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 ( Jan  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile1.3071.372
Median3.0463.629
Mean5.3768.066
75% Quartile6.5759.479
Interquartile Range5.2688.107

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
133.26859.138
227.88245.865
323.67140.829
421.20236.801
519.21333.902
617.33530.012
715.91627.395
814.82425.048
913.82222.811
1012.67321.204
1111.92019.920
1211.20018.557
1310.74317.561
1410.31816.597
159.90315.576
169.35814.796
178.99713.917
188.63013.059
198.24712.334
207.93611.783
217.67311.267
227.34110.711
237.07210.334
246.8749.802
256.5769.479
266.3619.206
276.1238.803
285.9498.491
295.7638.139
305.5927.764
315.4057.432
325.1957.106
335.0436.855
344.9166.615
354.7646.294
364.6286.047
374.4735.806
384.3375.588
394.2315.414
404.1055.190
413.9824.981
423.8524.829
433.7194.704
443.6104.536
453.4934.388
463.4104.227
473.3284.084
483.2233.903
493.1463.770
503.0463.629
512.9683.504
522.8943.383
532.8053.244
542.6883.115
552.6072.987
562.5112.837
572.4472.751
582.3632.666
592.2972.574
602.2412.457
612.1602.343
622.0842.262
632.0312.189
641.9412.100
651.8682.033
661.8141.965
671.7611.904
681.7181.825
691.6591.746
701.6031.691
711.5441.617
721.4811.559
731.4211.492
741.3611.434
751.3071.371
761.2491.317
771.2021.258
781.1561.206
791.1131.157
801.0551.094
811.0001.037
820.9490.984
830.8960.925
840.8320.878
850.7750.837
860.7250.784
870.6690.732
880.6190.691
890.5640.643
900.5230.591
910.4670.545
920.4180.493
930.3670.439
940.3150.378
950.2620.336
960.2180.290
970.1560.228
980.0740.178
990.0000.126


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 The historical reference is a probabilistic representation of the historical data.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


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