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 ( Feb 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile41.60883.482
Median71.747148.528
Mean82.593191.574
75% Quartile110.734248.547
Interquartile Range69.126165.065

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1274.554838.495
2237.906657.589
3214.590597.161
4200.778551.330
5190.480519.449
6179.907477.797
7172.940450.250
8166.157425.698
9161.759402.272
10155.147385.331
11151.351371.676
12148.016357.003
13143.996346.139
14140.086335.472
15136.740323.990
16133.622315.051
17130.973304.802
18127.971294.565
19125.084285.720
20122.739278.855
21120.462272.308
22118.083265.116
23115.902260.146
24113.042252.986
25110.782248.549
26109.088244.759
27107.193239.040
28104.871234.544
29103.288229.366
30101.247223.728
3199.692218.623
3298.265213.489
3396.535209.470
3494.873205.539
3593.241200.192
3691.852195.956
3790.191191.762
3888.823187.880
3987.082184.712
4085.747180.575
4184.097176.604
4282.348173.680
4380.826171.229
4479.409167.879
4578.282164.883
4676.903161.547
4775.642158.538
4874.413154.632
4973.121151.691
5071.747148.528
5170.648145.671
5269.682142.824
5368.441139.509
5466.948136.354
5565.772133.167
5664.839129.323
5763.593127.060
5862.544124.781
5961.512122.288
6060.330119.027
6159.088115.786
6257.859113.429
6356.893111.232
6455.790108.543
6554.191106.454
6652.956104.324
6751.955102.338
6850.88399.753
6949.53597.103
7048.51895.198
7146.93992.596
7245.95390.514
7344.73488.074
7443.04785.894
7541.60483.478
7640.40381.320
7739.30478.968
7837.94476.794
7936.67874.711
8035.63471.978
8134.19169.405
8232.92266.952
8331.63264.160
8430.33261.814
8528.97359.775
8627.76057.018
8725.84354.161
8824.00451.848
8922.15149.057
9020.32345.930
9118.38942.984
9215.96439.471
9313.32535.674
9411.67230.966
958.86927.522
965.65523.472
971.34617.360
980.00011.848
990.0005.033


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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