Seasonal Streamflow Forecasts

Probability distribution for Unregulated inflow to Hume Dam


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

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile56.046101.109
Median96.204174.410
Mean115.070241.788
75% Quartile151.375299.836
Interquartile Range95.329198.728

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1415.3171219.990
2343.960913.125
3313.366814.793
4290.454741.757
5274.042691.779
6258.175627.563
7246.812585.797
8238.263549.067
9231.354514.472
10221.782489.740
11214.217469.984
12207.573448.938
13201.673433.481
14195.500418.410
15189.753402.310
16185.177389.863
17181.457375.688
18177.107361.636
19173.540349.580
20169.502340.280
21164.977331.458
22162.366321.821
23158.859315.194
24154.863305.696
25151.408299.839
26149.166294.854
27145.990287.364
28143.017281.502
29140.420274.782
30137.975267.500
31135.784260.942
32133.665254.378
33131.359249.265
34128.949244.282
35126.983237.537
36124.573232.220
37122.322226.979
38120.186222.149
39118.339218.223
40115.798213.118
41113.652208.240
42111.455204.662
43109.674201.672
44107.889197.601
45105.736193.973
46103.542189.950
47101.634186.334
4899.860181.662
4997.811178.161
5096.204174.410
5194.170171.034
5292.250167.684
5390.759163.800
5489.138160.120
5587.598156.419
5686.118151.978
5784.371149.376
5883.062146.764
5981.514143.917
6080.082140.210
6178.768136.545
6277.005133.890
6375.218131.426
6473.844128.422
6572.333126.098
6670.993123.737
6769.405121.543
6867.646118.699
6966.481115.797
7064.892113.720
7163.451110.894
7261.648108.644
7360.138106.017
7457.966103.681
7556.045101.104
7654.65898.814
7753.06396.328
7851.50394.042
7950.06191.862
8048.57589.016
8147.02786.352
8244.95983.828
8343.27380.972
8441.57778.588
8539.45376.526
8637.50873.755
8735.70270.905
8833.82368.614
8931.24665.867
9028.78662.816
9126.86759.968
9224.04556.603
9321.32353.010
9418.21948.615
9515.13045.447
9610.80141.773
976.49236.340
980.89231.564
990.00025.833


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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