Seasonal Streamflow Forecasts

Exceedance probability for Total Inflows to Tullaroop reservoir


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Product list for Total Inflows to Tullaroop reservoir


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Exceedance probability for Total Inflows to Tullaroop reservoir(  )

Exceedance Probability Summary
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
103.99113.717
202.4177.839
301.6585.329
401.2063.685
500.8742.658
600.6351.864
700.4691.328
800.3050.895
900.1490.515

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
114.30840.018
210.45530.360
38.32626.798
46.97824.004
56.09522.026
65.43219.420
74.97817.697
84.53416.174
94.22914.739
103.99113.717
113.74312.907
123.54112.051
133.36111.428
143.15510.827
152.99710.193
162.8849.708
172.7469.163
182.6318.631
192.5088.181
202.4177.839
212.3217.519
222.2367.174
232.1606.939
242.0856.607
252.0156.405
261.9516.235
271.8855.982
281.7975.787
291.7295.565
301.6585.329
311.6025.119
321.5534.912
331.5014.753
341.4504.600
351.4014.395
361.3554.237
371.3224.082
381.2823.942
391.2423.829
401.2063.685
411.1663.548
421.1323.449
431.0983.368
441.0653.258
451.0293.161
460.9963.055
470.9662.961
480.9382.841
490.9082.752
500.8742.658
510.8492.575
520.8232.493
530.8012.400
540.7722.313
550.7452.227
560.7212.125
570.6962.066
580.6782.007
590.6561.944
600.6351.864
610.6181.785
620.5991.729
630.5791.678
640.5651.616
650.5481.569
660.5321.522
670.5171.478
680.4981.423
690.4871.367
700.4691.328
710.4541.275
720.4391.233
730.4241.186
740.4081.144
750.3891.098
760.3711.059
770.3531.016
780.3360.978
790.3200.942
800.3050.895
810.2940.853
820.2770.813
830.2580.770
840.2430.734
850.2270.703
860.2110.663
870.1980.623
880.1810.592
890.1650.555
900.1490.515
910.1360.478
920.1230.437
930.1100.395
940.0950.345
950.0780.311
960.0580.273
970.0440.221
980.0190.179
990.0000.133


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 The historical reference is a probabilistic representation of the historical data.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