Seasonal Streamflow Forecasts

Probability distribution for Gudgenby at Tennent


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Probability distribution for Gudgenby at Tennent( Oct 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile4.1854.449
Median7.55411.019
Mean10.17416.939
75% Quartile13.30124.250
Interquartile Range9.11619.800

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
144.38275.295
235.89664.267
332.38159.947
429.92656.398
527.22253.771
625.62850.118
724.27247.551
823.25845.152
922.14842.758
1021.27140.960
1120.46939.467
1219.61337.820
1318.78236.570
1418.13935.318
1517.55433.943
1617.13032.853
1716.37931.582
1815.92730.290
1915.44929.158
2015.06128.268
2114.61027.412
2214.23126.464
2313.94525.804
2413.59624.846
2513.30224.250
2613.01223.739
2712.64122.965
2812.36122.355
2912.09521.651
3011.76920.883
3111.50220.188
3211.22919.488
3310.94818.942
3410.68918.409
3510.45217.685
3610.23317.114
3710.05316.551
389.78916.033
399.56315.613
409.32915.067
419.12614.547
429.00714.167
438.77413.850
448.62913.420
458.43113.039
468.26712.618
478.08312.242
487.90511.760
497.68111.401
507.55411.019
517.40310.678
527.23510.342
537.0669.957
546.9219.595
556.7549.235
566.6258.808
576.4888.561
586.3408.315
596.2248.050
606.0977.709
615.9887.376
625.8587.138
635.7456.920
645.5756.657
655.4276.457
665.2946.255
675.1536.070
685.0245.833
694.8945.595
704.7955.426
714.6835.201
724.5385.024
734.4184.821
744.2944.642
754.1854.449
764.0714.280
773.9654.100
783.8453.936
793.7223.783
803.5973.587
813.4743.408
823.3573.241
833.2373.057
843.1382.907
852.9922.779
862.8462.612
872.7532.445
882.6172.314
892.4982.160
902.3601.996
912.1991.847
922.0381.678
931.8811.505
941.7251.305
951.5271.168
961.3551.018
971.1690.813
980.9860.650
990.6460.475


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 The historical reference is a probabilistic representation of the historical data.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