Seasonal Streamflow Forecasts

Exceedance probability for Running Ck at Dieckmans Bridge


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Product list for Running Ck at Dieckmans Bridge


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Exceedance probability for Running Ck at Dieckmans Bridge(  )

Exceedance Probability Summary
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1014.48311.105
2010.4657.367
308.2485.609
406.6484.338
505.4373.459
604.4692.702
703.5842.138
802.7001.625
901.8821.102

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
131.76930.057
225.49522.141
322.63319.550
420.28317.647
518.44116.302
617.39014.656
716.67413.578
815.95812.624
915.00711.736
1014.48311.105
1113.94010.605
1213.32910.076
1312.9119.686
1412.5429.303
1512.1708.900
1611.8268.593
1711.4078.237
1811.0547.888
1910.7207.593
2010.4657.367
2110.2407.152
229.9826.910
239.7176.757
249.4486.525
259.1436.386
268.9636.266
278.8146.082
288.6505.939
298.4575.784
308.2485.609
318.0725.455
327.8935.296
337.7335.176
347.5075.064
357.3794.903
367.2224.782
377.0874.659
386.9314.548
396.7744.456
406.6484.338
416.5044.226
426.3714.145
436.2594.075
446.1193.983
455.9853.901
465.8683.808
475.7613.728
485.6653.623
495.5323.542
505.4373.459
515.3523.383
525.2473.310
535.1533.221
545.0173.142
554.9073.056
564.8082.962
574.7202.904
584.6262.846
594.5312.785
604.4692.702
614.3702.624
624.2712.568
634.1802.514
644.0952.451
653.9832.401
663.9052.350
673.8112.304
683.7202.243
693.6532.182
703.5842.138
713.5032.078
723.4232.031
733.3441.976
743.2571.927
753.1741.874
763.0471.826
772.9661.775
782.8991.728
792.8031.683
802.7001.625
812.6271.570
822.5591.519
832.4871.462
842.4021.414
852.3081.372
862.2341.317
872.1581.261
882.0631.216
891.9691.162
901.8821.102
911.7801.047
921.6670.982
931.5540.914
941.4450.831
951.3050.771
961.1500.703
971.0150.604
980.8390.519
990.6240.418


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 The historical reference is a probabilistic representation of the historical data.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