Evaluating the use of "goodness-of-fit" measures in hydrologic and hydroclimatic model validation

Correlation and correlation-based measures (e.g., the coefficient of determ ination) have been widely used to evaluate the "goodness-of-fit" of hydrolo gic and hydroclimatic models. These measures are oversensitive to extreme v alues (outliers) and are insensitive to additive and proportional differenc es between model predictions and observations. Because of these limitations , correlation-based measures can indicate that a model is a good predictor, even when it is not. In this paper, useful alternative goodness-of-fit or relative error measures (including the coefficient of efficiency and the in dex of agreement) that overcome many of the limitations of correlation-base d measures are discussed. Modifications to these statistics to aid in inter pretation are presented. It is concluded that correlation and correlation-b ased measures should not be used to assess the goodness-of-fit of a hydrolo gic or hydroclimatic model and that additional evaluation measures (such as summary statistics and absolute error measures) should supplement model ev aluation tools.