Seasonal Streamflow Forecasts

Probability distribution for Cotter River at Gingera


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Product list for Cotter River at Gingera



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Probability distribution for Cotter River at Gingera ( May 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile6.2903.794
Median9.2266.370
Mean10.3598.271
75% Quartile13.23910.622
Interquartile Range6.9486.828

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
128.76833.674
225.85627.492
323.65725.215
422.06823.443
521.13322.134
620.29420.463
719.61319.325
818.95118.285
918.40717.290
1017.78716.565
1117.36315.979
1216.99115.350
1316.68514.878
1416.34814.410
1515.96813.910
1615.61513.524
1715.31413.073
1815.02612.623
1914.67912.239
2014.41611.942
2114.16311.658
2213.91111.334
2313.67111.129
2413.46110.814
2513.24210.625
2613.05010.461
2712.88310.207
2812.66110.009
2912.4719.792
3012.2769.546
3112.0409.329
3211.8399.102
3311.6758.930
3411.5128.769
3511.3768.536
3611.2238.359
3711.0678.179
3810.8998.017
3910.7367.881
4010.5857.706
4110.4727.538
4210.3207.417
4310.1597.312
4410.0187.173
459.8807.048
469.7626.907
479.6316.785
489.5216.623
499.3696.499
509.2266.370
519.0766.252
528.9596.138
538.8585.998
548.7375.874
558.6055.738
568.4565.588
578.3085.497
588.2085.404
598.1215.305
608.0205.171
617.9175.045
627.8264.953
637.7044.865
647.5934.762
657.5024.680
667.3844.596
677.2664.519
687.1334.418
697.0084.315
706.8634.242
716.7394.142
726.6214.062
736.5193.969
746.4123.886
756.2873.794
766.1343.713
776.0233.624
785.9033.543
795.8043.465
805.6523.364
815.4973.269
825.3773.178
835.2363.076
845.0742.991
854.9242.917
864.8082.818
874.6782.716
884.5292.634
894.3622.536
904.1732.426
914.0022.324
923.8382.203
933.6662.074
943.4451.915
953.2341.801
962.9521.669
972.6731.472
982.4011.300
991.9611.092


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 The historical reference is a probabilistic representation of the historical data.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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