Seasonal Streamflow Forecasts

Probability distribution for Mitta Mitta River at Hinnomunjie


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Product list for Mitta Mitta River at Hinnomunjie


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Probability distribution for Mitta Mitta River at Hinnomunjie( Jul 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile126.522113.257
Median162.522156.749
Mean167.287165.798
75% Quartile203.162208.741
Interquartile Range76.63995.485

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1328.412365.842
2304.281331.993
3289.438318.806
4280.268308.002
5273.241300.021
6264.668288.942
7258.588281.163
8252.417273.893
9247.899266.633
10243.599261.171
11239.662256.629
12236.582251.601
13233.075247.776
14230.105243.931
15227.826239.689
16224.455236.308
17221.373232.345
18217.964228.290
19215.181224.704
20213.314221.868
21211.290219.117
22208.569216.043
23206.904213.886
24205.083210.728
25203.163208.742
26200.993207.027
27198.632204.406
28196.756202.317
29195.115199.880
30193.661197.187
31191.761194.712
32190.298192.187
33188.605190.185
34186.840188.205
35185.126185.475
36183.704183.283
37182.056181.085
38180.262179.027
39178.441177.329
40176.977175.089
41175.743172.912
42173.954171.293
43172.541169.924
44171.329168.037
45169.771166.333
46168.226164.418
47166.728162.672
48165.165160.382
49163.665158.640
50162.522156.749
51161.482155.023
52160.234153.289
53158.709151.249
54156.963149.288
55155.528147.287
56154.008144.846
57152.766143.395
58151.205141.923
59149.885140.300
60148.544138.157
61147.034136.005
62145.903134.425
63144.371132.942
64143.162131.112
65141.538129.680
66140.147128.208
67138.578126.828
68137.396125.017
69136.002123.144
70134.686121.788
71133.128119.922
72131.347118.417
73129.794116.639
74128.234115.040
75126.509113.254
76124.719111.646
77123.198109.881
78121.235108.237
79119.807106.651
80118.036104.553
81115.957102.561
82113.648100.646
83111.30998.448
84109.18596.585
85107.22994.954
86104.83092.732
87102.43590.409
88100.58488.512
8998.47886.204
9096.31783.593
9193.48281.111
9290.87878.118
9387.51974.848
9483.22670.737
9579.63167.692
9674.74964.070
9769.03058.519
9861.92453.424
9951.04547.007


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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