Seasonal Streamflow Forecasts

Probability distribution for Total inflow to Dartmouth Dam


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Probability distribution for Total inflow to Dartmouth Dam ( Jun 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile227.004158.255
Median318.008250.172
Mean346.051299.512
75% Quartile439.168388.419
Interquartile Range212.164230.163

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1866.096983.808
2774.146838.785
3720.127784.049
4685.471740.099
5650.154708.203
6628.768664.808
7608.604634.992
8590.049607.647
9575.197580.867
10562.239561.076
11550.626544.862
12540.691527.181
13529.411513.916
14517.895500.750
15510.859486.422
16503.626475.156
17494.822462.120
18487.585448.976
19479.807437.519
20472.801428.566
21464.397419.978
22455.198410.490
23448.006403.900
24442.485394.360
25439.206388.422
26433.060383.333
27427.595375.628
28421.145369.547
29415.169362.522
30409.786354.842
31404.614347.865
32399.140340.825
33394.334335.300
34390.222329.882
35385.726322.493
36380.340316.624
37375.311310.800
38370.501305.399
39365.698300.983
40361.596295.208
41356.029289.656
42351.712285.561
43346.428282.125
44342.769277.424
45337.509273.214
46334.258268.524
47330.652264.287
48326.928258.783
49322.934254.636
50318.008250.172
51314.098246.137
52311.375242.114
53306.961237.427
54302.752232.964
55298.898228.455
56295.117223.014
57291.447219.811
58287.362216.584
59283.703213.054
60280.522208.438
61276.471203.850
62272.435200.513
63268.550197.405
64264.890193.600
65261.314190.647
66258.039187.635
67255.781184.829
68252.888181.178
69249.394177.436
70245.814174.748
71242.435171.080
72238.758168.147
73235.063164.711
74231.716161.645
75226.981158.250
76222.790155.220
77219.101151.921
78214.156148.876
79209.783145.961
80204.620142.141
81199.939138.550
82195.295135.133
83190.035131.249
84185.056127.992
85180.796125.165
86176.169121.351
87172.032117.408
88166.993114.223
89162.237110.388
90157.219106.103
91151.602102.081
92147.58997.300
93140.41092.156
94132.82585.812
95124.52681.198
96115.67375.803
97104.99867.730
9893.29360.529
9973.21851.743


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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