Seasonal Streamflow Forecasts

Probability distribution for Gudgenby at Tennent


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Product list for Gudgenby at Tennent


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Probability distribution for Gudgenby at Tennent(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile3.9713.866
Median6.5397.883
Mean8.30212.708
75% Quartile10.62215.971
Interquartile Range6.65212.106

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
134.51672.243
227.56056.680
324.23250.906
422.32346.418
520.90643.113
619.51038.921
718.42736.092
817.51933.532
916.59931.107
1015.96329.363
1115.38427.966
1214.83426.481
1314.34925.379
1413.93224.294
1513.60823.147
1613.19122.273
1712.79221.259
1812.41020.261
1912.15019.417
2011.86018.772
2111.63118.159
2211.36917.467
2311.09717.032
2410.83516.371
2510.62315.976
2610.42615.637
2710.17515.115
289.93314.712
299.66014.273
309.47213.780
319.32813.348
329.14012.903
338.94412.567
348.80312.256
358.63511.807
368.46611.471
378.31311.131
388.16310.827
398.04610.574
407.92010.252
417.7799.944
427.6249.724
437.4669.535
447.3369.286
457.1959.065
467.0198.814
476.9048.601
486.7838.319
496.6508.105
506.5397.883
516.4117.684
526.2887.491
536.1607.257
546.0367.051
555.9276.826
565.8326.582
575.7146.434
585.6166.285
595.5046.128
605.3905.916
615.2805.719
625.1725.575
635.0895.440
645.0005.281
654.9105.156
664.8365.031
674.7414.914
684.6454.765
694.5434.613
704.4624.505
714.3764.360
724.2674.245
734.1694.112
744.0643.994
753.9703.865
763.8843.752
773.7923.630
783.6673.518
793.5733.413
803.4503.277
813.3683.150
823.2693.032
833.1952.899
843.1072.790
853.0012.696
862.8772.571
872.7512.444
882.6572.344
892.5452.224
902.3902.094
912.2911.974
922.1711.835
932.0321.689
941.9101.515
951.7141.393
961.5511.255
971.3411.057
981.1250.891
990.8160.703


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 The historical reference is a probabilistic representation of the historical data.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