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Historical Reference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% Quartile1.4021.679
Median4.1518.310
Mean8.84617.541
75% Quartile11.58327.186
Interquartile Range10.18125.507

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
154.32289.820
245.51776.775
339.94271.649
435.63967.427
532.87464.293
630.73959.918
728.49856.827
826.85453.924
925.42551.009
1023.99148.804
1123.02846.963
1221.83644.918
1320.67843.355
1419.73841.780
1518.67140.036
1617.89038.642
1716.68037.003
1815.99535.322
1915.24333.832
2014.42232.651
2113.77131.506
2213.21430.225
2312.55829.326
2412.05528.012
2511.58427.187
2611.12726.475
2710.55525.390
2810.17024.528
299.83423.527
309.47122.427
319.11321.424
328.73020.410
338.36419.613
348.07718.833
357.70117.773
367.33316.935
377.10116.109
386.72615.349
396.43114.734
406.20813.938
415.93713.185
425.69212.638
435.49912.185
445.29411.575
455.10311.039
464.90410.454
474.6979.938
484.5109.286
494.3408.809
504.1518.310
514.0077.872
523.8687.449
533.7026.973
543.5246.537
553.3916.113
563.2675.626
573.1295.351
583.0025.083
592.9004.799
602.7984.445
612.6744.112
622.5463.880
632.4543.672
642.3373.428
652.2513.247
662.1313.069
672.0482.910
681.9702.712
691.8942.519
701.8042.386
711.7382.213
721.6532.082
731.5581.935
741.4731.810
751.4011.679
761.3161.568
771.2301.453
781.1741.352
791.0741.261
801.0091.148
810.9491.049
820.8920.960
830.8490.866
840.7810.793
850.7220.732
860.6480.657
870.5940.585
880.5400.531
890.4890.470
900.4330.409
910.3960.357
920.3540.302
930.2900.249
940.2390.194
950.1940.160
960.1440.126
970.0900.085
980.0360.057
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 The historical reference is a probabilistic representation of the historical data.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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