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( Oct 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.0280.081
Median0.1141.074
Mean0.4808.359
75% Quartile0.37810.534
Interquartile Range0.34910.453

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
16.16263.884
23.94652.703
32.87048.310
42.32144.690
51.95142.003
61.69538.252
71.47235.603
81.27833.113
91.14030.613
101.04528.722
110.94427.143
120.87025.389
130.81224.050
140.75322.701
150.70121.209
160.65820.018
170.61118.623
180.57217.197
190.54315.941
200.50314.954
210.47814.003
220.45012.953
230.42212.225
240.40111.179
250.37810.534
260.3569.988
270.3369.174
280.3188.546
290.3027.840
300.2847.095
310.2706.448
320.2575.827
330.2475.364
340.2354.932
350.2244.379
360.2153.971
370.2043.592
380.1943.265
390.1863.015
400.1782.709
410.1702.439
420.1622.253
430.1552.106
440.1451.918
450.1401.760
460.1351.598
470.1301.462
480.1251.299
490.1191.186
500.1141.074
510.1090.981
520.1040.894
530.1010.801
540.0950.721
550.0920.646
560.0870.564
570.0830.520
580.0790.479
590.0760.437
600.0710.387
610.0680.341
620.0640.311
630.0610.285
640.0580.256
650.0540.234
660.0520.214
670.0490.197
680.0460.176
690.0430.156
700.0400.144
710.0380.127
720.0360.115
730.0340.102
740.0310.092
750.0280.081
760.0260.073
770.0240.064
780.0220.057
790.0200.051
800.0180.043
810.0160.037
820.0140.032
830.0120.026
840.0110.022
850.0090.019
860.0080.015
870.0070.012
880.0050.010
890.0030.007
900.0020.005
910.0010.003
920.0000.001
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 The historical reference is a probabilistic representation of the historical data.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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