Seasonal Streamflow Forecasts

Probability distribution for Running Ck at Dieckmans Bridge


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Probability distribution for Running Ck at Dieckmans Bridge ( Mar 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile3.1284.446
Median6.78910.314
Mean9.89814.383
75% Quartile13.62820.791
Interquartile Range10.50016.346

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
143.81857.067
237.96249.328
334.45546.294
431.90543.800
529.81341.952
628.32539.380
726.48737.569
825.07835.874
923.61134.179
1022.61132.902
1121.74831.841
1220.69730.667
1319.81129.773
1419.06928.877
1518.54027.888
1617.77927.102
1717.17026.183
1816.57725.245
1916.17224.419
2015.71023.768
2115.24223.139
2214.77122.439
2314.39921.950
2413.93921.237
2513.62820.792
2613.34920.408
2713.02219.826
2812.68719.364
2912.29018.829
3011.93818.243
3111.61217.709
3211.28817.169
3310.95116.744
3410.61416.328
3510.36015.760
3610.07915.309
379.84014.862
389.61114.449
399.27314.111
408.98913.671
418.75513.248
428.48812.938
438.22912.679
447.99512.325
457.80312.010
467.55211.660
477.33011.346
487.13110.941
496.92810.638
506.78910.314
516.60210.023
526.4089.735
536.2359.403
546.0659.090
555.9058.776
565.7698.403
575.5908.186
585.4677.969
595.3217.734
605.1677.430
615.0187.132
624.8586.919
634.7256.722
644.5746.484
654.4346.302
664.2846.118
674.1415.949
684.0195.732
693.9005.512
703.7645.357
713.6535.148
723.5244.983
733.3634.794
743.2714.627
753.1264.445
763.0124.286
772.8674.116
782.7233.961
792.6103.816
802.4993.629
812.3233.457
822.2103.297
832.0483.119
841.9612.974
851.8572.850
861.7342.688
871.6272.524
881.5272.395
891.4142.245
901.2922.082
911.1791.934
921.0681.765
930.9001.592
940.7541.390
950.5911.251
960.4461.098
970.2490.886
980.0880.716
990.0000.531


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 The historical reference is a probabilistic representation of the historical data.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