Seasonal Streamflow Forecasts

Probability distribution for Unregulated inflow to Goulburn Weir


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Product list for Unregulated inflow to Goulburn Weir



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Probability distribution for Unregulated inflow to Goulburn Weir ( Jun 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile232.066243.149
Median359.240435.864
Mean411.160549.466
75% Quartile540.199744.018
Interquartile Range308.133500.868

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
11225.0681951.594
21057.7871678.366
3980.0971572.564
4915.1361486.321
5870.7021422.935
6838.5111335.533
7808.2171274.656
8783.0351218.204
9754.4581162.321
10736.9851120.639
11714.2111086.248
12697.7321048.491
13680.6491019.995
14664.308991.568
15653.441960.478
16641.315935.918
17627.812907.383
18615.312878.485
19605.173853.204
20592.524833.391
21579.192814.340
22569.689793.246
23561.835778.571
24551.392757.290
25540.290744.024
26531.019732.647
27521.090715.404
28513.689701.786
29506.521686.042
30497.674668.825
31489.381653.178
32481.368637.390
33474.478625.000
34464.391612.856
35456.773596.300
36448.572583.161
37441.515570.134
38433.064558.065
39426.393548.210
40418.345535.335
41411.617522.976
42405.841513.876
43399.140506.248
44393.552495.830
45387.660486.516
46381.771476.158
47374.090466.822
48369.088454.721
49364.738445.628
50359.240435.864
51353.313427.060
52347.725418.306
53342.233408.137
54336.964398.487
55332.142388.768
56326.778377.087
57321.975370.237
58317.180363.356
59311.837355.850
60306.275346.073
61301.118336.401
62296.708329.396
63291.155322.893
64286.774314.964
65283.350308.833
66278.345302.605
67273.852296.821
68267.652289.327
69264.020281.685
70259.184276.220
71253.847268.794
72248.570262.884
73243.373255.994
74237.808249.877
75232.018243.138
76227.619237.157
77222.178230.678
78217.657224.730
79210.939219.067
80205.516211.692
81200.621204.809
82195.354198.302
83189.646190.964
84184.103184.857
85178.787179.590
86172.011172.538
87166.381165.312
88161.136159.527
89155.101152.621
90149.795144.987
91142.338137.903
92135.947129.585
93127.464120.770
94120.316110.096
95110.540102.477
96100.88193.730
9792.10580.986
9881.53569.993
9959.32557.102


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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