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Flow forecasting system using meteorological data and ML regression models

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Long term Forecast of flow and its volume

flow forecast

the streamflow is derived from the volume using kNN and the same predictors used for the regressions. In this the method of regression doesn't affect significally the resultant error (see some metrics below)

The forecast ensembles spread change along the year for different initialisation times.

1st MAY snow

1st JULY snow

1st SEPTEMBER snow

1st NOVEMBER snow

Volume

1st MAY snow

1st JULY snow

1st SEPTEMBER snow

1st NOVEMBER snow

metrics

Continous Ranked Probability Skill Score (skill for many predictions) snow

CRPSS with latitude and month of initialisation snow

percentage bias snow

root mean square error snow

scatter plot of observed vs predicted snow

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Flow forecasting system using meteorological data and ML regression models

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