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Historical Reference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% Quartile588.017447.722
Median797.931845.301
Mean849.649876.224
75% Quartile1069.7591246.986
Interquartile Range481.742799.263

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
11857.1592298.386
21718.6672080.591
31629.4311995.013
41575.7521924.511
51504.2881872.168
61462.7691799.100
71417.4951747.471
81383.1731698.953
91343.6681650.214
101323.0241613.334
111304.7931582.521
121280.6301548.250
131258.6171522.051
141236.7121495.599
151215.4161466.276
161197.0231442.799
171180.8481415.143
181168.1941386.687
191151.2711361.388
201136.0271341.278
211120.7551321.690
221109.7861299.696
231097.6771284.192
241083.0801261.399
251069.8271246.993
261057.7871234.511
271048.0861215.359
281035.8881200.023
291022.5041182.050
301007.9281162.082
31995.6381143.631
32984.0581124.704
33971.9901109.621
34960.8601094.631
35949.4101073.848
36938.7501057.054
37928.1311040.125
38917.7441024.182
39904.8061010.970
40890.042993.433
41879.900976.289
42869.282963.465
43858.445952.575
44848.520937.490
45838.281923.790
46830.045908.303
47822.281894.107
48814.907875.358
49807.750860.996
50797.931845.301
51789.180830.894
52778.697816.317
53771.838799.058
54762.277782.334
55754.166765.136
56747.882743.968
57741.882731.287
58735.284718.339
59725.501703.969
60717.033684.845
61709.506665.451
62702.496651.091
63694.999637.518
64688.050620.633
65678.014607.316
66671.500593.542
67662.891580.525
68654.651563.318
69646.117545.357
70636.597532.246
71628.673514.059
72620.141499.270
73608.504481.660
74598.122465.681
75587.808447.693
76577.370431.377
77571.301413.326
78560.540396.403
79552.850379.973
80540.037358.122
81529.465337.268
82518.755317.172
83510.200294.101
84500.481274.627
85488.423257.683
86475.100234.873
87465.243211.519
88452.002192.984
89441.540171.252
90428.212148.031
91415.195127.542
92401.474105.181
93385.49183.868
94365.65761.724
95337.10448.450
96317.78035.731
97298.21821.613
98273.41913.060
99230.1106.461


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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