Evapotranspiration (version 1.10)

ET.JensenHaise: Jensen-Haise Formulation

Description

Implementing the Jensen-Haise formulation for estimating potential evapotranspiration.

Usage

# S3 method for JensenHaise
ET(data, constants, ts="daily", solar="sunshine hours", …)

Arguments

data

A list of data which contains the following items (climate variables) required by Jensen-Haise formulation: Tmax, Tmin, Rs or n or Cd

constants

A list named constants consists of constants required for the calculation of Jensen-Haise 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, lat_rad - latitude in radians, Gsc - solar constant = 0.0820 MJ.m^-2.min^-1.

The following constants are also required when argument solar has value of sunshine hours: as - fraction of extraterrestrial radiation reaching earth on sunless days, bs - difference between fracion of extraterrestrial radiation reaching full-sun days and that on sunless days.

ts

Must be either daily, monthly or annual, which indicates the disired time step that the output ET estimates should be on. Default is daily.

solar

Must be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evapotranspiration; sunshine hours indicates that solar radiation is to be calculated using the real data of sunshine hours; cloud sunshine hours is to be estimated from cloud data; monthly precipitation indicates that solar radiation is to be calculated directly from monthly precipitation. Default is sunshine hours.

Dummy for generic function, no need to define.

Value

The function prints a calculation summary to the screen containing the following elements: - ET model name and ET quantity estimated - Option for calculating solar radiation (i.e. the value of argument solar) - Time step of the output ET estimates (i.e. the value of argument ts) - Units of the output ET estimates - Time duration of the ET estimation - Number of ET estimates obtained in the entire time-series - Basic statistics of the estimated ET time-series including mean, max and min values.

The function also generates a list containing the following components, which is saved into a csv file named as ET_JensenHaise.csv in the working directory:

ET.Daily

Daily aggregated estimations of Jensen-Haise potential evapotranspiration.

ET.Monthly

Monthly aggregated estimations of Jensen-Haise potential evapotranspiration.

ET.Annual

Annually aggregated estimations of Jensen-Haise potential evapotranspiration.

ET.MonthlyAve

Monthly averaged estimations of daily Jensen-Haise potential evapotranspiration.

ET.AnnualAve

Annually averaged estimations of daily Jensen-Haise potential evapotranspiration.

ET_formulation

Name of the formulation used which equals to Jensen-Haise.

ET_type

Type of the estimation obtained which is Potential Evapotranspiration.

Details

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

References

Jensen, M.E.Haise, H.R. 1963, Estimating evapotranspiration from solar radiation. Proceedings of the American Society of Civil Engineers, Journal of the Irrigation and Drainage Division, vol. 89, pp. 15-41.

Prudhomme, C.Williamson, J. 2013, Derivation of RCM-driven potential evapotranspiration for hydrological climate change impact analysis in Great Britain: a comparison of methods and associated uncertainty in future projections. Hydrol. Earth Syst. Sci., vol. 17, no. 4, pp. 1365-1377.

Xu, C.Y.Singh, V.P. 2000, Evaluation and generalization of radiation-based methods for calculating evaporation., Hydrological Processes, vol. 14, no. 2, pp. 339-349.

See Also

ET,data,defaultconstants,constants

Examples

Run this code
# NOT RUN {
# Use processed existing data set and constants from kent Town, Adelaide
data("processeddata")
data("constants")

# Call ET.JensenHaise under the generic function ET
results <- ET.JensenHaise(data, constants, ts="daily", solar="sunshine hours")
# }

Run the code above in your browser using DataCamp Workspace