Disadvantage of this method is positive and negative value contribute together to reduce MBE. Usually MBE doesn’t consider alone, it can use with another index which is Cv(RMSE).
Root Mean Squared Error (RMSE) is a measure of the sample deviation of the differences between the measured values and the values predicted by the model. The Cv(RMSE) is the Coefficient of Variation of RMSE and is calculated as the RMSD normalized to the mean of the observed values. It defines total uncertainty in simulated data and reflect size of error and amount of scatter. It’s always positive and lower Cv(RMSE) indicate better calibration. It’s calculate by following equations.