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Historical Reference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% Quartile217.806274.149
Median342.205463.293
Mean358.638506.266
75% Quartile483.791688.205
Interquartile Range265.984414.056

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1852.2951485.571
2781.6251291.683
3737.9391219.964
4705.0761162.694
5689.1951121.211
6670.4691064.744
7651.5461025.838
8638.396990.009
9628.210954.720
10614.874928.477
11602.371906.853
12592.529883.118
13581.895865.196
14571.683847.295
15562.341827.676
16552.526812.137
17543.487794.022
18536.230775.598
19526.892759.397
20519.709746.638
21511.312734.312
22503.169720.590
23496.309710.991
24490.655696.991
25483.805688.209
26477.569680.643
27469.585669.109
28463.834659.939
29457.026649.265
30451.736637.499
31444.816626.713
32438.183615.734
33432.246607.047
34427.150598.466
35422.985586.657
36416.742577.188
37410.012567.711
38404.667558.845
39400.080551.542
40394.515541.911
41389.051532.563
42383.698525.614
43378.032519.742
44373.999511.651
45369.260504.347
46363.476496.140
47358.328488.664
48352.208478.857
49346.793471.396
50342.205463.293
51336.969455.901
52332.043448.467
53327.050439.723
54323.526431.309
55318.099422.717
56313.023412.224
57308.552405.982
58304.167399.643
59299.608392.645
60294.664383.396
61290.746374.089
62285.288367.244
63279.825360.811
64275.120352.855
65270.352346.618
66265.103340.200
67258.707334.165
68253.850326.234
69249.260318.009
70244.220312.037
71239.503303.800
72233.698297.138
73229.763289.246
74224.494282.120
75217.749274.136
76212.511266.925
77206.667258.975
78200.789251.544
79193.765244.344
80188.236234.777
81182.433225.641
82177.178216.810
83170.831206.609
84163.999197.912
85158.761190.251
86151.607179.745
87144.835168.667
88136.273159.551
89129.922148.362
90121.036135.573
91113.545123.272
92105.083108.248
9396.50191.561
9488.71270.153
9577.04153.951
9661.84234.250
9749.0543.043
9831.8820.000
998.7110.000


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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