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Historical Reference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% Quartile0.0841.679
Median0.4598.310
Mean1.88617.541
75% Quartile1.67927.186
Interquartile Range1.59525.507

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
123.33689.820
215.61876.775
312.07071.649
410.08267.427
58.53664.293
67.47359.918
76.59356.827
85.86653.924
95.28351.009
104.69148.804
114.29246.963
123.96744.918
133.68043.355
143.34241.780
153.14540.036
162.92138.642
172.74037.003
182.51435.322
192.36233.832
202.19832.651
212.06631.506
221.95030.225
231.86829.326
241.76228.012
251.68027.187
261.60326.475
271.50425.390
281.42724.528
291.34623.527
301.27922.427
311.21821.424
321.16120.410
331.09619.613
341.03818.833
350.98017.773
360.91816.935
370.86316.109
380.82215.349
390.78214.734
400.74113.938
410.70613.185
420.67312.638
430.64212.185
440.61111.575
450.58711.039
460.56310.454
470.5409.938
480.5109.286
490.4838.809
500.4598.310
510.4347.872
520.4147.449
530.3926.973
540.3766.537
550.3526.113
560.3305.626
570.3105.351
580.2945.083
590.2784.799
600.2624.445
610.2454.112
620.2333.880
630.2193.672
640.2063.428
650.1973.247
660.1863.069
670.1742.910
680.1622.712
690.1472.519
700.1362.386
710.1272.213
720.1142.082
730.1041.935
740.0951.810
750.0841.679
760.0751.568
770.0641.453
780.0551.352
790.0461.261
800.0391.148
810.0331.049
820.0260.960
830.0180.866
840.0120.793
850.0070.732
860.0010.657
870.0000.585
880.0000.531
890.0000.470
900.0000.409
910.0000.357
920.0000.302
930.0000.249
940.0000.194
950.0000.160
960.0000.126
970.0000.085
980.0000.057
990.0000.033


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 The historical reference is a probabilistic representation of the historical data.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