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Historical Reference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% Quartile64.11055.959
Median87.12980.308
Mean93.68893.346
75% Quartile115.302115.510
Interquartile Range51.19259.551

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1222.840299.056
2202.503245.572
3187.339227.276
4178.361213.232
5171.230203.369
6165.163190.360
7159.044181.672
8155.538173.870
9151.386166.369
10147.824160.909
11144.383156.485
12141.298151.707
13138.910148.153
14136.156144.649
15134.266140.862
16132.199137.901
17130.419134.493
18128.168131.075
19126.247128.108
20124.269125.798
21122.032123.588
22120.209121.153
23118.473119.465
24116.905117.027
25115.327115.511
26114.093114.214
27112.683112.252
28111.221110.705
29110.060108.919
30108.618106.969
31107.095105.198
32106.078103.411
33104.710102.009
34103.765100.635
35102.57798.760
36101.38897.271
37100.08995.792
3899.02394.420
3998.00693.298
4096.93691.829
4195.90290.415
4294.83089.372
4393.78388.495
4492.79287.296
4591.89386.220
4690.89185.020
4790.11583.935
4888.91982.522
4987.88181.457
5087.12980.308
5186.07379.267
5285.18378.228
5384.43277.015
5483.57675.858
5582.61574.686
5681.74973.268
5780.82672.431
5880.01671.587
5979.07270.661
6078.15469.447
6177.14568.237
6276.04567.354
6375.09666.531
6474.22065.519
6573.46564.732
6672.80163.927
6771.95763.176
6871.01162.195
6970.22161.187
7069.23060.461
7168.13959.466
7267.08958.668
7365.91157.731
7464.88256.891
7564.10955.958
7663.00855.122
7761.89854.209
7860.98653.363
7959.99652.549
8059.02251.479
8158.16250.468
8256.91649.501
8355.96948.396
8454.73947.465
8553.65546.653
8652.51445.551
8751.40344.404
8850.05943.472
8948.94542.343
9047.69041.071
9146.39639.868
9244.68738.424
9342.99136.853
9440.92134.889
9538.84333.441
9636.84131.724
9734.16029.102
9830.15726.703
9925.76123.684


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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