Seasonal Streamflow Forecasts

Probability distribution for Halls Creek at Bingara


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Product list for Halls Creek at Bingara



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Probability distribution for Halls Creek at Bingara ( May 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.4760.412
Median0.7520.745
Mean0.9351.108
75% Quartile1.1831.353
Interquartile Range0.7070.941

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
13.6816.388
23.0184.650
32.6644.103
42.4123.696
52.2193.406
62.0663.070
71.9752.844
81.8902.645
91.8242.461
101.7512.330
111.6832.226
121.6212.117
131.5802.036
141.5351.953
151.4931.872
161.4581.810
171.4261.733
181.3871.662
191.3541.602
201.3221.556
211.2931.511
221.2571.459
231.2301.429
241.2081.382
251.1841.353
261.1641.329
271.1401.290
281.1161.261
291.0961.229
301.0731.192
311.0511.160
321.0251.127
331.0071.102
340.9861.079
350.9661.046
360.9481.020
370.9330.995
380.9170.972
390.9000.953
400.8860.928
410.8730.905
420.8580.888
430.8460.873
440.8290.854
450.8160.837
460.8040.818
470.7920.801
480.7790.779
490.7640.762
500.7520.745
510.7380.729
520.7230.714
530.7090.695
540.7000.678
550.6880.660
560.6770.641
570.6670.629
580.6570.616
590.6480.604
600.6370.586
610.6280.570
620.6170.558
630.6040.547
640.5930.533
650.5810.523
660.5710.512
670.5600.502
680.5500.490
690.5400.477
700.5280.467
710.5170.455
720.5090.445
730.5010.433
740.4880.423
750.4760.412
760.4620.402
770.4520.391
780.4410.381
790.4310.371
800.4200.359
810.4090.347
820.3980.337
830.3870.324
840.3750.314
850.3630.305
860.3530.294
870.3420.282
880.3280.272
890.3140.260
900.3010.248
910.2840.236
920.2700.222
930.2570.207
940.2410.189
950.2240.177
960.2030.162
970.1850.141
980.1530.122
990.1100.100


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 The historical reference is a probabilistic representation of the historical data.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