Seasonal Streamflow Forecasts

Probability distribution for Gudgenby at Tennent


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Probability distribution for Gudgenby at Tennent ( Apr 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile3.3522.587
Median6.1725.617
Mean9.06210.956
75% Quartile11.52112.263
Interquartile Range8.1699.676

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
147.66490.968
237.30160.974
331.87751.843
428.41845.380
526.10840.943
624.00635.671
722.49832.318
820.97329.417
919.89926.778
1018.82724.940
1118.06423.502
1217.38122.006
1316.73620.917
1416.04419.861
1515.52418.764
1615.09717.938
1714.63616.992
1814.18516.074
1913.86815.308
2013.37514.727
2112.95514.180
2212.67413.568
2312.34313.186
2411.91112.610
2511.52612.267
2611.19811.975
2710.92811.527
2810.55511.183
2910.29410.811
3010.00310.394
319.76710.033
329.4889.661
339.2859.383
349.0679.125
358.8798.756
368.6508.481
378.4448.204
388.2567.957
398.0357.752
407.8537.493
417.6817.246
427.5137.070
437.3426.919
447.1986.721
457.0476.545
466.8266.347
476.6266.179
486.4745.958
496.3385.790
506.1725.617
516.0335.462
525.9225.312
535.7735.132
545.6344.973
555.5044.800
565.4064.613
575.2864.501
585.1584.387
595.0524.268
604.9574.107
614.8323.958
624.7033.850
634.6003.749
644.4963.630
654.3923.537
664.3173.443
674.1973.357
684.0973.246
693.9943.134
703.8873.055
713.7792.948
723.6752.863
733.5602.766
743.4742.680
753.3522.587
763.2452.504
773.1652.416
783.0582.336
792.9572.260
802.8322.162
812.7282.072
822.6031.988
832.5141.894
842.4091.816
852.3101.750
862.2041.662
872.1011.574
882.0071.504
891.9081.421
901.8031.331
911.7041.248
921.6151.153
931.5181.054
941.3560.937
951.1960.856
961.0580.764
970.9090.635
980.6970.528
990.4860.408


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 The historical reference is a probabilistic representation of the historical data.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