Seasonal Streamflow Forecasts

Probability distribution for Running Ck at Dieckmans Bridge


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

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile1.1031.755
Median1.6543.027
Mean1.8944.240
75% Quartile2.3985.243
Interquartile Range1.2953.488

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
15.76121.853
25.01316.320
34.52414.546
44.19513.214
53.98912.257
63.81511.140
73.68510.384
83.5619.712
93.4459.090
103.3078.643
113.2178.287
123.1167.914
133.0307.636
142.9677.349
152.9117.069
162.8566.852
172.8006.582
182.7426.336
192.6906.126
202.6275.963
212.5825.803
222.5325.619
232.4895.515
242.4425.347
252.3985.244
262.3605.156
272.3195.019
282.2794.913
292.2414.798
302.2124.667
312.1764.552
322.1464.433
332.1144.343
342.0824.259
352.0514.137
362.0154.045
371.9853.951
381.9523.867
391.9253.797
401.8973.707
411.8733.621
421.8413.559
431.8243.505
441.8003.434
451.7733.371
461.7433.299
471.7213.237
481.6983.155
491.6783.093
501.6543.027
511.6302.968
521.6062.911
531.5812.841
541.5572.779
551.5342.711
561.5122.636
571.4942.591
581.4692.544
591.4422.496
601.4172.429
611.3992.367
621.3792.321
631.3572.278
641.3402.227
651.3202.187
661.2952.146
671.2762.108
681.2552.059
691.2382.009
701.2171.973
711.1921.924
721.1701.885
731.1481.840
741.1231.799
751.1031.755
761.0811.716
771.0581.673
781.0331.634
791.0151.596
800.9931.547
810.9751.502
820.9521.458
830.9301.409
840.9031.369
850.8811.333
860.8551.286
870.8311.238
880.8021.199
890.7741.152
900.7491.100
910.7201.052
920.6900.995
930.6560.934
940.6210.860
950.5850.806
960.5380.745
970.4910.654
980.4220.574
990.3400.479


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 The historical reference is a probabilistic representation of the historical data.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