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 ( Jun 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile2.1091.878
Median4.7905.255
Mean9.48412.997
75% Quartile10.85414.366
Interquartile Range8.74512.488

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
174.074108.602
254.08381.405
344.17571.284
438.05863.317
533.44157.668
629.91050.228
727.18745.322
825.30340.999
923.68236.951
1022.00634.087
1120.52031.827
1219.27329.454
1318.10727.739
1417.22326.093
1516.42224.366
1615.75823.056
1714.97421.592
1814.32120.173
1913.80118.982
2013.17418.082
2112.66217.244
2212.18616.345
2311.72815.738
2411.34414.884
2510.85414.366
2610.48513.932
2710.14513.290
289.79312.796
299.45712.239
309.08511.648
318.78511.126
328.52610.615
338.24310.223
348.0189.848
357.7849.349
367.5748.965
377.3198.592
387.0608.255
396.7877.986
406.5497.642
416.3447.319
426.1087.086
435.9286.894
445.7286.637
455.5636.411
465.3946.165
475.2475.947
485.1075.672
494.9685.469
504.7905.255
514.6555.066
524.5294.882
534.3694.672
544.2114.477
554.0534.285
563.9404.059
573.8203.930
583.7253.802
593.6203.664
603.4923.488
613.3583.319
623.2823.198
633.1893.088
643.0632.956
652.9932.856
662.9052.756
672.8072.664
682.7262.547
692.6122.431
702.5442.349
712.4742.239
722.3662.154
732.2842.056
742.1981.970
752.1041.878
762.0131.798
771.9201.712
781.8271.635
791.7281.563
801.6381.472
811.5551.388
821.4771.311
831.3911.226
841.3261.157
851.2471.098
861.1771.022
871.0940.946
881.0010.887
890.9150.818
900.8400.744
910.7710.678
920.7090.603
930.6270.527
940.5560.439
950.4760.380
960.3940.315
970.2840.228
980.1870.160
990.0110.088


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 The historical reference is a probabilistic representation of the historical data.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