Seasonal Streamflow Forecasts

Probability distribution for Total Inflows to Lake Eppalock


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Product list for Total Inflows to Lake Eppalock



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Probability distribution for Total Inflows to Lake Eppalock ( Jan 2011 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.8570.000
Median4.2430.243
Mean14.4744.028
75% Quartile14.2112.549
Interquartile Range13.3542.549

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1144.15461.199
2102.70140.886
382.85033.523
471.21827.920
562.39724.103
656.12519.343
750.68616.404
846.49013.967
943.30811.822
1039.94310.390
1136.2209.311
1233.5988.227
1330.9837.475
1428.5176.779
1526.3656.075
1624.6385.559
1722.9775.002
1821.6014.481
1920.3134.058
2019.1823.748
2117.8543.465
2216.8633.170
2315.8252.976
2415.0322.708
2514.2122.549
2613.4392.418
2712.7752.228
2812.1652.085
2911.6011.926
3011.0671.761
3110.5331.619
3210.0411.482
339.5551.380
349.1691.283
358.6931.157
368.3631.062
378.0520.972
387.6920.892
397.3230.829
406.9680.749
416.6500.676
426.3680.624
436.0350.582
445.7070.526
455.4220.478
465.1260.427
474.9030.382
484.6610.326
494.4750.285
504.2430.243
514.0070.207
523.7980.172
533.6160.132
543.3870.096
553.2310.062
563.0720.022
572.9240.000
582.7480.000
592.6210.000
602.5030.000
612.3720.000
622.2720.000
632.1470.000
642.0370.000
651.9210.000
661.7890.000
671.6690.000
681.5780.000
691.4600.000
701.3410.000
711.2550.000
721.1400.000
731.0590.000
740.9370.000
750.8550.000
760.7570.000
770.6810.000
780.6040.000
790.5480.000
800.4640.000
810.3840.000
820.3220.000
830.2570.000
840.1930.000
850.1380.000
860.0780.000
870.0200.000
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 The historical reference is a probabilistic representation of the historical data.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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