Seasonal Streamflow Forecasts

Exceedance probability for Tarcutta Creek at Old Borambola


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Exceedance probability for Tarcutta Creek at Old Borambola(  )

Exceedance Probability Summary
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1017.68130.786
2013.46821.199
3011.08715.989
409.22411.987
507.8689.162
606.6246.744
705.5304.959
804.4153.392
903.1051.870

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
132.55159.720
227.74950.148
324.80446.446
422.95543.434
521.55441.225
620.56338.187
719.51636.078
818.90534.130
918.19932.211
1017.68130.786
1117.05329.615
1216.49228.335
1316.03627.374
1415.56226.419
1515.18925.380
1614.84524.563
1714.46723.619
1814.14322.669
1913.80021.843
2013.46821.199
2113.22120.583
2212.95519.904
2312.72419.434
2412.48618.757
2512.22518.337
2611.96017.978
2711.72117.436
2811.50917.011
2911.31316.521
3011.08715.989
3110.93015.509
3210.72715.027
3310.51414.651
3410.36214.284
3510.07913.787
369.89613.395
379.71813.008
389.51112.652
399.36412.363
409.22411.987
419.07511.628
428.93911.365
438.78811.146
448.64810.847
458.49010.582
468.39410.288
478.25410.025
488.1209.686
497.9739.433
507.8689.162
517.7758.919
527.6618.679
537.5208.401
547.3928.139
557.2407.877
567.1047.564
576.9957.381
586.8707.199
596.7487.001
606.6246.744
616.5206.491
626.4186.310
636.2906.142
646.1685.938
656.0655.781
665.9655.622
675.8365.476
685.7345.287
695.6365.095
705.5304.959
715.4104.774
725.3034.628
735.1904.459
745.0894.309
754.9614.145
764.8644.000
774.7653.844
784.6463.702
794.5233.567
804.4153.392
814.3083.230
824.1593.078
834.0372.908
843.9132.767
853.7722.646
863.6552.486
873.5122.322
883.4172.193
893.2742.039
903.1051.870
912.9211.715
922.7331.535
932.5831.346
942.3451.121
952.1640.962
961.8860.783
971.6260.527
981.2930.311
990.8680.065


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 The historical reference is a probabilistic representation of the historical data.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