Indicators for evaluation of model performance: irrigation hydraulics applications

Abstract

Several mathematical models have been developed for applications in the hydraulics of irrigation systems and several performance indicators of these models are used and suggested by the literature. Thus, the objective of this work was to investigate the performance of statistical indicators for the evaluation of models in irrigation hydraulics. For this, three case studies which represent typical irrigation hydraulics modeling were used to assess the indicators. A set of indicators were analyzed: a) difference-based: mean absolute error, mean square error, root mean square error, scaled root mean square error, and percent mean absolute error; b) efficiency-based: Nash-Sutcliffe and Legates-McCabe; c) correlation coefficient ( ); d) coefficient of determination ( ); e) index of agreement index ( ); f) Camargo and Sentelhas index ( ); and g) graphical methods: regression error characteristic curve based on relative absolute error and 1:1 scatter plot. For the evaluated cases, which are physical phenomena, differentiable indicators are similar measures and it is appropriate to report either or both indices. The assessment of models must also be supported by graphical analysis, which shows the real scenario of errors in the model evaluation processes. Efficiency-based indicators, , , , and  are not recommended and should be avoided in modeling of irrigation hydraulics.