Seasonal Streamflow Forecasts

Probability distribution for Tuross River at Tuross Vale


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Product list for Tuross River at Tuross Vale



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Probability distribution for Tuross River at Tuross Vale ( Jul 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile2.5421.628
Median5.4244.898
Mean7.1287.857
75% Quartile10.22811.736
Interquartile Range7.68610.108

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
127.10035.168
223.80430.231
321.70728.292
420.46526.696
519.26425.512
618.22723.861
717.34322.697
816.67621.604
916.01620.510
1015.41519.683
1114.95218.995
1214.52618.232
1314.14617.650
1413.73117.065
1513.20416.419
1612.85615.904
1712.48315.300
1812.14514.683
1911.84914.139
2011.55913.709
2111.31413.293
2210.97012.829
2310.68112.505
2410.46012.032
2510.23011.736
2610.01211.482
279.74711.095
289.52010.788
299.29410.432
309.04610.042
318.8769.687
328.6419.329
338.4269.048
348.2218.772
358.0168.397
367.8138.100
377.6317.806
387.4067.535
397.2377.314
407.0667.028
416.8456.754
426.7176.554
436.5446.387
446.3786.161
456.1875.960
466.0475.738
475.8795.540
485.7395.287
495.6015.098
505.4244.898
515.2804.720
525.1204.545
534.9984.345
544.8644.157
554.7113.971
564.5463.753
574.4173.626
584.3253.501
594.2243.367
604.1003.195
613.9763.029
623.8752.910
633.7362.802
643.6302.673
653.5242.575
663.4132.477
673.3162.388
683.2262.274
693.1482.160
703.0392.081
712.9541.975
722.8361.892
732.7491.798
742.6371.716
752.5421.628
762.4261.552
772.3061.471
782.2151.398
792.0911.331
802.0191.245
811.9371.168
821.8481.097
831.7411.019
841.6380.956
851.5380.904
861.4260.835
871.3390.768
881.2340.715
891.1520.655
901.0690.592
910.9890.535
920.8870.472
930.7610.409
940.6400.337
950.5440.290
960.4430.240
970.3200.173
980.1850.122
990.0000.071


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 The historical reference is a probabilistic representation of the historical data.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