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Historical Reference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)
1018.55734.087
2011.00418.082
307.53411.648
405.4637.642
503.9995.255
602.8883.488
702.0872.349
801.3241.472
900.6630.744

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
164.199108.602
246.14381.405
337.58271.284
432.09863.317
528.21257.668
625.38950.228
723.04345.322
821.35740.999
919.86436.951
1018.55734.087
1117.28731.827
1216.23529.454
1315.26727.739
1414.47126.093
1513.76124.366
1613.19623.056
1712.58721.592
1811.98220.173
1911.54718.982
2011.00418.082
2110.57717.244
2210.21216.345
239.82515.738
249.44114.884
259.12614.366
268.73813.932
278.46513.290
288.15412.796
297.86112.239
307.53411.648
317.34911.126
327.12310.615
336.90510.223
346.6999.848
356.4719.349
366.2948.965
376.1118.592
385.9018.255
395.6787.986
405.4637.642
415.2747.319
425.1027.086
434.9546.894
444.7676.637
454.6216.411
464.5096.165
474.3675.947
484.2535.672
494.1045.469
503.9995.255
513.8695.066
523.7264.882
533.5984.672
543.4754.477
553.3704.285
563.2534.059
573.1543.930
583.0653.802
592.9813.664
602.8883.488
612.7913.319
622.7123.198
632.6193.088
642.5552.956
652.4622.856
662.3912.756
672.3222.664
682.2382.547
692.1752.431
702.0872.349
712.0182.239
721.9422.154
731.8582.056
741.7931.970
751.7331.878
761.6481.798
771.5681.712
781.4921.635
791.4151.563
801.3241.472
811.2541.388
821.1881.311
831.1251.226
841.0591.157
851.0001.098
860.9431.022
870.8770.946
880.7960.887
890.7210.818
900.6630.744
910.6070.678
920.5500.603
930.4830.527
940.4220.439
950.3550.380
960.2990.315
970.1960.228
980.1150.160
990.0000.088


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 The historical reference is a probabilistic representation of the historical data.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