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 ( May 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.9740.936
Median2.9863.705
Mean8.69812.927
75% Quartile8.47614.279
Interquartile Range7.50213.343

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
182.839105.325
258.43183.783
347.66175.360
438.68568.460
533.36863.372
629.82156.347
727.19251.461
824.06346.952
922.18342.530
1020.54239.273
1119.28036.624
1217.80033.765
1316.49531.650
1415.33429.583
1514.26227.379
1613.48125.685
1712.92223.775
1812.25321.909
1911.50720.338
2010.93919.149
2110.52218.042
229.97016.859
239.42916.063
248.87114.949
258.48114.279
268.13713.720
277.78112.898
287.45312.271
297.10911.571
306.83110.836
316.53810.195
326.3259.573
336.0289.103
345.8048.658
355.5438.074
365.3157.630
375.1137.206
384.9216.827
394.6896.528
404.4716.150
414.2695.802
424.0755.553
433.9255.351
443.7855.082
453.6604.850
463.4964.599
473.3794.381
483.2624.108
493.1213.911
502.9863.705
512.8573.527
522.7503.354
532.6473.161
542.5512.984
552.4522.812
562.3552.615
572.2602.503
582.1732.394
592.1062.278
602.0132.132
611.8891.994
621.8141.898
631.7441.811
641.6691.708
651.5851.631
661.5181.555
671.4581.487
681.3891.401
691.3231.316
701.2721.257
711.2251.180
721.1551.121
731.0981.054
741.0410.997
750.9730.936
760.9210.884
770.8590.829
780.8030.781
790.7520.737
800.7050.681
810.6490.631
820.5970.586
830.5500.538
840.5010.500
850.4520.468
860.4050.427
870.3510.387
880.3030.357
890.2660.323
900.2360.288
910.1920.257
920.1510.223
930.1020.190
940.0580.154
950.0150.131
960.0000.107
970.0000.077
980.0000.056
990.0000.035


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 The historical reference is a probabilistic representation of the historical data.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