Kshipra Sub Basin - Asian Development Bank
Kshipra Sub Basin - Asian Development Bank
Kshipra Sub Basin - Asian Development Bank
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Support to the National Water Mission NAPCC<br />
Appendix 3 <strong>Kshipra</strong> <strong>Sub</strong> <strong>Basin</strong><br />
Figure 51: <strong>Kshipra</strong> <strong>Basin</strong> soils<br />
4. SWAT Model Calibration and Performance<br />
190. Model Evaluation Statistics (Dimensionless): Statistical parameters, namely regression<br />
coefficients (R 2 ) and Nash Sutcliffe efficiency coefficient (NSE) were used to assess the model<br />
efficiency on monthly SWAT hydrologic streamflow predictions. The Nash-Sutcliffe efficiency (NSE) is<br />
a normalized statistic that determines the relative magnitude of the residual variance (―noise‖)<br />
compared to the measured data variance (―information‖) (Nash and Sutcliffe, 1970 48 ). NSE indicates<br />
how well the plot of observed versus simulated data fits the 1:1 line. NSE is computed as:<br />
obs th sim th<br />
where Yi is the i observation for the constituent being evaluated, Yi is the i simulated value for<br />
the constituent being evaluated, Y mean is the mean of observed data for the constituent being<br />
evaluated, and n is the total number of observations. NSE ranges between −∞ and 1.0 (1 inclusive),<br />
with NSE = 1 being the optimal value. Values between 0.0 and 1.0 are generally viewed as acceptable<br />
48 Nash, J. E., and J. V. Sutcliffe. 1970. River flow forecasting through conceptual models: Part 1. A discussion of<br />
principles. J. Hydrology 10(3): 282-290<br />
86
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