Seasonal Streamflow Forecasts

Probability distribution for Mitta Mitta River at Hinnomunjie


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Product list for Mitta Mitta River at Hinnomunjie


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Probability distribution for Mitta Mitta River at Hinnomunjie(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile51.02352.127
Median70.68580.893
Mean75.45085.756
75% Quartile95.340113.842
Interquartile Range44.31761.715

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
1170.862204.901
2157.936185.886
3148.495178.422
4141.657172.279
5137.441167.721
6132.116161.364
7128.457156.878
8124.924152.667
9122.007148.442
10120.068145.249
11117.586142.584
12115.339139.624
13113.571137.364
14111.812135.085
15109.672132.561
16108.203130.544
17106.564128.171
18105.024125.733
19103.261123.570
20101.903121.853
21100.623120.184
2298.910118.312
2397.824116.995
2496.591115.062
2595.359113.843
2694.134112.787
2792.715111.171
2891.372109.879
2990.201108.368
3089.194106.693
3187.980105.150
3286.887103.570
3385.797102.315
3484.920101.070
3584.02499.348
3682.95497.962
3781.87896.568
3880.82395.260
3979.86094.178
4079.09492.747
4178.04491.353
4277.15890.314
4376.17289.434
4475.46488.219
4574.71187.118
4673.95385.879
4773.18884.748
4872.55283.261
4971.72582.127
5070.68580.893
5169.89579.765
5269.08478.630
5368.40777.292
5467.74776.004
5566.94474.687
5666.20073.077
5765.57772.119
5864.85271.146
5964.05470.072
6063.28168.653
6162.52567.226
6261.69866.177
6361.02165.193
6460.11763.977
6559.35663.025
6658.56762.047
6757.87161.129
6857.19059.925
6956.31558.681
7055.33657.780
7154.50956.541
7253.66155.543
7352.73654.365
7451.89353.306
7551.00752.126
7650.14851.065
7749.21149.902
7848.20548.823
7947.55447.783
8046.76246.412
8145.64145.115
8244.62043.874
8343.78342.455
8442.86441.260
8541.87040.218
8640.94438.807
8740.09137.343
8838.91936.156
8937.95334.724
9037.11433.122
9135.57531.616
9234.14229.826
9333.01427.903
9431.39825.541
9528.97423.834
9626.65521.853
9724.87118.932
9821.77616.382
9917.61013.364


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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