Seasonal Streamflow Forecasts

Probability distribution for Total inflow to Dartmouth Dam


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Product list for Total inflow to Dartmouth Dam


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Probability distribution for Total inflow to Dartmouth Dam(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile25.60328.119
Median38.53745.616
Mean44.40159.513
75% Quartile56.33274.131
Interquartile Range30.72946.012

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1140.858263.391
2119.562202.600
3109.241182.748
4102.264167.861
595.408157.597
689.905144.309
786.307135.600
883.656127.895
980.850120.594
1078.549115.348
1176.346111.139
1274.087106.638
1372.373103.321
1470.597100.075
1568.57996.597
1667.17093.898
1765.71290.816
1864.39087.750
1963.27285.111
2061.76283.070
2160.80181.129
2259.53379.003
2358.40877.538
2457.26475.433
2556.35374.132
2655.59873.023
2754.75871.353
2853.91470.044
2953.00868.540
3052.14466.906
3151.28665.431
3250.51263.952
3349.68162.797
3448.95561.670
3548.05860.140
3647.19358.932
3746.46157.738
3845.81356.636
3945.14355.738
4044.35954.569
4143.57253.449
4243.00952.627
4342.40851.938
4441.84750.999
4541.23750.161
4640.69349.230
4740.09248.392
4839.61147.306
4939.06646.491
5038.53745.616
5137.91844.828
5237.35144.043
5336.74543.132
5436.37942.268
5535.81741.396
5635.16040.348
5734.51839.732
5833.99039.114
5933.46238.438
6032.96237.557
6132.51636.683
6232.07136.049
6331.64435.460
6431.21434.739
6530.63534.182
6630.03633.614
6729.64133.085
6829.17832.399
6928.66631.697
7028.22331.193
7127.60630.507
7227.15229.960
7326.70529.319
7426.24528.749
7525.59928.118
7625.15827.556
7724.51226.945
7823.96926.382
7923.51025.843
8022.81725.139
8122.18024.478
8221.62523.850
8321.20123.137
8420.53722.541
8519.87222.023
8619.34521.327
8718.64120.607
8817.99920.027
8917.40619.330
9016.69518.552
9116.05717.823
9215.30416.957
9314.53416.028
9413.51214.885
9512.41514.055
9611.38613.087
9710.53911.642
988.93910.356
996.9348.793


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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