Seasonal Streamflow Forecasts

Probability distribution for Total flow of Kiewa River to Murray River


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Product list for Total flow of Kiewa River to Murray River


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Probability distribution for Total flow of Kiewa River to Murray River( Jun 2013 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile155.166138.533
Median214.953207.648
Mean221.273226.993
75% Quartile281.090295.657
Interquartile Range125.924157.124

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1464.888571.638
2432.130511.943
3412.451488.682
4394.475469.625
5382.085455.550
6370.575436.020
7363.094422.315
8355.716409.516
9348.392396.745
10342.266387.143
11337.494379.166
12333.025370.344
13328.240363.637
14323.182356.902
15318.441349.479
16313.254343.570
17309.795336.650
18306.044329.579
19301.232323.336
20297.820318.403
21293.516313.624
22289.892308.292
23286.885304.554
24283.554299.091
25281.102295.658
26277.905292.697
27275.254288.179
28272.198284.582
29269.876280.392
30267.222275.769
31265.022271.529
32261.965267.211
33259.600263.793
34256.595260.417
35253.655255.772
36250.134252.050
37247.589248.325
38244.563244.844
39241.638241.979
40239.225238.203
41236.684234.544
42234.065231.826
43231.367229.533
44228.594226.378
45226.341223.534
46224.354220.344
47222.309217.444
48220.059213.648
49218.007210.768
50214.953207.648
51212.433204.809
52210.293201.962
53207.854198.624
54205.808195.423
55203.521192.166
56200.967188.207
57198.837185.862
58196.286183.487
59194.007180.876
60191.643177.440
61188.825174.002
62186.565171.486
63184.239169.132
64182.312166.235
65179.765163.974
66177.724161.659
67175.074159.493
68173.139156.661
69170.461153.743
70167.504151.637
71165.366148.749
72162.921146.429
73160.392143.698
74157.729141.251
75155.160138.528
76152.131136.088
77149.440133.418
78146.892130.943
79144.711128.564
80142.100125.433
81139.138122.475
82135.228119.646
83132.295116.416
84129.424113.696
85126.298111.325
86123.142108.113
87118.620104.776
88114.036102.069
89109.98498.797
90105.39895.123
91102.15091.659
9295.74587.520
9388.15183.045
9482.91977.493
9578.22373.434
9671.77268.666
9761.84761.490
9848.52155.050
9930.55747.148


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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