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( Sep 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile3.6823.678
Median7.98611.248
Mean12.79627.016
75% Quartile16.40832.657
Interquartile Range12.72628.978

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
171.952191.939
258.434152.969
349.572137.866
444.795125.585
540.660116.598
637.434104.304
734.95595.844
832.91988.109
930.82880.589
1029.18875.092
1127.71770.640
1226.25465.855
1325.16362.321
1424.28158.869
1523.20755.184
1622.33552.344
1721.67749.129
1821.01245.969
1920.31343.288
2019.66341.243
2118.93439.324
2218.12437.255
2317.58535.850
2416.97133.864
2516.41032.657
2615.91431.641
2715.43530.135
2815.01928.974
2914.56227.664
3014.05426.270
3113.59925.038
3213.23623.829
3312.90422.903
3412.54022.016
3512.21320.839
3611.80719.930
3711.44119.052
3811.10718.257
3910.85317.623
4010.57216.813
4110.30416.055
4210.02415.509
439.72315.060
449.47114.458
459.25513.931
468.98713.357
478.74612.851
488.47412.211
498.21811.741
507.98611.248
517.81110.813
527.55910.389
537.3799.907
547.1299.461
556.9629.023
566.7968.510
576.6188.216
586.4337.926
596.2657.616
606.0507.221
615.9146.840
625.7116.571
635.5466.326
645.3706.033
655.2225.811
665.0385.589
674.8895.387
684.7495.131
694.5644.875
704.4044.696
714.2204.458
724.0804.272
733.9444.060
743.8473.876
753.6813.678
763.5383.506
773.3793.324
783.2163.160
793.0683.008
802.9502.814
812.8042.639
822.6412.477
832.5042.300
842.3502.157
852.1782.036
862.0231.879
871.9011.724
881.7701.604
891.6331.464
901.4761.316
911.3221.184
921.1601.035
931.0260.886
940.8680.716
950.7050.603
960.5250.480
970.3180.317
980.1260.191
990.0000.062


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 The historical reference is a probabilistic representation of the historical data.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