Seasonal Streamflow Forecasts

Probability distribution for Total inflow to Dartmouth Dam


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Probability distribution for Total inflow to Dartmouth Dam ( Jan 2013 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile33.39637.009
Median46.52657.436
Mean50.78564.900
75% Quartile64.09884.234
Interquartile Range30.70147.226

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1128.576199.667
2113.472168.757
3106.169157.780
4100.884149.193
596.526143.072
693.062134.874
789.709129.316
887.214124.264
984.854119.349
1082.443115.733
1180.523112.780
1278.522109.565
1377.219107.156
1475.907104.766
1574.830102.165
1673.334100.119
1772.11397.748
1870.66695.355
1969.66693.264
2068.70491.627
2167.67290.053
2266.88088.310
2365.93487.096
2464.98385.335
2564.12584.235
2663.43783.290
2762.47181.856
2861.64780.721
2960.83779.405
3060.14477.962
3159.43276.644
3258.77475.310
3358.01974.258
3457.24973.224
3556.52171.806
3655.74370.674
3755.08769.547
3854.15968.496
3953.41967.633
4052.74766.500
4152.12665.405
4251.47464.594
4350.85363.911
4450.04962.972
4549.44062.128
4648.91461.183
4748.30460.325
4847.71659.204
4947.00158.355
5046.52657.436
5145.83156.601
5245.19455.764
5344.69854.783
5444.20353.843
5543.71052.888
5643.32551.726
5742.82051.038
5842.36450.341
5941.85949.575
6041.40248.566
6140.79947.555
6240.30546.815
6339.70546.122
6439.12645.268
6538.70044.600
6638.21043.916
6737.59743.275
6836.90142.435
6936.34141.568
7035.84440.941
7135.39840.079
7234.91139.385
7334.37738.566
7433.89337.829
7533.39437.007
7632.74236.268
7732.28835.457
7831.49434.702
7930.87433.973
8030.23133.010
8129.65932.094
8229.07031.214
8328.43730.203
8427.70129.346
8526.94728.595
8626.18527.570
8725.62526.497
8825.10425.619
8924.33624.549
9023.67323.334
9123.03022.175
9222.05420.772
9321.13719.230
9420.03917.277
9518.54715.817
9617.11614.065
9715.37311.339
9813.8488.787
9911.3705.485


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 The historical reference is a probabilistic representation of the historical data.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