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( Aug 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile1.3511.469
Median2.8533.671
Mean4.5986.840
75% Quartile5.9278.880
Interquartile Range4.5767.410

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
125.52839.893
220.14332.522
317.61829.639
415.93627.320
514.50225.559
613.56923.252
712.74421.643
811.91620.146
911.34118.692
1010.75617.623
1110.31216.753
129.87015.815
139.31515.110
148.85814.409
158.48613.662
168.09913.088
177.81512.417
187.58911.754
197.34811.190
207.09810.758
216.79910.348
226.5549.883
236.3269.591
246.1369.148
255.9298.883
265.7858.656
275.5788.307
285.4118.037
295.2887.745
305.1207.418
314.9707.133
324.7666.839
334.6206.619
344.4916.415
354.3746.123
364.2615.906
374.1475.687
384.0185.493
393.9065.332
403.8075.127
413.7204.934
423.6054.796
433.5014.678
443.4204.523
453.3164.387
463.2154.233
473.1344.103
483.0273.932
492.9373.804
502.8533.671
512.7783.553
522.7013.439
532.6273.303
542.5593.183
552.4933.054
562.4392.914
572.3752.831
582.3072.746
592.2492.659
602.1982.541
612.1342.433
622.0692.354
632.0182.281
641.9592.196
651.9042.130
661.8422.063
671.7862.002
681.7391.923
691.6891.845
701.6331.790
711.5861.716
721.5281.658
731.4691.591
741.4071.532
751.3501.469
761.2901.414
771.2491.355
781.1931.301
791.1581.251
801.1021.187
811.0451.129
821.0021.074
830.9541.014
840.9180.965
850.8750.923
860.8270.868
870.7800.814
880.7150.771
890.6670.720
900.6100.666
910.5590.618
920.5060.562
930.4550.505
940.3920.439
950.3420.394
960.2810.344
970.2260.276
980.1270.221
990.0550.163


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 The historical reference is a probabilistic representation of the historical data.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