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Historical Reference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% Quartile4.7161.245
Median9.7433.319
Mean13.4777.088
75% Quartile19.0828.676
Interquartile Range14.3657.431

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
155.52447.853
247.49238.028
343.00734.247
440.11031.189
537.10428.963
634.97425.936
733.44823.866
831.84521.985
930.44120.165
1029.41718.841
1128.51017.771
1227.40916.625
1326.66515.780
1425.60614.955
1524.91714.075
1624.10513.398
1723.47212.630
1822.70011.875
1922.14711.234
2021.60310.744
2121.09110.283
2220.6289.786
2319.9689.447
2419.5388.968
2519.0868.676
2618.5998.429
2718.1058.063
2817.6237.780
2917.2497.460
3016.7497.118
3116.2906.815
3215.8296.516
3315.3426.287
3415.0356.066
3514.6915.772
3614.2715.545
3713.8675.324
3813.5015.124
3913.1274.963
4012.6524.757
4112.3324.564
4211.9774.425
4311.6834.309
4411.4394.154
4511.1174.018
4610.8213.870
4710.5813.738
4810.2893.571
4910.0263.448
509.7433.319
519.5353.204
529.2743.092
539.0572.964
548.8832.845
558.6722.727
568.4432.589
578.2132.510
587.9952.431
597.7292.347
607.5162.239
617.2752.135
627.0872.061
636.9101.993
646.6921.912
656.5031.850
666.2981.788
676.1101.731
685.9141.659
695.7481.587
705.5621.536
715.3811.469
725.2201.416
735.0521.355
744.8881.302
754.7161.244
764.4901.194
774.2971.141
784.1231.093
793.9081.049
803.7390.991
813.6120.939
823.4440.891
833.2280.838
843.0810.795
852.9070.758
862.7500.710
872.6050.663
882.4180.625
892.2730.582
902.1260.535
911.9360.494
921.7860.446
931.5690.398
941.4310.343
951.2730.306
961.0530.265
970.8520.209
980.6740.165
990.4090.119


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 The historical reference is a probabilistic representation of the historical data.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