Function precipitation_rainfall_erosivity()
calculates a multi-year
average of monthly rainfall erosivity using the MedREM model proposed by
Diodato and Bellochi (2010) for the Mediterranean area (see also Guerra et
al. 2016).
Usage
precipitation_rainfall_erosivity(
meteo_data,
longitude,
scale = c("month", "year"),
average = TRUE
)
Arguments
- meteo_data
A meteo tibble as with the dates and meteorological variables as returned by
interpolate_data
in the "interpolated_data" column.- longitude
Longitude in degrees.
- scale
Character, either 'month' or 'year'. Default to 'month'
- average
Boolean flag to calculate multi-year averages before applying MedREM's formula.
Value
A vector of values for each month (in MJ·mm·ha-1·h-1·month-1) or each year (in MJ·mm·ha-1·h-1·yr-1), depending on the scale
Details
MedREM model is: Rm = b0·P·sqrt(d)·(alpha + b1*longitude), where P is accumulated precipitation and d is maximum daily precipitation. Parameters used for the MedREM model are b0 = 0.117, b1 = -0.015, alpha = 2. Note that there is a mistake in Guerra et al. (2016) regarding parameters b1 and a.
References
Diodato, N., Bellocchi, G., 2010. MedREM, a rainfall erosivity model for the Mediterranean region. J. Hydrol. 387, 119–127, doi:10.1016/j.jhydrol.2010.04.003.
Guerra CA, Maes J, Geijzendorffer I, Metzger MJ (2016) An assessment of soil erosion prevention by vegetation in Mediterranean Europe: Current trends of ecosystem service provision. Ecol Indic 60:213–222. doi: 10.1016/j.ecolind.2015.06.043.
Examples
# \donttest{
interpolated_example <-
interpolate_data(points_to_interpolate_example, meteoland_interpolator_example)
#> ℹ Starting interpolation...
#> ℹ Temperature interpolation is needed also...
#> • Interpolating temperature...
#> ℹ Precipitation interpolation is needed also...
#> • Interpolating precipitation...
#> ℹ Relative humidity interpolation is needed also...
#> • Interpolating relative humidity...
#> ℹ Radiation calculation is needed also...
#> • Calculating radiation...
#> ℹ Wind interpolation is needed also...
#> • Interpolating wind...
#> • Calculating PET...
#> ✔ Interpolation done...
precipitation_rainfall_erosivity(
meteo_data = interpolated_example$interpolated_data[[1]],
longitude = 2.32,
scale = "month",
average = TRUE
)
#> 4
#> 48.02902
# }