Seasonal Streamflow Forecasts

Probability distribution for Total Inflows to Tullaroop reservoir


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Product list for Total Inflows to Tullaroop reservoir


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Probability distribution for Total Inflows to Tullaroop reservoir(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile2.3332.307
Median4.3157.248
Mean5.82012.488
75% Quartile7.48418.529
Interquartile Range5.15116.222

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
125.47959.141
221.18150.562
318.98447.193
417.24444.420
515.85442.363
614.85139.495
714.04737.472
813.31035.575
912.65433.674
1012.21232.241
1111.74631.046
1211.17829.723
1310.77328.715
1410.35927.701
1510.03226.583
169.73325.693
179.44524.650
189.08723.586
198.82222.647
208.49521.907
218.28421.193
228.05720.397
237.85219.842
247.67019.034
257.48918.529
267.30818.095
277.14217.437
286.96616.916
296.80816.314
306.63915.656
316.51415.059
326.37514.457
336.22413.987
346.07213.527
355.93712.904
365.80812.412
375.65211.928
385.54611.482
395.39411.121
405.28210.654
415.17910.209
425.0479.885
434.9539.616
444.8379.252
454.7378.930
464.6408.576
474.5528.261
484.4717.860
494.3957.562
504.3157.248
514.2146.969
524.1166.696
534.0426.385
543.9466.095
553.8345.809
563.7455.473
573.6485.280
583.5905.090
593.5034.886
603.4134.625
613.3394.375
623.2664.197
633.2004.035
643.1273.843
653.0463.696
662.9813.551
672.9063.418
682.8263.250
692.7463.083
702.6822.966
712.6242.811
722.5402.690
732.4642.553
742.3992.434
752.3312.306
762.2722.196
772.2002.079
782.1261.975
792.0631.879
801.9901.756
811.9341.646
821.8631.545
831.8011.434
841.7471.346
851.6841.272
861.6311.176
871.5651.081
881.5001.009
891.4230.925
901.3500.837
911.2470.759
921.1770.672
931.0690.586
940.9780.489
950.8950.426
960.7710.358
970.6490.269
980.5310.203
990.3440.137


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 The historical reference is a probabilistic representation of the historical data.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