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( Oct 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile156.718164.649
Median216.383280.064
Mean240.851350.286
75% Quartile301.095463.362
Interquartile Range144.376298.714

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1646.7401252.212
2560.1921064.863
3516.662993.309
4486.796935.493
5458.843893.325
6440.316835.675
7427.045795.883
8414.292759.266
9402.650723.300
10392.143696.660
11383.298674.803
12375.791650.936
13370.112633.013
14362.917615.213
15355.449595.832
16349.509580.588
17342.741562.947
18336.745545.160
19331.919529.662
20326.619517.556
21321.527505.948
22315.774493.132
23310.530484.237
24305.813471.370
25301.099463.367
26296.549456.513
27292.383446.145
28287.539437.972
29284.434428.538
30280.060418.240
31276.211408.897
32272.370399.484
33268.186392.107
34263.822384.883
35260.278375.046
36257.246367.247
37253.909359.521
38251.308352.369
39248.212346.532
40245.535338.909
41241.959331.595
42239.532326.212
43236.538321.700
44233.574315.538
45230.901310.030
46228.520303.904
47225.428298.382
48222.305291.224
49219.351285.843
50216.383280.064
51213.591274.850
52211.644269.664
53208.875263.636
54206.732257.911
55204.544252.141
56202.176245.200
57199.408241.125
58197.098237.028
59194.478232.555
60192.212226.723
61189.966220.945
62187.443216.754
63184.759212.860
64182.019208.106
65179.983204.424
66178.150200.680
67176.429197.198
68174.224192.681
69171.974188.065
70169.167184.759
71166.817180.260
72164.113176.673
73161.495172.483
74159.162168.756
75156.695164.642
76153.997160.983
77151.496157.011
78148.451153.357
79146.262149.869
80144.195145.317
81141.939141.055
82139.707137.016
83136.412132.445
84133.556128.630
85130.799125.330
86127.381120.897
87124.128116.338
88121.218112.674
89117.770108.284
90114.623103.410
91111.26098.863
92108.55893.496
93104.28487.770
94100.18980.780
9594.90375.750
9689.59869.927
9782.83361.343
9874.44953.825
9961.79644.851


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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