Compute evapotranspiration using the Blaney-Criddle method. A theoretical method used when no measured data on pan evaporation are available locally.
ETo(object, day.one = NULL, span = 150, lat = NULL, Kc = 1, p = NULL)
a numeric vector of geographic coordinates (lonlat) or
an array with two dimensions containing the temperature data;
1st dimension contains the day temperature and 2nd dimension the night
temperature. When lonlat is used, the function makes a call to
nasapower::get_power()
to fetch and concatenate environmental
data from NASA POWER (https://power.larc.nasa.gov/) for the parameters
T2M_MAX (Maximum Temperature at 2 m) and
T2M_MIN (Minimum Temperature at 2 m)
a vector of class Date
for the starting date to
capture the environmental data (YYYY-MM-DD)
an integer or a vector with integers for the duration of the timespan to be captured
a vector for the latitude (in Decimal degrees) used to compute mean daily percentage of annual daytime hours based on the latitude and month. See details
a numeric value for the crop factor for water requirement
optional, a numeric value (from 0 to 1) used if lat is not given, representing the mean daily percentage of annual daytime hours for different latitudes
The evapotranspiration in mm/day
When lat is used, it is combined with the month provided in
day.one to call for the system data daylight
to find
the correct value for p which represents the daily percentage
of daytime hours in the given month and latitude.
Brouwer C. & Heibloem M. (1986). Irrigation water management: Irrigation water needs. Food and Agriculture Organization of The United Nations, Rome, Italy. http://www.fao.org/3/S2022E/s2022e00.htm
Other climatology functions:
GDD()
,
rainfall()
,
temperature()
# NOT RUN {
# Using local sources
data("modis", package = "climatrends")
day <- as.Date("2013-10-28", format = "%Y-%m-%d")
ETo(modis,
day.one = day,
span = 10,
Kc = 0.92)
# }
# NOT RUN {
# Using remote sources
library("nasapower")
# random geographic locations around bbox(11, 12, 55, 58)
set.seed(123)
lonlat <- data.frame(lon = runif(2, 11, 12),
lat = runif(2, 55, 58))
# random dates around 2018-05-15 and 2018-05-20
set.seed(321)
dates <- as.integer(runif(2, 17666, 17670))
dates <- as.Date(dates, origin = "1970-01-01")
# the evapotranspiration in the first 50 days after day.one
ETo(lonlat,
day.one = dates,
span = 50,
lat = lonlat[["lat"]])
# }
# NOT RUN {
# }
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