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It is common for hydrological time series to contain missing values and to have differing start and end dates. Generally, Source calculates bivariate statistics using only data from those time steps for which there are complete data pairs. *TODO: where is this not true? Bivariate statis in charting??
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The NSE is a normalised statistic that measures the relative magnitude of the model error variance compared to the measured data variance (Nash and Sutcliffe, 1970). It is commonly used to evaluate the fit of modelled to observed streamflow data, and the definition and discussion below assume that it is being applied in this context. However, the NSE can be used to evaluate the fit between time series of any type.
The NSE defined as:
| Equation 1 |
|---|
where
Qobs,i is the observed flow for time step i
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Sensitive to extreme values and insensitive to small values. For example, the NSE is generally not suitable for evaluating the fit to low flows as the value will be dominated by the fit to high flows
Links
NSE of Log Data
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Definition
| Equation 2 |
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where
and c is a small constant equal to the maximum of 1 ML and the 10th percentile of the observed flow.
Interpretation
Links
sNSE-Bias penalty (Nash-Sutcliffe coefficient of efficiency with penalised bias solutions), daily and monthly variants
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