Seasonal Streamflow Forecasts

Probability distribution for Running Ck at Dieckmans Bridge


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

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile1.6301.383
Median2.6232.500
Mean3.2163.476
75% Quartile4.1124.460
Interquartile Range2.4823.077

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
111.97116.186
210.02912.957
38.87511.774
48.18310.858
57.66110.184
67.2239.329
76.8588.750
86.5538.224
96.2337.723
106.0657.360
115.8587.068
125.7126.755
135.5696.522
145.4146.291
155.2526.046
165.1035.857
174.9795.637
184.8405.419
194.7215.233
204.6055.090
214.4924.954
224.3734.799
234.3034.701
244.1964.551
254.1134.461
264.0524.384
273.9824.264
283.9144.170
293.8284.068
303.7563.953
313.6833.851
323.6093.746
333.5453.666
343.4793.591
353.4263.483
363.3553.402
373.2963.319
383.2503.245
393.1873.182
403.1253.103
413.0643.026
423.0112.971
432.9662.924
442.9182.861
452.8622.805
462.8132.741
472.7602.686
482.7192.613
492.6702.558
502.6232.500
512.5712.448
522.5232.397
532.4782.335
542.4372.280
552.4042.220
562.3542.154
572.3132.114
582.2712.074
592.2392.031
602.2011.972
612.1691.918
622.1241.878
632.0841.840
642.0401.795
651.9941.760
661.9651.724
671.9351.691
681.8981.648
691.8641.604
701.8231.572
711.7901.530
721.7511.496
731.7101.457
741.6641.422
751.6301.383
761.5891.349
771.5481.312
781.4961.278
791.4581.246
801.4081.204
811.3741.164
821.3321.127
831.2891.085
841.2541.050
851.2041.020
861.1580.980
871.1120.939
881.0610.905
891.0290.866
900.9820.822
910.9420.781
920.8910.733
930.8330.682
940.7890.620
950.7150.576
960.6350.525
970.5590.450
980.4800.385
990.3600.308


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 The historical reference is a probabilistic representation of the historical data.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