Seasonal Streamflow Forecasts

Probability distribution for Canungra Creek at Main Road Bridge


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Product list for Canungra Creek at Main Road Bridge


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Probability distribution for Canungra Creek at Main Road Bridge( Sep 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile1.2521.247
Median2.0772.169
Mean2.7252.882
75% Quartile3.4683.663
Interquartile Range2.2152.416

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
111.78913.401
29.38210.309
38.3529.284
47.6968.524
57.0617.979
66.5487.305
76.1336.857
85.7996.456
95.5046.078
105.3245.807
115.1505.589
124.9895.357
134.8305.185
144.6555.014
154.5134.833
164.3744.694
174.2414.532
184.0864.372
193.9804.235
203.8914.129
213.8154.029
223.7243.914
233.6293.841
243.5563.730
253.4693.663
263.3763.606
273.3083.517
283.2423.447
293.1673.371
303.1033.284
313.0323.208
322.9683.129
332.9123.068
342.8513.012
352.7872.930
362.7272.868
372.6692.805
382.6232.748
392.5582.700
402.5102.639
412.4592.580
422.4152.537
432.3802.500
442.3342.452
452.2852.408
462.2332.358
472.1932.315
482.1502.258
492.1182.214
502.0772.169
512.0442.127
522.0042.087
531.9672.037
541.9321.993
551.8981.945
561.8541.892
571.8181.859
581.7831.826
591.7421.791
601.7111.743
611.6771.698
621.6451.665
631.6131.634
641.5861.597
651.5551.567
661.5211.537
671.4901.509
681.4561.473
691.4301.436
701.4071.409
711.3751.373
721.3461.344
731.3081.310
741.2731.280
751.2521.247
761.2121.217
771.1841.185
781.1541.155
791.1261.126
801.0971.089
811.0691.054
821.0251.020
830.9900.983
840.9600.951
850.9280.924
860.8900.886
870.8590.848
880.8290.817
890.7970.780
900.7570.739
910.7180.700
920.6740.654
930.6380.604
940.6020.543
950.5430.499
960.4870.447
970.4130.370
980.3460.301
990.2550.217


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 The historical reference is a probabilistic representation of the historical data.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