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 ( Jul 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile225.108185.930
Median299.920278.742
Mean304.609288.648
75% Quartile379.052378.493
Interquartile Range153.944192.563

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1591.454645.191
2558.603589.801
3533.847568.043
4509.446550.123
5495.474536.821
6485.720518.258
7477.506505.146
8467.365492.828
9460.170480.460
10452.533471.104
11445.939463.291
12439.362454.605
13432.580447.966
14427.777441.267
15422.369433.844
16416.554427.904
17412.072420.910
18407.388413.718
19402.665407.329
20397.450402.252
21393.245397.311
22389.627391.766
23385.849387.859
24381.874382.120
25379.072378.495
26375.469375.356
27371.347370.543
28368.160366.691
29365.714362.181
30362.121357.175
31358.240352.553
32355.009347.818
33352.387344.048
34349.077340.304
35345.797335.120
36343.344330.937
37339.690326.725
38335.934322.764
39333.103319.484
40329.271315.138
41326.338310.895
42323.746307.726
43320.999305.039
44317.929301.321
45315.699297.949
46312.295294.144
47309.050290.663
48305.362286.074
49302.588282.567
50299.920278.742
51296.697275.238
52293.304271.701
53291.233267.524
54288.039263.488
55284.920259.350
56282.893254.274
57280.346251.244
58277.782248.157
59274.690244.742
60271.800240.213
61269.369235.640
62266.509232.268
63263.317229.092
64260.050225.156
65256.965222.064
66253.621218.877
67251.174215.878
68247.839211.929
69245.333207.829
70242.629204.850
71238.355200.737
72234.370197.410
73231.570193.468
74228.654189.909
75225.104185.924
76221.906182.327
77217.954178.368
78215.117174.673
79211.560171.100
80208.168166.366
81204.235161.862
82200.155157.526
83196.011152.545
84192.142148.324
85187.426144.628
86181.737139.596
87176.033134.343
88171.369130.065
89165.649124.874
90161.157119.031
91155.237113.509
92147.035106.909
93136.99299.779
94128.54290.972
95120.40484.580
96110.93177.146
9799.09666.168
9884.86556.606
9961.87045.367


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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