Compute 1d water level data through linear interpolation with neighboring gauging stations according to the INFORM 3-method Flood2 (Flut2)

This function computes a 1d water level according to the INFORM flood duration method Flood2 (Flut2) and stores it as column w of an S4 object of type WaterLevelDataFrame. Flood2 is designed to enable water level computation between gauging stations along waterways without reference water levels, provided for example by FLYS3. The function uses neighboring gauging stations for linear interpolation of gauging station water levels along the selected river stretch. Here it is provided mainly for historical reasons and more advanced functions like waterLevel or waterLevelPegelonline should be used.

Usage

waterLevelFlood2(wldf)

Arguments

wldf

an object of class WaterLevelDataFrame.

Value

An object of class WaterLevelDataFrame.

Details

This function computes a water level through simple linear interpolation of water levels at neighboring gauging stations. Historically it has been designed for rivers without 1d reference water levels provided by FLYS3 for df.flys.

References

Rosenzweig S, Giebel H, Schleuter M (2011). “Ökologische Modellierungen für die Wasser- und Schifffahrtsverwaltung – Das integrierte Flussauenmodell INFORM in seiner neuesten Fassung (Version 3). Bundesanstalt für Gewässerkunde, Koblenz, Germany.” doi:10.5675/bfg-1667 .

Examples

wldf <- WaterLevelDataFrame(river   = "Elbe",
                            time    = as.POSIXct("2016-12-21"),
                            station = seq(257, 262, 0.1))
wldf1 <- waterLevelFlood2(wldf)
wldf1
#>    station station_int     w
#> 1    257.0      257000 55.35
#> 2    257.1      257100 55.33
#> 3    257.2      257200 55.31
#> 4    257.3      257300 55.30
#> 5    257.4      257400 55.28
#> 6    257.5      257500 55.26
#> 7    257.6      257600 55.24
#> 8    257.7      257700 55.22
#> 9    257.8      257800 55.20
#> 10   257.9      257900 55.19
#> 11   258.0      258000 55.17
#> 12   258.1      258100 55.15
#> 13   258.2      258200 55.13
#> 14   258.3      258300 55.12
#> 15   258.4      258400 55.10
#> 16   258.5      258500 55.08
#> 17   258.6      258600 55.06
#> 18   258.7      258700 55.04
#> 19   258.8      258800 55.03
#> 20   258.9      258900 55.01
#> 21   259.0      259000 54.99
#> 22   259.1      259100 54.97
#> 23   259.2      259200 54.95
#> 24   259.3      259300 54.94
#> 25   259.4      259400 54.92
#> 26   259.5      259500 54.90
#> 27   259.6      259600 54.88
#> 28   259.7      259700 54.87
#> 29   259.8      259800 54.85
#> 30   259.9      259900 54.83
#> 31   260.0      260000 54.81
#> 32   260.1      260100 54.79
#> 33   260.2      260200 54.78
#> 34   260.3      260300 54.76
#> 35   260.4      260400 54.74
#> 36   260.5      260500 54.72
#> 37   260.6      260600 54.71
#> 38   260.7      260700 54.69
#> 39   260.8      260800 54.67
#> 40   260.9      260900 54.65
#> 41   261.0      261000 54.63
#> 42   261.1      261100 54.62
#> 43   261.2      261200 54.60
#> 44   261.3      261300 54.58
#> 45   261.4      261400 54.56
#> 46   261.5      261500 54.54
#> 47   261.6      261600 54.51
#> 48   261.7      261700 54.49
#> 49   261.8      261800 54.47
#> 50   261.9      261900 54.45
#> 51   262.0      262000 54.43