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 ( Jan 2012 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile122.29699.400
Median177.231174.499
Mean195.244212.107
75% Quartile251.225281.193
Interquartile Range128.929181.793

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1534.325815.239
2466.128663.019
3431.753609.975
4407.814569.540
5387.751540.030
6371.519502.700
7360.477477.417
8350.529454.378
9339.357432.324
10331.771416.254
11321.691403.234
12314.284389.215
13307.681378.676
14302.376368.167
15296.427356.910
16290.208348.201
17286.097337.949
18281.095327.691
19275.332318.876
20269.698312.037
21266.307305.456
22261.743297.917
23258.147293.115
24254.956285.728
25251.233281.246
26247.254277.368
27243.725271.324
28240.152266.584
29236.535261.376
30232.864255.426
31229.372250.146
32225.123244.612
33221.711240.383
34218.462236.415
35215.513230.605
36212.017226.195
37209.161221.672
38206.622217.566
39204.266214.112
40201.931209.650
41199.395205.328
42196.990202.198
43194.908199.475
44191.960195.855
45189.076192.595
46186.646188.863
47184.081185.644
48182.041181.320
49179.482177.996
50177.231174.499
51174.980171.320
52172.663168.200
53170.129164.363
54167.840160.936
55165.761157.133
56163.819152.936
57161.215150.355
58159.073147.711
59156.757144.910
60154.749141.051
61152.843137.409
62150.838134.713
63148.124132.143
64145.973129.085
65143.827126.649
66141.882124.158
67139.615121.830
68137.558118.790
69134.840115.662
70132.854113.406
71130.828110.316
72128.863107.836
73126.752104.918
74124.875102.303
75122.27299.395
76119.75196.788
77117.30893.937
78114.75491.293
79112.10188.750
80109.30385.400
81106.11182.232
82103.44179.199
83100.91175.731
8498.03172.804
8595.78970.248
8692.64166.778
8789.36063.162
8886.32760.220
8982.43456.650
9079.17252.625
9175.87348.810
9272.38044.224
9368.21339.226
9463.88732.961
9559.21028.329
9652.48822.824
9746.64414.389
9840.6346.637
9930.5580.000


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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