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Historical Reference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% Quartile124.907138.800
Median160.132193.893
Mean162.055198.496
75% Quartile196.632252.179
Interquartile Range71.725113.379

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1295.987407.772
2282.638375.445
3270.686362.747
4263.834352.290
5255.994344.529
6250.492333.698
7245.863326.049
8241.477318.863
9237.442311.649
10233.067306.192
11230.267301.634
12226.671296.568
13223.673292.696
14220.557288.789
15216.958284.460
16214.760280.996
17212.751276.917
18210.660272.723
19208.088268.997
20206.004266.036
21203.639263.154
22201.757259.921
23199.863257.642
24198.041254.295
25196.632252.180
26194.655250.349
27193.150247.542
28191.584245.295
29189.896242.664
30188.376239.743
31187.030237.046
32185.619234.282
33184.092232.082
34182.437229.897
35180.790226.870
36179.453224.427
37178.113221.968
38176.501219.654
39174.788217.738
40173.321215.198
41171.623212.718
42170.086210.865
43168.763209.293
44167.642207.118
45166.602205.145
46165.318202.918
47164.210200.879
48162.835198.191
49161.808196.136
50160.132193.893
51158.574191.838
52157.302189.762
53155.709187.308
54154.158184.936
55152.866182.503
56151.639179.515
57150.498177.729
58148.864175.910
59147.445173.894
60146.310171.219
61144.589168.515
62143.203166.519
63141.907164.636
64140.690162.300
65139.260160.463
66137.764158.568
67136.395156.781
68135.025154.426
69133.662151.976
70131.821150.193
71130.534147.727
72129.006145.728
73127.633143.354
74126.395141.207
75124.902138.796
76122.655136.615
77121.022134.207
78119.281131.954
79117.582129.768
80116.420126.862
81114.355124.085
82112.603121.401
83110.180118.302
84108.309115.662
85106.601113.339
86104.770110.160
87102.158106.817
88100.291104.077
8997.692100.727
9095.08096.921
9192.70893.288
9290.04988.895
9386.96184.081
9482.53378.024
9578.21273.544
9672.83568.232
9767.32460.167
9857.39252.893
9940.83243.991


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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