Seasonal Streamflow Forecasts

Exceedance probability for Muttama Creek at Coolac


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Exceedance probability for Muttama Creek at Coolac ( Jun 2014 )

Exceedance Probability Summary
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1018.42148.804
2010.19732.651
306.42522.427
404.14013.938
502.7608.310
601.8234.445
701.1552.386
800.6261.148
900.2490.409

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
148.06089.820
238.54176.775
333.34271.649
429.07867.427
526.68864.293
624.32559.918
722.31656.827
820.75853.924
919.58551.009
1018.42148.804
1117.47546.963
1216.49744.918
1315.36543.355
1414.55541.780
1513.75940.036
1612.90838.642
1711.99237.003
1811.35235.322
1910.77133.832
2010.19732.651
219.73531.506
229.23130.225
238.83929.326
248.37928.012
258.00627.187
267.66926.475
277.33325.390
287.06124.528
296.70623.527
306.42522.427
316.19521.424
325.89120.410
335.66719.613
345.41418.833
355.19417.773
364.95116.935
374.74816.109
384.54615.349
394.35214.734
404.14013.938
413.97913.185
423.84812.638
433.67712.185
443.50411.575
453.34711.039
463.24710.454
473.1279.938
482.9929.286
492.8758.809
502.7608.310
512.6347.872
522.5417.449
532.4386.973
542.3326.537
552.2446.113
562.1425.626
572.0635.351
581.9825.083
591.9174.799
601.8234.445
611.7504.112
621.6683.880
631.5913.672
641.5243.428
651.4533.247
661.3933.069
671.3352.910
681.2702.712
691.2212.519
701.1552.386
711.0982.213
721.0422.082
730.9861.935
740.9341.810
750.8871.679
760.8381.568
770.7851.453
780.7451.352
790.6871.261
800.6261.148
810.5881.049
820.5570.960
830.5200.866
840.4800.793
850.4360.732
860.3900.657
870.3600.585
880.3200.531
890.2830.470
900.2490.409
910.2280.357
920.1910.302
930.1550.249
940.1250.194
950.0890.160
960.0600.126
970.0320.085
980.0000.057
990.0000.033


About the exceedance probability 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 The historical reference is a probabilistic representation of the historical data.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. Further explanation of some technical terms is provided under the FAQ.


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