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( Apr 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile2.9570.917
Median9.0664.138
Mean20.16519.192
75% Quartile27.01017.863
Interquartile Range24.05216.946

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1125.552189.556
2106.722146.077
394.448129.118
484.439115.107
577.023104.303
670.51990.864
765.32981.284
861.10072.482
957.69864.180
1054.84158.153
1151.66853.376
1248.54048.415
1346.18744.769
1443.59041.072
1541.47737.546
1639.47434.887
1737.86531.684
1836.25728.871
1934.79326.553
2033.32824.824
2131.90323.173
2230.52921.346
2329.31120.354
2427.95218.793
2527.04517.873
2625.61917.103
2724.28015.949
2823.37215.083
2922.40614.171
3021.35713.177
3120.40412.339
3219.45111.502
3318.53610.891
3418.06010.340
3517.3439.571
3616.4589.015
3715.7418.471
3815.0477.998
3914.4897.616
4013.8057.142
4113.0996.705
4212.5616.401
4312.0916.145
4411.6935.816
4511.1665.532
4610.7245.220
4710.3244.961
489.9614.628
499.5534.385
509.0664.138
518.7163.924
528.2823.721
537.9063.483
547.6233.281
557.3843.066
567.0722.841
576.7762.710
586.5012.579
596.2702.447
606.0422.272
615.7892.116
625.5232.005
635.3191.904
645.0761.789
654.8291.701
664.6371.614
674.3971.536
684.2111.438
694.0601.342
703.8761.276
713.7021.189
723.5091.123
733.3131.048
743.1010.984
752.9560.917
762.8160.859
772.6680.799
782.4700.746
792.3350.697
802.1830.636
812.0160.583
821.8840.534
831.7640.482
841.6630.441
851.5460.407
861.3820.364
871.2770.322
881.1450.290
891.0270.254
900.9230.218
910.7810.186
920.6870.151
930.5850.118
940.4580.082
950.3520.059
960.2140.035
970.1200.006
980.0300.000
990.0000.000


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 The historical reference is a probabilistic representation of the historical data.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