Multi-objective assessment of hydrological model performances using Nash–Sutcliffe and Kling–Gupta efficiencies on a worldwide large sample of watersheds

We introduce a new diagnosis tool that is well suited to analyzing simulation results over large samples of watersheds. It consists modification the classical Taylor diagram simultaneously visualize several error components (based on bias, standard deviation or squared errors) are commonly used in efficiency criteria (such as Nash–Sutcliffe (NSE) Kling–Gupta (KGE)) evaluate hydrological model performance. propose methodological framework explicitly links graphical and numerical evaluation approaches, show how they can be usefully combined visually interpret experiments conducted datasets. The approach illustrated using obtained by testing two rainfall-runoff models sample 2050 watersheds from 8 countries calibrated with alternative objective functions (NSE KGE). assessment clearly highlights well-documented problems related use NSE for calibration models, which arise due interactions between ratio simulated observed deviations correlation coefficient. also illustrate negative impacts mathematical transformations (square root) applied streamflow when employing KGE metrics calibration.