floodcast_tub: Forecasting Coastal Flooding with a "Bathtub" Model
In ccb60/SLRSIM: Tools to Analyse Sea Level Rise

Description Usage Arguments Details See Also

Calculate estimated future frequency of flooding by adding a fixed "sea level rise offset" to past water levels, and counting up the number of days with at least one observation above a specified flood elevation.

floodcast_tub(.data, .dt, .wl, .slr, .fldlvl, .wl_update = 0)

floodcast_tub_lookup(
  .station,
  .slr,
  .fldlvl,
  .datum = c("MSL", "MTL", "MHW", "MHHW", "MLLW", "MLW", "NAVD", "STND"),
  .wl_update = 0,
  .use_epoch = TRUE,
  .start_yr = NULL,
  .end_yr = NULL,
  .units = c("metric", "english"),
  .timefmt = c("lst", "gmt")
)

`.data`	A source data frame. can be NULL if .dt and .wl are defined in the enclosing environment.
`.dt`	Dates and times. A data column in .data or a data vector defined in the enclosing environment that contains date-time information. Must inherit from POSIXct.
`.wl`	Water level. A numerical data column in .data or a numerical vector defined in the enclosing environment.
`.slr`	Sea level rise estimate. A numeric vector containing one or more values. What sea level rise scenarios should the analysis be based on? Selection of appropriate sea level rise estimates should be based on your time horizon and risk tolerance. NOAA forecasts of SLR for 2100 vary from 0.3 (almost certain) to 2.5 (highly unlikely) meters.
`.fldlvl`	Flood level. A single numeric value, that defines what constitutes a flood event. Must be specified in `floodcast_tub()`. In `floodcast_tub_lookup()`, will default to the "Highest Astronomical Tide" elevation, or HAT for the selected tide station.
`.wl_update`	A single numeric value that adjusts for any changes in sea level from the tidal epoch to the present day.
`.station`	What NOAA water level station are you interested in?
`.datum`	Character string, from a limited list of options. Specifies the vertical datum used to express the flood elevation. To ensure consistency, data will be downloaded, and analysis conducted in that datum.
`.use_epoch`	Boolean. Should analysis be based on the tidal epoch? Note that behavior may change on how this works with is this is set to "TRUE" for a
`.start_yr`	If you don't base the analysis on the period of the epoch, what is the first year to use for the reference period?
`.end_yr`	If you don't base the analysis on the period of the epoch, what is the last year to use for the reference period?
`.units`	Provide results in English (feet) or metric (meters) units?

floodcast_tub() conducts the analysis based on data provided by the user.

floodcast_tub_lookup() downloads data for a station of interest and then conducts the analysis based on the downloaded data.

The method follows an idea we were introduced to via the work of Peter Slovinsky, of the Maine Geological Survey. MGS has estimated future flooding risk at a variety of locations around Maine by adding a fixed SLR value to the historical record, and showing how frequent flooding would have been if base sea levels had been that much higher in the past. This provides a ready, and readily understood, estimate of impact of SLR on frequency of flooding.

Our method, while conceptually identical, is slightly different, as we count up the number of days with predicted flooding, rather than hours with flooding. The "days" are calendar days, defined on the same timezone as the source datetime parameter, .dt.)

There are, of course, many other metric we could use to evaluate frequency of future flooding, such as the number of flood events (continuous periods above flood elevation), or the number of tides with flooding. We took an approach that focuses on days with flooding in part for computational convenience, and in part because it corresponds well to how communities and individuals are likely to experience "nuisance" tidal flooding.

floodcast_tub_lookup() is a convenience function best suited for "quick and dirty" analysis. It retrieves large amounts of data from the NOAA API (making it relatively slow) and then runs the calculation of future flood frequencies on that data before tosses all of the data away. It is generally going to be far better to download the data yourself, using retrieve_data(), and call floodcast_tub(). That way you have the data to look over independently, and if you want to calculate additional flood forecasts with different flood levels of sea level rise scenarios, you won't be waiting to download the data again.

floodcast_arima

Other Flood frequency analysis functions: .sim_once(), floodfreq(), floodgraph(), floodmean()

ccb60/SLRSIM documentation built on Jan. 21, 2022, 1:31 a.m.