Seasonal Streamflow Forecasts

Exceedance probability for Tarcutta Creek at Old Borambola


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Exceedance probability for Tarcutta Creek at Old Borambola( Oct 2014 )

Exceedance Probability Summary
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1014.58681.234
2011.51258.763
309.67045.118
408.19733.776
507.03825.413
605.98918.205
705.03313.013
804.0328.681
902.8534.805

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
124.741140.519
222.034121.542
320.427114.101
419.180107.982
518.174103.448
617.15997.137
716.42092.693
815.63388.531
915.04884.369
1014.58681.234
1114.17078.627
1213.80975.740
1313.44573.545
1413.10271.339
1512.86168.909
1612.58466.975
1712.25464.712
1811.97762.403
1911.72260.368
2011.51258.763
2111.32357.212
2211.11255.485
2310.84354.278
2410.68652.520
2510.46651.419
2610.29350.472
2710.12049.033
289.95347.892
299.79546.569
309.67045.118
319.54443.795
329.39842.458
339.26041.406
349.12640.374
359.00138.966
368.85737.847
378.69736.737
388.50235.710
398.34034.871
408.19733.776
418.09232.726
427.98331.954
437.88131.308
447.78230.428
457.64729.642
467.52728.771
477.41727.988
487.29026.978
497.15326.221
507.03825.413
516.94724.687
526.85623.969
536.78423.139
546.68922.356
556.53821.573
566.42020.639
576.30620.096
586.20619.553
596.07618.965
605.98918.205
615.89217.460
625.79716.925
635.72316.433
645.62115.837
655.53515.381
665.43914.920
675.32514.496
685.22313.952
695.12213.402
705.03313.013
714.94012.489
724.83712.077
734.73511.601
744.65111.183
754.55310.728
764.44110.329
774.3359.902
784.2439.514
794.1369.149
804.0328.681
813.9218.250
823.8187.849
833.6527.404
843.5447.040
853.4406.730
863.3306.322
873.2175.912
883.0815.590
892.9525.213
902.8534.805
912.6744.435
922.4644.013
932.3143.579
942.1583.073
951.8742.726
961.6402.343
971.3481.814
980.9991.388
990.5750.928


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 The historical reference is a probabilistic representation of the historical data.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