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 2012 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile4.0111.372
Median8.5943.629
Mean12.8048.066
75% Quartile17.1219.479
Interquartile Range13.1118.107

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
159.34359.138
249.38845.865
345.13440.829
440.75836.801
537.99933.902
635.23130.012
733.66427.395
832.33125.048
930.87622.811
1029.43221.204
1127.83119.920
1226.72118.557
1325.75917.561
1424.79816.597
1523.92915.576
1623.15314.796
1722.47413.917
1821.71413.059
1921.07612.334
2020.35011.783
2119.70411.267
2218.97910.711
2318.41310.334
2417.8069.802
2517.1269.479
2616.6779.206
2716.2228.803
2815.8658.491
2915.5258.139
3015.0317.764
3114.6957.432
3214.3107.106
3313.9626.855
3413.6116.615
3513.1596.294
3612.7546.047
3712.4145.806
3812.0265.588
3911.6905.414
4011.3565.190
4111.0344.981
4210.7104.829
4310.3734.704
4410.0644.536
459.8134.388
469.5224.227
479.2954.084
489.0813.903
498.8523.770
508.5943.629
518.3653.504
528.1183.383
537.9043.244
547.6833.115
557.4742.987
567.2602.837
577.0872.751
586.8912.666
596.7092.574
606.5752.457
616.3372.343
626.1832.262
635.9492.189
645.7792.100
655.5862.033
665.4121.965
675.2321.904
685.0621.825
694.9311.746
704.7681.691
714.6091.617
724.4681.559
734.3121.492
744.1981.434
754.0061.371
763.8621.317
773.7131.258
783.5881.206
793.4931.157
803.3091.094
813.1401.037
822.9900.984
832.7950.925
842.6480.878
852.4910.837
862.3380.784
872.2040.732
882.0530.691
891.9540.643
901.8140.591
911.6610.545
921.5220.493
931.3660.439
941.1880.378
951.0790.336
960.9450.290
970.7800.228
980.5780.178
990.3490.126


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 The historical reference is a probabilistic representation of the historical data.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