Seasonal Streamflow Forecasts

Exceedance probability for Tuross River at Tuross Vale


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Product list for Tuross River at Tuross Vale


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Exceedance probability for Tuross River at Tuross Vale(  )

Exceedance Probability Summary
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1014.16817.623
209.75510.758
307.3657.418
405.4945.127
504.1473.671
603.2442.541
702.4491.790
801.6751.187
900.9650.666

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
130.96739.893
225.11432.522
322.31229.639
420.43127.320
518.84225.559
617.32623.252
716.45321.643
815.59820.146
914.95018.692
1014.16817.623
1113.81116.753
1213.24015.815
1312.53915.110
1412.05314.409
1511.59813.662
1611.14213.088
1710.81812.417
1810.48511.754
1910.07711.190
209.75510.758
219.47010.348
229.2279.883
238.9159.591
248.6889.148
258.3398.883
268.1058.656
277.9288.307
287.7438.037
297.5577.745
307.3657.418
317.0887.133
326.8376.839
336.6366.619
346.4506.415
356.2776.123
366.1185.906
375.9425.687
385.7765.493
395.6325.332
405.4945.127
415.3604.934
425.2154.796
435.0924.678
444.9354.523
454.8004.387
464.6824.233
474.5694.103
484.4043.932
494.2853.804
504.1473.671
514.0573.553
523.9553.439
533.8593.303
543.7513.183
553.6653.054
563.5812.914
573.4922.831
583.4102.746
593.3202.659
603.2442.541
613.1502.433
623.0802.354
632.9942.281
642.9042.196
652.8202.130
662.7592.063
672.6722.002
682.6051.923
692.5331.845
702.4491.790
712.3611.716
722.2751.658
732.2051.591
742.1131.532
752.0541.469
761.9801.414
771.9021.355
781.8221.301
791.7281.251
801.6751.187
811.6041.129
821.5241.074
831.4641.014
841.4110.965
851.3550.923
861.2830.868
871.1860.814
881.1170.771
891.0450.720
900.9650.666
910.8840.618
920.8210.562
930.7370.505
940.6420.439
950.5590.394
960.4890.344
970.4000.276
980.2710.221
990.1580.163


About the exceedance probability 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 The historical reference is a probabilistic representation of the historical data.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. Further explanation of some technical terms is provided under the FAQ.


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