Seasonal Streamflow Forecasts

Probability distribution for Unregulated inflow to Hume Dam


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Product list for Unregulated inflow to Hume Dam


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Probability distribution for Unregulated inflow to Hume Dam(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile1013.383614.811
Median1312.6201080.814
Mean1387.5701185.089
75% Quartile1690.6261643.333
Interquartile Range677.2431028.522

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
12980.5593230.326
22705.9872898.200
32504.4232767.858
42429.6052660.580
52338.8642581.009
62274.2272470.065
72213.2122391.788
82169.7572318.328
92129.2302244.653
102086.7842188.995
112048.2872142.563
122015.3752091.001
131982.4692051.646
141955.4852011.975
151917.0271968.076
161886.3291932.994
171858.0061891.747
181837.6041849.407
191813.3181811.857
201794.5541782.073
211768.4991753.124
221748.5981720.695
231726.4491697.886
241709.0241664.434
251691.2851643.345
261675.7491625.105
271656.6701597.186
281639.4091574.890
291621.3311548.830
301607.5051519.971
311589.8831493.399
321566.8521466.240
331551.2041444.671
341534.8851423.304
351515.6721393.798
361499.2291370.060
371487.6001346.234
381474.8201323.889
391460.8331305.445
401445.8621281.072
411432.5431257.367
421415.6261239.716
431404.8411224.786
441393.5431204.195
451377.2171185.584
461365.6411164.657
471351.8151145.581
481340.7671120.547
491326.8211101.500
501312.6201080.814
511300.5871061.951
521288.8051042.992
531277.9241020.710
541265.509999.297
551254.469977.468
561243.277950.869
571234.525935.082
581223.165919.081
591211.440901.461
601199.972878.249
611187.969854.989
621175.833837.953
631164.178821.999
641148.909802.356
651137.465787.026
661127.077771.322
671115.721756.624
681099.151737.413
691089.422717.624
701079.056703.350
711066.824683.792
721054.328668.094
731043.136649.642
741028.346633.124
751012.737614.782
761001.377598.373
77988.834580.465
78973.707563.904
79954.204548.028
80940.894527.202
81927.057507.610
82914.895488.957
83896.103467.770
84878.370450.021
85860.399434.632
86841.310413.912
87826.559392.553
88807.419375.365
89789.638354.753
90767.531331.860
91743.376310.521
92722.382285.373
93701.169258.633
94676.728226.168
95649.778202.969
96608.313176.339
97572.243137.630
98528.893104.414
99457.71865.820


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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