Seasonal Streamflow Forecasts

Probability distribution for Tarcutta Creek at Old Borambola


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Product list for Tarcutta Creek at Old Borambola



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Probability distribution for Tarcutta Creek at Old Borambola ( Jan 2009 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile1.3953.200
Median3.3317.050
Mean4.82411.126
75% Quartile6.43213.985
Interquartile Range5.03710.785

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
125.13770.133
219.93550.826
317.11444.684
415.62040.212
514.55637.067
613.71233.232
712.72930.727
812.01928.512
911.48826.451
1010.90124.988
1110.46423.825
129.96422.597
139.58921.690
149.16020.800
158.82219.862
168.52719.148
178.22118.319
187.95317.504
197.69516.815
207.42716.287
217.16815.785
226.97015.217
236.80814.860
246.63614.316
256.43413.989
266.28613.709
276.06913.276
285.93012.940
295.78412.575
305.63912.162
315.49411.800
325.33911.424
335.21711.140
345.09710.876
354.94710.493
364.82010.206
374.6959.914
384.5779.652
394.4669.433
404.3539.153
414.2528.885
424.1528.692
434.0368.526
443.9328.306
453.8308.110
463.7227.887
473.6127.697
483.5197.444
493.4147.251
503.3317.050
513.2486.869
523.1586.693
533.0816.479
542.9726.289
552.8866.081
562.8115.853
572.7345.715
582.6665.574
592.5975.426
602.5125.224
612.4485.036
622.3684.898
632.2914.768
642.2144.614
652.1504.492
662.0734.369
672.0004.255
681.9274.107
691.8433.956
701.7693.849
711.6963.703
721.6143.587
731.5343.452
741.4703.332
751.3953.200
761.3173.083
771.2412.956
781.1702.840
791.0912.729
801.0122.585
810.9482.450
820.8822.323
830.8002.180
840.7332.060
850.6581.957
860.5691.819
870.4751.678
880.3801.564
890.2871.429
900.2091.279
910.1131.139
920.0160.976
930.0000.802
940.0000.590
950.0000.439
960.0000.264
970.0000.009
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 The historical reference is a probabilistic representation of the historical data.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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