Evapotranspiration (version 1.7)

ET.McGuinnessBordne: McGuinness-Bordne Formulation

Description

Implementing the McGuinness-Bordne formulation for estimating potential evapotranspiration.

Usage

## S3 method for class 'McGuinnessBordne':
ET(data, constants, \dots)

Arguments

data

A list of data in class "McGuinnessBordne" which contains the following items (climate variables) required by McGuinness-Bordne formulation: "Tmax", "Tmin"

constants

A list named "constants" consists of constants required for the calculation of Penman formulation which must contain the following items: "Elev" - ground elevation above mean sea level in m, "lambda" - latent heat of vaporisation = 2.45 MJ.kg^-1,

...

Dummy for generic function, no need to define.

Value

• This function returns a object of class McGuinnessBordne. Such objects are list with components:
• ET.Daily
  A zoo object containing daily aggregated estimations of McGuinness-Bordne potential evapotranspiration.
• ET.Monthly
  A zoo object containing monthly aggregated estimations of McGuinness-Bordne potential evapotranspiration.
• ET.Annual
  A zoo object containing annually aggregated estimations of McGuinness-Bordne potential evapotranspiration.
• ET.MonthlyAve
  A zoo object containing monthly averaged estimations of daily McGuinness-Bordne potential evapotranspiration.
• ET.AnnualAve
  A zoo object containing annually averaged estimations of daily McGuinness-Bordne potential evapotranspiration.
• ET_formulation
  A character string containing the name of the formulation used which equals to "McGuinness-Bordne".
• ET_type
  A character string containing the type of the estimation obtained which is "Potential Evapotranspiration".

Details

This formulation provides a single calculation method with no alternatives available.

References

XU, C. Y. & SINGH, V. P. 2000. Evaluation and generalization of radiation-based methods for calculating evaporation. Hydrological Processes, 14, 339-349.

Examples

# Use processed existing data set from kent Town, Adelaide
data("processeddata")
data("constants")

# Set data class to be "McGuinnessBordne" to call function
funname <- "McGuinnessBordne" 
class(data) <- funname 

# Call generic function ET(data, ...) with class "McGuinnessBordne"
results <- ET(data, constants)