Seasonal Streamflow Forecasts

Probability distribution for Murray River at Biggara


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Probability distribution for Murray River at Biggara ( Feb 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile27.61824.515
Median35.91734.858
Mean37.11038.103
75% Quartile45.57748.305
Interquartile Range17.96023.790

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
172.18694.521
267.56484.083
364.91980.066
462.16276.801
560.36674.405
658.86571.103
757.56168.804
856.28866.669
955.45164.553
1054.49262.971
1153.62461.662
1252.95660.221
1352.24159.131
1451.48058.040
1550.72956.842
1650.13455.892
1749.54254.783
1849.00753.655
1948.48752.662
2047.77851.881
2147.40051.126
2246.96550.285
2346.40849.698
2445.96048.842
2545.58048.305
2645.16647.843
2744.68247.139
2844.26646.580
2943.83445.931
3043.38545.216
3142.95744.561
3242.51043.896
3342.02543.371
3441.61642.853
3541.32342.142
3640.97241.573
3740.63741.005
3840.19240.475
3939.82840.040
4039.49139.466
4139.06038.912
4238.72738.500
4338.43338.154
4437.99037.677
4537.60037.248
4637.26836.767
4736.94836.330
4836.68835.759
4936.27035.327
5035.91734.858
5135.59734.432
5235.22534.006
5334.84433.506
5434.56533.026
5534.26732.539
5633.99531.947
5733.69131.597
5833.41431.242
5933.07830.852
6032.68630.339
6132.39629.825
6232.08529.449
6331.75529.098
6431.52128.665
6531.18828.327
6630.81327.981
6730.52527.657
6830.19527.234
6929.78626.797
7029.34326.482
7128.99526.049
7228.65525.701
7328.37725.291
7427.99624.924
7527.61224.514
7627.28424.147
7726.93023.744
7826.64623.371
7926.23423.011
8025.74122.537
8125.28822.088
8224.97321.658
8324.47221.166
8424.04720.750
8523.41620.387
8622.98319.894
8722.54319.380
8822.01618.961
8921.45318.454
9020.88217.881
9120.31917.339
9219.70216.688
9318.98615.978
9418.23615.091
9517.41614.436
9616.46913.659
9714.73312.474
9813.38511.391
9911.09810.032


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 The historical reference is a probabilistic representation of the historical data.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