simulations | R Documentation |
The dataset is generated with the package own routines and represent 5 series of 18 years of runoff
data("simulations")
A list of three elements, containing (i) a data frame with 6570 observations of the following variables
YYYY
a numeric vector, year
MM
a numeric vector, month
DD
a numeric vector, day
timestamp
POSIXct
vector of the daily runoff
deseasonalized
deseasonalized time series
Qobs
observed runoff
r1
,...,r5
5 simulated runoff series
(ii) a data frame with the daily fitted kappa parameters and (iii) p-values of the daily ks.test
.
The data is included to illustrate the validation and visualization routines in demo("PRSim-validate")
.
The data has been generated with
set.seed(14); prsim( runoff[ runoff$YYYY>1999,], number_sim=5,
KStest=TRUE)
(default values for all other arguments).
Brunner, M. I., A. Bárdossy, and R. Furrer (2019). Technical note: Stochastic simulation of streamflow time series using phase randomization. Hydrology and Earth System Sciences, 23, 3175-3187, https://doi.org/10.5194/hess-23-3175-2019.
data(simulations)
names(simulations)
sim <- simulations$simulation
dim(sim)
sim$day_id <- rep(seq(1:365), times=length(unique(sim$YYYY)))
mean_obs <- aggregate(sim$Qobs, by=list(sim$day_id), FUN=mean, simplify=FALSE)
plot(unlist(mean_obs[,2]),lty=1,lwd=1,col="black", ylab="Discharge [m3/s]",
xlab="Time [d]", main="Mean hydrographs", ylim=c(0,22), type="l")
for(r in 7:(length(names(sim))-1)){
mean_hydrograph <- aggregate(sim[,r], by=list(sim$day_id), FUN=mean, simplify=FALSE)
lines(mean_hydrograph, lty=1, lwd=1, col="gray")
}
lines( mean_obs, lty=1, lwd=1, col="black")
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