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 ( Jan 2014 )

Exceedance Probability Summary
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
101.2533.533
200.9042.387
300.7001.832
400.5471.420
500.4351.128
600.3470.871
700.2670.674
800.1860.491
900.0960.297

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
12.8799.198
22.3036.816
32.0106.048
41.8415.484
51.6565.085
61.5474.596
71.4704.275
81.3923.990
91.3113.723
101.2533.533
111.2023.382
121.1623.221
131.1203.102
141.0832.985
151.0442.862
161.0162.767
170.9842.658
180.9602.549
190.9282.458
200.9042.387
210.8802.320
220.8552.244
230.8332.196
240.8172.123
250.7952.079
260.7732.041
270.7541.983
280.7361.937
290.7191.888
300.7001.832
310.6811.783
320.6631.732
330.6481.693
340.6321.657
350.6191.605
360.6051.565
370.5921.525
380.5761.489
390.5621.459
400.5471.420
410.5351.383
420.5221.357
430.5101.334
440.4991.303
450.4891.276
460.4791.245
470.4651.219
480.4541.183
490.4441.156
500.4351.128
510.4251.103
520.4151.078
530.4071.048
540.3961.022
550.3890.992
560.3810.960
570.3720.941
580.3640.921
590.3540.900
600.3470.871
610.3400.844
620.3320.825
630.3220.806
640.3140.784
650.3060.767
660.2990.749
670.2900.733
680.2810.712
690.2740.690
700.2670.674
710.2580.653
720.2510.637
730.2410.617
740.2350.600
750.2270.581
760.2200.563
770.2120.545
780.2030.528
790.1950.512
800.1860.491
810.1780.471
820.1690.452
830.1590.431
840.1500.414
850.1410.398
860.1340.378
870.1250.357
880.1140.340
890.1050.320
900.0960.297
910.0870.276
920.0750.252
930.0640.225
940.0530.193
950.0390.170
960.0260.143
970.0060.104
980.0000.069
990.0000.028


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 The historical reference is a probabilistic representation of the historical data.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