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( Oct 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile295.056447.722
Median425.857845.301
Mean470.281876.224
75% Quartile607.0781246.986
Interquartile Range312.022799.263

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
11204.4772298.386
21087.0102080.591
31021.1251995.013
4963.0851924.511
5922.5121872.168
6887.1141799.100
7863.3911747.471
8836.2091698.953
9819.7891650.214
10799.5941613.334
11774.2431582.521
12758.4631548.250
13746.2001522.051
14731.8511495.599
15718.3651466.276
16701.8271442.799
17689.6741415.143
18677.6191386.687
19662.2491361.388
20653.3891341.278
21642.2781321.690
22632.6501299.696
23623.6581284.192
24615.7181261.399
25607.1531246.993
26598.7031234.511
27590.2161215.359
28581.8751200.023
29572.3421182.050
30565.2541162.082
31554.7691143.631
32547.5291124.704
33538.9661109.621
34530.2791094.631
35523.8331073.848
36513.5951057.054
37504.9451040.125
38497.7171024.182
39491.4091010.970
40485.981993.433
41477.924976.289
42472.818963.465
43466.619952.575
44459.457937.490
45454.393923.790
46447.935908.303
47442.372894.107
48437.400875.358
49430.590860.996
50425.857845.301
51420.904830.894
52415.597816.317
53410.956799.058
54406.190782.334
55401.263765.136
56395.757743.968
57391.458731.287
58387.005718.339
59380.680703.969
60374.877684.845
61369.677665.451
62365.363651.091
63359.482637.518
64354.018620.633
65349.269607.316
66344.387593.542
67339.346580.525
68333.645563.318
69328.240545.357
70322.000532.246
71315.946514.059
72310.555499.270
73305.008481.660
74300.668465.681
75295.034447.693
76290.102431.377
77284.267413.326
78278.669396.403
79272.767379.973
80266.823358.122
81260.394337.268
82251.396317.172
83246.311294.101
84240.512274.627
85233.592257.683
86227.398234.873
87221.213211.519
88215.711192.984
89208.678171.252
90198.182148.031
91192.050127.542
92183.518105.181
93172.19383.868
94159.38761.724
95148.44448.450
96135.86235.731
97124.73321.613
98110.15713.060
9982.8286.461


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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