Seasonal Streamflow Forecasts

Probability distribution for Turon River at Sofala


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Product list for Turon River at Sofala



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Probability distribution for Turon River at Sofala ( Jun 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile2.1513.193
Median5.74410.794
Mean13.65033.481
75% Quartile14.82136.117
Interquartile Range12.67032.924

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1122.806283.662
289.873220.809
372.841196.225
461.451176.496
553.784161.581
647.446142.182
743.062128.799
838.980116.529
935.406104.817
1033.05296.372
1130.43389.625
1228.56882.492
1326.91877.244
1425.20372.127
1524.01866.792
1622.66262.782
1721.51558.203
1820.65053.789
1919.83150.136
2018.94047.396
2117.95444.839
2217.28642.009
2316.42140.263
2415.68437.661
2514.82236.135
2614.16034.845
2713.68532.893
2813.08131.412
2912.60529.834
3012.09128.096
3111.65926.611
3211.23025.111
3310.73024.003
3410.33722.995
359.93821.570
369.63620.530
379.26819.499
388.95418.595
398.64617.857
408.28016.934
417.94716.072
427.72815.468
437.43114.955
447.15514.292
456.89613.713
466.70513.070
476.47712.533
486.21811.836
495.98511.320
505.74410.794
515.55410.331
525.3409.891
535.1819.368
545.0468.918
554.8748.436
564.6947.927
574.5567.625
584.3697.324
594.1927.015
604.0626.604
613.8836.233
623.7335.967
633.6195.722
643.4775.440
653.2975.222
663.1715.006
673.0534.810
682.9454.563
692.7964.318
702.7024.147
712.5953.921
722.4773.746
732.3543.548
742.2533.376
752.1483.193
762.0433.035
771.9612.868
781.8502.720
791.7602.582
801.6772.409
811.5832.253
821.4972.110
831.3671.955
841.2631.831
851.1701.727
861.0731.593
870.9861.461
880.8911.360
890.7961.245
900.7181.123
910.6351.015
920.5420.896
930.4470.778
940.3640.647
950.2520.561
960.1700.469
970.0870.350
980.0000.262
990.0000.175


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 The historical reference is a probabilistic representation of the historical data.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