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Historical Reference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)
1010.59316.495
206.6659.725
304.7926.498
403.4154.337
502.4963.004
601.8252.000
701.3021.347
800.8310.841
900.4090.420

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
127.24938.407
221.47331.156
318.26528.341
416.69926.048
515.28424.367
614.13822.057
713.06920.460
812.20618.991
911.30117.554
1010.59316.495
1110.03915.631
129.49214.696
139.04014.000
148.67613.316
158.20112.579
167.88612.007
177.54411.354
187.30010.706
196.98910.152
206.6659.725
216.4659.322
226.2758.885
236.0928.586
245.8738.160
255.6647.900
265.4457.679
275.2707.351
285.1177.097
294.9376.808
304.7926.498
314.6236.223
324.4575.951
334.3155.742
344.1665.540
354.0155.271
363.9005.062
373.7794.860
383.6464.675
393.5274.527
403.4154.337
413.3254.159
423.2264.030
433.1383.923
443.0073.780
452.9093.654
462.8293.516
472.7463.394
482.6533.239
492.5743.125
502.4963.004
512.4232.898
522.3412.793
532.2802.674
542.1982.564
552.1462.455
562.0692.326
572.0092.252
581.9512.179
591.8922.101
601.8252.000
611.7751.903
621.7251.834
631.6631.771
641.5971.696
651.5451.638
661.5081.581
671.4631.528
681.4221.461
691.3461.394
701.3021.347
711.2511.284
721.2011.234
731.1491.178
741.0901.129
751.0441.076
761.0091.029
770.9630.980
780.9190.935
790.8850.894
800.8310.841
810.7960.793
820.7460.748
830.7090.699
840.6610.659
850.6150.625
860.5710.581
870.5270.537
880.4870.502
890.4440.462
900.4090.420
910.3700.381
920.3250.338
930.2810.294
940.2320.243
950.1950.208
960.1470.171
970.0980.120
980.0540.080
990.0000.038


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 The historical reference is a probabilistic representation of the historical data.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