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( Sep 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile528.404614.811
Median715.4591080.814
Mean771.3991185.089
75% Quartile964.1921643.333
Interquartile Range435.7881028.522

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
11879.9473230.326
21670.9062898.200
31534.9902767.858
41444.4532660.580
51393.5532581.009
61347.4492470.065
71309.2202391.788
81277.9182318.328
91248.3812244.653
101222.1842188.995
111197.0032142.563
121174.0762091.001
131155.1762051.646
141134.6712011.975
151118.1201968.076
161102.2841932.994
171086.0901891.747
181065.3161849.407
191047.6501811.857
201034.8721782.073
211018.7751753.124
221002.3461720.695
23989.0861697.886
24976.5221664.434
25964.2071643.345
26952.2961625.105
27940.7001597.186
28928.1731574.890
29916.8611548.830
30905.6351519.971
31896.6881493.399
32882.7351466.240
33870.9501444.671
34859.6721423.304
35850.4151393.798
36840.5571370.060
37830.6991346.234
38821.5301323.889
39811.7461305.445
40797.9181281.072
41789.0551257.367
42780.8641239.716
43772.0051224.786
44763.8951204.195
45755.2281185.584
46749.4521164.657
47739.9981145.581
48730.9671120.547
49722.7871101.500
50715.4591080.814
51709.7831061.951
52702.4071042.992
53693.4091020.710
54686.149999.297
55679.267977.468
56671.324950.869
57665.687935.082
58658.416919.081
59649.153901.461
60641.484878.249
61634.647854.989
62627.086837.953
63618.600821.999
64612.478802.356
65603.904787.026
66596.280771.322
67588.463756.624
68582.968737.413
69574.062717.624
70566.368703.350
71559.668683.792
72552.252668.094
73544.578649.642
74537.320633.124
75528.373614.782
76520.593598.373
77510.659580.465
78501.878563.904
79491.338548.028
80480.640527.202
81471.528507.610
82458.146488.957
83447.719467.770
84439.178450.021
85432.403434.632
86422.699413.912
87412.554392.553
88400.476375.365
89386.647354.753
90377.677331.860
91365.861310.521
92354.973285.373
93338.950258.633
94322.667226.168
95304.058202.969
96283.859176.339
97256.072137.630
98226.339104.414
99187.98865.820


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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