Seasonal Streamflow Forecasts

Exceedance probability for Adjungbilly Creek at Darbalara


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Exceedance probability for Adjungbilly Creek at Darbalara ( Apr 2014 )

Exceedance Probability Summary
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1017.41721.415
2013.75915.869
3011.51613.020
409.82110.812
508.4719.181
607.2627.686
706.0936.498
804.9665.341
903.5914.056

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
131.61145.433
226.85435.820
324.47732.591
422.52030.176
521.33028.439
620.34726.275
719.52124.832
818.61723.532
917.97922.302
1017.41721.415
1117.03920.703
1216.51619.942
1316.06619.374
1415.67318.811
1515.30018.212
1615.00517.752
1714.69517.213
1814.40316.678
1914.12716.221
2013.75915.869
2113.46715.531
2213.25915.147
2313.01614.903
2412.76714.529
2512.57414.304
2612.32114.109
2712.08413.807
2811.88513.571
2911.70413.313
3011.51613.020
3111.32812.760
3211.18112.490
3311.00012.284
3410.78312.092
3510.64111.811
3610.52011.599
3710.30011.383
3810.13411.187
399.97511.023
409.82110.812
419.66110.608
429.49610.461
439.37310.334
449.23610.165
459.09010.013
468.9719.840
478.8249.691
488.7039.493
498.5759.340
508.4719.181
518.3379.036
528.1888.895
538.0568.722
547.9368.568
557.8178.398
567.6888.211
577.5928.096
587.4647.979
597.3627.856
607.2627.686
617.1397.527
627.0337.410
636.9357.299
646.8067.166
656.6927.062
666.5656.955
676.4446.855
686.3236.726
696.2246.593
706.0936.498
715.9866.368
725.8906.264
735.7706.142
745.6536.033
755.5305.913
765.4175.805
775.3215.688
785.1935.580
795.0855.477
804.9665.341
814.8555.213
824.7695.092
834.6214.954
844.4954.838
854.3444.737
864.2324.601
874.0964.460
883.9234.346
893.7634.209
903.5914.056
913.4003.911
923.2503.739
933.1173.554
942.9053.324
952.6983.157
962.4862.960
972.2272.665
981.8982.400
991.3842.073


About the exceedance probability 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 The historical reference is a probabilistic representation of the historical data.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. Further explanation of some technical terms is provided under the FAQ.


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