Seasonal Streamflow Forecasts

Probability distribution for Boorowa River at Prossers Crossing


Return to catchment list
Product list for Boorowa River at Prossers Crossing


Download forecast data
Probability distribution for Boorowa River at Prossers Crossing( Apr 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile0.3011.050
Median1.4824.077
Mean5.52919.280
75% Quartile4.80514.758
Interquartile Range4.50413.708

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
165.035268.339
245.804171.220
333.395138.748
428.665115.196
523.60999.699
620.98980.891
718.84269.497
816.26760.111
914.45851.862
1013.17346.335
1112.12542.149
1211.12237.918
1310.33734.961
149.45132.203
158.90029.392
168.41027.314
177.89925.051
187.37322.914
196.90221.164
206.40619.868
216.02218.680
225.71017.429
235.37816.598
245.09315.445
254.80714.758
264.53314.187
274.36713.353
284.17512.720
293.99612.015
303.76411.277
313.56810.635
323.42110.014
333.2719.544
343.1169.099
352.9698.516
362.8458.071
372.7237.646
382.5857.265
392.4766.964
402.3446.583
412.2396.230
422.1265.978
432.0425.772
441.9615.498
451.8795.260
461.7925.003
471.7234.778
481.6184.496
491.5554.291
501.4824.077
511.4183.890
521.3513.709
531.2803.505
541.2143.318
551.1523.135
561.0882.923
571.0422.803
581.0002.684
590.9442.559
600.9052.400
610.8502.249
620.8012.143
630.7682.046
640.7261.932
650.6781.846
660.6391.761
670.5941.684
680.5621.586
690.5161.490
700.4741.423
710.4361.334
720.4031.266
730.3751.188
740.3341.122
750.3011.050
760.2660.988
770.2340.924
780.2030.866
790.1750.813
800.1460.746
810.1170.685
820.0850.630
830.0600.571
840.0410.523
850.0200.483
860.0000.432
870.0000.381
880.0000.343
890.0000.299
900.0000.252
910.0000.212
920.0000.167
930.0000.122
940.0000.073
950.0000.041
960.0000.007
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 The historical reference is a probabilistic representation of the historical data.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.


Creative Commons By Attribution logo
Unless otherwise noted, all material on this page is licensed under the Creative Commons Attribution Australia Licence