference in annual volumes for the other scenarios relative to Scenario A. The maximum (shown in black) and minimum (shown in red) diversions for Scenario A are 125.2 GL in 1954 and 11.3 GL in 1915 respectively.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 39 Table 4-8. Change in annual irrigation diversions in each calibration reach relative to Scenario A
Reach A Cwet Cmid Cdry GL/y % change relative to Scenario A 4232040 0.0 0% 0% 0% 4232011 4.1 4% 0% -2% 4232031 3.4 3% -1% -3% 4232021 12.5 17% -4% -18% 4230041 16.7 16% -3% -15% 4234243 4.7 17% -3% -18% 4324223 3.3 11% -4% -13% 4230011 6.9 2% -1% -3% g Total 51.5 12% -3% -12%
25 C range
stem modellin 20 y Cmid s r 15 A
10 4 Rive 5 Annual diversions (GL) diversions Annual 0 4232040 4232011 4232031 4232021 4230041 EOS total
Figure 4-3. Total average diversions under scenarios A and C from upstream to downstream
(a) (b)
140 25
120 20 100 15 80
60 10 40 5
Annual diversionsAnnual (GL) 20 Annual difference (GL) difference Annual 0 0 1895 1915 1935 1955 1975 1995 1895 1915 1935 1955 1975 1995
40 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 (c) (d)
4 0 2 -2 0 -4 -2 -6 -4 -8 -6 -10 -8 -10 -12 -12 -14
Annual difference (GL) difference Annual -14 (GL) difference Annual -16 -16 -18 1895 1915 1935 1955 1975 1995 1895 1915 1935 1955 1975 1995
Figure 4-4. (a) Total water use under Scenario A; (b) difference between total water use under scenarios A and Cwet; (c) difference s 4 River between total water use under scenarios A and Cmid; (d) difference between total use water use under scenarios A and Cdry
4.3.4 End of system flows y tmmodellin stem
Figure 4-5 shows the flow duration curves for the three end of systems locations: Warrego at Fords Bridge, Cuttaburra Creek and Widgeegoara-Noorama Creeks. Each of the scenarios are plotted on the same plot. The cease-to-flow percentiles for these scenarios are presented in Table 4-9. Cease-to-flow is considered to occur when model flows are less than 0.001 ML/day. g
(a) (b)
100000 100000 C range C range 10000 10000 Cmid Cmid 1000 1000 A A 100 P 100 P 10 10 1 1 0.1 0.1 Daily flow (ML) Daily flow(ML) 0.01 0.01 0.001 0.001 0 20 40 60 80 100 0 20406080100 % time flow is exceeded % time flow is exceeded
(c)
10000 C range 1000 Cmid A P 100
10 Daily flow (ML)Daily flow
1 0246810 % time flow is exceeded
Figure 4-5. Daily flow duration curves under scenarios A, C and P for lower end of flows for each end of system flow gauge - (a) Fords Bridge; (b) Cuttaburra Ck and (c) Norooma & Widgeegoara Ck
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 41 Table 4-9. Cease-to-flow percentiles for scenarios P, A and C
Outflow Name P A Cwet Cmid Cdry Fords Bridge 57.2% 40.7% 43.5% 38.8% 37.0% Cuttaburra Creek 55.6% 43.6% 47.7% 41.8% 37.9% Norooma & Widgeegoara Creek 0.6% 0.6% 1.0% 0.5% 0.4%
4.3.5 Surface water indicators
Inflows
There are several ways that the total inflows into the river system can be calculated. The obvious way would be to sum all of the inflows in the model. For the Warrego IQQM this is 605 GL/year (Figure 4-6). However, a large proportion of g the inflow is indirectly gauged (Table 4.6) and therefore estimated as part of model calibration. The approach used to calibrate these inflows varies considerably between model implementations. In some cases inflows are inflated and subsequently compensated for by loss relationships and in other cases the losses are inherent in the inflows. Because of these different approaches to calibration, totalling inflows does not provide a consistent assessment of total river system inflows across different models. stem modellin y An alternative to simply totalling modelled inflows is to locate the point of maximum average annual flow in the river s r system under pre-development conditions. As all river models are calibrated to achieve mass balance at mainstream gauges, the gauge with maximum average annual flow is a common reference across all models irrespective of how mass balance is calibrated. The pre-development scenario largely removes the influences of upstream extractions and 4 Rive regulation and gives a reasonable indication of total inflows without the influence of development. It is noted that in some cases even the pre-development scenario may include small impacts from water diversions where these are reflected in the historic streamflow observations to which the models predicting inflows are calibrated.
Each of the scenarios can be cross-checked against the pre-development scenario by adding to the maximum average flow upstream, net evaporation losses from public storages, and any upstream diversions minus any upstream returns (net upstream diversions). The three end of system subcatchments with distributary rivers (Warrego, Cuttaburra Creek and Widgeegoara-Noorama Creeks) were summed together to get a total flow for the distributaries. For reaches with discharges the discharge flow, less the discharge loss, was added back to flows in that sub-catchment and subsequent downstream catchments. A comparison between scenarios for reaches along the Warrego River are presented in Figure 4-6 which shows that the maximum average annual mainstream flow occurs at the Wyandra gauge (423203) with a value of 423 GL/year for the pre-development Scenario (P) and 422 GL/year for the baseline Scenario A.
700 C range 600 Cmid A 500 P 400
300
200 Annual flow (GL) flow Annual 100
0 4232040 4232011 4232031 4232021 4230041 EOS total
Figure 4-6. Transect of total river flow under scenarios P, A and C
Water availability
The water availability indicator shows the change in water availability relative to the baseline scenario of historic climate and current development. It is the ratio of mean annual flow under a given scenario to the mean annual flow under Scenario A, calculated at the location of the maximum average annual mainstream flow as defined in Table 4-10.
42 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Table 4-10. Annual water availability under Scenario C relative to Scenario A
A Cwet Cmid Cdry GL/y % change relative to Scenario A 422.4 47% -7% -30%
A time series of annual water availability under Scenario A is shown in Figure 4-7. The lowest annual water availability was 12 GL in 1977 while the greatest annual water availability was 2669 GL in 1989. Figure 4-8 shows the differences from Scenario A in annual water availability of Scenario C. Note as there are no major regulating structures upstream of the Wyandra Gauge the numbers presented in Figure 4-7 and Figure 4-8 are not influenced by regulation. ie s 4 River ) 3000
2500
2000 y tmmodellin stem 1500
1000
500
Annual water availability (GL availability water Annual 0 1895 1915 1935 1955 1975 1995 g
Figure 4-7. Scenario A water availability ) 2500 C range 2000 Cmid 1500 1000 500 0 -500 -1000
Annual water availablity (GL availablity water Annual -1500 1895 1915 1935 1955 1975 1995
Figure 4-8. Water availability under Scenario C relative to Scenario A
Level of development
The level of development assumed in the Warrego river model is indicated by the ratio of total net diversions to total inflows. Total net diversions are defined as the net water diverted for the full range of water products. This indicates the share of the available water that is diverted for consumptive use. Once again the most reliable indicator of the total inflow is point of maximum mainstream average annual flow.
Net diversions are used to reflect the change in mass balance of the system. They do not take into consideration the difference in water quality that may exist between diversions and returns. In the case of the Warrego River model no returns are modelled.
Table 4-11 shows the level of development indicators for each of the states and in total and for each of the scenarios. The level of development in the river model is relatively low compared to the rest of the Murray-Darling Basin with 12 percent of the water total resource being diverted under Scenario A and a three percent increase under Scenario Cdry.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 43 Table 4-11. Relative level of development under scenarios A and C
A Cwet Cmid Cdry Queensland 11% 8% 11% 13% New South Wales 1% 1% 2% 2% Total 12% 9% 13% 15%
Level of use
Table 4-12 shows the average level of use for all water products, as well as the average annual level of use for the lowest one, three and five-year periods for Scenario A and the percentage change from Scenario A for each other scenario. These figures indicate the impact on water use during dry periods.
Table 4-12. Indicators of level of use under Scenarios A and C g A Cwet Cmid Cdry GL/y % change relative to scenario A Lowest 1-year period 11.3 5% -15% -19% Lowest 3-year period 24.2 7% -8% -15%
stem modellin Lowest 5-year period 26.5 12% -4% -13% y
s Average 51.5 12% -3% -12% r
Non-diverted water 4 Rive There are several ways of considering the relative level of impact on non-diverted water and diversions. Table 4-13 presents two indicators for relative impact on non-diverted water:
x the average annual non-diverted water as a proportion of the maximum mainstream average annual flow x as proportion of the maximum mainstream average annual flow for Scenario A
For the Queensland portion of the region the current Water Resource Plan (WRP) requires that 89 percent of the long- term average cross border flows compared against pre-development cross border flows. Table 4-14 shows the change in cross border flows for each of the scenarios.
x The change in this ratio for each of the scenarios is also shown. Note the numbers quoted in the WRP are based on a different modelling period (1889-1999).
Figure 4-9 combines the results from water availability, level of development and non-diverted water into a bar chart. The size of the bars indicates total water availability and the sub-division of the bars indicates the diverted and non-diverted fractions.
Table 4-13. Relative level of available water not diverted for use under Scenarios A and C
A Cwet Cmid Cdry Non-diverted water as a percentage of total available water 88% 91% 87% 85% Non-diverted share relative to A Scenario non-diverted share 100% 151% 93% 68%
Table 4-14. Change in cross border flows under scenarios A and C
Queensland water reporting region P A Cwet Cmid Cdry GL/y % relative to pre-development flows Proportion of cross border flow relative to pre-development 217.4 89% 129% 83% 62% cross border flows
44 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 700 Diverted 600 Non diverted 500 400 300 200
Annual waterAnnual (GL) 100 0 P A Cw et Cmid Cdry
Figure 4-9. Comparison of diverted and non-diverted shares of water under Scenarios P, A and C ie s 4 River Reliability
The average reliability of water products can be indicated by the ratio of total diversions to the total long-term average diversion limit or equivalent benchmark. For the Warrego region regulated water use is compared against the nominal y tmmodellin stem volume of 2.612 GL. Use under Queensland unsupplemented access licenses is compared to the 90.88 GL/year limit and use under New South Wales unregulated licenses is compared to the annual pump capacity. In the absence of any clear benchmark the limit for stock and domestic use was defined as the long term average diversion. The average reliabilities are shown in Table 4-15. The 8.1 GL (nominal volume) of unallocated water has not been included within the existing 90.88 GL/year limit. The volumetric limit for this water will not be determined until once the water has been sold. g In most systems there is a difference between the water that is available for use and the water that is actually diverted for use. These differences are due to under utilisation of licenses and water being provided from other sources such as rainfall, surplus flows, on farm storages and groundwater. The difference between available and diverted water will vary considerably across products and time. These indicators represent how much of the available resource is consumed. Figure 4-10 shows the difference between allocated medium security water at the 30 April of each year (representing the highest allocation during a water year) and the medium security use for each of the scenarios in volume reliability plots. Figure 4-11 shows the reliability of unsupplemented access water for Queensland irrigators and unregulated water for New South Wales irrigators for each of the scenarios on the same plot.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 45 (a) (b)
3.0 3.0 2.5 2.5 2.0 2.0 1.5 1.5 Allocated w ater (GL) Allocated w ater (GL) 1.0 1.0 Diversions (GL) Diversions (GL) 0.5 0.5 Annual volume (GL) volume Annual Annual volume (GL) volume Annual 0.0 0.0 0 20406080100 0 20406080100 % of years exceeded % of years exceeded (c) (d) g 3.0 3.0 2.5 2.5
2.0 2.0 1.5 1.5 Allocated w ater (GL) Allocated w ater (GL) 1.0 1.0 stem modellin Diversions (GL) Diversions (GL) y 0.5 0.5 s Annual volume (GL) volume Annual r Annual volume (GL) volume Annual 0.0 0.0 0 20406080100 0 20406080100 % of years exceeded % of years exceeded 4 Rive
Figure 4-10. Reliability of diversions under general security licences - by water product for scenarios (a) A; (b) Cdry; (c) Cmid; and (d) Cwet(a)
(a) (b)
140 10 120 C range 8 100 C mid 80 A 6 60 4 C range 40 Cmid 2 20 A Annual diversionAnnual (GL) Annual diversion (GL) diversion Annual 0 0 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% % of years equal or exceeded % of years equal or exceeded
Figure 4-11. Reliability of unsupplemented access water for (a) QLD and (b) NSW irrigators for each scenario
46 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Table 4-15. Average reliability indicators under Scenarios A and C
A Cwet Cmid Cdry % change from Scenario A License private usage Medium security (nominal volume 2.612 GL/y) 0.97 0% 0% -1% QLD unsupplemented access (volumetric limit 90.88 GL/y) 0.38 22% -7% -18% NSW unregulated access 0.10 2% -1% -3% Stock and domestic 0.91 0% 0% 0%
Table 4-16. Average difference between allocated and diverted medium security usage ie s 4 River A Cwet Cmid Cdry GL/y Allocated water 2.6 2.6 2.6 2.6 y Diversion 2.5 2.5 2.5 2.5 modellin stem Difference 0.1 0.1 0.1 0.1
4.4 Discussion of key findings g The Warrego river system model is configured to represent the full utilisation of licences. This is achieved by configuring nodes with large irrigation areas and large on farm storages. This forces the model to take water whenever the opportunity arises. The amount of water that is taken is constrained by the pump capacity at the irrigation node. Pump capacities are set to reflect the sharing of volumetric constraints. There are several modelling implications of this type of configuration:
1. The irrigation demands do not reflect the change in demand as a function of climatic conditions as there is always a demand for water.
2. Crop areas are fixed at a large number and do not change as function of available water resources.
3. Irrigation usage is not calibrated and consequently modelled usage will be considerably larger than actual usage.
The model only considers supplemented and un-supplemented access from the main river and modelled distributaries. Extractions from the floodplain are not explicitly modelled and are considered in the mass balance as part of the un- attributed losses. The model is not capable of making any assessment to the changes in beneficial flooding of the lower floodplain areas.
The Warrego River model was originally set up by the QDNRW for the period of 1 January 1889 to 31 December 1999. This modelling period was subsequently used in the development of the WRP. The common reporting period for this study is 1 July 1895 to 30 June 2006. Given the variability of flows in the Warrego river system and the impact that individual events can have on results the numbers reported for the WRP may differ from the numbers reported in this study. Table 4-6 shows that the average annual inflow over the original modelling period is 652 GL/yr while for the common modelling period is 605 GL/yr. However when a comparison between pre-development and current cross border flows was made the percentage was identical to the 89 percent reported in the WRP (Table 4-13). This result suggests that this requirement is not influenced by modelling period.
The Warrego system has a low (0.02) degree of regulation (ratio of regulation to average inflow) (Table 4-1). The largest diversion is for un-supplemented irrigation, followed by regulated irrigation in the Queensland part of the region (Table 4.2). Overall the current level of development (ratio of water use to water availability) is only 12 percent (Table 4-11). The most pronounced impact of development is on the cease to flow percentile at the end of the system Figure 4-5 and Table 4-9. For the Warrego River and Cuttaburra Creek end of system cease to flows impacts for development are
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 47 much more significant than climate change. However the impacts on average flow are much more significant for the Cwet scenario Figure 4-6.
Under the climate change median scenario (Cmid), there is a six percent decrease in total inflow (Table 4-10). The effect on diversions is smaller, with up to a four percent decrease in some reaches (Table 4-6 and Table 4-8). The decrease is mostly associated with diversions for un-supplemented irrigation in Qld (Table 4.6). Level of development goes up only slightly from 12 percent to 13 percent (Table 4-11). However, water use in dry years is more affected with the lowest one- year water use decreased by 15 percent (Table 4-12). Overall, the impact of the scenario on water diversion is small, particularly for the supplemented users and the users upstream of Wyandra. The impact of the scenario on water remaining in the system is, on the other hand, greater with a seven percent decrease in non-diverted water (Table 4-13) and a seven percent decrease in end-of-system outflows at both Fords Bridge and Cuttaburra Creek (Table 4-6). However, the percentage of time when flows cease is only slightly reduced (Figure 4-5 and Table 4-9).
Under the climate change wet scenario (Cwet), there is a substantial increase in total inflow by 44 percent (Table 4-6) or g water availability by 47 percent (Table 4-10). This is a very extreme projection. Under the current diversion arrangement, there is only a 13 percent increase in diversion under this scenario (Table 4-6) as irrigators are constrained by pump capacities. Increases in flows remaining in the river system are similar to increases in available water, with the end-of- system flows at Fords Bridge and Cuttaburra Creek increased by 47 percent and 53 percent respectively (Table 4-6).
Under the climate change dry scenario (Cdry), there is a substantial decrease in total flow by 28 percent (Table 4-6) or
stem modellin water availability by 30 percent (Table 4-10). Again this is a very extreme projection. Under the current diversion y
s arrangement, there is a decrease in diversion by 12 percent. The smaller impact on users is due to a smaller change in r the opportunity to pump. For the large events the size is reduced but the amount of water that is diverted is identical. The end of system flows at Fords Bridge and Cuttaburra Creek are reduced in similar ratio to available water i.e.
4 Rive 27 percent and 35 percent respectively (Table 4-6).
The impacts on users upstream of Wyandra gauge and the supplemented water users is small in all scenarios for two reasons: the major usage in the system is downstream of these users and as they have the first opportunity to take the water downstream users get what is remaining after they have taken up to their pump capacity, and the re-regulation of water in the Allan Tannock Weir helps to buffer the impacts of drier climate on the supplemented users.
Pump capacity is limiting the opportunity to take water rather than the availability of flow consequently any increase in flow (Cwet) cannot be taken.
The Water Resource Plan that relates to the Queensland portion of the Warrego requires that at least 89 percent of the average flow into New South Wales is maintained; this implies that a maximum of 11 percent of the average ‘without development’ flow at the border may be diverted in Queensland for use. Given current surface water entitlements in Queensland this requirement is being met. Changes in inflows under future climate would alter the percentage diverted for use. Under the best estimate 2030 climate current Queensland entitlements would represent 12 percent of the ‘without development’ flow at the border. The range for the 2030 climate is from seven percent (wet extreme) to 15 percent (dry extreme). The Queensland Water Act 2000 allows for reviews and/or amendments to be made to water resource plans where there is new evidence indicating that the objectives of the plan are either no longer appropriate or are no longer being met.
The predicted impact of future climate change on the frequency with which flow ceases at the two major end-of-system points is considerably smaller than the level of impact that has already occurred due to water resource development.
48 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 5 Uncertainty in surface water modelling results
This chapter describes the assessment of uncertainty in the surface water modelling results which was conducted to provide an independent comparison for the river modelling results. It has four sub-sections:
x a summary of major issues and observations, and key messages and the uncertainty around the results x an overview of the approach x presentation of results x discussion of key findings.
5.1 Summary 5 Uncertaint
Using multiple lines of evidence, an assessment was made of the uncertainty that is internal to the river model (as opposed to that associated with the scenarios), and the implications that this has for our confidence in the results and their appropriate use. y nsraewtrmodellin water surface in 5.1.1 Issues and observations
x The density, accuracy and completeness of the gauging network in the Warrego are among the lowest in the Murray-Darling Basin. This however, is matched by a low level of water resources development. x The Warrego surface water system is ephemeral and characterised by very variable and infrequent high inflows upstream of Wyandra, and large losses downstream associated with flow spreading out into an extensive low relief floodplain with several distributaries and (almost) terminal wetlands. Regulation and diversion levels are both small to negligible. g
5.1.2 Key messages results
x The internal uncertainty of the model for the Warrego River upstream of Cunnamulla is low. The model provides reasonable estimates of changes in streamflow for the reaches. The uncertainty in future climate predictions is greater than the uncertainty in the river model for the reaches. x The uncertainty in the river model was greater for the lower two reaches, with poor predictions of low flows. This could affect the ability to provide environmental low flow maintenance in the lower reaches and affect water security for diversions from the Warrego downstream of the study region. x Diversions largely rely on flood harvesting, and wetland replenishment relies on peak flows. The model appears adequate to evaluate the response of high flows to rainfall events. x It was not feasible to analyse the model performance for the ungauged distributaries which contribute flows to Yantabulla Swamp, as there was a high uncertainty in predictions of changes in flow into this wetland due to lack of data. x The greatest likelihood for future ‘surprises’ were considered from processes not described by the river model or SIMHYD associated with changes in rainfall-runoff response due to changes in vegetation or landscape condition, and changed vegetation water use patterns. x The uncertainty in river model predictions associated with the possibility that groundwater influences future surface water processes in unexpected ways was considered low due to the low level of groundwater development. ‘Surprises’ associated with river regulation, irrigation and development also appear less likely given the low level of development and the limited flow regulation.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 49 5.2 Approach
5.2.1 General
In Chapter 4, scenarios of climate and/or development were analysed using a river model to assess expected changes in water balance, flow patterns and consequent water security. Uncertainty in that analysis can be formulated in two parts:
x External uncertainty refers to uncertainty external to the model. It includes uncertainty associated with the forcing data used in the model, determined by processes outside the model such as climate processes, land use and water resources development. x Internal uncertainty refers to the uncertainty in predictions that arises because the river model is an imperfect representation of reality. It can include uncertainty associated with the conceptual model, the algorithms and software code it is expressed in, and its specific application to a region (Refsgaard and Henriksen, 2004).
This section only addresses the internal uncertainty in the river model used. Fully quantifying uncertainty is impossible,
results and when scenarios take the model beyond circumstances that have been observed in the past, the quantifiable g uncertainty may only be a small part of the uncertainty (Weiss, 2003; Bredehoeft, 2005). Therefore we combined quantitative analysis with a qualitative interpretation of the adequacy of the model for its purpose (similar to ‘model pedigree’, cf. Funtowicz and Ravetz, 1990; Van der Sluijs et al., 2005). An approach was taken where multiple lines of modellin
r evidence were considered and synthesised to derive an overall assessment of confidence in model performance. These lines of evidence are:
x the quality of the hydrological observation network; x the components of total estimated stream flow gains and losses that are directly gauged, or can easily be attributed using additional observations and knowledge, respectively (through water accounting); x characteristics of model conceptualisation, assumptions and calibration; in surface wate y x the confidence with which the water balance can be estimated (through comparison of water balances from the baseline river model simulations and from water accounting); x measures of the baseline models performance in simulating observed stream flow patterns; and x the projected changes in flow pattern under the scenarios compared to the performance of the model in
5 Uncertaint reproducing historic flow patterns.
None of these lines of evidence are conclusive in their own right. In particular,
x the model may be ‘right for the wrong reasons’, e.g. by having compensating errors; x there is no absolute ‘reference’ truth: all observations inherently have errors, and the water accounts developed here use models and inference to attribute water balance components that were not directly measured; and x adequate reproduction of historically observed patterns does not guarantee that reliable predictions about the future are produced. This is particularly pertinent if model boundary conditions are outside historically observed conditions, such as in climate change studies like this one.
With these limitations, attempts were made to assess the likelihood that the river model provides realistic estimates of the changes that would occur under the scenarios evaluated. Qualitative model assessment is preferably done by expert elicitation (Refsgaard et al., 2007), but the time frame of the project did not allow this. Instead a tentative assessment was made and later adjusted following review by research area experts within and outside the project as well as stakeholder representatives. River model uncertainty needs to be interpreted against the sum of internal and external uncertainty. The range of projections under different scenarios that were evaluated in this study provides an indication of the external uncertainty. Only where internal uncertainty clearly exceeds the external uncertainty will river model improvements help to reduce overall uncertainty. The implication of overall uncertainty for the use of the results presented in this study depends on: (i) the magnitude of the assessed change and the level of threat that this implies; and (ii) the acceptable level of risk (e.g., Pappenberger and Beven, 2006). This is largely a subjective assessment with no judgements made.
50 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 A possible framework for users of the project results to consider the implications of the assessed uncertainties is shown in Table 5-1.
Table 5-1. Possible framework for considering implications of assessed uncertainties
Low threat High threat Current water sharing arrangements Current water sharing arrangements may be appear sufficient for ongoing inadequate for ongoing management of water management of water resources resources, as they do not adequately consider
Low future threats. uncertainty
Current water sharing arrangements Current water sharing arrangements are likely to appear sufficient for ongoing be inadequate for ongoing management of water management of water resources, but resources. Further work to reduce the major
High careful monitoring and adaptive sources of uncertainty can help guide changes management is recommended. to water sharing arrangements. 5 Uncertaint uncertainty
5.2.2 Information sources
Information on the gauging network was obtained from the Water Resources Station Catalogue y
(www.bom.gov.au/hydro/wrsc), the Pinneena 8 data base (provided on CD-ROM by NSW) and the Queensland modellin water surface in Department of Natural Resources and Water web site (www.nrm.qld.gov.au/watershed ). The model calibration report for the Warrego river system model (QDNRM, 2004) was provided by the Queensland Department of Natural Resources and Water. Time series of water balance components as modelled under the baseline scenario (Scenario A) and all other scenarios were derived as described in Chapter 4. The data used in water accounting are described in the following section.
5.2.3 Water balance accounting
Generic aspects of the water accounting methods are described in Chapter 1. This includes a description of the basic g purpose of the accounts which is to inform the uncertainty analysis carried out as part of this study using an independent results set of the different water balance components by reach and by month. The descriptions in Chapter 1 also cover the aspects of the remote sensing analyses for wetland and irrigation water use, as well as the calculations for attribution of apparent ungauged gains and losses. Aspects of the methods that pertain specifically to the Warrego are presented below.
Framework
The available stream flow data for this region was deemed sufficiently complete for water accounting for the water years 1993/94 to 2003/04 only, and therefore the assessment was limited to this 11-year period (July 1993 to June 2004). Water accounts could be established for four successive reaches. The associated catchment areas are shown in Figure 5-1 and are related to model reaches in Table 5-2. Not assessed in water accounting were an internally draining catchment and the head water catchment of the Warrego above Augathella. Furthermore, the river model simulates flow into two distributaries that are not gauged and for which water accounts could therefore not be developed separately (see Figure 5-1). Instead losses to these distributaries were included in the water balance of the associated reaches.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 51 Table 5-2. Comparison of water accounting reaches with reach codes used in the river model (QDNR, 2004)
Water accounting Subcatchment code From To Corresponding reach river model reach(es) 1 423203_1 Augathella Wyandra 2, 3 2 423202_1 Wyandra Allan Tannock Weir 4 3 423004_1 Allan Tannock Weir Barringun 5 4 423001_1 Barringun Fords Bridge 6 Not assessed 423204_0 (headwater) 1, 7, 8, 9 423203_3 (internal) 423424_3 (distributary) 423422_3 (distributary)
Diversion data
Diversion data were supplied by the Queensland Department of Natural Resources and Water. The majority of diversions were estimated as there is little metered data in this region. Diversions were itemised as Irrigation (further classified as Regulated, Unregulated and Water Harvesting), Total Urban, Industrial and Stock, and Floodplain Harvesting. The
results overall quantities in the Warrego are small, and therefore dealt only with the total of diversions. In years where there was g no floodplain harvesting, the total diversion was in the order of 3 GL, whereas in years with significant floodplain harvesting they were between 7 GL and 11 GL. The categories, and hence the summed total, were given as a single figure for the whole of the Warrego. Diversion data were provided as monthly figures for 1995/2005. For 1993/94, modellin
r diversion data were provided as an annual total. For 1994/95, no annual total or monthly data were provided. It was assumed that no diversions occurred in the NSW part of the region.
5.2.4 Model uncertainty analysis
The river model results and water accounts were used to derive measures of model uncertainty. The different analyses
in surface wate are described below. In the interest of brevity, details on the formulas used to calculate the indicators are not provided y here but can be found in Van Dijk et al. (in prep.). Calculations were made for each reach separately, but summary indicators were compared between reaches.
Completeness of hydrological observation network 5 Uncertaint Statistics on how well all estimated river gains and losses were gauged or, where not gauged, could be attributed based on additional observations and modelling were calculated for each reach:
x The volumes of water measured at gauging stations and off-takes, as a fraction of the grand totals of all estimated inflows or gains, and/or all outflows or losses, respectively. x The fraction of month-to-month variation in the above terms. x The same calculations as above, but for the sum of gauged terms plus water balance terms that could be attributed using the water accounting methods.
The results of this analysis were also visually presented as annual totals for interpretation.
Comparison of modelled and accounted reach water balance
The river reach water balance terms, as modelled by the baseline river model (Scenario A) and as accounted, were compared for the period of water accounting. Neither should be considered as an absolute truth, but large divergences are more likely to indicate large uncertainty in river modelling.
52 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 5 Uncertaint y nsraewtrmodellin water surface in g results
Figure 5-1. Map showing the subcatchments used in modelling, with the reaches for which river water accounts were developed (‘accounting reach’) and tributary catchments with gauged inflows (‘contributing catchment’). Shaded areas (‘floodplain and wetlands’) were classified as subject to periodic inundation; small irrigation areas are located inside and just outside subcatchment 4232021. Black dots and lines are nodes and links in the river model respectively.
Performance of the river model in explaining historical flow patterns
All the indicators used in this analysis were based on the Nash-Sutcliffe model efficiency (NSME; Nash and Sutcliffe, 1970) indicator. This indicator calculates the fraction of observed variability in flow patterns that is accurately reproduced
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 53 by the model. In addition to the conventional NSME calculated for monthly and annual outflows, NSME was calculated after log-transformation or ranking of the original data, as well as having been calculated for the ten percent of months with highest and lowest observed flows, respectively. (If the observed flows include months without flow, the long- transformed NSME could not be calculated. Likewise, if more than ten percent of months have zero flows, the NSME for low flows could not be calculated).
Using the same formulas, the ‘model efficiency’ of the water accounts in explaining observed outflows is calculated. This provides an indication of the scope for improving the model to explain more of the observed flow patterns: if NSME is much higher for the water accounts than for the model, then this suggests that the model can be improved upon and model uncertainty reduced. Conversely, if both are of similar magnitude, then it is less likely that a better model can be derived without additional observation infrastructure.
Stream flow patterns at the gauge at the end of the reach were also visually compared with the flows predicted by the baseline river model, and the outflows that could be accounted for (i.e., the net result of all measured or estimated water balance components other than main stem outflow – which ideally should equal main stem outflows in order to achieve mass balance). This was done in the form of monthly and annual time series and monthly flow duration curves. results g Scenario change-uncertainty ratio
Streamflow patterns simulated for any of the scenarios can be used as an alternative river model. If these scenario flows explain historically observed flows about as well or better than the baseline model, than it may be concluded that the modellin r modelled scenario changes are within the model ‘noise’, that is, smaller or similar to model uncertainty. Conversely, if the agreement between scenario flows and historically observed flows is poor – much poorer than between the baseline model and observations – then the model uncertainty may be assumed to be smaller than the modelled change, and the modelled change is detectable with the current model. The metric used to test this hypothesis is the change-uncertainty ratio. The definition was modified from Bormann (2005) and calculated as the ratio of Nash-Sutcliffe Model Efficiency for the scenario model to that for the baseline (scenario A) model. A value of around one or less suggests it is likely that the
in surface wate projected scenario change is not significant when compared to river model uncertainty. A ratio that is considerably y greater than one implies that the future scenario model is much poorer at producing historic observations than the baseline model, suggesting that the scenario indeed leads to a significant change in flow patterns. The change- uncertainty ratio is calculated for monthly as well as annual values, to account for the possibility that the baseline model may reproduce annual patterns well but not monthly. The same information was plotted as annual time series, monthly flow duration curves and a graphic comparison of monthly and annual change-uncertainty ratios for each scenario. 5 Uncertaint
5.3 Results
5.3.1 Density of the gauging network
Figure 5-2 shows the location of stream flow, rainfall, and evaporation gauges in the region, and Table 5-3 provides information on the measurement network. The Warrego region has the second sparsest gauging network of the reporting regions in the Murray-Darling Basin, after the Paroo region. The rainfall gauging network is about three times less dense than the basin average and the stream flow measurement network is about ten times less dense. This is for a region with very high temporal variability in rainfall and streamflow and considerable spatial variability, but with a low level of water resource development. The high variability suggests a greater and denser gauging network would help reduce uncertainty. However, given the low level of development additional gauges are unlikely to be an investment priority.
54 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Table 5-3. Some characteristics of the gauging network of the Warrego region (76,615 km2) compared with the entire Murray-Darling Basin (1,062,443 km2).
Gauging network characteristics Warrego Murray-Darling Basin Number per 1000 km2 Number per 1000 km2 Rainfall Total stations 143 1.87 6,232 5.87 Stations active since 1990 88 1.15 3,222 3.03 Average years of record 48 45 Streamflow Total stations 8 0.10 1,090 1.03 Stations active since 1990 6 0.08 881 0.83 Average years of record 23 20 Evaporation
Total stations 2 0.03 152 0.14 5 Uncertaint Stations active since 1990 1 0.01 104 0.10 Average years of record 32 27
5.3.2 Review of model calibration and evaluation information y
Model description modellin water surface in
The Warrego river model was developed in IQQM and covers the Warrego River to the Darling River confluence (see description in Chapter 4). The model extends beyond the region defined for this project and is therefore considered in this report.
Daily rainfall data was available for the whole of the Warrego River system from 40 rainfall stations and generally for a long period (as early as 1870 in some stations). Evaporation data was available from 14 pan evaporation stations covering different periods starting mostly around 1960. Potential evapotranspiration was assumed to be fairly close to pan evaporation, and therefore pan evaporation data were used directly.
There was no evidence that groundwater interaction has any significant effect on the surface water in the Warrego g
System on a catchment scale and therefore groundwater interaction was ignored. After the model was calibrated results assumptions were made to represent stock and domestic usage, unregulated irrigation, the Allan Tannock Weir, non- licensable man-made storages (excavated tanks and gully dams), and waterholes that occur naturally throughout the Warrego River system.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 55 results g modellin r in surface wate y 5 Uncertaint
Figure 5-2. Map showing the rainfall, stream flow and evaporation observation network along with the subcatchments used in modelling
56 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Model calibration
This section and Table 5.4 summarised the calibration report for the Warrego IQQM (QDNRM, 2004). The calibration was based on stream gauging station records from eight mainstream gauging stations on the Warrego (as well as two mainstream gauging stations on the Darling River that are outside the reporting region) (Table 5-4). Where needed, high flows ratings were extrapolated from low to medium flow discharge measurements. The height data from the automatic recorders were categorised as generally fair to good quality. The following methods and processes were considered:
x Inflows: recorded tributary inflows and calculated local inflows (calculated as outflows minus inflows) were used to calibrate a rainfall-runoff model (Sacramento) that was subsequently used to estimate missing data for the entire period of modelling. Where there was no recorded flow data the rainfall-runoff model was used with parameters from a similar catchment. x Diversions: There was minimal data on historical extractions but diversions were known to be small. Therefore
no diversions were accounted for in model calibration. 5 Uncertaint x Infrastructure: No infrastructure was accounted for in model calibration. The Allan Tannock Weir downstream of the Cunnamulla Township was built in 1991, after the calibration period. Non-licensable man-made storages were assumed to have minimal effect on calibration results due to their size and date of construction relative to the calibration period. y
x Losses: the final step in calibration is simulation of losses (ascribed to floodplain dissipation, evaporation, modellin water surface in seepage and tributary breakout) that are not accounted for separately. These are empirical functions, calibrated to minimise the mismatch between modelled and recorded flow duration curves at the same location.
Table 5-4. Details of stream flow rating uncertainty, calibration and validation periods, number of years between 1895 and 2006 (112 years) with annual rainfall less than the driest and more than the wettest year in the calibration period, respectively, and prior assessment of the models performance (source: QDNR, 2004, with exception of the climate range information).
Reach Downstream % of Calibration Years Years Validation Assessment gauging station stage period out of out of period code and name height 112 112 range drier wetter g rated results 1 423204A 81% 1967-1987 8 5 1992-2002 Model replicates the flow well over a long period, but for (Warrego River the shorter period, 62% overestimation @ Augathella) 2 423201A 49% 1942-1971 0 0 1927-1941 Model replicates the high flows well but not for low flows (Warrego River (<1000 ML/d) @ Charleville) 3 423203A 59% 1968-2002 6 5 1968-1983, Except for very high flows (ten percent overestimation), (Warrego River 1984-2002 the model replicates the flow well and is responsive to @ Wyandra) different time periods. 4 423202C 96% 1992-2002 6 13 None Inaccurate model calibration due to short period of records (Warrego River and large tributary breakout losses @ Allan Tannock Weir) 5 423003 ? 1968-1981 10 10 None Inaccurate model calibration due to short period of records (Warrego River and large tributary breakout losses and difficulty in @ Barringun) modelling low flows 6 423002 ? 1973-2002 6 5 1973-1987, Large transmission losses. The calibration model (Warrego River 1988-2002 replicates the recorded flow quite well. Overestimation and @ Fords Bridge) difficulty in modelling low flows
Model performance assessment
The model was used to simulate the historical runoff and water use for the period 1 January 1889 to 30 June 2002. Statistical comparison generally showed good agreement over the length of record, which includes calibration periods. The results are summarised in Figure 5-3.
Model testing downstream of Fords Bridge gauging station did not occur as no downstream flow data exists and validation is not possible. The quality of the data was judged to be satisfactory over both periods. Some model inadequacies with respect to response to low flow regimes occurred, but it was deemed this would not be able to be resolved without longer periods of flow record, more sophisticated model structure, and additional information on regional
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 57 groundwater levels. While limited stream flow data meant that broad assumptions were necessary, the model was considered still able to provide useful qualitative results (QDNRM, 2004).
The Warrego IQQM model was identified as having areas of weakness adding to the uncertainty of the model (QDNRM, 2004). These were mainly related to a general lack of data, and sensitivity analysis was recommended to assess the uncertainty associated with each of the following areas:
x In-stream storages: The rainfall-runoff models were calibrated without considering the effect of the storages. When the storages where added they reduced the flows reaching the gauges, and compensation inflows were added. For scenarios, this method may introduce some error if different storages are used. x Losses on the ungauged break-outs and further reach break-up. x Flow passing through unlicensed storages, extractions, and water harvesting operations. x Groundwater impacts, especially in the headwater catchments connected to the Great Artesian Basin.
5.3.3 Model uncertainty analysis results g The calculated indicators of calibration climate range are listed in Table 5-4. Otherwise all other indicators and results are listed by reach in Appendix C. This section provides a summary of those assessments. modellin
r Completeness of hydrological observation network
The effectiveness of gauging for each river reach is shown in Figure 5-3. Most of the ungauged losses could be attributed to river floodplain and wetland losses, which are inherently hard to gauge. The magnitude of these losses agreed with remote sensing-based estimates, and losses increased towards the lower reaches. Because losses dominate the river water balance in the lower reaches, the fraction of the total water balance (the sum of reach gains and losses) that was gauged also decreased. Remote sensing is probably the most practical way of estimating diffuse losses. in surface wate y It was concluded that a considerable part of the water balance is ungauged, and there are other observations– directly or through models – that can be used to at least qualitatively understand the water balance with a reasonable degree of confidence. As such the hydrology of the catchment can be considered to be reasonably well understood.
5 Uncertaint (a) (b)
1.0 1.0 inflows/gains
0.8 0.8 variance inflows/gains 0.6 0.6 outflows/losses 0.4 0.4 Fraction attributed Fraction gauged variance 0.2 0.2 outflows/losses
0.0 total flow 0.0 25 30 35 40 45 components 25 30 35 40 45
Cumulative catchment area (x1000 km2) variance total flow Cumulative catchment area (x1000 km2) components
Figure 5-3. Patterns along the length of the river (expressed as the cumulative contributing catchment area) of indicators of the fraction of inflows/gains, outflows/losses and the total of water balance components that is (a) gauged or (b) could be attributed in the water accounts.
Comparison of modelled and accounted reach water balance
A summary of the regional water balance simulated by the river model and derived by water accounting is listed in Table 5-5. In both cases, numbers are averages for the period 1993 to 2004 to allow direct comparison. To aid interpretation, it is worthwhile noting that:
58 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 x The stream flow data used at Fords Bridge does not include the bypass flows which are included in the modelling (C.Johansen, pers. comm.). This affects the comparison between the modelled outflows and the accounted outflows. x Classification suggested that the estimated total area of ephemerally inundated floodplains and wetlands in the reach considered for water accounting was 20,660 km2, while the area of irrigated land was estimated at 11.6 km2. Due to the classification approach these should be considered maximum estimates. Also, areas classified as irrigated land were not necessarily entirely cropped each year. x In the water accounts, distributary outflows are included in river and floodplain losses, because none of the distributaries had sufficient gauging data for water accounting. x Neither the river model nor the water accounts include stream flow losses to groundwater recharge, because no data were available to constrain such estimates. (see Discussion of Key Findings 5.4). Linear scaling of SIMHYD monthly runoff estimates proved insufficient to explain the pattern of ungauged
x 5 Uncertaint inflows into the Reach 1 (Augathella to Wyandra). Visual inspection showed that this was because the SIMHYD estimates underestimated peak flows and overestimated low flows. On the basis of this, the estimates were transformed non-linearly.
The following conclusions can be drawn when comparing modelled and accounted water balance: y
x 377 GL/y or 26 percent of total estimated gains and losses could not be attributed (Table 5-5; note that this modellin water surface in includes all noise, i.e. errors in measurements as well as in the estimation of monthly water balance components). x Total modelled inflows were 63 percent higher than the total of inflows that could be attributed. Of the total 377 GL/y unattributed gains and losses 148 GL/y were associated with ungauged gains and 113 GL/y with ungauged losses in Reach 1 (Augathella to Wyandra). This reflects issues in reproducing (apparent) local runoff generation using the SIMHYD estimates in this reach (Table 5-5, Reach 1, Appendix C). x Diversions simulated by the river model reflect potential diversions assuming full entitlement utilisation, and as such are almost seven times greater than best estimates of historical diversions. However diversions represent
small numbers in any case: modelled diversions are <5 percent and estimated values one percent of total g
inflows or losses (Table 5-5). Therefore uncertainty in diversion estimates is unlikely to affect modelled stream results flow patterns.
Table 5-5. Regional water balance modelled and estimated on the basis of water accounting
Water balance (Jul 1993 – Jun 2004) Model (A) (GL/y) Accounts (GL/y) Difference (GL/y) Main stem inflows 44 43 1 Tributary inflows 0 0 0 Local inflows 849 505 343 Subtotal gains 893 549 344 Unattributed gains and noise - 188 687 End of system outflows 73 28 45 Distributary outflows 456 0 456 Net diversions 42 6 36 Net river flux to groundwater 0 0 0 River and floodplain losses 60 517 -465 Unspecified losses 260 - 260 Subtotal losses 892 551 341 Unattributed losses and noise - 189 637
Climate range calibrated
The number of years outside the calibrated annual rainfall range varied between reaches, from 0 to 20 years out of 112. Generally, the number of years that were wetter than those included in the calibration were similar to the number that were drier (Table 5-4). The climate range calibrated is least for the two reaches between Wyandra and Barringun (19–20
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 59 years outside calibration range). By comparison, the historic rainfall record had six years that were drier and five years that were wetter than the extremes during the period of water accounting 1993–2004.
Overall, the calibration period for the upper reaches and for the water accounting period appear to provide a reasonable representation of historic rainfall conditions (88 percent to 90 percent of historical variability in annual rainfall). For the Warrego River between Wyandra to Barringun the climate range was more limited (82 percent to 83 percent). Wetter and drier years occurred in comparable numbers.
Performance of the river model in explaining historic flow patterns
The better the baseline model simulates stream flow patterns, the greater the likelihood is that it represents the response of river flows to changed climate, land use and regulation changes (notwithstanding the possibility that the model is right for the wrong reasons through compensating errors).
In Appendix C, indicators are listed reach by reach of the models performance in reproducing different aspects of the patterns in historically measured monthly and annual flows (all are variants of Nash-Sutcliffe model efficiency). In Figure 5-4, these different indicators are shown for each reach along the river. The Warrego river model explained observed results
g patterns very well in the upper catchment, but less well in the lower two reaches. These reaches are strongly losing reaches (~70–80 percent of average inflow is lost in each reach) and therefore it appears that the model simulates these losses less well.
For the lowest reach, it was demonstrated that there is considerable uncertainty in the balance of local inflows and modellin r (floodplain) losses as simulated by the model, and this may well explain the lesser model performance in simulating end of system flows, although the omission of bypass flows in the accounting needs to be considered here. This was confirmed by the model evaluation by QDNRM (2004; Table 5-4).
1.0 monthly - normal 0.8 in surface wate y monthly - ranked 0.6
0.4 monthly - high flow s Model efficiency Model 0.2 5 Uncertaint annual - normal 0.0 25 30 35 40 45 annual - ranked Cumulative catchment area (x1000 km 2)
Figure 5-4. Changes in the model efficiency (the relative performance of the river model in explaining observed streamflow patterns) along the length of the river (expressed as the cumulative contributing catchment area).
Scenario change-uncertainty ratio
The ratios of change over uncertainty are shown in Figure 5-5. A high ratio corresponds with a scenario change in flows that is likely to be significant given the uncertainty, or noise, in the model, and a value of around one means that the modelled change is of similar magnitude as the uncertainty in the model.
The modelled changes are considerably greater than uncertainty for the upper reaches, but less so for the lower ones (Figure 5-5) because the model is less uncertain in upper reaches. Perhaps unsurprisingly, given the small diversions, the flows simulated under the pre-development (P) scenario do not appear significantly different from baseline flows. The climate change scenarios signal can be considered strong in the top two reaches, but less so in the lower two reaches. Only the Cwet scenario shows a relatively strong change signal in the lower two reaches. It is noted that the small irrigation uses as well as the identified environmental assets are located in the lower two reaches.
60 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 1000 1000
100 100
10 10
1 1 Change-uncertainty ratio 0 Change-uncertainty ratio 0 25 30 35 40 45 25 30 35 40 45 Cumulative catchment area (x1000 km2) Cumulative catchment area (x1000 km2)
P Cwet Cmid Cdry P Cwet Cmid Cdry 5 Uncertaint Figure 5-5. Pattern along the river (expressed as cumulative river catchment area) of the ratio of the projected change over the river model uncertainty for the different scenarios modelled for (a) monthly and (b) annual flows
5.4 Discussion of key findings y nsraewtrmodellin water surface in 5.4.1 Completeness of the gauging network The hydrology of the Warrego surface water system is very sparsely gauged: the rainfall, evaporation and stream flow gauging network is amongst the sparsest in the Murray-Darling Basin (Section 5.3.1). The accuracy of the stream flow gauging stations in the gaining upper section of the river has been assessed as fair to good quality, but the quality of the stage measurement and rating curve for the losing lower section is unclear (Section 5.3.2). Less than 60 percent of the total of river reach gains and losses was estimated to be directly measured for three of the four river reaches that were analysed (Section 5.3.3). Most diversions occur in the reach that is well gauged.
5.4.2 Conceptual understanding of regional surface hydrology g
Despite the sparseness of the gauging network, the conceptual understanding of the current hydrology of the Warrego results surface water system appears reasonable. The Warrego surface water system is ephemeral and characterised by very variable and infrequent high inflows upstream of Wyandra, and large losses downstream associated with flow spreading out into an extensive low relief floodplain with several distributaries and (almost) terminal wetlands. Most losses can be accounted for using additional information. Regulation and diversion levels are both small to negligible (5.3.3).
Groundwater development is very limited at present and there was no groundwater model for the region (Chapter 6). As a consequence, neither the river model nor water accounts included an estimate of surface water-groundwater exchanges. A qualitative estimate of its potential importance in explaining wetland and floodplain losses can be derived as follows. The total losses from floodplains and wetlands in these four reaches was estimated at 508–517 GL/y from an estimated area of 20,660 km2 . This suggests stream flow losses equate to ~25 mm/y averaged over the floodplain area. Groundwater recharge rates would be expected to be in the order of a few millimetres per year, and therefore may therefore represent in the order of 50 GL/y or 10 percent of total floodplain and wetland losses. Uncertainty associated with the possibility that groundwater influences future surface water processes in unexpected ways is rated as low.
Surprises associated with river regulation, irrigation and development would also appear less likely given the low level of development, and the limited possibilities for flow regulation.
There may be more internal model uncertainty in assumptions about runoff generation that are implicit in the river modelling methodology. River inflows in this region are a very small fraction of rainfall and produced by a small number of events (Chapter 3), and end of system outflows in turn are a small fraction of runoff (Chapter 4). Therefore, small changes in rainfall, evapotranspiration and/or floodplain and wetland losses can potentially lead to large relative changes in outflow patterns. Potential surprises that the river modelling, or SIMHYD predictions, have not addressed include changes in rainfall-runoff response due to changes in vegetation or landscape condition, bushfires and changed vegetation water use patterns (Chapter 3).
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 61 5.4.3 Performance and uncertainty in aspects of the river model The sparse gauging network does lead to considerable quantitative uncertainty in the river model. Water accounting for the river system between Augathella to Fords Bridge left 26 percent of total gains and losses unattributed, split about half-half between gains and losses. About two-thirds (261 GL/y out of 377 GL/y) of these occur in the strongly gaining reach 1 (between Augathella and Wyandra). However, estimated diversion, river and floodplain losses in this strongly gaining reach appear limited and therefore local runoff can arguably be inferred from the existing gauges (Section 5.3.3), which is confirmed by the generally good performance of the river model in reproducing flows observed in the upper two reaches (Section 5.3.2 and below).
More problematic are the lower reaches. Prior assessment (QDNRM, 2004) considered that the model calibration was inaccurate for the section between Wyandra and Fords Bridge, due to the generally short calibration period, large tributary breakout losses and difficulty in reproducing low flow patterns (Section 5.3.2). The range of annual rainfall variability included in the river model calibration was narrower than for the upper reaches (Table 5-4). Comparison with observed flow confirms that the river model does not reproduce low flow patterns very well at Barringun, and perhaps overestimates end-of-system flows at Fords Bridge. For the end-of-system-flow however, the occurrence of bypass flows that are simulated by the model need to be considered (C. Johanssen, QDNR, pers. comm.). Gauging data for the results g bypass channel were not available at the time of constructing the accounts. Comparison between the water accounts and the modelled river balance suggested rather large uncertainty for this lowest reach in particular. The model simulated considerable local inflows and losses that partially compensated each other over longer time scales (both in the order of 170 GL/y), whereas the water accounting suggested much smaller local inflows (38 GL/y) and floodplain and modellin r wetland losses (90 GL/y). This could have implications for planning diversions from the Warrego River downstream of this region which are considered in the Barwon-Darling region.
Diversion is dominated by flood harvesting and therefore not directly metered. The river model used in the assessment simulated potential diversions for full entitlement realisation rather than historical or current diversion levels. Estimates of historical diversions provided by QDNR suggest that the model overestimated diversions almost seven times. Because diversions are such a small component of the water balance, it is not expected that this will have had an important effect in surface wate y on modelled stream flow patterns.
5.4.4 Implications for use of the results of this study The changes in flow pattern predicted under the scenarios were greater than the uncertainty in modelling for the two upper reaches, but changes were small compared to model uncertainty for the lower reaches. Only the Cwet scenario 5 Uncertaint showed a change that was greater than model uncertainty.
The internal uncertainty of the river model was considered sufficiently small to provide estimates of changes in stream flow conditions for the Warrego River above Cunnamulla with modest uncertainty. The uncertainty in the river model was greater for the lower two reaches. Changes in average flows under future scenarios was assessed to have an uncertainty that is similar or greater than the predicted change, and the river model does not adequately reproduce low flow patterns.
Diversions largely rely on flood harvesting and replenishment relies on peak flows. The model appears adequate to evaluate the response of high flows to rainfall events.
Analysis of the model performance for the ungauged distributaries, which also contribute flows to Yantabulla Swamp, was not conducted. The uncertainty in the predictions of changes in flow into this wetland are therefore high due to lack of data alone.
The internal uncertainty and external uncertainty associated with future development were both assessed to be small when compared to the large natural variability in large rainfall events and the range of climate change predictions. Model improvements may therefore not reduce the uncertainty in prospective decision making much.
5.5 References
Bormann H (2005) Evaluation of hydrological models for scenario analyses: Signal-to-noise-ratio between scenario effects and model uncertainty. Advances in Geosciences 5, 43–48. Bredehoeft J (2005) The conceptual model problem—surprise. Hydrogeology Journal 13, 37–46.
62 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Funtowicz SO and Ravetz J (1990) Uncertainty and Quality in Science for Policy. Kluwer Academic Publishers, Dordrecht. Kirby JM, Mainuddin M, Podger G and Zhang L (2006a) Basin water use accounting method with application to the Mekong Basin. In: Sethaputra S and Promma K (Ed.s), Proceedings on the International Symposium on Managing Water Supply for Growing Demand, Bangkok, October 2006, Bangkok, Thailand. pp 67–77. Kirby JM, Mainuddin M, Mobin-ud-Din A, Marchand P and Zhang L (2006b) Water use account spreadsheets with examples of some major river basins. In: Proceeding of the 9th International River Symposium. Kirby M et al. (2007) River reach water balance accounts across the Murray-Darling Basin (1990-2006). A report to the Australian Government from the CSIRO Murray-Darling Basin Sustainable Yields Project. CSIRO, Australia. In prep. Nash JE and Sutcliffe JV (1970) River flow forecasting through conceptual models 1: a discussion of principles. Journal of Hydrology 10, 282–290. McVicar TR and Jupp DLB (2002) Using covariates to spatially interpolate moisture availability in the Murray-Darling Basin. Remote Sensing of Environment 79, 199–212. Pappenberger F and Beven KJ (2006) Ignorance is bliss: Or seven reasons not to use uncertainty analysis. Water Resources Research 42. QDNRM (2004). Warrego River System Hydrology Volume 1. Calibration Of Daily Flow Simulation Model From Upstream Of Augathella (Qld AMTD 447.4km) To Darling River (NSW AMTD 0 Km). Hydrology Report 423002.PR/1, Surface Water Group. Queensland
Department of Natural Resources and Mines. 5 Uncertaint Refsgaard JC and Henriksen HJ (2004) Modelling guidelines–terminology and guiding principles. Advances in Water Resources 27, 71– 82. Refsgaard JC, van der Sluijs JP, Brown J and van der Keur P (2006) A Framework for dealing with uncertainty due to model structure error. Advances in Water Resources 29, 1586–1597. Van der Sluijs, JP, Craye M, Funtowicz S, Kloprogge P, Ravetz J and Risbey J (2005) Combining quantitative and qualitative measures
of uncertainty in model based environmental assessment: the NUSAP System. Risk Analysis 25, 481–492. y
Van Dijk AIJM (2006) Climate variability impacts on the already stretched Murray-Darling Basin water system – assessment and policy modellin water surface in implications. In: Proceedings of the World Water Week, Stockholm, Sweden. Van Dijk AIJM and Mattersdorf G (2007) Comparison of MODIS-based scaling of potential evapotranspiration with on-ground observations. Geophysical Research Abstracts 9. Van Dijk AIJM et al. (2007) River model uncertainty assessment. A report to the Australian Government from the CSIRO Murray-Darling Basin Sustainable Yields Project. CSIRO, Australia. In prep. Walker WE, Harremoës O, Rotmans J, van der Sluijs JP, van Asselt MBA, Janssen P, Krayer von Krauss MP (2003). Defining uncertainty a conceptual basis for uncertainty management in model-based decision support. Integrated Assessment 4, 5–17. Weiss C (2003) Expressing scientific uncertainty. Law, Probability and Risk 2, 25–46. g results
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 63 6 Groundwater assessment
As noted in the Introduction, the groundwater resources of the Warrego were assigned a very low priority in the context of the Basin-wide project due to the comparatively low level of groundwater use and limited potential for groundwater to impact on streamflow. Due to this low priority the groundwater assessments for the Warrego were limited to providing an overview of the hydrogeological setting including surface-groundwater connectivity, and describing the current and potential future level of groundwater use. It is noted that while these limited assessments are appropriate with the constraints and for the terms of reference of this project, additional work may be required for local management of groundwater resources.
6.1 Summary
6.1.1 Issues and observations assessment r x The groundwater management units in the Warrego have been assessed as very low priority in the context of the overall project on the basis of the size of the aquifers, the level of development and the assumed degree of connectivity with the surface water system.
x Assessment of the water resources of the deeper confined aquifers of the Great Artesian Basin are beyond the scope of this project. 6 Groundwate 6.1.2 Key messages
x The groundwater systems in the Warrego include some shallow alluvial and sandstone aquifers and the deeper confined aquifers of the Great Artesian Basin. Water quality in nearly all aquifers is poor relative to surface water and is generally only suitable for stock and domestic use. x The deeper groundwater systems are largely unconnected to the shallow systems or the river. Groundwater use in the Warrego has little impact on streamflow relative to total streamflow. x Groundwater use is low, particularly from the shallow aquifers for which use represents less than 0.1% of total groundwater use in the MDB. x Groundwater extraction is unlikely to increase significantly in the future. x Given the low level of use, the generally low water quality and the lack of connection to the river, climate change does not present a risk to groundwater in the Warrego.
6.1.3 Uncertainty
x The limited assessments undertaken for groundwater in the Warrego are appropriate given the size and importance of the resource, and are sufficiently reliable for Basin-wide planning purposes.
6.2 Groundwater management units – hydrogeology and connectivity
The Warrego region is underlain by consolidated sandstones, shales and mudstones that constitute the multi-layered aquifers of the Great Artesian Basin (GAB). The GAB is overlain with alluvial sediments up to 30 m thick. There are no GMUs in the Queensland portion of the region. The GMUs of the New South Wales portion of the region are the GAB GMU, an Upper Darling Alluvium GMU and a GAB Alluvial GMU (Table, 6.1; Figure 6.1). These GMUs are managed through the Water Act (1912) with the rules and proposed extraction limit values from the draft NSW Groundwater Macro Plan, whereas the confined aquifers of the GAB are covered by the GAB Water Sharing Plan.
64 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 rudae assessment 6 Groundwater
Figure 6-1. Map of groundwater management units
Apart from some minor stream infiltration to the very north of the Queensland portion of the region (where GAB aquifers outcrop) and direct infiltration of GAB recharge beds in the headwaters of the Warrego River, there is no rainfall recharge to GAB aquifers within this region. In the New South Wales part of the region the aquifers are artesian to sub-artesian and rainfall will not infiltrate (DWE). The GAB groundwater systems are considered to be unconnected to the shallow aquifers and the river, and hence there is very little impact on streamflow. The freshwater, semi-permanent Warrego
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 65 River Waterholes and Yantabulla Swamp are generally believed to be replenished by floodwater, and existing information makes no reference to the role of groundwater in their hydrology (http://wiserivers.nationalparks.nsw.gov.au/).
The northernmost GAB aquifers show variable water levels and good quality groundwater (Skelt et al., 2004), but quality declines to the south. The water in the shallow alluvial aquifers (at 6–10 m below ground level) is believed to be mostly saline to brackish – although data is limited. Due to the low quality these aquifers are little utilised, being only suitable for stock and domestic use. Water use from the alluvial and shallow sandstone aquifers represents less than 0.1% of the total groundwater use in the MDB. Greater use is made of artesian water from the GAB, although once again this is limited to stock and domestic use due to the quality of the water. As an indication of the level of GAB use, the combined Warrego-Paroo-Nebine region in Queensland is allocated only one percent of the total Queensland MDB groundwater allocation, of which approximately 74 percent is to GAB bores, 23 percent is to shallower sandstone aquifers and only three percent is to the alluvial systems. Overall, groundwater use in the Warrego is minor and has not led to declining groundwater levels in the shallow systems; however, early development and wastage of the GAB aquifers caused significant (100 m) drawdown of artesian water pressures before capping under the GAB Sustainability Initiative reduced wastage and has allowed artesian water pressures to recover (Power et al., 2007).
.
Table 6-1. Categorisation of groundwater management units including annual extraction, entitlement and recharge details in New South Wales assessment r
Code Priority Name Extraction 2004– Entitlement Long term average Recharge ranking 2005 extraction limit
GL/yr N601 very low GAB unknown 1 na* na*
6 Groundwate N63 very low GAB Alluvium unknown 0.02 1.3 2.1 N46 very low Upper Darling Alluvium unknown 0.2 1.7 3.4 * not available
6.3 References
DWE, (in prep.) New South Wales Groundwater Macro Plan, Department of Water and Energy. Skelt K, Ife D and Hillier J. 2004. Murray Darling-Basin Groundwater Status 1990-2000 Catchment Report: Warrego-Paroo Catchment, Murray Darling Basin Commission, Canberra. Power RE, Biggs AJW and Burton DWG (2007). Salinity Audit – Warrego and Paroo Catchments, Queensland Murray-Darling Basin. Department of Natural Resources and Water, Queensland.
66 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 7 Environment
This chapter describes the major water-related environmental assets in the region for which scenario assessments have been possible. It has four sub-sections:
x a summary of major issues and observations, key messages and the uncertainty of the results x an overview of the approach x presentation of results x discussion of key findings
7.1 Summary 7 Environment
7.1.1 Issues and observations
x The low degree of water resource development and extraction means the Warrego is a relatively natural hydrological system and this is likely to be reflected in the health of its wetland and aquatic ecosystems. The Warrego supports higher fish abundances and a richer fish assemblage than other rivers in the Murray-Darling Basin (Gehrke et al., 1995).
x However, the river and wetland ecosystems of the Warrego are poorly investigated and understood compared with many other parts of the MDB. Limited assessments have only been undertaken for two of the several wetlands listed for the region in the Directory of Important Wetlands in Australia – the Warrego River Waterholes and Yantabulla Swamp.
7.1.2 Key messages
x The frequency of low-minor beneficial flooding events in Yantabulla Swamp has not been affected by the current low levels of water resource development.
x The average period between low-minor flood events in the Yantabulla Swamp increases by ten percent for the best estimate 2030 climate change scenario. The primary vegetation communities at Yantabulla Swamp are adapted to extended dry periods and would be unlikely to change in distribution under this scenario. However, the condition of this vegetation association might be affected. The reduction in flood frequency might also have an adverse effect on waterbird usage and breeding.
x For the dry extreme climate change scenario the average period between low-minor flood events in the Yantabulla Swamp increases by 43 percent (nine months). It is considered very likely that this level of change would affect the condition of the vegetation and the frequency of waterbird breeding. The wet extreme climate change scenario would cause a 29 percent reduction in the average period between flood events. This would be of benefit to wetland habitat and waterbirds.
x The frequency of flow events that allow beneficial connecting of the Warrego River Waterholes has not been affected by current levels of irrigation diversions.
x The average period between connecting flow events for the waterholes increases by nine percent under the best estimate climate change scenario, increases by 48 percent under the dry extreme climate scenario and falls by 37 percent under the wet extreme climate scenario. Increases in the average period – especially the dry extreme result – would be likely to lead to a reduction in the frequency of successful reproduction of native fish including bony bream, catfish and yellow belly due to the decreased frequency and longer period between events. Both extreme results would be likely to lead to changes in the fish population structure of the Warrego River.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 67 7.1.3 Uncertainty
The main uncertainties involving analysis and reporting include:
x Aquatic and wetland ecosystems are highly complex and many factors in addition to water regime can affect ecological features and processes, such as water quality and land use practices. x The indicators are based on limited hydrologic parameters with no direct quantitative relationships for environmental responses. This study only makes general observations on the potential implications of changed water regimes and some related ecological responses. x Using two assets and two indicators for each to represent overall aquatic ecosystem outcomes is a major simplification. Actual effects on these and other assets or localities are likely to vary. x Uncertainties expressed in Chapters 3, 4 and 5 affect the hydrologic information used in the environmental assessments.
7.2 Approach
The Directory of Important Wetlands in Australia (Environment Australia, 2001) lists many wetlands in the Warrego region including: 7 Environment
x Lake Dartmouth Area (QLD168) x Warrego River Distributary System (QLD169) x Warrego River Waterholes (Charleville-Wyandra) (QLD171) x “Old Bando” Swamp (QLD 172) x Green Creek Swamp (NSW013) x Willeroo Lake (NSW018) x Yantabulla Swamp (Cuttaburra Basin) (NSW019) x Dick Lake (NSW150) x Birdsnest Swamp (NSW163) x Bottom Lila Lake (NSW164) x Lake Yandaroo (NSW165) x Racecourse Swamp (NSW166) x Toms Lake (NSW168) x Yarran Swamp (NSW169)
From these, two environmental assets were identified – the Warrego River Waterholes and Yantabulla Swamp – for which literature is available to identify a clear connection between ecological condition and flows in the Warrego River. The studies of Kingsford et al. (2002) and Balcombe et al. (2006), as outlined in this chapter, provide information on these connections.
68 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 7 Environment
Figure 7-1. Location map of environmental assets
The descriptions of these two environmental assets are based on information from the Directory of Important Wetlands in Australia (Environment Australia, 2001), or other sources as cited.
7.2.1 Yantabulla Swamp (Cuttaburra Basin) (code NSW019)
Yantabulla Swamp is part of the Cuttaburra Basin system. Most of the inflow to the Swamp is from Cuttaburra Creek, which flows from the Warrego River. However, the area also receives water from the Paroo overflow (see Paroo regional report from this project), as well as Clarks Creek and Brindingabba Creek which are more localised sources. The swamp covers over 37,000 ha and floods on average every three years (Kingsford et al., 1994). The main vegetation communities are Cane Grass (Eragrostis australiasica), Lignum (Muelhlenbeckia florulenta), fringing Yapunyah (Eucalyptus ochrophloia), River Red Gum (E. camaldulensis), Coolibah (E. coolibah) and river cooba (Acacia stenophylla).
The swamp is an important breeding habitat for the Freckled Duck (Stictonetta naevosa), a vulnerable species in New South Wales, and other waterbird species protected under international treaties. Kingsford et al. (1994) identified Yantabulla Swamp as the most important waterbird breeding site of 30 wetlands in the north-west of New South Wales during the period 1987 to 1990. At times the Swamp provides for over 40,000 waterbirds and for over 30 species (Kingsford et al. 1994). Kingsford et al. (1997) also identified Yantabulla Swamp as one of the most important wetlands in the Murray Darling Basin, particularly for waterbirds.
Land tenure for the swamp is Western Lands lease with grazing the predominant land use. Disturbance to the swamp is localised and mostly from stock trails and at stock watering points.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 69 7 Environment
Figure 7-2. Satellite image of Yantabulla Swamp (Cuttaburra Basin)
7.2.2 Warrego River Waterholes (Charleville-Wyandra) (code QLD171)
The Warrego River Waterholes are a string of large, permanent and intermittent waterholes and billabongs covering some 500 ha along the Warrego River channel in Queensland, between Charleville to south of Wyandra. These sites receive flooding from the river on a seasonal basis and in most years. Many of the sites provide habitat for aquatic fauna- invertebrates, fish, turtles and birds. River Red Gum (Eucalyptus camaldulensis), Coolibah (E. coolibah) and river cooba (Acacia stenophylla) woodlands and lignum (Muelhlenbeckia florulenta) understorey are the dominant vegetation communities. Significant waterbird populations are known to inhabit the waterholes, particularly after flooding. Seasonal flooding is a primary hydrological feature but with a mix of intermittent and more permanent inundation for the swamps and waterholes. The deeper more persistent waterholes provide drought refuges. Waterbirds are common including ducks, pelicans, cormorants and large waders.
Land tenure around the waterholes is mostly leasehold with grazing the main land use. Disturbance is mostly due to grazing activities and use of the waterholes for watering points by stock. Substantial populations of European carp (Cyprinus carpio) are likely to occur in the waterholes and impact adversely on native fish species.
70 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 7 Environment
Figure 7-3. Satellite image of Warrego River Waterholes Charleville-Wyandra
7.2.3 Summary of environmental flow rules
Queensland Water Resource Plans do not establish specific environmental water allocations; rather environmental water is protected via water access rules such as pumping thresholds. The Water Resource (Warrego, Paroo, Bulloo and Nebine) Plan 2003 (QDNR, 2003) establishes the following performance indicators for environmental flow objectives:
1. end of system flow 2. low flow 3. summer flow 4. beneficial flooding flow 5. one in two-year flood.
End of system flows – both for the region and for the Queensland portion of the region – are reported on in Chapter 4. Both of the hydrological indicators defined below relate to the categories of ‘beneficial flooding’ and ‘one in two-year flood’. As explained in Chapter 5, the river system model providing the data for assessing hydrologic change does not provide sufficiently reliable information on low flows and hence these are not assessed. No published studies were available to define ecologically relevant hydrological indicators specifically for ‘summer flow’.
There is no equivalent Water Sharing Plan for the New South Wales portion of the Warrego River and no environmental flow provisions have been established at this time.
7.2.4 Environmental indicators
Yantabulla Swamp
Kingsford et al. (2002) provides information on the general hydrology, flood inundation using satellite images and waterbirds on the wetlands of the Warrego and Paroo River systems. Kingsford et al. (2002) also investigated relationships between river flows at Wyandra and inundation extend for the period 1983 to 2000 for the Cuttaburra Basin (including Yantabulla Swamp). A number of high flows between about 65 GL/month and 2,400 GL/month at Wyandra were investigated. Flows of around 146 GL/month were considered a ‘low-minor event’ while the 2400 GL/month was a major event.
The 146 GL/month flow was selected for use in this study. As a low-minor event it is likely to represent a ‘commence to flood’ level for Yantabulla Swamp. Satellite image analysis in Kingsford et al. (2002) indicates the Cuttaburra Basin is
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 71 inundated at these flow volumes. Floods of a larger magnitude, but reduced frequency, would provide broader wetland flooding and likely filling of Yantabulla Swamp.
It is important to note that the monthly indicator may underestimate the frequency of flooding for the swamp when an event commences late in one month and spans into the next month where neither month reaches a total discharge of 146,000 ML, but where the combined total for the event does exceed 146 GL. The importance of these month spanning events was tested, and the relative difference between scenarios in the number of events is consistent with the more easily calculated and interpreted monthly based indicator presented by Kingsford et al. (2002).
The average and maximum period between occurrences of low to minor events that wet the Yantabulla Swamp are calculated. These measures are useful as a major lengthening in the periods between inundations could result in altered vegetation structure and adversely affect fish and birdlife.
Warrego River Waterholes
A survey of native fish was carried out along the Warrego River from October 2001 to May 2003 at sites from downstream of Charleville to near the New South Wales border, with a focus on waterholes, including sites in the Warrego River Waterholes (Balcombe et al., 2006). This study found ten species of native fish and three species of exotic fish, and provided evidence for the importance of the waterholes to these fish during dry and low flow periods, as well as for the importance of high flow periods for fish response. 7 Environment During the study a high flow event occurred in January 2002 which established hydrological connectivity between the study waterholes. Balcombe et al. (2006) considered this event was important for redistributing the previously isolated fish assemblage. Also this event was associated with recruitment by native fish, bony bream (Nematolosa erebi), catfish (Neosilurus hyrtii) and yellowbelly (Macquaria ambigua).
The January 2002 flow event peaked at around 17 GL/day at Charleville and was therefore selected as the indicator for assessment. As for Yantabulla Swamp, the period between events in the Warrego River Waterholes is also reported. It is noted that other aspects of the hydrologic regime are expected to be important for the ecology of the waterholes, in particular the frequency and duration of no-flow periods and subsequent drying. However, as noted in Chapter 5, the river system model does not model low flows well at Charleville, and a robust assessment of changes in low flows under the different scenarios was not possible.
Table 7-1. Definition of environmental indicators
Name Description Yantabulla Swamp Average period between flows in excess of 146,000 ML/month at Wyandra (gauging station 423203) indicators Maximum period between flows in excess of 146,000 ML/month at Wyandra (gauging station 423203)
Warrego River Water Average period between flows in excess of 17,000 ML/d at Charleville (gauging station 423201) Holes indicators Maximum period between flows in excess of 17,000 ML/d at Charleville (gauging station 423201)
7.3 Results The projected changes in the chosen environmental indicators are listed for the various scenarios in Table 7-2. These were assessed using scenario outputs for the Wyandra and Charleville gauges from the Warrego river system model (see Chapter 4).
Table 7-2. Values of environmental indicators for scenarios P and A, and percentage changes from Scenario A for the remaining scenarios
P A Cdry Cmid Cwet Yantabulla Swamp indicator 146,000 ML/month Months Percent change from A average period between events 21 21 43% 10% -29% maximum period between events 97 97 14% 22% 0% Warrego River Waterholes indicator 17,000 ML/day Days average period between events 524 524 48% 9% -37% maximum period between events 2905 2905 3% 3% 0%
72 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 7.4 Discussion of key findings
Yantabulla Swamp
The frequency of low-minor events in the Yantabulla Swamp has not been affected by the current low levels of water resource development.
The average period between low-minor events in the Yantabulla Swamp increases by ten percent for the best estimate climate change scenario. The primary vegetation communities at Yantabulla Swamp (eg. Lignum, Cane Grass and Coolibah) are adapted to extended dry periods and would not be likely to change in distribution under this scenario. However, the condition of this vegetation association might be affected due to less frequent flooding. The reduction in flood frequency might also have an adverse effect on waterbird usage and breeding.
For the dry extreme climate change scenario the average period increases by 43 percent (nine months) relative to 7 Environment Scenario A. It is considered very likely that this level of change would affect the condition of the vegetation and the frequency of waterbird breeding. The wet extreme climate change scenario suggests a 29 percent reduction in the average period between flood events, which would be of benefit to wetland habitat and waterbirds.
The maximum period between low to minor events in the Yantabulla Swamp increases 14 percent in the dry extreme climate change scenario, and increases by around 22 percent in the best estimate climate change scenario. However, this increase in maximum period for the best estimate climate change scenario is due to a single event in ‘1903’ which is very close to the threshold across all scenarios, and slightly under the threshold for the best estimate climate change climate scenario. Taking account of this ‘near-event’ showed that the maximum period between events is in fact very similar across all climate change scenarios and Scenario A.
Warrego River Waterholes
The frequency of water hole-connecting flow events has not been affected by current levels of irrigation diversion, which in any case mostly occur downstream of Charleville.
The average period between waterhole wetting events, and the changes under the climate scenarios, are similar to those for Yantabulla Swamp. The average period between event increases by nine percent under the best estimate climate change scenario, increases by 48 percent under the dry extreme climate scenario, and falls by 37 percent under the wet extreme climate scenario. Increases in the average period – especially the dry extreme result – would be likely to lead to a decrease in the recruitment by native fish including bony bream (Nematolosa erebi), catfish (Neosilurus hyrtii) and yellow belly (Macquaria ambigua) due to the decreased frequency and longer period between events. Both extreme results, however, would be likely to lead to changes in the fish population structure of the Warrego River, with either wetter, more frequently connected waterholes or dryer more isolated waterholes favouring different fish species.
The maximum period between events does not alter significantly between the scenarios.
7.5 References
Balcombe SR, Arthington AH, Foster ND, Thoms MC, Wilson GG and Bunn SE (2006) Fish assemblages of an Australian dryland river: abundance, assemblage structure and recruitement patterns in the Warrego River, Murray-Darling Basin. Marine and Freshwater Research 57, 619–633. Environment Australia (2001) A Directory of Important Wetlands in Australia. Third Edition. Environment Australia, Canberra. Gehrke PC, Brown P, Schiller CB, Moffatt DB and Bruce AM (1995) River regulation and fish communities in the Murray-Darling River system, Australia. Regulated Rivers: Research and Management 11, 363–375. Kingsford RT, Bedward M and Porter JL (1994) Waterbirds and Wetlands in Northwestern New South Wales. National Parks and Wildlife Service Occasional Paper No 19. NSW National Parks and Wildlife Service, Hurstville. Kingsford, RT and Thomas, R (1997) Significant wetlands for waterbirds in the Murray-Darling Basin. NSW National Parks and Wildlife Service, Hurstville. Kingsford RT, Brandis K, Young WJ and Fryar S (2002) Environmental Flows on the Paroo and Warrego Rivers: Progress Report Year 2. Department of Environment and Heritage, Canberra. QDNR (2003) Water Resource (Warrego, Paroo, Bulloo and Nebine) Plan 2003. Queensland Department of Natural Resources.
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 73
Appendix A Rainfall-runoff results for selected subcatchments
Table A-1. Summary of modelling results for the subcatchments under Scenarios A and C
A Cdry Cmid Cwet Modelling Area Rainfall APET Runoff Runoff Runoff Rainfall Runoff Rainfall Runoff Rainfall Runoff catchment km2 mm coeff (%) cont (%) % change % change % change 4230011 5500 328 1607 5.2 2 5 -8 -15 -4 -7 12 54 4230041 3966 331 1627 5.3 2 4 -8 -13 -4 -5 12 49 A
4232011 7959 498 1638 11.1 2 16 -8 -28 -3 -6 10 38 ppendix 4232021 5044 376 1644 5.7 2 5 -8 -28 -4 -6 12 48 4232031 26182 455 1649 9.4 2 44 -8 -28 -3 -6 11 45
4232033 2005 420 1675 8.0 2 3 -8 -23 -3 -4 12 52 A analrnf eut o selected subcatchments for results Rainfall-runoff 4232040 8747 575 1600 5.5 1 9 -8 -27 -3 -11 8 51 4234223 9166 354 1626 5.4 2 9 -8 -16 -4 -5 12 48 4234243 8048 299 1622 4.0 1 6 -7 -10 -4 -4 12 46
76615 422 1633 7.2 2 100 -8 -25 -4 -6 11 46
(a) (b)
4232031 3 Scenario C range Scenario A 2 Scenario Cmid
1 Mean monthly runoff (mm) 0 JFMAMJ JASOND
(c) (d)
4232040 3 Scenario C range Scenario A 2 Scenario Cmid
1 Mean monthly runoff (mm) 0 JFMAMJJASOND
Figure A-1. Daily flow duration curves under Scenarios A and C for mean monthly and daily runoff for subcatchments 4232031 and 4232040
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 75 Appendix A Rainfall-runoff results for selected subcatchments
76 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Appendix B River water modelling reach mass balances
Each scenario starts on 01/07/1895 and ends on 30/6/2006.
Subcatchment 4232040
River system model average annual water balance A Cwet Cmid Cdry GL/y
Storage volume App Initial storage 1.562 1.558 1.559 1.556 ni ie ae modellin water River B endix Final storage 0.236 0.231 0.222 0.206 Average annual change 0.0 0.0 0.0 0.0 Inflows Directly gauged 52.016 78.299 46.077 37.818 Outflows End of system outflow 50.39 76.491 44.495 36.345 Net evaporation natural water bodies 1.638 1.821 1.594 1.485 Sub-total 52.0 78.3 46.1 37.8 Unattributed fluxes
Total 0 0 0 0 g ec mass balances reach Mass balance error (%) -0.05 -0.03 -0.05 -0.06
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 77 Subcatchment 4232011
River system model average annual water balance A Cwet Cmid Cdry GL/y Storage volume Initial storage 6.555 6.536 6.525 6.512 Final storage 6.533 6.457 6.322 5.541 Average annual change 0.0 0.0 0.0 0.0 Inflows Sub-catchments Directly gauged 50.39 76.491 44.495 36.345 Indirectly gauged 163.882 225.56 153.343 117.199 Sub-total 214.3 302.1 197.8 153.5 Diversions QLD Unsupplemented access (volumetric limit 90.88 GL/y) 4.08 4.244 4.069 3.981 Stock and domestic 0.071 0.072 0.072 0.073 Sub-total 4.2 4.3 4.1 4.1 reach mass balances g Outflows End of system outflow 170.097 231.734 158.546 124.277 Net evaporation natural water bodies 7.452 7.851 7.5 7.278
modellin Sub-total 177.5 239.6 166.0 131.6 r Unattributed fluxes
wate Total 32.573 58.151 27.652 17.944 r Mass balance error (%) 0.00 0.00 0.00 -0.01 endix B Rive pp A
78 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Subcatchment 4232031
River system model average annual water balance A Cwet Cmid Cdry GL/y Storage volume Initial storage 20.173 20.121 19.994 19.971 Final storage 10.679 11.785 10.141 9.245 Average annual change 0.1 0.1 0.1 0.1 Inflows Sub-catchments App Directly gauged 170.097 231.734 158.546 124.277 ni ie ae modellin water River B endix Indirectly gauged 327.814 474.711 309.767 235.685 Sub-total 497.9 706.4 468.3 360.0 Diversions QLD Unsupplemented access (volumetric limit 90.88 GL/y) 3.375 3.475 3.35 3.283 Stock and domestic 0.004 0.004 0.004 0.004 Sub-total 3.4 3.5 3.4 3.3 Outflows End of system outflow 414.897 613.121 387.283 286.929 Net evaporation natural water bodies 39.528 45.143 39.079 34.862 Sub-total 454.4 658.3 426.4 321.8 g
Unattributed fluxes mass balances reach Total 40.19 44.776 38.684 34.979 Mass balance error (%) -0.03 -0.02 -0.04 -0.05
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 79 Subcatchment 4232021
River system model average annual water balance A Cwet Cmid Cdry GL/y Storage volume Initial storage 1.603 1.596 1.598 1.594 Final storage 3.527 4.15 3.015 2.828 Average annual change 0.0 0.0 0.0 0.0 Inflows Sub-catchments Directly gauged 414.897 613.121 387.283 286.929 Indirectly gauged 35.312 52.275 33.25 25.295 Sub-total 450.2 665.4 420.5 312.2 Diversions QLD Unsupplemented access (volumetric limit 90.88 GL/y) 12.389 14.446 11.854 10.173 Stock and domestic 0.008 0.008 0.008 0.008 Sub-total 12.4 14.5 11.9 10.2 reach mass balances g Outflows End of system outflow 339.639 483.551 318.993 240.106 Effluent outflow 92.475 160.427 84.229 57.427
modellin Net evaporation natural water bodies 5.66 6.919 5.42 4.482 r Sub-total 437.8 650.9 408.6 302.0
wate Unattributed fluxes r Total 0 0 0 0 Mass balance error (%) 0.01 0.01 0.01 0.01 endix B Rive pp A
80 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Subcatchment 4230041
River system model average annual water balance A Cwet Cmid Cdry GL/y Storage volume Initial storage 5.7 5.7 5.7 5.7 Final storage 4.966 5.016 4.957 4.921 Average annual change 0.0 0.0 0.0 0.0 Inflows Sub-catchments App Directly gauged 339.639 483.551 318.993 240.106 ni ie ae modellin water River B endix Indirectly gauged 6.129 9.131 5.838 5.307 Sub-total 345.8 492.7 324.8 245.4 Diversions Licensed private diversions Medium security (nominal volume 2.612 GL/y) 2.528 2.532 2.522 2.513 QLD Unsupplemented access (volumetric limit 90.88 GL/y) 14.149 16.833 13.645 11.588 Sub-total 16.7 19.4 16.2 14.1 Stock and domestic QLD unsupplemented access 0.007 0.007 0.006 0.006 Sub-total 16.7 19.4 16.2 14.1 g
Outflows mass balances reach End of system outflow 68.183 93.394 64.215 51.009 Effluent outflow 257.341 375.758 240.858 176.793 Sub total 325.5 469.2 305.1 227.8 Net evaporation Cunnamulla Weir 2.326 2.405 2.417 2.427 Natural water bodies 1.215 1.732 1.15 1.06 Sub-total 3.5 4.1 3.6 3.5 Sub-total 329.1 473.3 308.6 231.3 Unattributed fluxes Total 0 0 0 0 Mass balance error (%) 0.00 0.00 0.00 0.00
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 81 Subcatchment 4234243
River system model average annual water balance A Cwet Cmid Cdry GL/y Inflows Indirectly gauged 128.032 194.401 119.163 84.213 Diversions QLD Unsupplemented access (volumetric limit 90.88 GL/y) 4.676 5.492 4.553 3.856 Outflows End of system outflow 82.648 126.569 76.789 53.839 Unattributed fluxes Total 40.707 62.34 37.821 26.518 Mass balance error (%) 0.00 0.00 0.00 0.00
Subcatchment 4234223
reach mass balances River system model average annual water balance A Cwet Cmid Cdry g GL/y Storage volume Initial storage 0.03 0.03 0.03 0.03 modellin r Final storage 0.03 0.03 0.03 0.03 Average annual change 0.0 0.0 0.0 0.0 wate r Inflows Indirectly gauged 92.475 160.427 84.229 57.427 Diversions QLD Unsupplemented access (volumetric limit 90.88 GL/y) 3.339 3.715 3.222 2.903
endix B Rive Outflows pp End of system outflow 3.493 6.204 2.997 1.945 A Net evaporation natural water bodies 0.02 0.02 0.02 0.02 Sub-total 3.5 6.2 3.0 2.0 Unattributed fluxes Total 85.616 150.481 77.984 52.553 Mass balance error (%) 0.01 0.00 0.01 0.01
82 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Subcatchment 4230011
River system model average annual water balance A Cwet Cmid Cdry GL/y Storage volume Initial storage 1.124 1.122 1.122 1.121 Final storage 0.361 0.362 0.318 0.318 Average annual change 0.0 0.0 0.0 0.0 Inflows Sub-catchments App Directly gauged 68.183 93.394 64.215 51.009 ni ie ae modellin water River B endix Indirectly gauged 148.703 211.26 139.738 109.068 Sub-total 216.9 304.7 204.0 160.1 Diversions NSW unregulated access 6.914 7.047 6.821 6.741 Outflows End of system outflow 57.174 84.305 53.393 41.569 Net evaporation natural water bodies 3.749 5.285 3.548 3.3 Sub-total 60.9 89.6 56.9 44.9 Unattributed fluxes Total 149.043 208.011 140.19 108.466 g
Mass balance error (%) 0.00 0.00 0.00 0.00 mass balances reach
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 83 Appendix C River system model uncertainty assessment by reach
This Appendix contains the results of river reach water accounting for this region, as well as an assessment of the magnitude of the project change under each scenario compared to the uncertainty associated with the river model. Each page provides information for a river reach that is bounded by a gauging station on the upstream and downstream side, and for which modelling results are available. Table C-1 provides a brief explanation for each component of the results page.
Table C-1. Explanation of components of the uncertainty assessments
Table Description Land use Information on the extent of dryland, irrigation and wetland areas.
Land use areas are based on remote sensing classification involving BRS land use mapping, water resources infrastructure and remote sensing-based estimates of actual evapotranspiration. Gauging data Information on how well the river reach water balance is measured or, where not measured, can be inferred from observations and modelling.
The volumes of water measured at gauging stations and off-takes is compared to the grand totals of all inflows or gains, and/or all outflows or losses, respectively. The ‘fraction of total’ refers to calculations performed on average annual flow components over the period of analysis. The ‘fraction of variance’ refers to the fraction of month-to- month variation that is measured. Also listed are the same calculations but for the sum of gauged terms plus water balance terms that could be attributed to the components listed in the ‘Water balance’ table with some degree of confidence.
The same terms are also summed to water years and shown in the diagram next to this table. Correlation with Information on the likely nature of ungauged components of the reach water balance. ungauged gains/losses Listed are the coefficients of correlation between ungauged apparent monthly gains or losses on one hand, and measured components of the water balance on the other hand. Both the ‘normal’ (parametric) and the ranked (or non-parametric) coefficient of correlation are provided. High coefficients are highlighted. Positive correlations imply that the apparent gain or loss is large when the measured water balance component is large, whereas negative correlation implies that the apparent gain or loss is largest when the measured water balance component is small.
In the diagram below this table, the monthly flows measured at the gauge at the end of the reach are compared with the flows predicted by the baseline river model, and the outflows that could be accounted for (i.e., the net result of all measured or estimated water balance components other than main stem outflow – which ideally should equal main stem outflows in order to achieve mass balance) Water balance Information on how well the modelled and the best estimate river reach water balances agree, and what the nature of any unspecified losses in the river model is likely to be.
The river reach water balance terms are provided as modelled by the baseline river model (scenario A) over the period of water accounting. The accounted terms are based on gauging data, diversion records, and (adjusted) estimates derived from SIMHYD rainfall-runoff modelling, remote sensing of water use and simulation of temporary
Appendix C River system model uncertainty assessment by reach storage effects. Neither should be considered as absolutely correct, but large divergences point to large uncertainty in river modelling. Model efficiency Information on the performance of the river model in explaining historic flow patterns at the reach downstream gauge, and the scope to improve on this performance.
All indicators are based on the Nash-Sutcliffe model efficiency (NSME) indicator. In addition to the conventional NSME calculated for monthly and annual outflows, it has also been calculated after log-transformation or ranking of the original data, as well as having been calculated for the 10% of months with highest and lowest observed flows, respectively. Using the same formulas, the ‘model efficiency’ of the water accounts in explaining observed outflows is calculated. This provides an indication of the scope for improving the model to explain more of the observed flow patterns: if NSME is much higher for the water accounts than for the model, than this suggests that the model can be improved upon and model uncertainty reduced. Conversely, if both are of similar magnitude, then it is less likely that a better model can be derived without additional observation infrastructure.
84 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Table Description Change- Information on the significance of the projected changes under different scenarios, considering the performance of uncertainty ratios the river model in explaining observed flow patterns at the end of the reach.
In this table, the projected change is compared to the river model uncertainty by testing the hypothesis that the scenario model is about as good or better in explaining observed historic flows than the baseline model. The metric to test this hypothesis is the change-uncertainty ratio, which is calculated as the ratio of Nash-Sutcliffe Model Efficiency indicators for the scenario model and for the baseline (scenario A) model, respectively. A value of around one or less suggests that is likely that the projected scenario change is not significant when compared to river model uncertainty. Conversely, a ratio that is considerably greater than one implies that the scenario model is much worse in reproducing historic observations than the baseline model, which provides greater confidence that the scenario indeed leads to a significant change in flow patterns. The change-uncertainty ratio is calculated for monthly as well as annual values, to account for the possibility that the baseline model may reproduce annual patterns well but not monthly.
Below this table on the left, the same information is provided in a diagram. Below the table on the right, the observed annual flows at the end of the reach is compared to those simulated by the baseline model and in the various scenarios. To the right of this table, the flow-duration curves are shown for all scenarios. A pni ie ytmmdlucranyassmn yreach by uncertainty assessment model system River C ppendix
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 85 Downstream gauge 423203 Warrego River @ Wyandra Reach 1 Upstream gauge 423204 Warrego River @ Augathella
Reach length (km) 200 This is a strongly gaining reach. FlowsFlows are are dominated dominated by by runoff runoff Area (km2) 26182 immediately following rain. Outflow/inflow ratio 12.44 Net gaining reach Few of the inflows are gauged. Estimated local runoff explains most of the ungauged gains but a considerablemoderate adjustment adjustment was was required. required. There are no diversionsrecorded diversions and ungauged and ungauged losses are losses small. are small. Land use ha % Dryland 2,508,599 96 Baseline model performance is excellent. Accounting also explains Irrigable area - - observed flows very well. Open water* - - River and wetlands 109,561 4 The projected changes are much greater than river model uncertainty. Open water* - - * averages for 1990–2006
Gauging data Inflows Outflows Overall 3000 and gains and losses unattributedgauged Fraction of total gainslosses Gauged 0.07 0.82 0.45 2000 ungauged Attributed 0.77 0.83 0.80 gains Fraction of variance 1000 Gauged -0.11 0.84 0.37 gaugedGL gains Attributed 0.95 0.96 0.95 0 unattributedungauged lossesgains Correlation with ungauged Gains Losses Linear adjustment -1000 ungaugedgauged normal ranked normal ranked lossesgains
Main gauge inflows -0.87 -0.64 -0.02 -0.23 losses (GL/y) losses (GL/y) gains and gains and Reach Reach Tributary inflows - - - - -2000 gaugedGL losses Main gauge outflows -1.00 -0.99 -0.02 -0.01 Distributary outflows - - - - -3000 Recorded diversions - - - -
Estimated local runoff -0.91 -0.87 -0.00 -0.07 Adjusted 222.4% 90/91 91/92 91/92 92/93 92/93 93/94 93/94 94/95 94/95 95/96 95/96 96/97 96/97 97/98 97/98 98/99 98/99 99/00 99/00 00/01 00/01 01/02 01/02 02/03 02/03 03/04 03/04 04/05 04/05 05/06 05/06
10000
1000 gauged accounted model gauged 100 100 accountedaccounted 10 10 model model 1 1 0.1 0.1 0.01
Monthly streamflow (GL/mo) streamflow Monthly 0.01 Monthly streamflow (GL/mo) streamflow Monthly 0.001
0.001 3 6 0 3 7 1 6 7 1 6 8 2 7 0 2 7 4 1 7 4 2 7 5 0 8 1 8 151 335 425 608 79 881 065 156 339 612 79 886 069 342 52 617 800 892 073 25 347 53 622 803 078 4 4 4 45 4 4 4 5 5 52 5 55 5 5 5 6 62 6 6 6 6 6 69 7 7 7 7 7 7 79 8 3 Jul-93342 3 3 3 Jul-943 34700 3 3 Jul-95349 3 3 3 Jul-963 35431 3 3 Jul-9735704 3 3 359 Jul-983 36161 3 3 Jul-9936434 3 3 367 Jul-003 3 3 3 Jul-0137165 3 3 37438 Jul-023 3 377 3 Jul-0337895 3 3
Water balance Model (A) Accounts Difference Model efficiency Model (A) Accounts 10000 Jul 1990 – Jun 2006 Monthly Gains GL/y GL/y GL/y Normal 1.00 0.89 1000 Main stem inflows 44 43 1 Log-normalised - - Tributary inflows 0 0 0 Ranked 0.90 0.49 Local inflows 652 461 191 Low flows only - - 100 Unattributed gains and noise - 148 - High flows only 1.00 0.86 Losses GL/y GL/y GL/y Annual 10 Main stem outflows 547 539 8 Normal 1.00 0.93 Distributary outflows 0 0 0 Log-normalised - - 1 Net diversions 8 0 8 Ranked 0.99 0.85 River flux to groundwater 0 - - River and floodplain losses 47 2 46 Definitions: 0.1 Monthly streamflow (GL/mo) . streamflow (GL/mo) Monthly Monthly streamflow (GL/mo) . streamflow (GL/mo) Monthly Unspecified losses 93 - - - low flows (flows<10% percentile ) : 0.0 GL/mo . streamflow (GL/mo) Monthly Unattributed losses and noise - 113 - - high flows (flows>90% percentile) : 57.7 GL/mo 0.01
Change-uncertainty ratios 0.001 0 20406080100 P B Cwet Cmid Cdry Dwet Dmid Ddry Annual streamflow 1.2 288.8 9.5 38.4 Pecentage of months flow is exceeded Monthly streamflow 1.0 207.4 9.4 22.2
B C D gauged 10001000 45004500 gauged
Appendix C River system model uncertainty assessment by reach + high A - low 40004000 O medium 100 A 100100 35003500 P
B 30003000 P 1010 25002500 Cwet Cwet 20002000 Cmid 11 0.010.01 0.1 0.1 1 1 10 100 1000 15001500 Cdry Cmid Annual streamflow (GL/y) Annual streamflow (GL/y) Annual streamflow (GL/y) 10001000 0.10.1 Dwet Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly 500500 Cdry Dmid 0.010.01 00 Annual Change-Uncertainty Ratio 90/91 90/91 91/92 91/92 92/93 92/93 93/94 93/94 94/95 94/95 95/96 95/96 96/97 96/97 97/98 97/98 98/99 98/99 99/00 99/00 00/01 00/01 01/02 01/02 02/03 02/03 03/04 03/04 04/05 04/05 05/06 05/06 90/91 91/92 92/93 93/94 94/95 95/96 96/97 97/98 98/99 99/00 00/01 01/02 02/03 03/04 04/05 05/06
86 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Downstream gauge 423202 Warrego River @ Cunnamulla Reach 2 Upstream gauge 423203 Warrego River @ Wyandra
Reach length (km) 108 This is a losingmoderately reach. losing reach. Area (km2) 5044 Outflow/inflow ratio 0.76 Most of the inflows are gauged. There are somesmall diversions,recorded diversions, andbut Net losing reach considerableand considerable river riverand andfloodplain floodplain losses. losses.
Baseline model performance is excellent. Accounting also explains Land use ha % observed flows very wellwell. after removing all modelled local runoff. Dryland 316,231 63 Irrigable area - - The projected scenario changes are generally greater than river Open water* - - model uncertainty,uncertainty. although the Cmid scenario is close to uncertainty. River and wetlands 188,149 37 Open water* - - * averages for 1990–2006
Gauging data Inflows Outflows Overall 3000 and gains and losses unattributedgauged Fraction of total 2500 gainslosses Gauged 0.97 0.75 0.86 2000 2000 ungauged A Attributed 0.97 0.93 0.95 gains
Fraction of variance 1500 reach by uncertainty assessment model system River C ppendix 1000 GL Gauged 1.00 0.88 0.94 gauged 1000 gains Attributed 1.00 1.00 1.00 5000 unattributedungauged lossesgains 0 Correlation with ungauged Gains Losses Linear adjustment -1000 ungaugedgauged normal ranked normal ranked -500 lossesgains
Main gauge inflows -0.01 -0.33 -0.97 -0.78 (GL/y) (GL/y) losses losses and and gains gains Reach Reach -1000 GL Tributary inflows - - - - -2000 gauged losses Main gauge outflows -0.06 -0.16 -0.94 -0.68 -1500 Distributary outflows - - - - -2000-3000 Recorded Diversions -0.17 -0.25 -0.05 -0.07 Estimated local runoff -0.07 -0.15 -0.60 -0.48 Adjusted -100.0% 90/91 91/92 91/92 92/93 92/93 93/94 93/94 94/95 94/95 95/96 95/96 96/97 96/97 97/98 97/98 98/99 98/99 99/00 99/00 00/01 00/01 01/02 01/02 02/03 02/03 03/04 03/04 04/05 04/05 05/06 05/06
100001000
1000 gaugedgauged gauged accounted model 100 10010 accountedaccounted 10 10 model 1 0.11 0.1 0.1 0.01
Monthly streamflow (GL/mo) 0.01 0.001Monthly streamflow (GL/mo) 0.001
0.00111 33 55 5 6 8 0 0 1 3 5 6 7 9 1 11 22 44 66 66 77 4 6 77 88 00 2 2 3 55 77 77 8 0 2 2 5 7 8 3 0 0 5 8 77 0 4 2 1 1515 2424 33 42 51 88 97 06 52 61 7070 7979 88 52 61 70 89 98 07 16 25 34 43 53 479 533 543 561 643 670 680 725 807 3434 Jul-933434 34343 34344253434516 Jul-943463460834734700347903 3488134 Jul-953497334 3506535 35156351 352435247 Jul-96335339335431353552 353 Jul-973535 3535 35835 359359 Jul-983606936069 3616136161 3625136251 3634236342 Jul-99364343 3652636 366136 336 Jul-003368 3636892 3636982 3737073 Jul-01373716 373 37337 3743837 Jul-023753037 37622376 37712377 37803 Jul-03378937895 379837987 33807
Water balance Model (A) Accounts Difference Model efficiency Model (A) Accounts 10000 Jul 1990 – Jun 2006 Monthly Gains GL/yGL/yGL/yNormal 0.991.00 1000 Main stem inflows 547 539 8 Log-normalised - - Tributary inflows 0 0 0 Ranked 0.97 0.70 Local inflows 16 0 16 Low flows only - - 100 Unattributed gains and noise - 15 - High flows only 0.99 0.99 Losses GL/y GL/y GL/y Annual 10 Main stem outflows 391 407 -16 Normal 0.99 0.99 Distributary outflows 158 0 158 Log-normalised - - 1 Net diversions 11 6 6 Ranked 0.94 0.94 River flux to groundwater 0 - - River and floodplain losses 3 109 -106 Definitions: 0.1 Monthly streamflow (GL/mo) . Unspecified losses 0 - - - low flows (flows<10% percentile ) : 0.0 GL/mo Monthly streamflow (GL/mo) . Unattributed losses and noise - 37 - - high flows (flows>90% percentile) : 49.6 GL/mo 0.01
Change-uncertainty ratios 0.001 0 20406080100 P B Cwet Cmid Cdry Dwet Dmid Ddry 0 20406080100 Annual streamflow 0.7 28.7 3.1 15.1 Pecentage of months flow is exceeded Monthly streamflow 1.0 12.2 2.6 6.3
B C D gauged 1000 100 25002500 gauged + high A - low A O medium 100 20002000 P 10 B P 10 15001500 Cwet 1 Cwet 0.01 0.1 1 10 100 Cmid 1 10001000 0.01 0.1 1 10 100 1000 Cdry Cmid
0.1 (GL/y) streamflow Annual 0.1 Annual streamflow (GL/y) 0.1 500500 Dwet Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly Cdry Dmid 0.01 0.01 00 Annual Change-Uncertainty Ratio 90/91 90/91 91/92 91/92 92/93 92/93 93/94 93/94 94/95 94/95 95/96 95/96 96/97 96/97 97/98 97/98 98/99 98/99 99/00 99/00 00/01 00/01 01/02 01/02 02/03 02/03 03/04 03/04 04/05 04/05 05/06 05/06
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 87 Downstream gauge 423004 Warrego River @ Barringun #2 Reach 3 Upstream gauge 423202 Warrego River @ Cunnamulla
Reach length (km) 100 This is a strongly losing reach. Most of the inflow is gauged. Area (km2) 3966 Estimated local runoff is very small. There are fewno recorded diversions. diversions. Outflow/inflow ratio 0.21 Ungauged losses are large and attributed to river and floodplain Net losing reach losses.
Baseline model performance is modest.modest; Accountinghigh flows are explains reproduced Land use ha % observedmoderately flows well, moderately. but low flows are not simulated very well. Accounting Dryland 19,265 5 explains observed flows well. Irrigable area - - The projected changes are of similar order to the uncertainty for CH Open water* - - andThe CMprojected scenarios, changes and aregreater of similar than uncertaintyorder to the for uncertainty B and CL for CH River and wetlands 377,375 95 scenarios.and CM scenarios, and greater than uncertainty for B and CL Open water* - - scenarios. * averages for 1990–2006
Gauging data Inflows Outflows Overall 18002000 and gains and losses unattributedgauged 1600 Fraction of total 1500 gainslosses Gauged 0.95 0.20 0.58 1400 ungauged Attributed 0.97 0.94 0.96 1000 1200 gains Fraction of variance Gauged 1.00 0.15 0.57 1000500 gaugedGL gains Attributed 1.00 1.00 1.00 800 0 unattributedungauged 600 lossesgains Correlation with ungauged Gains Losses Linear adjustment -500400-500 ungaugedgauged normal ranked normal ranked 200 lossesgains -1000-1000
Main gauge inflows -0.03 -0.03 -1.00 -0.84 (GL/y) (GL/y) losses losses and and gains gains Reach Reach (GL/y) losses and gains Reach Tributary inflows - - - - 0 gaugedGL -1500-1500 losses Main gauge outflows -0.47 -0.35 -0.72 -0.65 -200 Distributary outflows - - - - -2000-2000-400 Recorded Diversions - - - - Estimated local runoff -0.61 -0.35 -0.12 -0.26 Adjusted -67.3% 90/91 90/91 90/91 91/92 91/92 91/92 92/93 92/93 92/93 93/94 93/94 93/94 94/95 94/95 94/95 95/96 95/96 95/96 96/97 96/97 96/97 97/98 97/98 97/98 98/99 98/99 98/99 99/00 99/00 99/00 00/01 00/01 00/01 01/02 01/02 01/02 02/03 02/03 02/03 03/04 03/04 03/04 04/05 04/05 04/05 05/06 05/06 05/06
1000 gauged accounted model 100 gauged
10 10 accounted 1 1 model 0.1 0.1 0.01 gauged accounted model
Monthly streamflow (GL/mo) 0.01 Monthly0.001 streamflow (GL/mo)
0.001 1 3 5 8 0 0 1 3 5 6 7 9 6 6 7 9 1 1 2 4 2 2 3 5 7 7 8 0 7 8 4 3 5 4 3 4 3 3 3 15 79 88 97 06 15 24 97 06 16 25 07 16 25 34 470 479 488 579 588 597 698 707 807 3415134Jul-9334243342 34335343 34425 34516 Jul-94346034608 334700 343 343 Jul-9534 35 35135 35235 Jul-9635339353 35431 35521 35612 Jul-9735704 33579 33588 353 Jul-9836 36 36 363 Jul-9936434364 36526 36617 36708 Jul-0036800 368936892 3 373 Jul-0137 37 37 374 Jul-0237530375 37622 37712 37803 Jul-0337895 3798 3
Water balance Model (A) Accounts Difference Model efficiency Model (A) Accounts 1000 Jul 1990 – Jun 2006 Monthly Gains GL/yGL/yGL/yNormal 0.780.83 Main stem inflows 391 407 -16 Log-normalised - - 100 Tributary inflows 0 0 0 Ranked 0.85 0.74 Local inflows 6 6 0 Low flows only - - 10 Unattributed gains and noise - 14 - High flows only 0.52 0.72 Losses GL/y GL/y GL/y Annual Main stem outflows 79 85 -6 Normal 0.80 0.88 1 Distributary outflows 298 0 298 Log-normalised - - Net diversions 15 0 15 Ranked 0.51 0.95 River flux to groundwater 0 - - 0.1 River and floodplain losses 4 316 -313 Definitions: Monthly streamflow (GL/mo) . Unspecified losses 0 - - - low flows (flows<10% percentile ) : 0.0 GL/mo Monthly streamflow (GL/mo) . Unattributed losses and noise - 24 - - high flows (flows>90% percentile) : 22.0 GL/mo 0.01
Change-uncertainty ratios 0.001 0 20406080100 P B Cwet Cmid Cdry Dwet Dmid Ddry Appendix C River system model uncertainty assessment by reach Annual streamflow 1.1 4.5 1.2 1.0 Pecentage of months flow is exceeded Monthly streamflow 0.9 4.0 1.3 0.7
B C D gauged 1000 100 450450 gauged + high A - low 400400 A O medium 100 P 10 350350 B 300300 P 10 250250 Cwet 1 Cwet 0.010.01 0.1 0.1 1 10 100 200200 Cmid 1 0.01 0.1 1 10 100 1000 150150 Cdry Cmid 0.1 Annual streamflow (GL/y) 0.1 Annual streamflow (GL/y) 100100 0.1 Dwet Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly 5050 Cdry Dmid 0.01 0.01 00 Annual Change-Uncertainty Ratio 90/91 91/92 92/93 93/94 94/95 95/96 96/97 97/98 98/99 99/00 00/01 01/02 02/03 03/04 04/05 05/06 90/91 91/92 92/93 93/94 94/95 95/96 96/97 97/98 98/99 99/00 00/01 01/02 02/03 03/04 04/05 05/06
88 ƒ Water availability in the Warrego September 2007 © CSIRO 2007 Downstream gauge 423001 Warrego River @ Fords Bridge Reach 4 Upstream gauge 423004 Warrego River @ Barringun #2
Reach length (km) 141 This is a strongly losing reach. Flows Flows are are dominated dominated by by inflows inflows from from Area (km2) 5500 upstream. Outflow/inflow ratio 0.33 Net losing reach Most of the inflow is gauged. Estimated local runoff explains most of the ungauged gains.gains butThere large are adjustment no recorded of runoffdiversions. model Ungauged estimates waslosses required. are large There and areattributed few diversions. to wetland Ungauged and floodplain losses losses. are large Land use ha % and attributed to wetland and floodplain losses. Dryland 192,715 35 Baseline model performance is modest. Accounting explains Irrigable area - - Baselineobserved model flows moderately.performance The is modest. projected Accounting scenario changesexplains are of Open water* - - observedsimilar order flows to themoderately. uncertainty The for projected Cwet and scenario Cmid scenarios, changes areand of River and wetlands 357,315 65 similargreater order than uncertaintyto the uncertainty for the forCdry CH scenario. and CM scenarios, and greater Open water* - - than uncertainty for BP and CL scenarios. * averages for 1990–2006
Gauging data Inflows Outflows Overall 400 and gains and losses unattributedgauged Fraction of total 300 gainslosses Gauged 0.64 0.21 0.42 ungauged A Attributed 0.92 0.88 0.90 200 gains
Fraction of variance reach by uncertainty assessment model system River C ppendix Gauged 0.52 0.35 0.44 100 gaugedGL gains Attributed 0.94 0.99 0.97 0 unattributedungauged lossesgains Correlation with ungauged Gains Losses Linear adjustment -100 ungaugedgauged normal ranked normal ranked lossesgains -200
Main gauge inflows -0.26 -0.05 -0.92 -0.86 (GL/y) (GL/y) losses losses and and gains gains Reach Reach Tributary inflows - - - - gaugedGL -300 losses Main gauge outflows -0.87 -0.46 -0.19 -0.43 Distributary outflows - - - - -400 Recorded Diversions - - - - Estimated local runoff -0.59 -0.30 -0.02 -0.32 90/91 91/92 92/93 93/94 94/95 95/96 95/96 96/97 96/97 97/98 97/98 98/99 98/99 99/00 99/00 00/01 00/01 01/02 01/02 02/03 02/03 03/04 03/04 04/05 04/05 05/06 05/06
1000
gauged accounted model 100 gaugedgauged 10 accountedaccounted 10 1 modelmodel 1 0.1 0.1 0.01
Monthly streamflow (GL/mo) 0.01 Monthly0.001 streamflow (GL/mo)
0.001 1 3 5 8 0 0 1 3 5 6 7 9 6 6 7 9 1 1 2 4 2 2 3 5 7 7 8 0 7 8 4 3 5 4 3 4 3 3 3 15 79 88 97 06 15 24 97 06 16 25 07 16 25 34 470 479 488 579 588 597 698 707 807 3415134Jul-9334243342 34335343 34425 34516 Jul-94346034608 334700 343 343 Jul-9534 35 35135 35235 Jul-9635339353 35431 35521 35612 Jul-9735704 33579 33588 353 Jul-9836 36 36 363 Jul-9936434364 36526 36617 36708 Jul-0036800 368936892 3 373 Jul-0137 37 37 374 Jul-0237530375 37622 37712 37803 Jul-0337895 3798 3
Water balance Model (A) Accounts Difference Model efficiency Model (A) Accounts 1000 Jul 1990 – Jun 2006 Monthly Gains GL/yGL/yGL/yNormal <00.46 Main stem inflows 79 85 -6 Log-normalised - - 100 Tributary inflows 0 0 0 Ranked 0.68 0.11 Local inflows 174 38 136 Low flows only - - 10 Unattributed gains and noise - 11 - High flows only <0 <0 Losses GL/y GL/y GL/y Annual Main stem outflows 73 28 45 Normal <0 0.71 1 Distributary outflows 0 0 0 Log-normalised - - Net diversions 7 0 7 Ranked 0.72 0.88 River flux to groundwater 0 - - 0.1 River and floodplain losses 6 90 -84 Definitions: Monthly streamflow (GL/mo) . (GL/mo) streamflow Monthly Monthly streamflow (GL/mo) . Unspecified losses 167 - - - low flows (flows<10% percentile ) : 0.0 GL/mo Monthly streamflow (GL/mo) . Unattributed losses and noise - 16 - - high flows (flows>90% percentile) : 5.0 GL/mo 0.01
Change-uncertainty ratios 0.001 0 20406080100 P B Cwet Cmid Cdry Dwet Dmid Ddry Annual streamflow 1.4 3.3 1.0 0.4 Pecentage of months flow is exceeded Monthly streamflow 1.3 3.1 1.0 0.5
B C D gauged 1000 100 400400 gauged + high A - low 350350 A O medium 100 P 10 300300 B P 10 250250 Cwet 1 200200 Cwet 0.01 0.1 1 10 100 Cmid 1 150150 0.01 0.1 1 10 100 1000 Cdry Cmid 0.1 100100 Annual streamflow (GL/y) streamflow Annual Annual streamflow (GL/y) Annual streamflow (GL/y) 0.1 Dwet Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly Monthly Change-Uncertainty Ratio Ratio Change-Uncertainty Monthly 505050 Cdry Dmid 0.01 0.01 000 Annual Change-Uncertainty Ratio 90/91 90/91 90/91 91/92 91/92 91/92 92/93 92/93 92/93 93/94 93/94 93/94 94/95 94/95 94/95 95/96 95/96 95/96 96/97 96/97 96/97 97/98 97/98 97/98 98/99 98/99 98/99 99/00 99/00 99/00 00/01 00/01 00/01 01/02 01/02 01/02 02/03 02/03 02/03 03/04 03/04 03/04 04/05 04/05 04/05 05/06 05/06 05/06
© CSIRO 2007 September 2007 Water availability in the Warrego ƒ 89 Enquiries
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