Seasonal Streamflow Forecasts

Probability distribution for Tarcutta Creek at Old Borambola


Return to catchment list
Product list for Tarcutta Creek at Old Borambola



Download forecast data
Probability distribution for Tarcutta Creek at Old Borambola ( Feb 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile1.7673.200
Median4.1227.088
Mean6.03111.451
75% Quartile8.04414.239
Interquartile Range6.27711.040

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
132.12674.760
225.19453.619
321.96946.950
419.43042.116
517.54538.727
616.39734.608
715.27031.928
814.54229.563
913.94127.369
1013.35225.814
1112.83224.581
1212.35223.281
1311.89322.323
1411.47321.383
1510.99920.395
1610.76319.643
1710.43418.772
189.98817.917
199.69217.194
209.42116.642
219.13916.117
228.89215.524
238.55915.151
248.28814.583
258.04414.243
267.80813.952
277.56713.502
287.38713.153
297.20412.773
306.98312.345
316.80411.970
326.63211.581
336.47311.288
346.32211.015
356.16210.620
366.00910.324
375.82610.023
385.6669.753
395.4889.528
405.3599.240
415.2148.964
425.1038.767
434.9968.596
444.8698.371
454.7248.170
464.5997.943
474.4887.748
484.3747.490
494.2527.293
504.1227.088
514.0256.904
523.9176.724
533.8296.506
543.7006.313
553.6216.101
563.5115.871
573.4095.730
583.2995.588
593.2265.438
603.1245.234
613.0125.044
622.9414.904
632.8614.773
642.7784.618
652.6954.495
662.5954.371
672.4964.257
682.4044.108
692.3083.957
702.2063.849
712.1203.703
722.0253.586
731.9473.451
741.8503.331
751.7673.199
761.6953.083
771.5942.956
781.5302.840
791.4212.730
801.3192.587
811.2252.453
821.1302.327
831.0122.185
840.9242.067
850.8381.965
860.7481.829
870.6331.689
880.5391.577
890.4301.444
900.3261.297
910.2181.161
920.1091.000
930.0000.830
940.0000.625
950.0000.478
960.0000.309
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 The historical reference is a probabilistic representation of the historical data.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.


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