Seasonal Streamflow Forecasts

Probability distribution for Tuross River at Tuross Vale


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Product list for Tuross River at Tuross Vale


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Probability distribution for Tuross River at Tuross Vale(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile3.8251.628
Median7.6074.898
Mean9.1837.857
75% Quartile13.14311.736
Interquartile Range9.31810.108

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
130.37935.168
227.04530.231
325.19428.292
423.73026.696
522.41225.512
621.40823.861
720.49722.697
819.92921.604
919.24120.510
1018.72519.683
1118.12718.995
1217.62918.232
1317.23017.650
1416.88017.065
1516.38916.419
1615.92015.904
1715.61015.300
1815.23314.683
1914.89214.139
2014.56813.709
2114.24713.293
2213.95512.829
2313.67912.505
2413.41812.032
2513.14411.736
2612.87811.482
2712.64411.095
2812.36310.788
2912.07810.432
3011.82210.042
3111.6119.687
3211.3559.329
3311.1459.048
3410.9168.772
3510.7058.397
3610.5098.100
3710.2707.806
3810.0177.535
399.8107.314
409.5857.028
419.3506.754
429.1686.554
438.9656.387
448.7646.161
458.5425.960
468.3695.738
478.1775.540
487.9925.287
497.7925.098
507.6074.898
517.4414.720
527.2774.545
537.0794.345
546.8674.157
556.6803.971
566.5193.753
576.3373.626
586.1833.501
596.0453.367
605.8903.195
615.7413.029
625.5852.910
635.4632.802
645.2892.673
655.1592.575
665.0092.477
674.8782.388
684.7622.274
694.6452.160
704.5392.081
714.4011.975
724.2881.892
734.0771.798
743.9431.716
753.8241.628
763.6951.552
773.5221.471
783.3731.398
793.2061.331
803.0941.245
812.9961.168
822.8481.097
832.6721.019
842.5490.956
852.4160.904
862.2640.835
872.1120.768
881.9800.715
891.8650.655
901.7300.592
911.6060.535
921.4830.472
931.3000.409
941.0920.337
950.9500.290
960.7890.240
970.6320.173
980.4160.122
990.1760.071


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 The historical reference is a probabilistic representation of the historical data.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