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Historical Reference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)
105.27912.602
203.6957.286
302.8035.063
402.2203.589
501.7512.646
601.4041.892
701.0821.372
800.7940.934
900.4870.531

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
113.09748.802
210.52531.978
38.80426.984
47.93123.484
57.26321.097
66.80118.278
76.29216.496
85.94914.961
95.57513.569
105.27912.602
115.06811.848
124.85511.066
134.69210.497
144.4959.947
154.3199.376
164.1788.947
174.0668.457
183.9627.981
193.8327.585
203.6957.286
213.5907.004
223.4816.689
233.3916.493
243.3076.197
253.2026.021
263.1245.871
273.0425.642
282.9275.466
292.8715.276
302.8035.063
312.7484.879
322.6914.689
332.6154.548
342.5514.417
352.4894.229
362.4314.090
372.3713.949
382.3153.824
392.2693.721
402.2203.589
412.1603.465
422.1033.376
432.0463.300
441.9953.200
451.9413.112
461.9003.012
471.8632.928
481.8182.816
491.7782.732
501.7512.646
511.7152.568
521.6702.493
531.6392.403
541.5992.323
551.5632.237
561.5272.144
571.5012.088
581.4632.031
591.4281.972
601.4041.892
611.3631.818
621.3291.765
631.3081.715
641.2761.656
651.2441.610
661.2171.563
671.1871.521
681.1501.466
691.1191.411
701.0821.372
711.0581.319
721.0271.278
730.9981.230
740.9731.188
750.9431.142
760.9091.101
770.8841.058
780.8601.019
790.8310.982
800.7940.934
810.7660.890
820.7280.849
830.6990.804
840.6670.766
850.6370.734
860.6090.691
870.5850.649
880.5540.615
890.5150.575
900.4870.531
910.4540.492
920.4110.446
930.3630.399
940.3340.343
950.2960.304
960.2550.261
970.2040.200
980.1430.149
990.0670.094


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 The historical reference is a probabilistic representation of the historical data.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