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(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile226.993274.149
Median352.406463.293
Mean368.306506.266
75% Quartile494.514688.205
Interquartile Range267.521414.056

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1863.1751485.571
2792.6281291.683
3751.6651219.964
4715.6941162.694
5699.9761121.211
6679.8731064.744
7662.5921025.838
8649.405990.009
9639.778954.720
10626.262928.477
11613.165906.853
12603.597883.118
13593.112865.196
14582.511847.295
15573.431827.676
16564.906812.137
17554.355794.022
18546.820775.598
19538.434759.397
20529.627746.638
21522.611734.312
22514.224720.590
23508.011710.991
24501.011696.991
25494.545688.209
26488.694680.643
27480.886669.109
28474.584659.939
29467.815649.265
30462.511637.499
31455.462626.713
32449.433615.734
33442.261607.047
34438.197598.466
35433.939586.657
36426.807577.188
37421.340567.711
38414.805558.845
39410.221551.542
40405.101541.911
41400.207532.563
42394.137525.614
43388.648519.742
44384.559511.651
45379.294504.347
46373.696496.140
47368.984488.664
48362.195478.857
49357.221471.396
50352.406463.293
51347.140455.901
52341.997448.467
53337.207439.723
54333.427431.309
55328.373422.717
56323.694412.224
57318.619405.982
58314.736399.643
59309.664392.645
60305.396383.396
61300.569374.089
62295.706367.244
63289.859360.811
64284.292352.855
65279.832346.618
66275.216340.200
67268.033334.165
68264.093326.234
69258.519318.009
70253.391312.037
71248.882303.800
72243.576297.138
73239.074289.246
74233.700282.120
75226.984274.136
76221.020266.925
77215.804258.975
78209.793251.544
79202.909244.344
80197.335234.777
81191.470225.641
82185.850216.810
83179.846206.609
84172.395197.912
85166.152190.251
86159.544179.745
87152.186168.667
88143.450159.551
89137.437148.362
90128.032135.573
91120.617123.272
92111.409108.248
93103.20591.561
9495.02470.153
9583.79053.951
9668.43234.250
9754.3973.043
9835.2990.000
9910.6480.000


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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