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 ( Apr 2014 )

Basic Statistics
Historical Reference
(3 month total flow in GL)
25% Quartile37.575
Median55.763
Mean66.714
75% Quartile82.958
Interquartile Range45.383

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Historical Reference
(3 month total flow in GL)
1234.600
2189.155
3173.810
4162.107
5153.931
6143.203
7136.076
8129.702
9123.600
10119.174
11115.598
12111.746
13108.889
14106.078
15103.046
16100.682
1797.966
1895.248
1992.894
2091.065
2189.319
2287.397
2386.067
2484.149
2582.959
2681.941
2780.404
2879.194
2977.799
3076.278
3174.899
3273.510
3372.422
3471.356
3569.905
3668.753
3767.612
3866.554
3965.690
4064.561
4163.475
4262.675
4362.004
4461.086
4560.264
4659.348
4758.520
4857.445
4956.635
5055.763
5154.974
5254.187
5353.269
5452.395
5551.511
5650.443
5749.814
5849.180
5948.485
6047.576
6146.670
6246.011
6345.396
6444.643
6544.057
6643.459
6742.901
6842.174
6941.427
7040.890
7140.156
7239.567
7338.877
7438.259
7537.574
7636.961
7736.293
7835.674
7935.080
8034.300
8133.565
8232.863
8332.062
8431.388
8530.802
8630.008
8729.183
8828.514
8927.706
9026.798
9125.941
9224.916
9323.805
9422.423
9521.407
9620.209
9718.391
9816.741
9914.685


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 The historical reference is a probabilistic representation of the historical data.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 The historical reference plot and the historical data plots are derived from the available historical record.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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