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Table 4

Statistical indicators of the degree of precision of the calculations used

Abbreviation	Name	Comments
ME	Mean error	Basic statistical indicator
RMSE	Root mean square error	Gives the standard deviation of the model prediction error
PBIAS	Percentual bias	Percentual average deviation (quantifying the average undervaluation/overvaluation of the model)
NSE	Nash–Sutcliffe efficiency	Standard in hydrology, primary indicator in this work
cp	Coefficient of persistence	Compares the model's performance against a simple model using the observed value of the previous day as the prediction for the current day
R²	Coefficient of determination	Proportion of the variance in the dependent variable that is predictable from the independent variables. The coefficient of determination ranges from 0 to 1; an R² value of 1 indicates that the regression predictions perfectly fit the data.

Abbreviation	Name	Comments
ME	Mean error	Basic statistical indicator
RMSE	Root mean square error	Gives the standard deviation of the model prediction error
PBIAS	Percentual bias	Percentual average deviation (quantifying the average undervaluation/overvaluation of the model)
NSE	Nash–Sutcliffe efficiency	Standard in hydrology, primary indicator in this work
cp	Coefficient of persistence	Compares the model's performance against a simple model using the observed value of the previous day as the prediction for the current day
R²	Coefficient of determination	Proportion of the variance in the dependent variable that is predictable from the independent variables. The coefficient of determination ranges from 0 to 1; an R² value of 1 indicates that the regression predictions perfectly fit the data.