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Historical Reference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% Quartile216.150144.741
Median259.761201.064
Mean260.862206.631
75% Quartile304.830261.632
Interquartile Range88.680116.891

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1422.908425.121
2405.277391.071
3387.011377.703
4376.803366.696
5367.874358.529
6362.380347.137
7357.073339.093
8351.908331.540
9347.786323.959
10343.252318.227
11340.281313.442
12337.467308.123
13334.276304.061
14331.375299.962
15328.456295.422
16325.504291.790
17322.636287.516
18320.104283.122
19317.441279.220
20315.130276.122
21312.958273.106
22310.736269.723
23308.288267.341
24306.741263.842
25304.831261.633
26303.135259.720
27301.330256.788
28299.699254.443
29297.220251.697
30294.952248.650
31292.611245.839
32290.811242.959
33289.160240.667
34287.313238.392
35285.113235.243
36283.167232.702
37281.178230.145
38279.642227.741
39277.861225.751
40276.378223.114
41275.056220.541
42273.021218.620
43271.286216.991
44269.608214.738
45268.169212.695
46266.424210.390
47265.002208.281
48263.142205.503
49261.637203.379
50259.761201.064
51258.499198.943
52256.953196.803
53255.152194.275
54254.008191.833
55252.366189.329
56250.658186.258
57248.952184.424
58246.949182.556
59245.318180.489
60243.147177.747
61241.278174.978
62239.742172.935
63237.949171.011
64236.284168.625
65234.756166.750
66233.391164.816
67231.529162.995
68229.402160.597
69227.770158.104
70225.870156.291
71223.642153.787
72221.584151.758
73219.748149.352
74217.918147.176
75216.145144.737
76214.037142.532
77211.814140.100
78210.041137.826
79208.087135.622
80205.449132.695
81202.821129.902
82200.426127.204
83198.096124.093
84195.510121.445
85192.680119.118
86189.936115.936
87187.532112.593
88184.035109.855
89181.424106.510
90178.677102.714
91174.15799.093
92169.95594.715
93165.24989.919
94158.50983.883
95152.26479.414
96144.83574.108
97136.23766.022
98127.52258.685
99111.80849.620


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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