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 ( Jan 2013 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.2860.336
Median0.9271.106
Mean2.3823.635
75% Quartile2.5623.288
Interquartile Range2.2762.951

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
122.96345.471
216.16927.825
312.65722.594
410.63718.998
59.27616.597
68.30513.833
77.42912.134
86.86010.705
96.2239.442
105.6768.584
115.2567.927
124.8167.257
134.5446.778
144.2966.322
154.0785.855
163.8725.510
173.6785.121
183.4824.750
193.3244.446
203.1774.219
213.0224.007
222.8983.774
232.7683.630
242.6633.415
252.5633.289
262.4653.182
272.3463.021
282.2352.898
292.1162.766
302.0542.621
311.9632.496
321.8902.370
331.8322.276
341.7602.190
351.6852.068
361.6091.978
371.5451.889
381.4961.810
391.4391.745
401.3741.664
411.3211.588
421.2811.534
431.2271.488
441.1771.428
451.1231.375
461.0771.317
471.0401.267
481.0001.203
490.9691.155
500.9271.106
510.8901.062
520.8561.020
530.8220.970
540.7870.927
550.7570.880
560.7280.830
570.7050.801
580.6760.771
590.6530.740
600.6270.698
610.6010.661
620.5750.634
630.5470.608
640.5240.579
650.4950.556
660.4790.534
670.4500.513
680.4270.487
690.4050.460
700.3850.442
710.3640.417
720.3410.398
730.3180.376
740.3030.357
750.2860.336
760.2670.318
770.2470.299
780.2310.282
790.2110.266
800.1920.246
810.1740.227
820.1570.210
830.1410.192
840.1260.176
850.1090.163
860.0930.147
870.0790.130
880.0640.117
890.0480.102
900.0290.086
910.0120.072
920.0000.056
930.0000.039
940.0000.020
950.0000.008
960.0000.000
970.0000.000
980.0000.000
990.0000.000


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 The historical reference is a probabilistic representation of the historical data.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