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Historical Reference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)
102.2716.476
201.5293.788
301.1422.655
400.8871.895
500.6941.406
600.5421.013
700.4120.737
800.2950.505
900.1700.289

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
16.17124.772
24.75216.184
34.05013.689
43.55311.924
53.22810.763
62.8969.326
72.6928.428
82.5227.663
92.3826.963
102.2716.476
112.1486.096
122.0685.698
131.9855.412
141.9015.137
151.8184.848
161.7514.629
171.6884.383
181.6394.144
191.5893.942
201.5293.788
211.4793.644
221.4333.489
231.3843.383
241.3493.234
251.3053.143
261.2703.066
271.2352.951
281.1992.863
291.1672.762
301.1422.655
311.1212.559
321.0892.464
331.0612.391
341.0342.321
351.0082.227
360.9792.153
370.9532.081
380.9282.016
390.9061.963
400.8871.895
410.8681.831
420.8461.785
430.8221.746
440.8021.694
450.7861.648
460.7671.597
470.7501.552
480.7291.494
490.7121.451
500.6941.406
510.6721.365
520.6591.326
530.6451.280
540.6301.237
550.6111.194
560.5961.144
570.5821.115
580.5701.085
590.5561.054
600.5421.013
610.5280.973
620.5140.945
630.5000.919
640.4870.887
650.4740.863
660.4610.838
670.4490.816
680.4340.787
690.4230.758
700.4120.737
710.4000.709
720.3860.687
730.3730.662
740.3610.640
750.3510.615
760.3370.594
770.3250.571
780.3150.550
790.3040.530
800.2950.505
810.2850.482
820.2730.460
830.2590.435
840.2470.415
850.2350.398
860.2230.375
870.2100.352
880.1950.334
890.1830.312
900.1700.289
910.1550.268
920.1410.243
930.1300.217
940.1170.187
950.1010.166
960.0820.142
970.0610.108
980.0390.081
990.0030.049


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 The historical reference is a probabilistic representation of the historical data.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