Seasonal Streamflow Forecasts

Probability distribution for Tarcutta Creek at Old Borambola


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Product list for Tarcutta Creek at Old Borambola


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Probability distribution for Tarcutta Creek at Old Borambola(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile2.8763.200
Median5.7987.088
Mean8.10111.451
75% Quartile10.73814.239
Interquartile Range7.86311.040

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
140.50574.760
231.44453.619
328.12546.950
424.39242.116
522.57638.727
621.00534.608
719.85031.928
818.72629.563
917.96727.369
1017.39225.814
1116.78924.581
1216.09823.281
1315.40822.323
1414.92921.383
1514.32420.395
1613.94919.643
1713.55318.772
1813.18617.917
1912.77817.194
2012.36116.642
2112.01716.117
2211.72415.524
2311.42215.151
2411.11414.583
2510.74014.243
2610.41813.952
2710.15213.502
289.86013.153
299.62012.773
309.37112.345
319.13311.970
328.89111.581
338.69011.288
348.51711.015
358.35110.620
368.11810.324
377.94110.023
387.7169.753
397.5109.528
407.3359.240
417.1588.964
426.9918.767
436.8678.596
446.6958.371
456.5278.170
466.3957.943
476.2537.748
486.0917.490
495.9247.293
505.7987.088
515.6526.904
525.5306.724
535.3856.506
545.2736.313
555.1346.101
564.9745.871
574.8455.730
584.7275.588
594.6155.438
604.5225.234
614.4065.044
624.2884.904
634.1684.773
644.0504.618
653.9564.495
663.8534.371
673.7384.257
683.6314.108
693.4913.957
703.3873.849
713.2993.703
723.1663.586
733.0713.451
742.9813.331
752.8743.199
762.7593.083
772.6432.956
782.5272.840
792.4212.730
802.2822.587
812.1662.453
822.0402.327
831.8972.185
841.7812.067
851.6841.965
861.5541.829
871.4271.689
881.2971.577
891.1551.444
900.9961.297
910.8611.161
920.7181.000
930.6020.830
940.4290.625
950.2570.478
960.0300.309
970.0000.063
980.0000.000
990.0000.000


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 The historical reference is a probabilistic representation of the historical data.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


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