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Historical Reference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% Quartile7.2617.793
Median11.70114.627
Mean14.46721.790
75% Quartile18.41027.366
Interquartile Range11.14919.573

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
154.582115.302
245.06089.622
340.37080.490
437.29973.427
534.78668.463
632.53761.945
730.77257.629
829.36153.792
928.19450.148
1027.13547.528
1126.20945.430
1225.51543.189
1324.53141.542
1423.97539.935
1523.44238.219
1622.77836.892
1722.14835.383
1821.60333.889
1921.13032.610
2020.56531.625
2120.15330.692
2219.67829.676
2319.30528.978
2418.77227.980
2518.42027.366
2618.09426.845
2717.76126.063
2817.43425.452
2917.07524.754
3016.76524.000
3116.45723.322
3216.09422.646
3315.80822.122
3415.50321.611
3515.28920.923
3615.07120.382
3714.70219.851
3814.46019.362
3914.24618.967
4014.00918.454
4113.73717.965
4213.47917.608
4313.25417.310
4413.03616.906
4512.79116.546
4612.57716.149
4712.32415.793
4812.09615.335
4911.90714.993
5011.70114.627
5111.49414.300
5211.30213.976
5311.09913.601
5410.94213.248
5510.73112.894
5610.55512.470
5710.40612.224
5810.22611.976
5910.06511.708
609.90211.360
619.74311.017
629.54110.770
639.41110.541
649.23410.263
659.04210.049
668.8879.832
678.7569.632
688.5729.372
698.3089.109
708.1478.921
717.9728.666
727.7698.464
737.6088.229
747.4288.021
757.2617.793
767.0697.591
776.9137.372
786.7797.172
796.6326.982
806.4666.736
816.2596.506
826.0896.290
835.8796.046
845.7035.844
855.5735.671
865.3485.439
875.1585.201
884.9505.012
894.7644.786
904.5494.538
914.3474.308
924.1054.038
933.8803.754
943.6233.411
953.3123.167
963.0792.888
972.6952.483
982.1542.136
991.4711.732


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 The historical reference is a probabilistic representation of the historical data.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