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pbiasfdc

Percent Bias in the Slope of the Midsegment of the Flow Duration Curve


Description

Percent Bias in the slope of the midsegment of the flow duration curve (FDC) [%]. It is related to the vertical soil moisture redistribution.

Usage

pbiasfdc(sim, obs, ...)

## Default S3 method:
pbiasfdc(sim, obs, lQ.thr=0.7, hQ.thr=0.2, na.rm=TRUE, 
       plot=TRUE, verbose=FALSE, ...)

## S3 method for class 'data.frame'
pbiasfdc(sim, obs, lQ.thr=0.7, hQ.thr=0.2, na.rm=TRUE, 
       plot=TRUE, verbose=FALSE, ...)

## S3 method for class 'matrix'
pbiasfdc(sim, obs, lQ.thr=0.7, hQ.thr=0.2, na.rm=TRUE, 
       plot=TRUE, verbose=FALSE, ...)
       
## S3 method for class 'zoo'
pbiasfdc(sim, obs, lQ.thr=0.7, hQ.thr=0.2, na.rm=TRUE, 
       plot=TRUE, verbose=FALSE, ...)

Arguments

sim

numeric, zoo, matrix or data.frame with simulated values

obs

numeric, zoo, matrix or data.frame with observed values

lQ.thr

numeric, used to classify low flows. All the streamflows with a probability of exceedence larger or equal to lQ.thr are classified as low flows

hQ.thr

numeric, used to classify high flows. All the streamflows with a probability of exceedence larger or equal to hQ.thr are classified as high flows

na.rm

a logical value indicating whether 'NA' values should be stripped before the computation proceeds.

plot

a logical value indicating if the flow duration curves corresponding to obs and sim have to be plotted or not.

verbose

logical; if TRUE, progress messages are printed

...

further arguments passed to the fdc function of the hydroTSM package or from other methods.

Value

Percent Bias in the slope of the midsegment of the flow duration curve, between sim and obs.

If sim and obs are matrixes, the returned value is a vector, with the Percent Bias in the slope of the midsegment of the flow duration curve, between each column of sim and obs.

Note

The result is given in percentage (%).

It requires the hydroTSM package.

Author(s)

Mauricio Zambrano Bigiarini <mzb.devel@gmail.com>

References

Yilmaz, K. K., H. V. Gupta, and T. Wagener (2008), A process-based diagnostic approach to model evaluation: Application to the NWS distributed hydrologic model, Water Resour. Res., 44, W09417, doi:10.1029/2007WR006716

Yilmaz, K. K., H. V. Gupta, and T. Wagener (2008), A process-based diagnostic approach to model evaluation: Application to the NWS distributed hydrologic model, Water Resour. Res., 44, W09417, doi:10.1029/2007WR006716

See Also

Examples

## Not run: 
sim <- 1:10
obs <- 1:10
pbiasfdc(sim, obs)

sim <- 2:11
obs <- 1:10
pbiasfdc(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 relative index of agreement for the "best" (unattainable) case
pbiasfdc(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 relative index of agreement
pbiasfdc(sim=sim, obs=obs, col=c("black", "blue"))

## End(Not run)

hydroGOF

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

v0.4-0
GPL (>= 2)
Authors
Mauricio Zambrano-Bigiarini [aut, cre, cph] (<https://orcid.org/0000-0002-9536-643X>)
Initial release

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