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(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile4.7494.501
Median10.73415.760
Mean17.80333.111
75% Quartile23.88947.295
Interquartile Range19.14042.794

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
191.483182.064
278.175153.243
369.755141.929
463.631132.618
559.338125.714
654.332116.095
750.715109.318
848.239102.970
945.45796.620
1043.26091.839
1140.92287.865
1239.10783.470
1337.46180.132
1436.21176.785
1534.80673.106
1633.46770.187
1732.30966.785
1830.89863.330
1929.17260.303
2028.19857.931
2127.34955.652
2226.29853.134
2325.50351.386
2424.88648.862
2523.89547.296
2622.87245.958
2722.11943.943
2821.43942.362
2920.68240.550
3020.06938.589
3119.34736.827
3218.80335.073
3318.21533.715
3417.56632.399
3517.03030.635
3616.47129.260
3716.04427.920
3815.57926.701
3915.13425.722
4014.54624.466
4114.08223.286
4213.53322.434
4313.13421.731
4412.79620.788
4512.40619.962
4612.03619.062
4711.71018.269
4811.26917.265
4911.00016.530
5010.73415.760
5110.36015.081
5210.04914.421
539.78113.675
549.58312.986
559.34112.312
569.09311.527
578.86811.080
588.60610.641
598.34310.172
608.0999.580
617.8269.012
627.5908.613
637.3408.252
647.0867.823
656.8787.500
666.6297.179
676.3716.888
686.1336.521
695.8876.158
705.6795.906
715.4635.572
725.2735.314
735.0795.022
744.9494.770
754.7474.501
764.5384.269
774.3414.025
784.1083.808
793.9263.608
803.6693.356
813.4893.129
823.2552.923
833.0902.699
842.9172.521
852.6952.372
862.5202.180
872.3491.993
882.1431.849
891.9761.685
901.8141.513
911.6721.363
921.4951.196
931.3181.032
941.1270.851
950.9410.733
960.7450.608
970.5330.449
980.3240.331
990.0870.217


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 The historical reference is a probabilistic representation of the historical data.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