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 ( Jun 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.4620.422
Median0.7040.754
Mean0.8401.103
75% Quartile1.0531.351
Interquartile Range0.5910.929

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
12.9836.170
22.4364.514
32.2023.987
42.0403.603
51.9063.333
61.7883.004
71.7012.789
81.6422.599
91.5762.422
101.5162.296
111.4622.197
121.4172.091
131.3682.013
141.3271.937
151.2971.856
161.2701.795
171.2431.723
181.2181.653
191.1921.594
201.1711.549
211.1461.506
221.1221.457
231.1001.426
241.0751.379
251.0531.351
261.0321.327
271.0131.290
280.9971.261
290.9801.229
300.9631.194
310.9471.163
320.9331.130
330.9131.106
340.8971.083
350.8821.050
360.8671.026
370.8571.001
380.8450.978
390.8320.959
400.8190.935
410.8030.912
420.7920.895
430.7790.881
440.7700.862
450.7590.845
460.7480.826
470.7340.810
480.7230.788
490.7130.771
500.7040.754
510.6930.738
520.6820.723
530.6740.705
540.6640.688
550.6530.670
560.6440.651
570.6350.639
580.6270.627
590.6170.614
600.6070.597
610.5990.580
620.5910.569
630.5810.557
640.5710.544
650.5610.534
660.5510.523
670.5420.513
680.5320.500
690.5200.487
700.5100.478
710.5010.465
720.4930.455
730.4820.444
740.4730.433
750.4620.422
760.4520.412
770.4440.401
780.4330.391
790.4250.381
800.4160.369
810.4080.357
820.3980.346
830.3870.334
840.3750.324
850.3640.315
860.3540.303
870.3430.291
880.3280.281
890.3170.269
900.3060.256
910.2890.244
920.2750.230
930.2620.215
940.2450.197
950.2260.184
960.2070.169
970.1860.146
980.1580.127
990.1210.104


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 The historical reference is a probabilistic representation of the historical data.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