Seasonal Streamflow Forecasts

Probability distribution for Muttama Creek at Coolac


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Product list for Muttama Creek at Coolac


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Probability distribution for Muttama Creek at Coolac(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile3.8782.790
Median9.51313.855
Mean14.78620.504
75% Quartile20.98632.889
Interquartile Range17.10830.099

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
167.35684.720
258.13573.979
353.40769.759
448.64166.282
545.76963.700
643.12860.097
741.12057.551
839.05455.158
937.36252.755
1035.94250.936
1134.42549.417
1232.98347.727
1331.66046.435
1430.32545.131
1529.29743.686
1628.42342.529
1727.34241.166
1826.43839.764
1925.37938.518
2024.58637.527
2123.93436.563
2223.31835.481
2322.59734.718
2421.81533.597
2520.99132.890
2620.35432.277
2719.71131.337
2819.07130.585
2918.42929.704
3017.87328.727
3117.34927.826
3216.85926.903
3316.33726.169
3415.83725.441
3515.35424.434
3614.99823.623
3714.55522.808
3814.06722.044
3913.59421.414
4013.19720.581
4112.69919.772
4212.31019.170
4311.94418.662
4411.60617.963
4511.21617.334
4610.73816.629
4710.45515.990
4810.13315.158
499.84114.530
509.51313.855
519.24713.246
528.97512.641
538.70011.941
548.49611.281
558.24210.622
567.9979.841
577.6909.390
587.3688.943
597.1338.463
606.8807.851
616.6547.263
626.4936.849
636.2206.475
645.9846.032
655.7855.700
665.5575.372
675.3835.077
685.1474.709
694.8974.349
704.7464.102
714.5573.780
724.3773.535
734.2223.262
744.0473.031
753.8772.789
763.6682.585
773.4302.376
783.2682.193
793.1382.028
802.9951.826
812.8321.650
822.6761.495
832.5671.331
842.3891.205
852.2181.103
862.0270.975
871.8930.855
881.7660.767
891.6250.670
901.4580.573
911.3120.491
921.1510.406
931.0150.328
940.8820.247
950.7490.199
960.5720.151
970.4410.097
980.2740.062
990.1200.034


About the probability distribution 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 The historical reference is a probabilistic representation of the historical data.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. The 25% quartile, also defined as the first quartile cuts off the lowest 25% of data. The 75% quartile, also defined as the third quartile cuts off the lowest 75%. The interquartile range, also called the middle fifty, is a measure of statistical dispersion, being equal to the difference between the third and first quartiles.
  9. Further explanation of some technical terms is provided under the FAQ.


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