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Historical Reference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% Quartile0.4140.395
Median1.3891.486
Mean4.6327.785
75% Quartile4.3195.637
Interquartile Range3.9065.242

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
151.662111.552
237.99972.032
328.13458.315
423.87848.351
520.22141.516
617.72933.561
715.55328.682
813.81224.625
912.49221.098
1011.50818.748
1110.69316.979
129.83615.205
139.07713.960
148.40512.792
157.86711.619
167.16610.766
176.7529.821
186.3448.937
195.9938.224
205.7687.701
215.4697.220
225.0926.697
234.8456.379
244.5925.911
254.3235.640
264.1155.413
273.9355.072
283.7614.816
293.5414.546
303.3844.252
313.2234.002
323.0733.752
332.9373.570
342.7983.404
352.6323.172
362.5213.004
372.4102.838
382.2932.694
392.2152.577
402.1202.431
412.0222.296
421.9552.202
431.8732.122
441.8242.019
451.7361.930
461.6591.831
471.5831.749
481.5171.643
491.4521.565
501.3891.486
511.3321.417
521.2671.351
531.2121.274
541.1521.207
551.1001.136
561.0471.062
571.0061.018
580.9580.974
590.9220.930
600.8880.871
610.8530.817
620.8220.780
630.7790.745
640.7370.705
650.7010.674
660.6700.644
670.6340.617
680.6030.582
690.5700.549
700.5440.525
710.5250.494
720.4990.470
730.4720.443
740.4470.420
750.4140.395
760.3830.374
770.3590.352
780.3300.332
790.3090.314
800.2840.291
810.2580.270
820.2350.252
830.2120.232
840.1950.216
850.1790.203
860.1600.186
870.1410.169
880.1260.156
890.1110.142
900.0900.127
910.0740.114
920.0590.099
930.0420.085
940.0260.070
950.0110.060
960.0000.049
970.0000.036
980.0000.026
990.0000.017


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 The historical reference is a probabilistic representation of the historical data.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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