Fitting of Hydrologic Models: A Close Look at the Nash–Sutcliffe Index

By S. Jain, K. Sudheer. 2008

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Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling (2009, background): “…(McCuen and Snyder, 1975; Martinec and Rango, 1989; Legates and McCabe, 1999; Krause et al., 2005; McCuen et al., 2006; Schaefli and Gupta, 2007; Jain and Sudheer, 2008) and several authors have proposed modifications – e.g. Mathevet et al. (2006) proposed a bounded version of NSE and Criss and…”
Improved Estimators of Model Performance Efficiency for Skewed Hydrologic Data (2020, background): “Over the years, numerous authors have evaluated the behavior of NSE (see, e.g., Bardsley, 2013; Gupta & Kling, 2011; Gupta et al., 2009; Jain & Sudheer, 2008; Legates & McCabe, 1999; Liu et al., 2018; Martinec & Rango, 1989; McCuen et al., 2006; Pool et al., 2018; Schaefli & Gupta, 2007, and many…”
Wavelet Bootstrap Multiple Linear Regression Based Hybrid Modeling for Daily River Discharge Forecasting (2014, background): “Jain and Sudheer (2008) also discussed this issue in detail and suggested not to rely on E alone, but that it should be used with some additional performance indices.”
Series distance – an intuitive metric to quantify hydrograph similarity in terms of occurrence, amplitude and timing of hydrological events (2011, unknown): “Along the same lines, Schaefli and Gupta (2007) as well as Jain and Sudheer (2008) found that NSE is a poor metric if the test series show strong seasonality.”