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Historical Reference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% Quartile564.907445.797
Median850.904789.177
Mean962.9521010.223
75% Quartile1247.7001349.975
Interquartile Range682.793904.177

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
12810.1793745.379
22442.7403184.739
32261.6312969.421
42119.5332794.867
52019.0922667.214
61912.1172492.202
71861.9162371.068
81809.2132259.354
91750.0032149.398
101702.7192067.818
111654.5082000.799
121605.9471927.538
131569.0081872.473
141532.4831817.742
151500.1221758.113
161472.3741711.184
171441.6251656.854
181403.2601602.054
191380.2911554.292
201357.2701516.979
211334.4721481.202
221313.3081441.702
231289.2351414.289
241268.4181374.641
251247.7981349.987
261223.0071328.880
271208.2121296.954
281180.8641271.795
291158.8341242.768
301142.8491211.098
311126.6621182.380
321108.3951153.465
331095.2821130.817
341081.4381108.653
351067.6771078.493
361051.7811054.603
371033.1471030.955
381018.7661009.079
391002.233991.239
40987.232967.964
41971.821945.651
42958.053929.244
43943.281915.501
44929.792896.749
45913.712880.002
46902.949861.395
47890.447844.639
48877.854822.943
49862.803806.654
50850.904789.177
51839.995773.429
52830.113757.781
53816.643739.616
54801.693722.388
55791.141705.048
56775.476684.220
57764.275672.012
58754.332659.751
59744.555646.381
60732.139628.973
61719.459611.756
62708.738599.287
63698.392587.717
64688.865573.609
65676.054562.701
66667.305551.619
67655.830541.330
68645.192527.998
69636.296514.400
70624.881504.675
71614.189491.459
72600.798480.940
73588.372468.674
74574.634457.781
75564.578445.778
76552.969435.120
77539.700423.571
78527.995412.966
79515.538402.862
80503.262389.701
81491.004377.408
82475.245365.781
83461.580352.658
84448.484341.728
85435.982332.297
86424.910319.657
87412.127306.693
88396.442296.304
89380.651283.889
90362.683270.149
91345.537257.379
92328.389242.362
93309.764226.417
94292.494207.060
95272.558193.208
96244.049177.264
97217.971153.946
98188.398133.733
99149.921109.890


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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