rfs: Rhine flood seasonality
In ERottler/rfs: Rhine Flood Seasonality Analysis

Description Author(s) Examples

Rhine flood seasonality analysis. PhD project by Berry Boessenkool. The main functions are introduced in the examples below.

Berry Boessenkool, berry-b@gmx.de, 2017

# qdoyCompute aggregates streamflow values per day of the year (doy)
# The first examples require the original data to be in seasFolder.
# Unfortunately, we are not allowed to make it publicly available.
# Please contact berry-b@gmx.de if you need the raw data. 

load(seasFolder("data/dismeta.Rdata"))
dd <- selectDates(1990,2010, df=dis)[,c("date","Koeln")]
qdoy <- qdoyCompute("date", "Koeln", data=dd, shift=117) # 2 secs
str(qdoy)

# Visualize the result:
qdoyVis(qdoy, shift=117)
qdoyVis(qdoy, main="Cologne 1990-2010", RPs=50, cols=4, ylim=c(2e3,10e3), shift=117, lab=0)
qdoyVis(qdoy, dist="empirical", RPs=50, cols=3, add=TRUE, lab=0)
legend("topright", c("empirical", "gev"), col=3:4, lwd=3)

# qdoyPeriods computes the aggregates for separate periods. 
# This procedure was applied to 55 stations at large streams and rivers.
# (see source code rfs-package.R)
# The result is stored in this package, see   ?seas

# Elements from that list can be visualized as follows:
qdoyVisPeriods("Rekingen")

# You can visualize your own data split up in periods with
qdoy <- qdoyPeriods("Koeln") # 3x3 seconds
str(qdoy)
qdoyVisPeriods("Koeln", list(Koeln=qdoy))

# By default, the package dataset "seas" will be used:
qdoyVisPeriods("Mainz")
qdoyVisPeriods("Mainz", sd=3) # for smoothing

qdoyVisPeriods("Oberriet_Blatten") # can handle NAs