Seasonal Streamflow Forecasts

Probability distribution for Gudgenby at Tennent


Return to catchment list
Product list for Gudgenby at Tennent



Download forecast data
Probability distribution for Gudgenby at Tennent ( Jan 2011 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile7.2161.372
Median14.8583.629
Mean19.9148.066
75% Quartile27.6699.479
Interquartile Range20.4538.107

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
182.80559.138
268.65645.865
361.17540.829
457.01736.801
552.84133.902
650.22330.012
747.72527.395
845.72325.048
943.84422.811
1041.98621.204
1140.60419.920
1239.47718.557
1338.20017.561
1437.34616.597
1536.25515.576
1635.31114.796
1734.44013.917
1833.38013.059
1932.53212.334
2031.59311.783
2130.90011.267
2230.04010.711
2329.15110.334
2428.3249.802
2527.6719.479
2626.9679.206
2726.2828.803
2825.6058.491
2924.9998.139
3024.4367.764
3123.7957.432
3223.3487.106
3322.7546.855
3422.1726.615
3521.6406.294
3621.0686.047
3720.5185.806
3819.9185.588
3919.4255.414
4019.0595.190
4118.5424.981
4218.1364.829
4317.7344.704
4417.3984.536
4516.9534.388
4616.4794.227
4716.0124.084
4815.7663.903
4915.3373.770
5014.8583.629
5114.5523.504
5214.1293.383
5313.7193.244
5413.4383.115
5513.0902.987
5612.8052.837
5712.4402.751
5812.0922.666
5911.7682.574
6011.3952.457
6111.1062.343
6210.7932.262
6310.4782.189
6410.1382.100
659.8782.033
669.5541.965
679.3001.904
689.0301.825
698.7841.746
708.5371.691
718.2431.617
728.0271.559
737.7491.492
747.4551.434
757.2161.371
766.9801.317
776.6741.258
786.4341.206
796.1681.157
805.9201.094
815.6471.037
825.3750.984
835.1050.925
844.8340.878
854.5200.837
864.2330.784
874.0370.732
883.8000.691
893.5900.643
903.3310.591
913.0650.545
922.8570.493
932.5810.439
942.2900.378
952.0250.336
961.7890.290
971.5050.228
981.1530.178
990.7510.126


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 The historical reference is a probabilistic representation of the historical data.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


Creative Commons By Attribution logo
Unless otherwise noted, all material on this page is licensed under the Creative Commons Attribution Australia Licence