Author Topic: A rational performance criterion for hydrological model  (Read 216 times)

Pankaj Dey

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  • Institute : Indian Institute of Science
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A rational performance criterion for hydrological model
« on: November 22, 2020, 12:51:16 AM »
Performance criteria are essential for hydrological model identification or its parameters estimation. The Kling-Gupta efficiency (KGE), which combines the three components of Nash-Sutcliffe efficiency (NSE) of model errors (i.e. correlation, bias, ratio of variances or coefficients of variation) in a more balanced way, has been widely used for calibration and evaluation hydrological models in recent years. However, the KGE does not take a reference forecasts or simulation into account and still underestimates of variability of flow time series when optimizing its value for hydrological model. In this study, we propose another performance criterion as an efficiency measure through reformulating the previous three components of NSE. Moreover, the distribution function of the new criterion was also derived to analyze uncertainties of the new criterion, which is originated from the distinction between the theoretical or population statistic and its corresponding sampling properties. The proposed criterion was tested by calibrating the “abcd” and XAJ hourly hydrological models at monthly and hourly time scales data for two different case study basins. Evaluation of the results of the case study clearly demonstrates the overall better or comparable model performances from the proposed criterion. The analysis of the uncertainties of the new criterion based on its distribution probability function suggests a rational approach to distinguish between the probabilistic properties and behavior of the theoretical statistics and the rather different sampling properties of estimators of those statistics when computed from data.