Seasonal Streamflow Forecasts

Probability distribution for Boorowa River at Prossers Crossing


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Product list for Boorowa River at Prossers Crossing


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Probability distribution for Boorowa River at Prossers Crossing( Oct 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile1.3493.040
Median3.43810.080
Mean7.47523.440
75% Quartile8.42630.722
Interquartile Range7.07727.683

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
161.763147.731
244.256121.465
336.384111.183
431.989102.746
528.52796.510
625.70687.864
722.70981.812
820.56176.183
919.34270.603
1017.74666.441
1116.55563.014
1215.72759.262
1314.82056.444
1413.98953.647
1513.13950.611
1612.41248.233
1711.85845.497
1811.39442.763
1910.86740.407
2010.47638.586
2110.04636.859
229.55534.977
239.26833.687
248.87931.849
258.42830.723
268.10129.770
277.77928.349
287.44827.248
297.19625.999
306.91824.662
316.67223.477
326.42622.308
336.16421.411
345.96320.550
355.75119.405
365.58018.519
375.37417.663
385.20416.888
395.02016.269
404.84915.478
414.66514.739
424.49414.208
434.35013.770
444.21813.184
454.07012.672
463.96112.116
473.83311.626
483.72511.007
493.57910.554
503.43810.080
513.3189.662
523.2099.256
533.0918.796
542.9718.371
552.8867.955
562.8097.470
572.6937.193
582.6066.921
592.5216.630
602.4426.261
612.3645.907
622.2935.658
632.2225.431
642.1625.162
652.0544.958
661.9894.755
671.9004.571
681.8204.338
691.7464.107
701.6753.946
711.6023.732
721.5453.566
731.4713.377
741.4113.214
751.3483.039
761.2732.888
771.1942.728
781.1182.586
791.0542.454
800.9902.286
810.9402.136
820.8871.998
830.8281.847
840.7781.726
850.7211.625
860.6701.494
870.6211.366
880.5711.266
890.5191.152
900.4531.032
910.4090.926
920.3560.807
930.3130.689
940.2580.557
950.1950.470
960.1400.377
970.0870.256
980.0100.165
990.0000.074


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 The historical reference is a probabilistic representation of the historical data.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