Seasonal Streamflow Forecasts

Probability distribution for Total Inflows to Tullaroop reservoir


Return to catchment list
Product list for Total Inflows to Tullaroop reservoir


Download forecast data
Probability distribution for Total Inflows to Tullaroop reservoir(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.2331.098
Median0.5992.658
Mean1.2165.468
75% Quartile1.4376.405
Interquartile Range1.2045.307

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
19.79240.018
27.32130.360
36.15326.798
45.08424.004
54.37022.026
63.86619.420
73.53817.697
83.20216.174
92.93814.739
102.79113.717
112.61112.907
122.46812.051
132.35911.428
142.22910.827
152.13310.193
162.0429.708
171.9689.163
181.8978.631
191.8188.181
201.7447.839
211.6667.519
221.6137.174
231.5516.939
241.4896.607
251.4376.405
261.3806.235
271.3275.982
281.2635.787
291.2175.565
301.1755.329
311.1305.119
321.0954.912
331.0504.753
341.0114.600
350.9864.395
360.9574.237
370.9294.082
380.8903.942
390.8693.829
400.8353.685
410.8013.548
420.7763.449
430.7553.368
440.7293.258
450.7063.161
460.6823.055
470.6602.961
480.6402.841
490.6192.752
500.5992.658
510.5812.575
520.5632.493
530.5472.400
540.5292.313
550.5102.227
560.4932.125
570.4722.066
580.4582.007
590.4421.944
600.4261.864
610.4121.785
620.3991.729
630.3841.678
640.3671.616
650.3541.569
660.3431.522
670.3301.478
680.3141.423
690.3031.367
700.2901.328
710.2791.275
720.2681.233
730.2551.186
740.2451.144
750.2321.098
760.2221.059
770.2121.016
780.2020.978
790.1920.942
800.1820.895
810.1700.853
820.1610.813
830.1530.770
840.1440.734
850.1350.703
860.1270.663
870.1160.623
880.1060.592
890.0950.555
900.0830.515
910.0730.478
920.0640.437
930.0520.395
940.0420.345
950.0270.311
960.0160.273
970.0020.221
980.0000.179
990.0000.133


About the probability distribution 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 The historical reference is a probabilistic representation of the historical data.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. The 25% quartile, also defined as the first quartile cuts off the lowest 25% of data. The 75% quartile, also defined as the third quartile cuts off the lowest 75%. The interquartile range, also called the middle fifty, is a measure of statistical dispersion, being equal to the difference between the third and first quartiles.
  9. Further explanation of some technical terms is provided under the FAQ.


Creative Commons By Attribution logo
Unless otherwise noted, all material on this page is licensed under the Creative Commons Attribution Australia Licence