Seasonal Streamflow Forecasts

Probability distribution for Gudgenby at Tennent


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Probability distribution for Gudgenby at Tennent ( May 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile9.4163.866
Median15.0507.883
Mean18.27812.708
75% Quartile23.80115.971
Interquartile Range14.38612.106

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
164.90872.243
253.00156.680
348.98650.906
445.34146.418
542.55943.113
640.25338.921
738.43536.092
836.82733.532
935.41631.107
1034.22329.363
1132.92927.966
1231.85226.481
1330.96825.379
1430.14624.294
1529.49323.147
1628.70422.273
1728.16821.259
1827.31520.261
1926.86719.417
2026.37418.772
2125.87718.159
2225.29617.467
2324.80117.032
2424.31716.371
2523.80415.976
2623.30015.637
2722.75915.115
2822.34214.712
2921.85414.273
3021.41013.780
3120.97613.348
3220.65812.903
3320.33412.567
3420.06112.256
3519.72311.807
3619.33111.471
3719.02211.131
3818.72210.827
3918.35210.574
4018.04610.252
4117.7339.944
4217.4069.724
4317.1329.535
4416.8379.286
4516.5339.065
4616.2548.814
4715.9298.601
4815.6558.319
4915.3288.105
5015.0507.883
5114.7837.684
5214.4877.491
5314.3017.257
5414.0937.051
5513.8266.826
5613.5606.582
5713.3446.434
5813.0506.285
5912.8566.128
6012.6545.916
6112.4445.719
6212.2395.575
6312.0595.440
6411.8165.281
6511.6385.156
6611.4335.031
6711.2154.914
6811.0384.765
6910.7854.613
7010.5574.505
7110.2714.360
7210.0634.245
739.8764.112
749.6713.994
759.4133.865
769.2353.752
779.0583.630
788.8413.518
798.6303.413
808.4383.277
818.2263.150
827.9793.032
837.7282.899
847.4732.790
857.2642.696
867.0152.571
876.7952.444
886.5802.344
896.3232.224
905.9982.094
915.7131.974
925.4381.835
935.1701.689
944.8571.515
954.4491.393
964.0941.255
973.7511.057
983.1630.891
992.5790.703


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 The historical reference is a probabilistic representation of the historical data.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