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Historical Reference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% Quartile0.0690.497
Median0.4451.476
Mean1.2084.092
75% Quartile1.2993.993
Interquartile Range1.2303.497

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
112.32746.480
28.25528.520
36.39423.399
45.50919.892
54.83217.546
64.36214.831
73.91713.148
83.46111.722
93.19810.450
102.9349.579
112.7068.907
122.5608.218
132.4147.722
142.2917.246
152.1866.757
162.0646.393
171.9545.981
181.8445.585
191.7715.258
201.6435.012
211.5594.783
221.4784.528
231.4134.370
241.3544.134
251.3003.995
261.2443.877
271.1923.697
281.1333.559
291.0773.412
301.0333.248
310.9953.106
320.9492.962
330.9082.855
340.8762.756
350.8392.616
360.8062.512
370.7702.408
380.7352.316
390.7072.241
400.6772.145
410.6532.055
420.6361.991
430.6051.936
440.5811.865
450.5581.802
460.5321.732
470.5121.672
480.4871.594
490.4661.536
500.4451.476
510.4251.423
520.4031.371
530.3811.310
540.3651.256
550.3471.198
560.3271.136
570.3101.098
580.2951.061
590.2731.022
600.2560.969
610.2430.921
620.2280.886
630.2140.854
640.1970.816
650.1860.787
660.1740.757
670.1620.730
680.1490.696
690.1370.661
700.1230.637
710.1090.605
720.1010.579
730.0890.550
740.0780.524
750.0690.496
760.0570.472
770.0460.446
780.0330.423
790.0230.401
800.0140.373
810.0030.348
820.0000.324
830.0000.298
840.0000.276
850.0000.258
860.0000.234
870.0000.211
880.0000.192
890.0000.170
900.0000.147
910.0000.126
920.0000.102
930.0000.077
940.0000.048
950.0000.029
960.0000.008
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 The historical reference is a probabilistic representation of the historical data.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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