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Historical Reference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% Quartile1.4651.109
Median3.3702.758
Mean6.0085.553
75% Quartile7.1916.495
Interquartile Range5.7255.387

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
139.00842.326
230.91531.108
325.61127.157
422.58024.138
519.91722.045
618.23519.342
717.01517.588
815.80416.056
914.68314.629
1013.78213.621
1112.97012.825
1212.36111.988
1311.76511.380
1411.22110.795
1510.77210.178
1610.4029.708
179.9129.179
189.4448.662
199.0868.226
208.6867.893
218.4117.582
228.0987.245
237.7457.017
247.4776.693
257.1936.495
266.9536.329
276.7216.081
286.4925.889
296.3145.672
306.1035.439
315.9125.232
325.7115.027
335.5634.869
345.3074.717
355.1654.514
365.0334.355
374.8884.201
384.7664.061
394.6453.947
404.5403.802
414.4173.664
424.2993.565
434.1533.482
444.0453.370
453.9573.272
463.8293.164
473.6943.068
483.5862.945
493.4912.854
503.3702.758
513.2702.672
523.1712.588
533.0692.491
542.9992.401
552.9202.311
562.8122.205
572.7262.143
582.6542.082
592.5782.016
602.5061.931
612.4321.848
622.3541.788
632.2801.734
642.1991.668
652.1301.618
662.0671.567
671.9951.521
681.9321.461
691.8661.401
701.7861.358
711.7181.301
721.6521.256
731.5821.204
741.5221.158
751.4641.109
761.4051.065
771.3381.018
781.2700.976
791.2160.936
801.1520.884
811.0840.837
821.0310.793
830.9790.744
840.9300.703
850.8750.669
860.8200.623
870.7590.577
880.7070.541
890.6520.499
900.5970.453
910.5440.410
920.4700.362
930.4030.312
940.3440.253
950.2760.212
960.1990.166
970.1380.103
980.0530.050
990.0000.000


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 The historical reference is a probabilistic representation of the historical data.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