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Historical Reference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% Quartile294.497257.602
Median380.122388.018
Mean396.415405.705
75% Quartile483.666532.557
Interquartile Range189.169274.955

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1790.425925.552
2730.981843.696
3695.053811.555
4668.863785.090
5644.772765.452
6631.424738.057
7615.832718.716
8604.667700.553
9593.496682.323
10580.542668.540
11572.772657.034
12563.921644.247
13555.474634.480
14549.817624.627
15543.363613.715
16535.963604.986
17528.596594.714
18523.711584.157
19517.617574.784
20511.440567.341
21504.827560.099
22498.535551.977
23493.413546.258
24488.522537.860
25483.671532.560
26478.332527.971
27473.305520.939
28467.815515.316
29463.973508.734
30459.051501.434
31454.833494.700
32449.220487.805
33445.247482.320
34442.200476.878
35437.562469.347
36432.357463.275
37428.745457.167
38424.860451.427
39420.811446.679
40416.640440.392
41412.478434.261
42409.135429.686
43406.019425.808
44402.143420.448
45398.354415.592
46395.002410.118
47390.483405.114
48386.917398.526
49383.749393.497
50380.122388.018
51376.563383.006
52373.225377.952
53368.749371.991
54365.551366.239
55362.429360.351
56358.752353.141
57355.902348.843
58352.769344.471
59349.323339.639
60346.008333.242
61342.845326.796
62340.159322.050
63337.049317.587
64333.346312.065
65329.938307.734
66326.431303.277
67322.780299.087
68319.263293.582
69315.637287.876
70312.633283.738
71308.090278.035
72305.317273.430
73301.389267.984
74297.842263.078
75294.472257.594
76290.360252.654
77286.945247.227
78284.522242.173
79281.276237.295
80276.708230.845
81272.268224.723
82268.074218.845
83263.091212.105
84259.392206.407
85254.262201.426
86249.971194.660
87243.495187.610
88237.768181.881
89233.182174.940
90227.749167.141
91222.228159.783
92215.474150.997
93209.626141.516
94202.301129.804
95194.774121.297
96183.301111.383
97172.39396.681
98159.91183.777
99138.19568.429


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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