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( Sep 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile304.389241.981
Median447.360418.224
Mean506.151506.555
75% Quartile651.110684.675
Interquartile Range346.721442.694

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
11394.6831658.464
21228.9341441.609
31149.6081357.428
41082.1321288.677
51024.8181238.053
6989.6481168.088
7951.7101119.222
8923.0811073.790
9892.2171028.689
10870.097994.955
11851.394967.053
12833.316936.343
13811.395913.108
14793.961889.876
15779.264864.401
16762.380844.225
17750.114820.722
18734.386796.850
19720.152775.902
20706.677759.442
21694.605743.577
22682.880725.968
23672.586713.687
24662.729695.836
25651.281684.681
26639.873675.097
27628.769660.541
28620.765649.017
29611.188635.665
30601.549621.024
31592.026607.682
32583.326594.184
33574.923583.566
34567.848573.134
35559.457558.877
36550.206547.530
37542.223536.252
38535.464525.778
39527.277517.207
40519.097505.984
41512.035495.182
42504.019487.212
43496.424480.518
44487.686471.358
45480.944463.152
46473.668454.007
47467.079445.745
48460.812435.011
49454.596426.926
50447.360418.224
51441.829410.362
52436.334402.527
53428.588393.405
54422.922384.728
55417.788375.968
56412.672365.412
57407.817359.207
58402.320352.963
59395.661346.138
60391.199337.230
61384.025328.395
62378.597321.981
63373.159316.017
64366.715308.730
65360.420303.085
66354.811297.340
67347.722291.996
68343.158285.060
69337.798277.971
70332.563272.891
71327.607265.977
72321.805260.463
73315.718254.023
74309.543248.294
75304.321241.971
76298.118236.347
77292.762230.244
78287.336224.630
79280.510219.275
80274.987212.287
81268.192205.749
82262.733199.555
83256.545192.553
84250.285186.713
85243.511181.666
86237.752174.893
87228.218167.935
88221.699162.351
89214.890155.670
90206.493148.263
91200.563141.369
92190.850133.248
93181.501124.611
94172.797114.104
95163.092106.572
96148.97997.887
97135.25485.159
98119.72074.099
9997.14761.020


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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