Seasonal Streamflow Forecasts

Probability distribution for Gudgenby at Tennent


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Probability distribution for Gudgenby at Tennent ( Feb 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.5671.215
Median1.5343.428
Mean3.0119.490
75% Quartile3.4859.665
Interquartile Range2.9188.449

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
122.62691.962
217.11865.470
314.32855.992
412.04848.742
510.40243.735
69.40337.327
78.72033.226
88.02229.698
97.42026.465
106.98324.221
116.48122.475
126.11120.664
135.81119.370
145.47118.138
155.16616.858
164.90015.894
174.74314.825
184.54313.797
194.38412.940
204.22312.295
214.06511.697
223.89711.059
233.74110.630
243.60410.028
253.4879.665
263.3609.360
273.2708.912
283.1518.568
293.0328.181
302.9307.772
312.8517.411
322.7757.059
332.6776.790
342.5826.532
352.4726.191
362.3805.929
372.3085.675
382.2205.446
392.1555.264
402.0845.030
412.0124.812
421.9664.655
431.9124.526
441.8684.353
451.7974.201
461.7344.036
471.6813.890
481.6273.706
491.5803.571
501.5343.428
511.4933.303
521.4463.180
531.3993.041
541.3492.912
551.2992.785
561.2552.636
571.2072.550
581.1732.466
591.1302.376
601.0882.261
611.0442.149
621.0012.071
630.9601.999
640.9291.913
650.8881.847
660.8541.782
670.8091.723
680.7781.647
690.7521.571
700.7171.518
710.6891.448
720.6591.393
730.6291.330
740.5961.275
750.5661.215
760.5421.164
770.5131.109
780.4791.060
790.4521.014
800.4210.956
810.3900.903
820.3620.854
830.3370.800
840.3080.756
850.2800.719
860.2450.671
870.2200.623
880.1960.586
890.1670.543
900.1250.497
910.0930.456
920.0580.410
930.0260.363
940.0000.309
950.0000.273
960.0000.233
970.0000.181
980.0000.140
990.0000.097


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 The historical reference is a probabilistic representation of the historical data.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