DOI: 10.25911/v2te-n739
title: Colloff et al. (2024) Data supporting the state of the Murray-Darling Basin report

description: The data is in the form of time series, with graphs, for 27 indicators (in Indigenous, economic, environmental, social and compliance themes).
description: Details of methods and data used for each indicator
Indigenous theme.
Indicator 1. Indigenous water holdings.
We used the total standardised volume of surface water entitlements held by Indigenous organisations based on 2020 data from Hartwig et al. (2021), and 2009 and 2018 data from Hartwig et al. (2020). The 2009 and 2018 data only cover the New South Wales part of the Basin. Therefore, we excluded all other States from the data of Hartwig et al. (2021) to display the temporal change in the New South Wales Basin (Fig. 2.1). Data for the total annual non-environmental entitlement share is from DPE (2023). 
Indicator 2. Volume of environmental water released to wetlands within areas represented by Indigenous organisations
Data on watering actions was from Commonwealth Environmental Water Office (CEWO) annual reports for 2012-13 (DSEWPaC 2013) and from MDBA Basin Plan annual reports on environmental water use by each jurisdiction (Schedule 12, Item 9.3) (e.g. MDBA 2015) from 2013-14 to 2022-23. We calculated the volume of water released annually by CEWO, and its State agency partners in the case of joint watering actions, for flooding flows, identified by the flow component categories of ‘overbank’ and ‘wetland’ in areas represented by Indigenous Organisations. Flow component categories are listed for each environmental watering action in Long Term Intervention Monitoring (LTIM) synthesis reports (e.g. Hale et al., 2020; Appendix 1 therein). Boundaries were based on the definition of Indigenous areas, including Native Title claim areas, Aboriginal Land Councils in New South Wales, Registered Aboriginal Parties in Victoria and Cultural Heritage Bodies in Queensland (Costanza-van den Belt et al. 2022; Figs. 1 & 2 therein). We used flooding flows as these best represent aspects of the flow regime that correspond with the Indigenous concept of cultural flows and the cultural value of water (Moggridge and Thompson 2021; Weir 2009, pp. 119–128).
We included flooding flows for wetlands in the Queensland part of the Condamine–Balonne west of Chinchilla, Border Rivers, Gwydir, Namoi, Macquarie, Barwon–Darling, mid-Lachlan, Victorian central Murray, Goulburn–Broken, Ovens, the Victorian lower Murray and the South Australian Lower Murray between Morgan and Murray Bridge and the Coorong and Lower Lakes. We also included Indigenous Protected Areas (Werai and Toogimbie) and wetlands in which there has been a history of Indigenous engagement with environmental watering (Costanza-van den Belt et al. 2022; Table 1 therein), including flooding flows to Narran Lakes, Barmah-Millewa forests and the Lowbidgee Gayini Nimmie–Caira. We then compared the volume of flooding flows for each of these wetlands with the total volume of environmental flows released by CEWO and calculated the percentage (Fig. 2.2). 
Economic theme.
Indicators 3 and 4. Mean personal income by Basin Local Government Area.
The indicators are: (3) mean personal community (i.e. non-farm) income; and (4) the disparity between LGAs with lowest and highest incomes, i.e. the range. Data were from ABS (2023b). We included mean income for all Local Government Areas (LGAs) that have most of their area within the Basin except where major population centres of LGAs were outside the Basin boundary. We overlayed a map of LGA boundaries (ABS 2023a) with a map of the irrigation districts in the Basin (MDBA 2021a) and divided the Basin LGAs into those containing irrigation districts and those without and those in the Northern Basin and those in the Southern Basin. We used data on mean personal income for LGAs from 2011-12 to 2020-21 (ABS 2023b) and compared the overall mean for irrigation LGAs in the Northern Basin (n = 17) and Southern Basin (n = 22) with those for non-irrigation LGAs in the Northern Basin (n = 17) and Southern Basin (n = 53); excluding unincorporated areas and the ACT (Fig. 2.3). We converted the nominal dollar income (as published by ABS) to real dollars (i.e. adjusting for increases in the Consumer Price Index (CPI) using 2011-12 as the reference year (RBA 2021). As a measure of change in income disparity between LGAs in irrigation districts and non-irrigation LGAs in the Northern and Southern Basin, we calculated annual difference between the means of the five lowest and the five highest LGAs in each of the four categories and expressed these as the range, as a measure of income disparity (i.e. highest mean of mean personal income LGA minus lowest) (Fig. 2.4). 
Indicator 5. Gross value of irrigated agricultural production
Gross value of irrigated agricultural production (GVIAP) in the Basin is reported annually by the Australian Bureau of Statistics up to 2017-18, based on nominal (current) dollar values (ABS 2019), From 2018-19, GVIAP is published as part of the Water Account, Australia series, with 2019-20 as the latest release of data (ABS 2021a). Estimates of GVIAP were not included in the 2021-22 Water Account because the quality of survey responses was lower than required to produce the statistics (ABS 2023c). We reported real value from 2010-11 (the end of the Millennium Drought) to 2019-20 (the most recent year of data available), i.e. adjusting the figures by the CPI using 2010-11 as the reference year (RBA 2021), as well as the GVIAP for the Basin as a percentage of national GVIAP (Fig. 2.4).
Indicator 6. Irrigation water use and production value 
We divided GVIAP, as detailed above, by the total volume of irrigation water use from all sources in the Basin (ABS 2021b) to derive GVIAP per gigalitre of irrigation water used, namely water use productivity (Fig. 2.5).
Indicator 7. Cash income of irrigation farms
Data on annual cash income for cotton, dairy, horticulture and rice farms (2006-07 to 2015-16) was from the ABARES survey of irrigation farms in the Murray–Darling Basin (Ashton 2020). Data on rate of return for cotton (2006-07 to 2017-18), dairy (2006-07 to 2018-19) and rice farms (2006-07 to 2018-19) was from the ABARES Murray–Darling water markets report (Goesch et al. 2020, Fig. 19 therein). Data on rate of return for horticulture (2006-07 to 2015-16) was from (Ashton 2020). We compared change in cash income and rate of return of irrigation farms with the increase in volume of annual environmental water allocations to the Commonwealth Environmental Water Holder (CEWO 2024). 
Indicator 8. Farmland price
Data on annual mean broadacre farmland price ($AU per hectare) for the period 2006-07 to 2022-23 was from ABARES (2024a). We used the mean price for those ABARES regions (ABARES 2024b) contained within, or partly within, the Murray–Darling Basin (121, New South Wales North West Slopes and Plains; 122, New South Wales Central West; 123, New South Wales Riverina; 221, Victorian Mallee; 222, Victorian Wimmera; 223, Victorian Central North; 321, Queensland Eastern Darling Downs; 322, Queensland Darling Downs and Central Highlands and 422, South Australian Murray Lands and Yorke Peninsula), compared with the national mean (Fig. 2.6). We converted the nominal dollar price (as published by ABARES) to real dollars (i.e. adjusting for increases in the Consumer Price Index (CPI) using 2006-07 as the reference year (RBA 2021).
Indicator 9. Surface water diversions
Data on annual metered and estimated surface water take by State and Territory for the period 2012-13 to 2021-22 was from the MDBA 2021-22 annual water take report 2021-22 (MDBA 2023a; Table 3.1 therein). The data represents the sum of surface water take for consumptive purposes from regulated rivers, watercourses (unregulated), floodplain harvesting, commercial plantations and by runoff dams (e.g. MDBA 2023a; Table 3.2 therein). Data from 1999-00 to 2011-12 was from MDBA (2016; Table 2 and Appendix C therein) (Fig. 2.6). Because over 90% of surface water take is for irrigation, we compared take with the area irrigated in the Basin, using data from the annual water use on Australian farms survey (e.g. ABS 2022) between 2005-06 (when data at the Basin scale were first published) and the last survey in 2020-21.
Environmental theme
Indicator 10. Flooding of Ramsar wetlands 
We selected six major wetlands that receive managed environmental flows; three from the southern Basin (Barmah–Millewa, Gunbower–Koondrook–Perricoota) and Riverland) and three from the north (Macquarie Marshes, Gwydir Wetlands and Narran Lakes). Extent of flooding of Ramsar wetlands was determined using Landsat satellite image data obtained from the Digital Earth Australia Wetlands Insight Tool (Dunn et al. 2023; Geosciences Australia 2024). We downloaded .csv files for each wetland feature, which contain the proportion of the site covered with open water and water mixed with vegetation (wet ground). Data on unobstructed open water are derived from the Water Observations from Space (WOfS) algorithm and areas of wetlands that are wet but not identified by the WofS algorithm, i.e. areas of mixed vegetation and water, are based on Tasselled Cap Wetness (Dunn et al. 2023). 
We converted files to Excel spreadsheets and used area data for each wetland contained in the Ramsar Information Sheets (RISs) to calculate for each water year the maximum extent, in hectares, the sum of open water and wet ground for each wetland feature. We used data for the water years 1999-00 to 2020-21. We combined data for the adjacent Barmah Forest and the Millewa Forest group (the latter is part of the New South Wales Central Murray Forests Ramsar Site). Data for the Millewa Group is presented in the Wetlands Insight Tool as four sub-sites (the former State forests of Millewa, Moira, Gulpa Creek and Tuppal [including Deniliquin State Forest]). We also combined data for Gunbower Forest, Koondrook–Perricoota Forest and Campbells Island. (The latter two are also part of the New South Wales Central Murray Forests Ramsar Site). Area data for each sub-site was sourced from NRC (2009; p. 35, Table 2.5). Having estimated combined spatial extent of flooding for Barmah–Millewa and Gunbower, Koondrook–Perricoota and Campbells Island, we then converted the value in hectares back to percentage flood extent, using the data on total area of each wetland mentioned above, and plotted this (Fig. 2.10a). We then calculated change in flood extent between 1999-00 and 2011-12 (pre-Basin Plan) with the period 2012-13 (the first year of implementation of the Basin Plan) and 2020-21 (the last year of available data in the Wetlands Insight Tool). We calculated the number of years of extensive flooding or that were particularly dry, based on maximum annual percentage extent of open water and wet areas that were greater or less than the mean  half a standard deviation, respectively. We then expressed these as the proportion of years extensively flooded or very dry, before and after the Basin Plan (Fig. 2.10b).
Indicator 11. Vegetation condition of Ramsar wetlands 
Leaf area index (LAI) was used as an indicator of the condition of woody vegetation at Ramsar wetlands using remote sensing data obtained from the Centre for Water and Landscape Dynamics, Australian National University (CWLD 2023). We used Australia’s Environmental Explorer (https://www.wenfo.org/aex) to access data on LAI at the same six Ramsar wetlands as for Indicator 10, for the calendar years 2000-2023. We combined data and calculated the mean for Barmah and the Millewa group of forests, for Gunbower, Koondrook–Perricoota and Campbells Island and for the Gwydir Wetlands (Crinolyn, Goddards Lease, Old Dromana and Windella). Because the LAI plots for the wetlands are variable and show no apparent trend (Fig. 2.11a), to obtain an estimate of frequency of high and low LAI, indicating improvement or decline in vegetation condition, we compared the number of years during which LAI was more than one standard deviation greater or lesser than the long-term mean, both before the Basin Plan was implemented (2000-2011) and after (2012-2023) (Fig. 2.11b). 
Indicator 12. River flows
The data represents the percentage difference between observed flows, measured at 27 hydrological indicator sites throughout the Basin, compared with expected flows at the same sites (gigalitres per year), modelled under the Basin Plan. The data covers the seven-year period 2012-13 to 2018-19 (Wentworth Group 2020, Table 2 therein) (Fig. 2.12). 
Indicator 13. Waterbirds
The data for the Basin on abundance and number of breeding species is from the annual Eastern Australian Waterbird Survey (Kingsford et al. 2020; Porter et al. 2020) and its associated database (https://www.unsw.edu.au/research/ecosystem/our-research/rivers-and-wetlands/eastern-australian-waterbird-survey) (Fig. 2.13). Data for 2022 and 2023 were sourced from Porter et al. (2024).
Indicator 14. Threatened species
We used data on the annual frequency of occurrence of five of the eight species selected by Ryan et al. (2021) to assess the effectiveness of environmental flows for threatened species conservation (southern bell frog Litoria raniformis; Australasian bittern Botaurus poiciloptilus; Australian painted snipe Rostratula australis; trout cod Maccullochella macquariensis; and silver perch Bidyanus bidyanus. We did not include Sloane’s froglet Crinia sloanei, Murray hardyhead Craterocephalus fluviatilis or flathead galaxias Galaxias rostratus because these species have highly restricted ranges and there are very few records added annually to the relevant databases.
Annual frequency of occurrence for the calendar years 2012-2023 was derived from records from the Atlas of Living Australia (ALA 2024), which incorporates data from the Victorian Biodiversity Atlas (DELWP 2024) and the New South Wales BioNet Atlas (DPIE 2024a). We downloaded records for each species, removed those from outside the Basin and used the annual number of records for each species as a measure of frequency of occurrence. We corrected for sampling bias, i.e. where multiple records were made for the same sampling event (e.g. on the same day) at the same location and by the same observer, they were counted as a single record. To show a clear time series for each species on the graph, frequency of occurrence was displayed on a log.10 scale after transforming it using (n + 1) to remove zeros (Fig. 2.14). To indicate trend more clearly among the variable data, we added the exponential line of bet fit to each time series.
Indicator 15. Fish kills
We compiled data on fish kills between 1980 and 2023 within the New South Wales Basin using data obtained from the New South Wales Department of Primary Industries fish kill database, which covers the period 1929-2019. Data for the New South Wales Basin since 2019 was published online until March 2023 but was subsequently restricted to the 2023-24 water year (DPIE 2024b). Basin-wide data on events between 1975 and 2019 was collated in the report of the Australian Academy of Science into the 2018–19 fish kills at Menindee but is incomplete (AAS 2019). Data for Victoria is collated by Environment Protection Authority Victoria but is not made public (EPA Victoria 2024). We used four categories of magnitude, based on the estimated number of fishes killed: 1,000-10,000; 10,000-100,000; 100,000-1,000,000 and &gt;1,000,000 (Fig. 2.15).
Indicators 16 and 17. Salinity
The indicators are: (16) electrical conductivity of River Murray waters and (17) mean annual discharge of salt from the Murray Mouth. Data are from MDBA reports on Basin salinity management targets (2010-11 to 2021-22) (e.g. MDBA 2022a). The data for Indicator 16 represents the percentage of days where electrical conductivity (EC) of river water was above the target electrical conductivity (EC) values (in S cm-1) for 95% of the time at five indicator sites: River Murray at Murray Bridge: 830 S cm-1; River Murray at Morgan: 800; River Murray at Lock 6: 580; Darling River at Burtundy: 830 and Lower Lakes at Milang: 1,000; between 2009-10 and 2021-22, based on five-year rolling averages (Fig. 2.16). Indicator 17 represents the discharge of salt over the Lower Lakes barrages to the Coorong and Murray mouth, which was reported annually up until 2018-19 (MDBA 2020a) but subsequently as three-year rolling averages (MDBA 2021b; 2022) (Fig. 2.17). 
Indicator 18. Nutrient pollution
We used data on total Kjeldahl nitrogen (TKN) and total phosphorus (P) concentrations measured at three sites representing the upper, central and lower River Murray (Kiewa River at Bandiana, River Murray at Swan Hill and River Murray at Morgan, respectively), collected as part of the River Murray Water Quality Monitoring Program (MDBA 2021c). Weekly data (2000-01 to 2012-13) and monthly data (2013-14 to 2022-23) for the Kiewa River at Bandiana (site no. 402205) and weekly data for the River Murray at Swan Hill (site no. 409204) were downloaded from the Victorian Government Department of Environment, Land, Water and Planning (DELWP) water monitoring website (https://data.water.vic.gov.au/). Weekly data (2000-01 to 2021-22) for the River Murray at Morgan (site no A4260554) was supplied by the MDBA. We assessed whether nutrient concentrations were above or below water quality target values (defined as annual medians) as detailed in Schedule 11 of the Basin Plan (Commonwealth of Australia, 2012), using values for streams and rivers and names and abbreviations for Target Application Zones therein: Bandiana (A6 Kiewa, lowland): TKN 0.29 mg L-1; P 0.03 mg L-1; Swan Hill (cM1 Central Murray, lower): TKN 0.7 mg L-1; P 0.08 mg L-1; Morgan (1M Lower Murray): TKN 1 mg L-1; P 0.1 mg L-1. We then assessed the proportion of time these standards were exceeded at each site, for TKN concentration (Fig. 2.18a) and total P (Fig. 2.18b).
Indicator 19. Cold water pollution
To assess the effects of mitigation of cold water pollution we compared monthly means of water temperature (2012-13 to 2022-23), recorded as daily means, at the nearest river gauges upstream and downstream of major dams (&gt;350 GL capacity) in the New South Wales Basin (Table S1). with Temperature data was sourced from river gauge data reported by BoM (2024). We calculated the mean monthly difference between upstream and downstream temperature (upstream minus downstream; a positive value indicating downstream is colder and a negative value it is warmer) at dams fitted with cold water pollution mitigation infrastructure and with operating protocols in place (Burrendong, Windamere) and those without (Hume, Keepit, Wyangala), including one with infrastructure but no operating protocol (Burrinjuck) (Fig. 2.19a). The Victorian Basin has no dams fitted with thermal pollution control devices. We then calculated the mean upstream-downstream difference for the summer months (December-February) for each water year from 2012-13 to 2022-23 (Fig. 2.19b).
Indicator 20. Fish populations
For New South Wales, we used relative abundance of Murray cod and golden perch, derived from the graphs published by Crook et al. (2023; Fig. 2 therein), which are based on data from the New South Wales Department of Primary Industries Fisheries Freshwater Ecosystem database for catchments in the New South Wales Basin. For Victoria, we used proportional change in abundance in each year (where positive values indicate increased populations and negative ones decreases) for Murray cod and golden perch from the Loddon, Campaspe, Goulburn, Broken, Murray, Ovens and King rivers and Broken Creek (Yen et al. 2021). Although the units of measurement are not compatible, the overall trends for the two datasets are broadly comparable. We generated raw mean relative abundance and proportional change in abundance data in Excel format for each species for each year by digitising each graph using GetData Graph Digitiser (version 2.26) software (cf. Informer Technologies Inc., https://getdata-graph-digitizer.software.informer.com/) (Fig. 2.20).
Indicator 21. Murray Mouth
Estimation of the number of days the Murray Mouth is open is based on the diurnal tide ratio (DTR), which is the ratio of tidal energy between Goolwa Barrage and Victor Harbor (DEW 2018). A ratio of 0.3 indicates the mouth is functionally open, allowing flow to the ocean and the flushing of salt, whereas a ration of 0.2 indicates the mouth is constricted by sand deposition from the ocean and requires dredging. We used the proportion of each year in which dredging was undertaken, from 2002-03 to 2018-19 (regardless of whether one or two dredgers were in operation), the proportion of time the mouth was open and discharge from the barrages, using data from DEW (2019, p. 38). We digitised each graph using GetData Graph Digitiser software (cf. Indicator 20 above) (Fig. 2.21).
Social theme
Indicators 22 and 23. Town water security
The indicators are: (22) the number of days of water restrictions and (23) the number of drinking water quality incidents (e.g. boil water alerts). We used the number of days per year in which restrictions on domestic water use were in place for Local Government Areas (LGAs) in the New South Wales Murray–Darling Basin (DPIE 2024c). Between 2013-14 and 2019-20, 39 LGAs in the New South Wales Basin had water restrictions in place for some of the time and 17 did not. We ranked LGAs with restrictions according to average number of days over the period of record, from most to least and calculated the decile values of the range as a basis to select ten LGAs (Bourke, Carrathool, Central Darling, Dubbo, Gwydir, Lachlan, Liverpool Plains, Walgett, Warren and Yass Valley). We then calculated the mean number of days per year water restrictions were in place for these ten LGAs (Fig. 2.22 & 23).
Indicator 24. Water quality threats 
Data for the total number of threats were compiled from threats of cyanobacterial (blue-green algal) blooms, low dissolved oxygen, hypoxic blackwater and high turbidity. We only included events considered likely and almost certain (excluding those deemed only possible: all bushfire contamination and elevated salinity threats) (Fig. 2.24). The data was derived from water quality threats maps published by MDBA, commencing in October 2020 (for example, MDBA, 2023b). The maps are produced approximately monthly between the warmer November-April period and less frequently during the cooler May-October period. The maps were obtained on request from the MDBA but are not archived by MDBA publicly. The Wayback Machine (https://archive.org/) can be used to locate what was publicly available at the time. We collated the data into seasonal numbers of likely and almost certain threats. Because the data were incomplete, we divided the total of likely and almost certain threats by the number of months-worth of data in each season to obtain a crude seasonal mean.
Compliance and enforcement theme
Indicators 25 and 26. Sustainable Diversion Limits
The indicators are: (25) compliance of Sustainable Diversion Limits (SDLs) for each surface water resource unit in the Basin and (26) the adjusted cumulative balance for each surface water resource unit. SDL accounting came into effect in July 2019. We used data from the annual registers of take of surface waters from the 27 SDL resource units for the years 2019-20, 2020-21 and 2021-22 (MDBA 2021d, 2022b, 2023c). The registers report annual permitted take (APT), which is ‘an annualised expression of the SDL volume’ and is ‘based on the management rules and assumptions about water user behaviour given the climate conditions in the 2021–22 water year. The annual permitted take (APT) should be less than or equal to the long-term average SDL.’ (MDBA 2023c, p. 9). Subtracting the annual actual take (AAT) from the APT gives the annual balance. AAT is based on metered or estimated volumes measured by the Basin States and Territory (Fig. 2.25). The annual balance, as a credit or debit, is then used to derive the cumulative balance over time, whereby credits and debits are added to those from previous years, with opening and closing balances for each water year. The cumulative balance is then adjusted to account for acquisition and use of held environmental water or its incomplete recovery in some resource units (MDBA 2023c, pp. 11–12). We used the adjusted cumulative balance (ACB) at the end of each of the three water years for each surface water SDL resource unit, expressed as a proportion of the long-term average SDL. Increases in the ACB over time indicate a reduction in take and that the ACB is moving away from the SDL, while decreases indicate take is increasing and is moving towards the SDL (Fig. 2.26). Because change in ACB as a proportion of the SDL may be non-linear (e.g. with a decrease in 2020-21 relative to 2019-20 and then an increase in 2021-22), we calculated the mean trajectory of change from the line of best fit for the three years in order to assess which SDL resource units had increases in take and were moving towards the SDL and which ones were not.
Indicator 27. Breaches of water laws
Data on court cases for breaches of water laws is held in databases of case law (e.g. NSW Caselaw 2023; AUSTLI 2024). But some of these databases cannot be searched for specific offences (NSW Caselaw is an exception). Data on all enforcement actions, including prosecutions, is held by State government agencies in Queensland (DRDMW 2022), Victoria (DEECA 2024), South Australia (DEW 2024) and New South Wales (NSW Ombudsman 2017). Legal structures, processes and penalties to address enforcement of water laws are quite different for each State and data cannot be aggregated and compared at whole-of-Basin scale. For Victoria, only prosecutions are reported by location within or outside the Basin but other actions cannot be disaggregated. New South Wales is the only Basin State with an independent agency responsible for ensuring compliance with water laws. The Public Register of the New South Wales Natural Resources Access Regulator (NRAR 2024), reports breaches by Local Government Area for penalty notices and directions issued, enforcible undertakings entered into and prosecutions for offences under the Water Management Act 2000 (NSW), from the establishment of the NRAR in 2018. Some earlier data is provided by NSW Ombudsman (2017). 
We downloaded the NRAR Public Register and sorted records by LGA, from 2018-19 to 2022-23, according to whether they were located in the northern or southern Basin. We also used data in the Public Register on successful prosecutions, cross-checked against annual NRAR progress reports (e.g. NRAR 2023) and compared these with successful prosecutions of offences committed in the Victorian Basin over the same period (Fig. 2.27). We also estimated the mean number of successful prosecutions in each Basin State (2018-19 to 2022-23) per thousand irrigator businesses. Numbers of irrigator businesses in each Basin State were compiled from ABS Water use on Australian farms reports (e.g. 2021b), using the data download for States, Territories and NRM regions.
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