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(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile104.96698.796
Median140.688146.814
Mean145.323151.014
75% Quartile179.856197.429
Interquartile Range74.89098.633

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1301.484331.633
2275.512303.794
3263.576292.857
4250.888283.847
5245.444277.159
6237.032267.825
7232.402261.230
8228.679255.034
9223.937248.811
10219.649244.103
11216.306240.170
12213.751235.798
13210.414232.455
14207.427229.082
15203.662225.343
16201.232222.350
17198.612218.826
18195.395215.201
19193.447211.979
20190.990209.419
21188.782206.927
22186.170204.129
23184.192202.158
24182.141199.260
25179.862197.430
26177.863195.844
27175.959193.413
28174.463191.466
29172.612189.187
30170.750186.655
31168.862184.317
32166.908181.921
33165.530180.012
34164.121178.116
35162.746175.490
36160.965173.369
37159.446171.233
38158.063169.224
39156.594167.559
40155.311165.352
41153.606163.196
42152.162161.585
43150.361160.218
44148.891158.327
45147.597156.610
46146.199154.672
47144.951152.898
48143.680150.557
49142.259148.767
50140.688146.814
51139.516145.023
52137.863143.214
53136.358141.076
54135.073139.008
55133.817136.886
56132.494134.280
57131.302132.723
58130.058131.136
59128.747129.377
60127.468127.044
61125.786124.684
62124.036122.942
63122.796121.300
64121.680119.262
65120.380117.660
66119.098116.007
67117.411114.449
68116.040112.395
69114.290110.260
70112.725108.706
71111.059106.559
72109.446104.818
73108.097102.754
74106.509100.887
75104.96198.793
76103.28796.900
77101.46594.812
7899.70792.861
7997.97390.971
8096.18088.461
8194.34286.068
8292.66983.760
8391.11981.102
8489.37878.844
8587.72076.863
8685.38374.161
8782.89471.332
8881.27069.024
8979.15066.216
9076.32663.048
9174.14460.047
9271.42756.451
9368.69352.559
9465.61247.741
9561.90744.240
9656.59540.168
9752.46134.162
9844.81428.952
9932.98222.873


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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