Seasonal Streamflow Forecasts

Probability distribution for Kyeamba Creek at Ladysmith


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Product list for Kyeamba Creek at Ladysmith



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Probability distribution for Kyeamba Creek at Ladysmith ( Jun 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.0990.406
Median1.0452.655
Mean4.46512.631
75% Quartile4.41113.153
Interquartile Range4.31212.747

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
140.226110.375
232.60087.830
328.46178.992
425.13271.731
522.28266.362
619.44158.916
717.54053.708
816.08448.874
914.73344.103
1013.54840.569
1112.19637.679
1211.11634.547
1310.28932.221
149.38229.942
158.69527.506
168.10725.633
177.59023.520
187.01421.459
196.64019.730
206.31018.425
215.88517.215
225.38915.929
234.99415.068
244.70113.870
254.42213.154
264.09112.559
273.86711.690
283.67811.032
293.44210.302
303.2369.542
313.0568.884
322.8818.253
332.7507.779
342.6017.333
352.4396.754
362.2776.318
372.1735.905
382.0645.539
391.9645.252
401.8564.892
411.7384.564
421.6244.331
431.5254.143
441.4513.894
451.3753.681
461.2953.453
471.2343.256
481.1563.012
491.0962.836
501.0452.655
510.9802.499
520.9152.349
530.8652.183
540.8042.032
550.7481.887
560.6981.721
570.6471.628
580.6031.538
590.5611.443
600.5161.325
610.4771.214
620.4471.137
630.4141.068
640.3880.987
650.3600.927
660.3300.868
670.3010.816
680.2700.750
690.2440.686
700.2150.642
710.1960.584
720.1710.541
730.1460.492
740.1250.450
750.0990.406
760.0830.369
770.0650.330
780.0480.297
790.0270.266
800.0130.227
810.0000.194
820.0000.164
830.0000.131
840.0000.106
850.0000.085
860.0000.059
870.0000.034
880.0000.015
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 The historical reference is a probabilistic representation of the historical data.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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