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(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile302.002326.311
Median448.268561.322
Mean496.459642.549
75% Quartile641.751879.350
Interquartile Range339.750553.039

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
11320.4301862.185
21164.1911652.935
31089.6571571.023
41032.3991503.731
5984.5631453.907
6947.4671384.593
7923.6781335.817
8900.2431290.155
9877.1601244.486
10853.1341210.080
11836.5701181.447
12814.2771149.732
13795.0721125.587
14776.9171101.306
15766.3981074.513
16753.6901053.161
17737.0461028.129
18724.1451002.521
19709.093979.888
20699.480961.992
21687.725944.647
22678.145925.277
23665.209911.694
24654.410891.837
25641.771879.357
26632.369868.589
27625.300852.155
28614.546839.073
29605.568823.832
30598.167807.019
31586.979791.601
32577.698775.906
33567.906763.489
34562.196751.230
35552.147734.373
36543.917720.874
37535.302707.380
38527.187694.779
39517.836684.418
40510.156670.781
41503.377657.581
42497.815647.792
43491.320639.541
44485.458628.201
45478.177617.996
46471.692606.569
47466.516596.199
48461.786582.657
49455.209572.405
50448.268561.322
51440.569551.264
52434.394541.199
53428.651529.429
54422.627518.179
55416.960506.771
56411.444492.955
57406.427484.799
58401.965476.566
59394.887467.539
60389.781455.709
61384.025443.927
62379.217435.342
63373.925427.337
64367.902417.527
65360.344409.905
66354.905402.129
67349.117394.880
68344.017385.446
69338.088375.778
70332.860368.834
71326.676359.360
72322.472351.790
73314.926342.929
74308.536335.031
75301.860326.297
76295.172318.516
77287.633310.058
78282.661302.267
79276.430294.825
80271.345285.102
81264.962275.993
82257.744267.354
83252.935257.580
84245.705249.421
85239.059242.368
86234.555232.899
87227.615223.171
88219.004215.364
89213.285206.025
90205.417195.678
91197.622186.056
92189.185174.737
93180.751162.720
94167.559148.145
95156.304137.731
96144.242125.769
97132.111108.342
98114.89193.323
9993.64075.752


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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