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 ( Apr 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile123.016160.251
Median189.543266.258
Mean228.831357.686
75% Quartile289.955443.795
Interquartile Range166.938283.544

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1827.8841689.653
2669.4731280.992
3606.2441148.923
4555.5411050.412
5523.475982.776
6496.220895.579
7472.793838.673
8453.978788.494
9437.263741.108
10422.430707.153
11407.154679.981
12394.485650.983
13379.017629.651
14367.792608.823
15358.039586.539
16351.385569.286
17344.362549.612
18334.567530.079
19325.506513.297
20318.383500.335
21312.578488.025
22306.833474.564
23300.533465.299
24295.688452.005
25290.084443.799
26285.400436.810
27279.783426.299
28274.880418.065
29269.954408.618
30265.433398.371
31259.634389.132
32254.844379.877
33250.324372.660
34245.940365.622
35241.380356.084
36237.458348.559
37233.483341.135
38229.950334.287
39225.735328.717
40222.942321.466
41219.470314.532
42216.239309.443
43212.163305.187
44208.934299.387
45206.546294.215
46202.990288.476
47199.490283.313
48195.624276.636
49192.626271.628
50189.543266.258
51185.774261.423
52183.104256.619
53180.465251.045
54177.778245.759
55174.496240.439
56172.323234.048
57170.037230.300
58167.138226.535
59164.975222.428
60162.095217.076
61159.670211.779
62156.621207.939
63153.567204.372
64151.095200.019
65148.702196.650
66146.014193.223
67143.309190.038
68140.503185.905
69138.022181.683
70136.239178.659
71133.329174.542
72131.250171.259
73128.288167.425
74125.856164.012
75122.969160.245
76119.200156.891
77117.108153.250
78114.998149.898
79112.355146.697
80110.197142.515
81107.701138.596
82104.941134.878
83102.076130.666
8498.957127.145
8596.078124.097
8692.732119.997
8789.541115.773
8886.373112.373
8982.940108.291
9079.610103.748
9176.71199.500
9273.41494.472
9369.17089.089
9464.23782.488
9559.51677.716
9653.61372.165
9748.64063.924
9841.42156.642
9932.66247.851


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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