Seasonal Streamflow Forecasts

Exceedance probability for Muttama Creek at Coolac


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Product list for Muttama Creek at Coolac


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Exceedance probability for Muttama Creek at Coolac(  )

Exceedance Probability Summary
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
107.59239.273
203.96119.149
302.45310.836
401.4956.150
500.9223.705
600.5232.132
700.2651.257
800.0640.681
900.0000.288

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
133.522105.325
223.15083.783
318.48975.360
415.33768.460
513.09063.372
611.67656.347
710.19451.461
89.24046.952
98.39842.530
107.59239.273
116.97136.624
126.32833.765
135.88431.650
145.48929.583
155.20027.379
164.85825.685
174.56423.775
184.32221.909
194.11720.338
203.96119.149
213.73818.042
223.55116.859
233.33816.063
243.20014.949
253.08114.279
262.97013.720
272.82112.898
282.67912.271
292.56011.571
302.45310.836
312.34410.195
322.2349.573
332.1059.103
341.9918.658
351.8768.074
361.7907.630
371.7147.206
381.6366.827
391.5566.528
401.4956.150
411.4295.802
421.3695.553
431.3075.351
441.2625.082
451.2044.850
461.1634.599
471.0944.381
481.0444.108
490.9813.911
500.9223.705
510.8743.527
520.8223.354
530.7803.161
540.7502.984
550.7192.812
560.6782.615
570.6252.503
580.5922.394
590.5592.278
600.5232.132
610.4971.994
620.4691.898
630.4421.811
640.4061.708
650.3781.631
660.3561.555
670.3321.487
680.3031.401
690.2851.316
700.2651.257
710.2461.180
720.2191.121
730.1931.054
740.1750.997
750.1590.936
760.1440.884
770.1240.829
780.1040.781
790.0840.737
800.0640.681
810.0440.631
820.0240.586
830.0100.538
840.0000.500
850.0000.468
860.0000.427
870.0000.387
880.0000.357
890.0000.323
900.0000.288
910.0000.257
920.0000.223
930.0000.190
940.0000.154
950.0000.131
960.0000.107
970.0000.077
980.0000.056
990.0000.035


About the exceedance probability product


  1. The forecast is a simulation from the Bayesian Joint Probability (BJP) Model. The simulation comprises 5000 members.
  2. The forecast skill of the BJP model is different for different forecast periods of the year. Please look at the Model Validation results to assess model skill for this forecast period.
  3. The historical reference is a probabilistic representation of the historical data.
  4. The forecast location name is displayed in the graph title. Site forecast locations are followed by the Australian Water Resources Council (AWRC) river station number in brackets e.g. (405219).
  5. The streamflow data used for new forecasts and for verification is from realtime data sources which are not rigorously quality controlled.
  6. The historical reference plot and the historical data plots are derived from the available historical record. The legend shows the year associated with the start month of the forecast period.
  7. The RMSEP skill scores have been defined as less than 10 very low skill, 10-20 low skill, 20-40 moderate skill, greater than 40 high skill.
  8. Further explanation of some technical terms is provided under the FAQ.


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