Seasonal Streamflow Forecasts

Probability distribution for Running Ck at Dieckmans Bridge


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

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile3.5793.049
Median6.7876.053
Mean9.4169.953
75% Quartile12.26912.041
Interquartile Range8.6908.992

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
143.92263.491
234.78746.806
330.55441.132
428.27136.918
526.35833.920
624.87430.241
723.61727.832
822.61225.700
921.38923.721
1020.04422.319
1119.34921.209
1218.40420.040
1317.69819.180
1417.05518.339
1516.60617.456
1616.06816.787
1715.61716.014
1815.08515.257
1914.67714.620
2014.30314.135
2113.78913.675
2213.46213.157
2313.05812.832
2412.68012.339
2512.27412.044
2612.00811.792
2711.72811.404
2811.41911.105
2911.16510.779
3010.90110.414
3110.58610.094
3210.3399.765
3310.0949.516
349.8949.286
359.6438.954
369.4808.706
379.2728.455
389.0248.230
398.7668.044
408.6077.805
418.3837.578
428.1687.416
438.0067.276
447.8147.091
457.6336.928
467.4346.742
477.2836.585
487.0996.376
496.9136.217
506.7876.053
516.6175.905
526.4265.762
536.2885.588
546.1665.435
555.9865.268
565.8475.086
575.7304.976
585.5854.865
595.4514.748
605.3004.589
615.1944.442
625.0694.335
634.9624.234
644.8734.115
654.7564.021
664.6303.927
674.5293.840
684.3903.727
694.2823.613
704.1533.532
714.0353.422
723.9263.336
733.8363.235
743.7113.146
753.5773.049
763.4492.963
773.3242.870
783.2092.785
793.0962.705
802.9782.602
812.8632.505
822.7652.415
832.6392.313
842.5032.229
852.3772.157
862.2602.061
872.1361.964
882.0201.886
891.8981.794
901.7771.693
911.6361.600
921.5121.491
931.3681.378
941.2021.241
951.0341.145
960.8931.036
970.6890.879
980.4640.746
990.1510.594


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 The historical reference is a probabilistic representation of the historical data.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