Seasonal Streamflow Forecasts

Probability distribution for Total Inflows to Lake Nillahcootie


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Product list for Total Inflows to Lake Nillahcootie


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Probability distribution for Total Inflows to Lake Nillahcootie(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.6421.656
Median1.5443.944
Mean2.3596.969
75% Quartile3.1298.432
Interquartile Range2.4876.776

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
112.99051.133
210.19335.889
38.84830.949
48.11227.577
57.37425.091
66.78622.243
76.37120.359
86.03618.709
95.67817.198
105.36216.122
115.11515.281
124.91414.412
134.71813.770
144.49113.067
154.32312.444
164.16911.965
173.99711.345
183.86710.819
193.75710.352
203.6339.994
213.5399.642
223.4569.241
233.3609.017
243.2408.655
253.1298.435
263.0458.247
272.9547.957
282.8917.733
292.8167.490
302.7357.217
312.6466.978
322.5826.732
332.5176.546
342.4516.374
352.3916.125
362.3235.939
372.2595.751
382.1755.583
392.1145.443
402.0675.264
412.0105.093
421.9614.971
431.9034.866
441.8364.727
451.7854.604
461.7414.465
471.6874.346
481.6454.188
491.5904.069
501.5443.944
511.5043.833
521.4633.725
531.4263.593
541.3773.477
551.3343.351
561.2933.213
571.2603.130
581.2153.045
591.1862.956
601.1582.835
611.1182.723
621.0852.642
631.0542.564
641.0172.474
650.9822.402
660.9362.330
670.9022.263
680.8702.177
690.8402.090
700.8092.028
710.7781.943
720.7301.877
730.7001.799
740.6731.731
750.6411.656
760.6091.590
770.5701.518
780.5351.453
790.5091.391
800.4791.310
810.4501.236
820.4131.166
830.3821.087
840.3521.021
850.3240.965
860.2910.891
870.2470.814
880.2040.754
890.1670.681
900.1290.602
910.0950.529
920.0570.443
930.0160.353
940.0000.245
950.0000.169
960.0000.082
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 The historical reference is a probabilistic representation of the historical data.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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