MERITS OF STATISTICAL CRITERIA FOR THE PERFORMANCE OF HYDROLOGICAL MODELS¹

Abstract

The performance of a hydrological model is usually assessed first by visual inspection of the measured and computed hydrographs. Numerous statistical criteria are available for numerical evaluations of model accuracy in each single year, in a particular season of the year, or in a sequence of years or seasons. In the last case, the problem of computing the overall result has to be considered. If too many criteria are used and the criteria are switched frequently, an assessment of a model's performance becomes difficult for a potential user. Therefore, this paper concentrates on just three criteria and their combined evaluation: The Nash‐Sutcliffe coefficient, which compares the model computed discharge with the average measured discharge; the “coefficient of gain from daily means” in which a uniform average discharge is replaced by daily average discharges; and the volumetric difference between the total measured and computed runoff. The three criteria are combined in a three dimensional representation that allows intercomparisons of model performance in a single diagram.

Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance

“…Additionally, basins with higher streamflow variance and frequent precipitation events have better model performance. Therefore, to give a more standardized picture of model performance across varying hydroclimatologies, the NSE was recomputed using the long-term monthly mean flow instead of mean flow (denoted MNSE hereafter), thus preventing climatological seasonality from inflating the NSE and more accurately ranking basins by the degree to which the model added value over climatology in response to weather events (Garrick et al, 1978;Martinec and Rango, 1989;Schaefli et al, 2005). MNSE in this context is defined for each day of year (DOY) via a 31-day window centered on a given DOY.…”

Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds

“…Model performance was evaluated using the Nash-Sutcliffe coefficient, NS [36] the deviation from measured data, Dv [37], and stream flow hydrographs. The NS (Equation 1) is a measure of model efficiency that compares simulated values to corresponding measured values.…”

Subdividing Large Mountainous Watersheds into Smaller Hydrological Units to Predict Soil Loss and Sediment Yield Using the GeoWEPP Model

“…In respect to model evaluation, observed (O i ) and predicted (P i ) annual sediment values were compared by using the percent deviation (Dv) [24], Nash and Sutcliffe (1970) simulation coefficient (ENS), and the coefficient of determination (R 2 ) [20,23,25]. The deviation of sediment values, Dv, given by the following equation is one criterion for goodness-of-fit: 10 (1988-94, 1996, 1999, and 2000) that had all the monthly measurements done by the SHA in order to make the comparison properly with the predicted values.…”