Seasonal Streamflow Forecasts

Probability distribution for Unregulated inflow to Hume Dam


Return to catchment list
Product list for Unregulated inflow to Hume Dam


Download forecast data
Probability distribution for Unregulated inflow to Hume Dam( Apr 2014 )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile119.633160.251
Median184.366266.258
Mean222.731357.686
75% Quartile282.254443.795
Interquartile Range162.622283.544

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1808.7311689.653
2653.8441280.992
3589.3701148.923
4541.9841050.412
5511.514982.776
6483.000895.579
7460.652838.673
8443.299788.494
9427.647741.108
10410.841707.153
11396.982679.981
12384.335650.983
13369.278629.651
14358.662608.823
15349.060586.539
16342.285569.286
17335.321549.612
18326.191530.079
19316.649513.297
20310.014500.335
21304.771488.025
22298.337474.564
23292.631465.299
24287.947452.005
25282.356443.799
26277.926436.810
27272.130426.299
28267.625418.065
29262.503408.618
30258.187398.371
31252.733389.132
32248.072379.877
33243.993372.660
34239.435365.622
35235.060356.084
36231.123348.559
37227.343341.135
38223.863334.287
39219.840328.717
40216.809321.466
41213.700314.532
42209.986309.443
43206.188305.187
44203.447299.387
45200.908294.215
46197.300288.476
47194.145283.313
48190.566276.636
49187.063271.628
50184.366266.258
51180.666261.423
52178.026256.619
53175.465251.045
54172.726245.759
55169.576240.439
56167.515234.048
57165.188230.300
58162.155226.535
59160.170222.428
60157.720217.076
61155.013211.779
62152.377207.939
63149.384204.372
64146.731200.019
65144.245196.650
66141.849193.223
67139.236190.038
68136.659185.905
69134.129181.683
70132.340178.659
71129.604174.542
72127.279171.259
73124.715167.425
74122.285164.012
75119.584160.245
76115.718156.891
77113.605153.250
78111.658149.898
79109.224146.697
80106.838142.515
81104.419138.596
82101.763134.878
8399.152130.666
8496.113127.145
8593.146124.097
8689.884119.997
8787.130115.773
8883.716112.373
8980.210108.291
9077.211103.748
9174.43799.500
9271.17194.472
9366.91489.089
9462.06182.488
9557.46077.716
9651.50772.165
9746.93363.924
9839.60456.642
9931.79147.851


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.


Creative Commons By Attribution logo
Unless otherwise noted, all material on this page is licensed under the Creative Commons Attribution Australia Licence