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To help irrigators and other water users better understand the likelihood of improvements in their water allocations, the department has prepared water availability projections for climatic conditions ranging from extremely dry to wet.

They indicate how likely water allocations are to reach the projected level during 2019‑20, based on historical rainfall and temperature data from the last 30 years, current River Murray storage levels and operational conditions across the Murray-Darling Basin.

The water availability projections are calculated using River Murray system modelling and South Australia’s River Murray water allocation framework.

According to the projections, unless improvements in water availability for the remainder of 2019-20 are worse than for any year in the last 30, water allocations are likely to get to 100 per cent by the end of the water year.

The Bureau of Meteorology (BoM) has provided a seasonal outlook for the three months from October to December 2019. The outlook continues to indicate that it is likely to be drier and warmer than average across most of the Murray-Darling Basin.

Class 3 water allocation scenarios            

SA River Murray
Irrigation Allocation Scenarios
All Purpose - Class 3
Minimum Allocation 1 Nov 1 Jan 1 Apr
Projected allocation as a percentage
Exceptionally dry
- 99 % likelihood allocation will be at least
87 88 97 100
Extreme dry conditions
- 95% likelihood allocation will be at least
87 93 100 100
Very dry conditions
- 90% likelihood allocation will be at least
87 96 100 100
Dry conditions
- 75% likelihood allocation will be at least
87 99 100 100
Average conditions
- 50% likelihood allocation will be at least
87 100 100 100
Wet conditions
- 25% likelihood allocation will be at least
87 100 100 100

DISCLAIMER: This data is provided for information only. Historical performance is not necessarily an indicator of future outcomes. Projections are based on historical climate variability across the last 30 years. The Government of South Australia accepts no liability for any loss resulting from the use of or reliance on any of this data or information.

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