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Historical Reference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% Quartile213.284180.546
Median281.420285.645
Mean295.299300.463
75% Quartile365.551402.165
Interquartile Range152.267221.619

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1603.664716.756
2555.995651.353
3533.510625.663
4514.063604.506
5494.873588.804
6484.639566.892
7473.135551.418
8463.552536.883
9455.474522.289
10446.511511.253
11438.597502.038
12432.282491.794
13425.429483.967
14418.091476.069
15412.375467.320
16407.019460.320
17401.915452.081
18397.542443.610
19392.395436.087
20388.177430.111
21383.633424.295
22379.063417.771
23374.343413.177
24370.640406.428
25365.617402.167
26361.309398.478
27357.305392.823
28353.413388.300
29349.480383.005
30345.676377.130
31341.233371.709
32337.151366.157
33334.032361.740
34330.830357.355
35328.078351.286
36324.911346.392
37321.412341.468
38317.824336.839
39314.528333.010
40311.470327.938
41308.146322.991
42305.390319.298
43302.130316.168
44299.463311.841
45296.743307.920
46294.248303.499
47290.902299.457
48287.789294.135
49284.141290.072
50281.420285.645
51278.614281.595
52275.795277.511
53273.048272.694
54270.576268.045
55267.569263.287
56265.216257.460
57262.674253.987
58260.344250.455
59257.648246.551
60254.922241.385
61252.801236.180
62250.266232.350
63247.555228.748
64245.028224.294
65243.118220.803
66240.700217.211
67238.361213.836
68235.294209.405
69232.399204.816
70229.304201.490
71226.064196.910
72222.851193.215
73220.005188.851
74216.965184.923
75213.227180.539
76210.306176.596
77207.422172.269
78204.152168.247
79200.535164.372
80197.573159.259
81193.510154.418
82189.418149.782
83186.019144.484
84183.197140.018
85179.918136.127
86175.660130.858
87171.314125.394
88167.765120.973
89164.381115.644
90160.460109.691
91156.559104.111
92151.80197.501
93146.17290.436
94139.51281.814
95133.52575.631
96126.41068.517
97116.52758.167
98104.97849.298
9993.21039.046


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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