Seasonal Streamflow Forecasts

Probability distribution for Unregulated inflow to Hume Dam


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Product list for Unregulated inflow to Hume Dam


  • Jan

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Probability distribution for Unregulated inflow to Hume Dam ( Jan 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile63.99399.400
Median101.853174.499
Mean115.809212.107
75% Quartile151.801281.193
Interquartile Range87.808181.793

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1353.150815.239
2310.608663.019
3285.995609.975
4267.064569.540
5250.950540.030
6240.171502.700
7233.211477.417
8225.759454.378
9218.594432.324
10212.367416.254
11205.599403.234
12199.949389.215
13195.066378.676
14191.060368.167
15186.173356.910
16182.274348.201
17177.999337.949
18174.066327.691
19171.148318.876
20167.862312.037
21164.068305.456
22161.068297.917
23158.080293.115
24155.206285.728
25151.819281.246
26150.005277.368
27147.159271.324
28144.487266.584
29141.889261.376
30139.328255.426
31137.340250.146
32135.378244.612
33133.410240.383
34131.177236.415
35129.305230.605
36127.309226.195
37124.901221.672
38122.864217.566
39121.007214.112
40118.791209.650
41117.074205.328
42115.221202.198
43113.551199.475
44111.949195.855
45110.703192.595
46109.108188.863
47107.451185.644
48105.927181.320
49103.921177.996
50101.853174.499
51100.478171.320
5298.766168.200
5397.040164.363
5495.364160.936
5593.767157.133
5691.971152.936
5790.719150.355
5888.906147.711
5987.550144.910
6086.115141.051
6184.891137.409
6283.677134.713
6382.331132.143
6481.018129.085
6579.679126.649
6678.482124.158
6777.347121.830
6875.623118.790
6973.816115.662
7072.016113.406
7170.423110.316
7269.346107.836
7367.766104.918
7465.916102.303
7563.97499.395
7662.20596.788
7760.88393.937
7859.22391.293
7957.50088.750
8055.53685.400
8153.84182.232
8251.83279.199
8349.78875.731
8447.90672.804
8545.96370.248
8644.25066.778
8742.53463.162
8840.67960.220
8938.51956.650
9036.30252.625
9133.71348.810
9230.73844.224
9327.89939.226
9424.82732.961
9521.25228.329
9617.79322.824
9714.57214.389
989.4936.637
990.0000.000


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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