Seasonal Streamflow Forecasts

Probability distribution for Total Inflows to Lake Eppalock


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Product list for Total Inflows to Lake Eppalock


  • Jan

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Probability distribution for Total Inflows to Lake Eppalock ( Jan 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.0000.000
Median0.2820.243
Mean3.1124.028
75% Quartile2.1942.549
Interquartile Range2.1942.549

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
144.19361.199
228.01740.886
321.91233.523
417.24427.920
514.06024.103
612.29619.343
710.45216.404
89.19113.967
98.39311.822
107.43410.390
116.6309.311
125.9718.227
135.4307.475
145.0276.779
154.5226.075
164.1545.559
173.8735.002
183.6314.481
193.3424.058
203.1293.748
212.8653.465
222.6693.170
232.4882.976
242.3382.708
252.1942.549
262.0412.418
271.9262.228
281.8102.085
291.6871.926
301.6051.761
311.4881.619
321.3941.482
331.2841.380
341.1901.283
351.1281.157
361.0421.062
370.9480.972
380.8670.892
390.7840.829
400.7270.749
410.6620.676
420.6100.624
430.5600.582
440.5120.526
450.4670.478
460.4230.427
470.3780.382
480.3460.326
490.3110.285
500.2820.243
510.2470.207
520.2170.172
530.1760.132
540.1470.096
550.1140.062
560.0870.022
570.0570.000
580.0320.000
590.0090.000
600.0000.000
610.0000.000
620.0000.000
630.0000.000
640.0000.000
650.0000.000
660.0000.000
670.0000.000
680.0000.000
690.0000.000
700.0000.000
710.0000.000
720.0000.000
730.0000.000
740.0000.000
750.0000.000
760.0000.000
770.0000.000
780.0000.000
790.0000.000
800.0000.000
810.0000.000
820.0000.000
830.0000.000
840.0000.000
850.0000.000
860.0000.000
870.0000.000
880.0000.000
890.0000.000
900.0000.000
910.0000.000
920.0000.000
930.0000.000
940.0000.000
950.0000.000
960.0000.000
970.0000.000
980.0000.000
990.0000.000


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 The historical reference is a probabilistic representation of the historical data.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