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Historical Reference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% Quartile231.614274.149
Median357.030463.293
Mean372.598506.266
75% Quartile497.942688.205
Interquartile Range266.328414.056

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1865.5201485.571
2795.5881291.683
3755.0551219.964
4726.7551162.694
5702.3651121.211
6686.1741064.744
7669.4061025.838
8653.168990.009
9641.902954.720
10627.692928.477
11618.976906.853
12609.071883.118
13597.066865.196
14588.406847.295
15578.510827.676
16569.509812.137
17560.921794.022
18552.951775.598
19543.791759.397
20535.182746.638
21526.674734.312
22521.388720.590
23514.015710.991
24506.542696.991
25498.072688.209
26492.379680.643
27487.521669.109
28481.441659.939
29474.561649.265
30467.233637.499
31461.238626.713
32454.788615.734
33447.995607.047
34441.596598.466
35435.570586.657
36430.251577.188
37424.351567.711
38419.584558.845
39414.580551.542
40408.346541.911
41403.007532.563
42397.915525.614
43394.180519.742
44388.950511.651
45381.791504.347
46376.539496.140
47371.531488.664
48366.581478.857
49361.636471.396
50357.030463.293
51351.511455.901
52346.656448.467
53342.310439.723
54337.529431.309
55333.338422.717
56328.574412.224
57324.903405.982
58320.511399.643
59314.843392.645
60309.222383.396
61304.521374.089
62299.846367.244
63295.861360.811
64290.796352.855
65285.088346.618
66279.148340.200
67274.322334.165
68268.544326.234
69265.041318.009
70259.161312.037
71254.164303.800
72248.603297.138
73242.801289.246
74237.695282.120
75231.590274.136
76225.605266.925
77220.725258.975
78213.228251.544
79208.457244.344
80201.507234.777
81195.410225.641
82190.154216.810
83183.305206.609
84177.348197.912
85170.054190.251
86163.365179.745
87156.516168.667
88147.387159.551
89140.255148.362
90131.439135.573
91123.345123.272
92114.812108.248
93106.60391.561
9494.90970.153
9583.98653.951
9671.91234.250
9757.3413.043
9837.3700.000
997.0390.000


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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