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Historical Reference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% Quartile292.079257.602
Median377.190388.018
Mean393.507405.705
75% Quartile480.288532.557
Interquartile Range188.209274.955

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1786.571925.552
2726.041843.696
3691.475811.555
4664.102785.090
5640.775765.452
6627.658738.057
7612.619718.716
8600.821700.553
9589.946682.323
10576.774668.540
11568.810657.034
12560.032644.247
13552.199634.480
14546.381624.627
15539.926613.715
16532.262604.986
17525.086594.714
18519.941584.157
19513.973574.784
20507.805567.341
21501.118560.099
22494.700551.977
23490.083546.258
24485.189537.860
25480.344532.560
26474.844527.971
27469.974520.939
28465.015515.316
29460.480508.734
30455.847501.434
31451.510494.700
32446.056487.805
33442.151482.320
34438.772476.878
35434.328469.347
36429.298463.275
37425.646457.167
38421.635451.427
39417.777446.679
40413.363440.392
41409.383434.261
42406.244429.686
43402.705425.808
44399.071420.448
45395.482415.592
46392.151410.118
47387.657405.114
48384.064398.526
49380.864393.497
50377.190388.018
51373.830383.006
52370.067377.952
53366.095371.991
54362.709366.239
55359.532360.351
56355.995353.141
57353.273348.843
58349.885344.471
59346.653339.639
60343.305333.242
61340.019326.796
62337.134322.050
63334.378317.587
64330.651312.065
65327.303307.734
66323.918303.277
67320.331299.087
68316.720293.582
69313.141287.876
70309.814283.738
71305.767278.035
72302.711273.430
73298.832267.984
74295.448263.078
75292.027257.594
76287.731252.654
77284.464247.227
78281.965242.173
79278.916237.295
80274.423230.845
81270.071224.723
82265.767218.845
83261.034212.105
84257.340206.407
85252.023201.426
86247.892194.660
87241.436187.610
88235.773181.881
89230.984174.940
90225.732167.141
91220.341159.783
92213.482150.997
93207.895141.516
94200.668129.804
95192.942121.297
96181.380111.383
97170.81296.681
98158.30283.777
99136.79168.429


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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