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Historical Reference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% Quartile757.214614.811
Median996.5211080.814
Mean1060.7351185.089
75% Quartile1310.2231643.333
Interquartile Range553.0091028.522

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
12422.1813230.326
22150.6782898.200
31997.0592767.858
41914.8952660.580
51845.1042581.009
61788.1462470.065
71727.3212391.788
81684.1012318.328
91658.2702244.653
101630.1832188.995
111593.9682142.563
121568.1562091.001
131546.9362051.646
141524.4892011.975
151497.9401968.076
161469.2741932.994
171449.4551891.747
181427.9261849.407
191411.6891811.857
201393.4981782.073
211373.6851753.124
221358.0561720.695
231343.6461697.886
241322.9311664.434
251310.2761643.345
261291.3191625.105
271275.7041597.186
281263.7601574.890
291247.1861548.830
301231.9751519.971
311220.2301493.399
321206.3311466.240
331190.1171444.671
341177.0201423.304
351160.4811393.798
361147.5991370.060
371135.0841346.234
381125.1991323.889
391113.9711305.445
401103.7491281.072
411093.6161257.367
421081.8341239.716
431071.2761224.786
441057.6221204.195
451048.4821185.584
461037.9971164.657
471027.8471145.581
481017.0421120.547
491006.4961101.500
50996.5211080.814
51987.5741061.951
52977.3341042.992
53967.8841020.710
54958.639999.297
55950.258977.468
56940.013950.869
57931.566935.082
58922.957919.081
59913.001901.461
60899.645878.249
61891.158854.989
62881.209837.953
63872.063821.999
64862.217802.356
65852.574787.026
66841.471771.322
67832.175756.624
68823.543737.413
69813.417717.624
70802.890703.350
71794.254683.792
72785.014668.094
73778.116649.642
74767.914633.124
75757.089614.782
76744.907598.373
77733.918580.465
78721.321563.904
79707.431548.028
80694.300527.202
81679.227507.610
82668.054488.957
83656.366467.770
84642.229450.021
85631.969434.632
86619.016413.912
87606.295392.553
88592.163375.365
89574.441354.753
90557.108331.860
91542.905310.521
92528.576285.373
93507.213258.633
94487.425226.168
95465.081202.969
96437.336176.339
97410.582137.630
98366.713104.414
99313.37365.820


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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