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Historical Reference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% Quartile2.0541.312
Median4.8736.954
Mean8.65614.415
75% Quartile10.80822.626
Interquartile Range8.75421.315

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
152.00872.496
241.27162.129
336.12158.055
432.32554.700
529.27052.208
627.21048.731
725.53846.274
824.05843.966
922.83241.647
1021.46339.894
1120.18838.430
1219.09236.802
1318.11735.558
1417.38634.303
1516.54332.913
1615.89931.802
1715.16630.494
1814.57729.152
1913.92327.961
2013.42627.016
2112.78726.098
2212.16525.071
2311.76324.349
2411.28223.292
2510.81122.627
2610.51522.052
2710.14021.176
289.78620.478
299.49719.665
309.20518.770
318.89417.952
328.66417.122
338.40516.468
348.12915.826
357.82614.950
367.62314.255
377.38613.567
387.09512.933
396.86912.417
406.65011.749
416.40611.114
426.18810.651
435.96510.267
445.8299.748
455.6329.292
465.4798.792
475.3338.351
485.1967.792
495.0187.382
504.8736.954
514.7286.577
524.5886.213
534.4245.803
544.3005.428
554.1615.064
563.9834.645
573.8634.409
583.7704.180
593.6593.937
603.5663.635
613.4173.350
623.3063.153
633.2052.977
643.1092.771
653.0302.618
662.9262.468
672.8172.334
682.7412.168
692.6332.006
702.5301.896
712.4511.752
722.3411.643
732.2421.522
742.1621.419
752.0511.311
761.9471.221
771.8621.127
781.7801.045
791.7040.971
801.6390.880
811.5690.801
821.4870.730
831.4170.655
841.3330.597
851.2530.550
861.1900.490
871.0920.434
881.0090.392
890.9470.345
900.8750.298
910.8080.259
920.7350.217
930.6730.178
940.5740.137
950.4860.111
960.3970.087
970.3100.057
980.2330.038
990.1170.021


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 The historical reference is a probabilistic representation of the historical data.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