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 ( Jun 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile532.629445.797
Median804.940789.177
Mean915.7371010.223
75% Quartile1187.9341349.975
Interquartile Range655.306904.177

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
12711.9843745.379
22348.9973184.739
32173.1872969.421
42036.4022794.867
51936.0662667.214
61832.4272492.202
71787.8502371.068
81727.4152259.354
91674.3382149.398
101623.4402067.818
111577.8412000.799
121535.6011927.538
131500.4171872.473
141463.8921817.742
151431.9721758.113
161403.4831711.184
171374.3871656.854
181341.4521602.054
191316.0941554.292
201293.8101516.979
211272.2701481.202
221251.5791441.702
231228.2611414.289
241207.8631374.641
251188.2451349.987
261166.4091328.880
271150.9391296.954
281123.8561271.795
291101.3521242.768
301086.4731211.098
311070.3541182.380
321054.2321153.465
331039.9851130.817
341027.7761108.653
351014.8091078.493
36997.5141054.603
37983.2471030.955
38966.5981009.079
39951.788991.239
40937.601967.964
41923.721945.651
42908.291929.244
43893.461915.501
44881.559896.749
45866.878880.002
46856.586861.395
47844.114844.639
48831.069822.943
49817.608806.654
50804.940789.177
51796.118773.429
52783.910757.781
53773.130739.616
54758.406722.388
55749.364705.048
56734.085684.220
57722.932672.012
58712.604659.751
59703.990646.381
60690.497628.973
61678.971611.756
62669.653599.287
63659.640587.717
64649.624573.609
65638.999562.701
66630.151551.619
67620.562541.330
68609.124527.998
69599.854514.400
70590.318504.675
71578.198491.459
72565.676480.940
73555.463468.674
74542.233457.781
75532.450445.778
76520.890435.120
77507.953423.571
78496.814412.966
79486.104402.862
80473.180389.701
81462.375377.408
82447.599365.781
83434.259352.658
84421.866341.728
85411.283332.297
86398.641319.657
87387.268306.693
88371.692296.304
89355.429283.889
90338.929270.149
91324.490257.379
92307.179242.362
93289.237226.417
94272.723207.060
95254.047193.208
96227.057177.264
97201.890153.946
98175.927133.733
99137.784109.890


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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