ggof: Graphical Goodness of Fit

Description

Graphical comparison between two vectors (numeric, ts or zoo), with several numerical goodness of fit printed as a legend. Missing values in observed and/or simulated values can removed before the computations.

Usage

ggof(sim, obs, na.rm = TRUE, dates, date.fmt = "%Y-%m-%d", 
     pt.style = "ts", ftype = "o",  FUN, 
     gof.leg = TRUE,  digits=2, 
     legend=c("Sim", "Obs"), leg.cex=1,
     tick.tstep = "months", lab.tstep = "years", lab.fmt,
     cal.ini=NA, val.ini=NA,
     main, xlab = "Time", ylab=c("Q, [m3/s]"),  
     col = c("blue", "black"), 
     cex = c(0.5, 0.5), cex.axis=1.2, cex.lab=1.2,
     lwd = c(1, 1), lty = c(1, 3), pch = c(1, 9), ...)

Arguments

sim

numeric or zoo object with with simulated values

obs

numeric or zoo object 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 ar

dates

character, factor or Date object indicating how to obtain the dates for the corresponding values in the sim and obs time series If dates is a character or factor, it is converted into Date class, using the date form

date.fmt

OPTIONAL. character indicating the format in which the dates are stored in dates, cal.ini and val.ini. See format in as.Date. Default value is %Y-%

pt.style

Character indicating if the 2 ts have to be plotted as lines or bars. When ftype is NOT o, it only applies for the annual values. Valid values are: -) ts : (default) each ts is plotted as a lines along the 'x' axis -)

ftype

Character indicating how many plots are desired by the user. Valid values are: -) o : only the original sim and obs time series are plotted -) dm : it assumes that sim and obs ar

FUN

OPTIONAL, ONLY required when ftype is in c('dm', 'ma', 'dma'). Function that have to be applied for transforming from daily to monthly or annual time step (e.g., for precipitation FUN MUST be sum, for temperature and

gof.leg

logical, indicating if several numerical goodness of fit have to be computed between sim and obs, and plotted as a legend on the graph. If leg.gof=TRUE, then x is considered as observed and y

digits

OPTIONAL, only used when leg.gof=TRUE. Numeric, representing the decimal places used for rounding the goodness-of-fit indexes.

legend

character of length 2 to appear in the legend.

leg.cex

OPTIONAL. ONLY used when leg.gof=TRUE. Character expansion factor for drawing the legend, *relative* to current 'par("cex")'. Used for text, and provides the default for 'pt.cex' and 'title.cex'. Default value = 1

tick.tstep

character, indicating the time step that have to be used for putting the ticks on the time axis. Valid values are: -) days, -) months, -) years

lab.tstep

character indicating the time step that have to be used for putting the labels on the time axis. Valid values are: -) days, -) months, -) years

lab.fmt

Character indicating with the format to be used for the label of the axis. See format in as.Date. If not specified, it will try "%Y-%m-%d" when lab.tstep=="days",

cal.ini

OPTIONAL. Character, indicating the date in which the calibration period started. ONLY used for drawing a vertical red line at this date.

val.ini

OPTIONAL. Character, the date in which the validation period started. ONLY used for drawing a vertical red line at this date.

main

character representing the main title of the plot.

xlab

label for the 'x' axis.

ylab

label for the 'y' axis.

col

character, representing the colors of sim and obs

cex

numeric, representing the values controlling the size of text and symbols of 'x' and 'y' with respect to the default

cex.axis

numeric, representing the magnification to be used for the axis annotation relative to 'cex'. See par.

cex.lab

numeric, representing the magnification to be used for x and y labels relative to the current setting of 'cex'. See par.

lwd

vector with the line width of sim and obs

lty

numeric with the line type of sim and obs

pch

numeric with the type of symbol for x and y. (e.g., 1: white circle; 9: white rhombus with a cross inside)

...

further arguments passed to or from other methods.

Value

meMean Error
maeMean Absolute Error
rmseRoot Mean Square Error
nrmseNormalized Root Mean Square Error
PBIASPercent Bias
pbiasfdcPBIAS in the slope of the midsegment of the Flow Duration Curve
RSRRatio of RMSE to the Standard Deviation of the Observations, RSR = rms / sd(obs). ( 0 <= rsr="" <="+Inf" )<="" description="">
rSDRatio of Standard Deviations, rSD = sd(sim) / sd(obs)
NSeffNash-Sutcliffe Efficiency ( -Inf <= nseff="" <="1" )<="" description="">
mNSeffModified Nash-Sutcliffe Efficiency
rNSeffRelative Nash-Sutcliffe Efficiency
dIndex of Agreement ( 0 <= d="" <="1" )<="" description="">
mdModified Index of Agreement
rdRelative Index of Agreement
cpPersistence Index ( 0 <= pi="" <="1" )<="" description="">
rPearson Correlation coefficient ( -1 <= r="" <="1" )<="" description="">
r.SpearmanSpearman Correlation coefficient ( -1 <= r.spearman="" <="1" )<="" description="">
R2Coefficient of Determination ( 0 <= r2="" <="1" ).="" gives="" the="" proportion="" of="" variance="" one="" variable="" that="" is="" predictable="" from="" other="" variable<="" description="">
bR2R2 multiplied by the coefficient of the regression line between sim and obs ( 0 <= br2="" <="1" )<="" description="">
KGEKling-Gupta efficiency between sim and obs ( 0 <= kge="" <="1" )<="" description="">

Details

Plots observed and simulated values in the same graph.

If gof.leg=TRUE, it computes the numerical values of: 'me', 'mae', 'rms', 'nrms', 'PBIAS', 'RSR, 'rSD', 'NSeff', 'mNSeff', 'rNSeff', 'd', 'md, 'rd', 'cp', 'r', 'r.Spearman', 'R2', 'bR2'

References

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 Krause P., Boyle D.P., and B"{a}se F., Comparison of different efficiency criteria for hydrological model assessment, Advances in Geosciences 5 (2005), pp. 89--97 Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D., Veith, T.L. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations Transactions of the ASABE. 50(3):885-900 Boyle, D. P., H. V. Gupta, and S. Sorooshian (2000), Toward Improved Calibration of Hydrologic Models: Combining the Strengths of Manual and Automatic Methods, Water Resour. Res., 36(12), 3663--3674 Kitanidis, P. K., and R. L. Bras (1980), Real-Time Forecasting With a Conceptual Hydrologic Model 2. Applications and Results, Water Resour. Res., 16(6), 1034--1044 J.E. Nash and J.V. Sutcliffe, River flow forecasting through conceptual models. Part 1: a discussion of principles, J. Hydrol. 10 (1970), pp. 282--290 Yapo P. O., Gupta H. V., Sorooshian S., 1996. Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration data. Journal of Hydrology. v181 i1-4. 23--48 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

Examples

Run this code

obs <- 1:10
sim <- 2:11

ggof(sim, obs)

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

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

# Getting the numeric goodness of fit for the "best" (unattainable) case
gof(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)

# Getting the new numeric goodness of fit 
gof(sim=sim, obs=obs)

# Getting the graphical representation of 'obs' and 'sim' along with the numeric 
# goodness of fit for the daily and monthly time series 
require(hydroTSM)
ggof(sim=sim, obs=obs, ftype="dm", FUN=mean)

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