rNSE: Relative Nash-Sutcliffe efficiency

In hydroGOF: Goodness-of-Fit Functions for Comparison of Simulated and Observed Hydrological Time Series

Description

Relative Nash-Sutcliffe efficiency between sim and obs, with treatment of missing values.

Usage

rNSE(sim, obs, ...)

## Default S3 method:
rNSE(sim, obs, na.rm=TRUE, ...)

## S3 method for class 'data.frame'
rNSE(sim, obs, na.rm=TRUE, ...)

## S3 method for class 'matrix'
rNSE(sim, obs, na.rm=TRUE, ...)

## S3 method for class 'zoo'
rNSE(sim, obs, na.rm=TRUE, ...)

Arguments

sim	numeric, zoo, matrix or data.frame with simulated values
obs	numeric, zoo, matrix or data.frame with observed values
na.rm	a logical value indicating whether 'NA' should be stripped before the computation proceeds. When an 'NA' value is found at the i-th position in obs OR sim, the i-th value of obs AND sim are removed before the computation.
...	further arguments passed to or from other methods.

Details

rNSE = 1 - ( sum( ( (obs - sim)/ obs )^2 ) / sum( abs( (obs - mean(obs)) / mean(obs) )^2 )

Value

Relative Nash-Sutcliffe efficiency between sim and obs.

If sim and obs are matrixes, the returned value is a vector, with the relative Nash-Sutcliffe efficiency between each column of sim and obs.

Note

obs and sim has to have the same length/dimension

The missing values in obs and sim are removed before the computation proceeds, and only those positions with non-missing values in obs and sim are considered in the computation

If some of the observed values are equal to zero (at least one of them), this index can not be computed.

Author(s)

Mauricio Zambrano Bigiarini <[e-mail]>

References

Krause, P., Boyle, D. P., and Base, F.: Comparison of different efficiency criteria for hydrological model assessment, Adv. Geosci., 5, 89-97, 2005

Legates, D. R., and G. J. McCabe Jr. (1999), Evaluating the Use of "Goodness-of-Fit" Measures in Hydrologic and Hydroclimatic Model Validation, Water Resour. Res., 35(1), 233-241.

See Also

NSE, mNSE, gof, ggof

Examples

sim <- 1:10
obs <- 1:10
rNSE(sim, obs)

sim <- 2:11
obs <- 1:10
rNSE(sim, obs)

##################
# Loading daily streamflows of the Ega River (Spain), from 1961 to 1970
data(EgaEnEstellaQts)
obs <- EgaEnEstellaQts

# Generating a simulated daily time series, initially equal to the observed series
sim <- obs 

# Computing the 'rNSE' for the "best" (unattainable) case
rNSE(sim=sim, obs=obs)

# Randomly changing the first 2000 elements of 'sim', by using a normal distribution 
# with mean 10 and standard deviation equal to 1 (default of 'rnorm').
sim[1:2000] <- obs[1:2000] + rnorm(2000, mean=10)

# Computing the new 'rNSE'
rNSE(sim=sim, obs=obs)

hydroGOF documentation built on March 14, 2020, 1:07 a.m.