fld.depth {VulnToolkit} | R Documentation |
Calculates flooding depth above an elevation of interest
Description
Flooding depths are calculated from water level or tide data. If water levels are used, the median (or other percentile) flooding depth is calculated based on all observations of flooded conditions (when water depth is equal to or greater than the elevation of interest). If a high/low tide dataset is used, flooding depth percentiles will be just for high tides that flood the selected elevation. The latter case includes only peak high water levels, and so will yield greater flooding depths for the same elevation.
Using data from a nearby, user-defined NOAA station, bias is estimated by comparing the relationship between flooding duration and elevation in datasets covering two time periods: (1) the time periodof water level logger deployment, and (2) the reference time period (some number of years).
Usage
fld.depth(level, elevation, percentile = 0.5)
Arguments
level |
a numeric vector of water levels or tide data |
elevation |
elevation(s) of interest (marsh platform,
MHW). A vector of elevations is accepted. Elevation should
be in the same vertical datum as |
percentile |
the percentile(s) to calculate (median flooding depth is calculated by default). A vector of percentiles is accepted. |
Value
if 'percentile' argument is of length one, the value(s) returned are the corresponding flooding percentiles for the elevation(s) of interest. To ensure clarity when more than one 'percentiles' are sought, in those cases a dataframe is output to report elevations and flooding depths.
See Also
Examples
data(NL_6min_2013)
MHW <- 0.9117 # New London MHW in 2013: 0.9117 m relative to MLLW
fld.depth(level = NL_6min_2013[, 2], elevation = MHW,
percentile = 0.5)
fld.depth(level = NL_6min_2013[, 2], elevation = MHW,
percentile = c(0.25, 0.5, 0.75))
fld.depth(level = NL_6min_2013[, 2], elevation = c(0, MHW, 1.5),
percentile = 0.75)
fld.depth(level = NL_6min_2013[, 2], elevation = c(0, MHW, 1.5),
percentile = c(0.25, 0.5, 0.75))