Seasonal Streamflow Forecasts

Exceedance probability for Ovens River at Bright


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Exceedance probability for Ovens River at Bright ( Jan 2014 )

Exceedance Probability Summary
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1015.33421.124
2013.02616.461
3011.38913.853
4010.11911.695
509.15610.015
608.2528.399
707.3577.034
806.3565.643
905.0293.993

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
122.88737.274
220.72331.406
319.23529.292
418.23527.630
517.56026.442
616.99124.848
716.47423.767
816.06622.784
915.72421.827
1015.33421.124
1115.01620.551
1214.72719.927
1314.47219.459
1414.14918.996
1513.92718.493
1613.74818.097
1713.58317.640
1813.36517.178
1913.19216.776
2013.02616.461
2112.81816.159
2212.66115.825
2312.49815.593
2412.31115.256
2512.13115.046
2611.98514.866
2711.80814.593
2811.65914.377
2911.56914.127
3011.38913.853
3111.26013.603
3211.12513.351
3311.01713.152
3410.89412.957
3510.75112.690
3610.62512.477
3710.51312.266
3810.37612.069
3910.23611.907
4010.11911.695
4110.01911.491
429.92011.340
439.83811.213
449.74711.039
459.65010.882
469.54610.707
479.45710.548
489.34210.341
499.25510.185
509.15610.015
519.0809.862
528.9879.708
538.9059.529
548.8149.357
558.7159.183
568.6248.971
578.5368.846
588.4428.720
598.3428.581
608.2528.399
618.1568.216
628.0668.083
637.9717.959
647.8707.805
657.7907.686
667.7087.564
677.6257.449
687.5417.299
697.4417.145
707.3577.034
717.2636.881
727.1646.759
737.0746.614
746.9576.485
756.8576.340
766.7416.211
776.6446.069
786.5545.937
796.4525.811
806.3565.643
816.2405.485
826.1085.333
835.9665.159
845.8445.012
855.7334.884
865.6294.709
875.4794.527
885.3374.378
895.1824.197
905.0293.993
914.8673.799
924.7093.566
934.5313.311
944.3712.990
954.1462.752
963.9272.469
973.6332.033
983.2691.630
992.8231.117


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 The historical reference is a probabilistic representation of the historical data.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