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 ( Jun 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile1.2951.762
Median2.4013.166
Mean3.4004.654
75% Quartile4.3465.710
Interquartile Range3.0513.949

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
116.96126.029
213.62719.178
311.69016.959
410.55615.335
59.69314.187
68.94112.785
78.36811.867
87.87111.054
97.53010.297
107.1909.759
116.8559.331
126.6298.879
136.3438.546
146.0938.218
155.8727.873
165.6987.610
175.4867.305
185.2957.005
195.1286.751
204.9556.557
214.8366.372
224.7026.163
234.5776.032
244.4695.832
254.3475.712
264.2325.609
274.1425.449
284.0505.326
293.9595.192
303.8425.040
313.7564.907
323.6784.769
333.6074.665
343.5034.568
353.4254.427
363.3404.322
373.2554.215
383.1914.119
393.1094.038
403.0363.936
412.9813.837
422.9063.767
432.8233.706
442.7503.625
452.7043.553
462.6223.472
472.5643.402
482.5053.310
492.4563.239
502.4013.166
512.3433.099
522.2753.035
532.2252.957
542.1782.887
552.1292.811
562.0802.728
572.0372.677
581.9962.626
591.9522.572
601.9122.498
611.8692.430
621.8242.380
631.7762.332
641.7412.276
651.7082.232
661.6712.187
671.6282.145
681.5742.091
691.5302.037
701.4911.997
711.4531.944
721.4201.902
731.3771.853
741.3311.809
751.2941.761
761.2591.719
771.2161.673
781.1701.631
791.1321.591
801.0901.538
811.0541.489
821.0211.443
830.9831.391
840.9431.348
850.9031.311
860.8601.261
870.8231.210
880.7701.169
890.7211.120
900.6721.066
910.6281.016
920.5800.956
930.5390.894
940.4790.818
950.4460.763
960.3790.701
970.3160.609
980.2340.530
990.1150.436


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 The historical reference is a probabilistic representation of the historical data.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