Seasonal Streamflow Forecasts

Probability distribution for Muttama Creek at Coolac


Return to catchment list
Product list for Muttama Creek at Coolac


Download forecast data
Probability distribution for Muttama Creek at Coolac( Jul 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile5.4552.790
Median13.01713.855
Mean18.35320.504
75% Quartile26.75732.889
Interquartile Range21.30230.099

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
175.73984.720
264.98073.979
360.23769.759
455.81166.282
552.46163.700
649.76760.097
747.79857.551
845.65055.158
943.87852.755
1042.33350.936
1140.74749.417
1239.48247.727
1337.98146.435
1436.69545.131
1535.42643.686
1634.29742.529
1733.55941.166
1832.50039.764
1931.41938.518
2030.49737.527
2129.78136.563
2228.99635.481
2328.25934.718
2427.57033.597
2526.78432.890
2625.88432.277
2725.10331.337
2824.33430.585
2923.71129.704
3023.03528.727
3122.40827.826
3221.81826.903
3321.27826.169
3420.71125.441
3520.13624.434
3619.65623.623
3719.06422.808
3818.45022.044
3917.97521.414
4017.48920.581
4116.99519.772
4216.46119.170
4315.96418.662
4415.59817.963
4515.12917.334
4614.58816.629
4714.09715.990
4813.73315.158
4913.41614.530
5013.01713.855
5112.59113.246
5212.26112.641
5311.94311.941
5411.59011.281
5511.24810.622
5610.9299.841
5710.5809.390
5810.1268.943
599.8318.463
609.5167.851
619.2457.263
628.9826.849
638.6916.475
648.3046.032
658.0295.700
667.7955.372
677.4945.077
687.2054.709
696.9394.349
706.6454.102
716.4093.780
726.1683.535
735.9643.262
745.7253.031
755.4522.789
765.2382.585
774.9432.376
784.6882.193
794.4992.028
804.2721.826
814.0591.650
823.8371.495
833.6751.331
843.4591.205
853.2181.103
862.9640.975
872.7600.855
882.5650.767
892.3780.670
902.1510.573
911.9480.491
921.7200.406
931.5130.328
941.3580.247
951.1810.199
960.9280.151
970.7260.097
980.4960.062
990.2510.034


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 The historical reference is a probabilistic representation of the historical data.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