[SOLVED] 代写 R math statistic Version 1.14

Version 1.14
Date 2019-05-31
Package ‘Evapotranspiration’
May 31, 2019
Title Modelling Actual, Potential and Reference Crop Evapotranspiration
Author Danlu Guo [aut, cre] , Seth Wes-
tra [aut] , Tim Peterson [ctb]
Maintainer Danlu Guo
Depends R (>= 2.10), zoo
Description Uses data and constants to calculate potential evapotranspiration (PET) and actual evapo- transpiration (AET) from 21 different formulations including Penman, Penman-
Monteith FAO 56, Priestley-Taylor and Morton formulations.
License GPL (>= 2)
NeedsCompilation no
Repository CRAN
Date/Publication 2019-05-31 07:50:08 UTC
R topics documented:
climatedata ………………………………….. 2 constants …………………………………… 3 data……………………………………… 5 defaultconstants………………………………… 5 ET………………………………………. 6 ET.Abtew…………………………………… 8 ET.BlaneyCriddle……………………………….. 10 ET.BrutsaertStrickler ……………………………… 13 ET.ChapmanAustralian…………………………….. 15 ET.GrangerGray………………………………… 18 ET.Hamon…………………………………… 21 ET.HargreavesSamani……………………………… 23 ET.JensenHaise………………………………… 25 ET.Linacre ………………………………….. 27
1

2 climatedata
ET.Makkink………………………………….. 29 ET.MattShuttleworth ……………………………… 31 ET.McGuinnessBordne…………………………….. 34 ET.MortonCRAE……………………………….. 36 ET.MortonCRWE……………………………….. 39 ET.Penman ………………………………….. 42 ET.PenmanMonteith ……………………………… 46 ET.PenPan…………………………………… 49 ET.PriestleyTaylor ………………………………. 52 ET.Romanenko ………………………………… 54 ET.SzilagyiJozsa ……………………………….. 56 ET.Turc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 ETComparison ………………………………… 61 ETForcings ………………………………….. 63 ETPlot…………………………………….. 65 E_OBS ……………………………………. 66 ReadInputs ………………………………….. 67 ReadOBSEvaporations …………………………….. 71
Index
climatedata Raw Climate Data Required for Calculating Evapotranspiration
Description
73
This data set contains the raw climate data including the variables required for calculating evap- otranspiration in function ET over the observation period between 1/3/2001 and 08/31/2004 at the Kent Town station in Adelaide, Australia.
Usage
climatedata
Format
A data frame containing 10240 obserations of 9 objects:
Station.Number – weather station number, Year – year of record,
Month – month of record,
Day – day of record,
Hour – hour of record,
Tdew – subdaily dew point temperature in degree Celcius, RH – subdaily relative humidity in percentage,
Rs – subdaily solar radiation in Megajoule per square meter, uz – subdaily wind speed in meter per second.

constants 3 Source
Bureau of Meteorology, Kent Town, Adelaide, Australia
constants Constants Required for Calculating Evapotranspriation
Description
This data set contains the universal constants, and examples of other variable constants required for calculating evapotranspiration in function ET, based on the climatic condition at Kent Town station in Adelaide, Australia.
Usage
constants
Format
A list containing 36 constant values including:
– 20 universal constants, which should be kept unchanged for most conditions:
lambda latent heat of evaporisationin = 2.45 MJ.kg^-1 at 20 degree Celcius, sigma Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1, Gsc solar constant = 0.0820 MJ.m^-2.min^-1
Roua mean density of air = 1.2 kg.m^-3 at 20 degree Celcius
Ca specific heat of air = 0.001013 MJ.kg^-1.K^-1
G soil heat flux negligible for daily time-step = 0 (Allen et al., 1998, page 68) alphaA Albedo for Class-A pan = 0.14
alphaPT Priestley-Taylor coefficient:
= 1.26 for Priestley-Taylor formula (Priestley and Taylor, 1972, Sect. 6; Eichinger et al., 1996, p.163);
= 1.31 for Szilagyi-Jozsa formula (Szilagyi and Jozsa, 2008);
= 1.28 for Brutsaert-Strickler formula (Brutsaert and Strickler, 1979),
ap constant in Penpan formula = 2.4,
b0 constant in Morton’s procedure = 1 (Chiew and McMahon, 1991, Table A1),
b1 constant in Morton’s procedure = 14 W.m^-2 (Chiew and McMahon, 1991, Table A1), b2 constant in Morton’s procedure = 1.2 (Chiew and McMahon, 1991, Table A1),
e0 constant for Blaney-Criddle formula = 0.81917 (Frevert et al., 1983, Table 1),
e1 constant for Blaney-Criddle formula = -0.0040922 (Frevert et al., 1983, Table 1),
e2 constant for Blaney-Criddle formula = 1.0705 (Frevert et al., 1983, Table 1),
e3 constant for Blaney-Criddle formula = 0.065649 (Frevert et al., 1983, Table 1),
e4 constant for Blaney-Criddle formula = -0.0059864 (Frevert et al., 1983, Table 1),
e5 constant for Blaney-Criddle formula = -0.0005967 (Frevert et al., 1983, Table 1), epsilonMo Land surface emissivity in Morton’s procedure = 0.92,

4
constants
sigmaMo Stefan-Boltzmann constant in Morton’s procedure = 5.67e-08 W.m^-2.K^-4.
– 16 variable constants, which are specific for the climatic condition at Kent Town station in Ade-
laide, Australia:
lat latitude = -34.9211 degrees for Kent Town station,
lat_rad latitude in radians = -0.6095 radians for Kent Town station,
as fraction of extraterrestrial radiation reaching earth on sunless days = 0.23 for Australia (Roder- ick, 1999, page 181),
bs difference between fracion of extraterrestrial radiation reaching full-sun days and that on sunless days = 0.5 for Australia (Roderick, 1999, page 181),
Elev ground elevation above mean sea level = 48m for Kent Town station,
z height of wind instrument = 10m for Kent Town station,
fz constant in Morton’s procedure:
= 28.0 W.m^-2.mbar^-1 for CRAE model for T >= 0 degree Celcius;
= 28.0*1.15 W.m^-2.mbar^-1 for CRAE model for T < 0 degree Celcius;= 25.0 W.m^-2.mbar^-1 for CRWE model for T >= 0 degree Celcius;
= 28.75 W.m^-2.mbar^-1 for CRWE model for T < 0 degree Celcius (Morton, 1983a, page65).a_0 constant for estimating sunshine hours from cloud cover data = 11.9 for Adelaide (Chiew and McMahon, 1991, Table A1),b_0 constant for estimating sunshine hours from cloud cover data = -0.15 for Adelaide,c_0 constant for estimating sunshine hours from cloud cover data = -0.25 for Adelaide,d_0 constant for estimating sunshine hours from cloud cover data = -0.0107 for Adelaide, gammaps product of Psychrometric constant and atmospheric pressure as sea level:= 0.66 mbar. degree Celcius^-1 for CRAE model for T >= 0 degree Celcius;
= 0.66/1.15 mbar. degree Celcius^-1 for CRAE model for T < 0 degree Celcius.PA annual precipitation = 285.8mm for Kent Town station,alphaMo constant in Morton’s procedure: = 17.27 when T >= 0 degree Celcius;
= 21.88 when T < 0 degree Celcius.betaMo constant in Morton’s procedure:= 237.3 degree Celcius when T >= 0 degree Celcius; = 265.5 degree Celcius when T < 0 degree Celcius.lambdaMo latent heat of vaporisation in Morton’s procedure: = 28.5W.day.kg^-1 when T >= 0 degree Celcius;
= 28.5*1.15W.day.kg^-1 when T < 0 degree Celcius.Sourcevarious referencesdata 5 See Alsodefaultconstantsdata Processed Climate Data Required for Calculating EvapotranspirationDescriptionThis data set contains the processed climate data including the variables required for calculating evapotranspiration in function ET over the observation period between 1/3/2001 and 31/8/2004 at the Kent Town station in Adelaide, Australia.UsagedataFormatA list containing 11 non-empty variables:Date.daily – date in daily time step,Date.monthly – date in monthly time step,J – julian days,i – month,ndays – days in month,Tmax – daily maximum temperature in degree Celcius, Tmin – daily minimum temperature in degree Celcius, RHmax – daily maximum relative humidity in percentage, RHmin – daily minimum relative humidity in percentage, uz – daily wind speed in meters per second,Rs – daily solar radiation in Megajoule per square meter.SourceBureau of Meteorology, Kent Town, Adelaide, Australiadefaultconstants Universal constants Required for Calculating EvapotranspriationDescriptionThis data set contains the universal constants required for calculating evapotranspiration in function ET, which should be kept unchanged for most conditions. Please note that additional constants may be ET models – check the manual for individual ET models for details.6 ET UsageconstantsFormatA list containing 20 constant values including:lambda latent heat of evaporisationin = 2.45 MJ.kg^-1 at 20 degree Celcius, sigma Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1,Gsc solar constant = 0.0820 MJ.m^-2.min^-1Roua mean density of air = 1.2 kg.m^-3 at 20 degree CelciusCa specific heat of air = 0.001013 MJ.kg^-1.K^-1G soil heat flux negligible for daily time-step = 0 (Allen et al., 1998, page 68) alphaA Albedo for Class-A pan = 0.14alphaPT Priestley-Taylor coefficient:= 1.26 for Priestley-Taylor formula (Priestley and Taylor, 1972, Sect. 6; Eichinger et al., 1996, p.163);= 1.31 for Szilagyi-Jozsa formula (Szilagyi and Jozsa, 2008);= 1.28 for Brutsaert-Strickler formula (Brutsaert and Strickler, 1979),ap constant in Penpan formula = 2.4,b0 constant in Morton’s procedure = 1 (Chiew and McMahon, 1991, Table A1),b1 constant in Morton’s procedure = 14 W.m^-2 (Chiew and McMahon, 1991, Table A1), b2 constant in Morton’s procedure = 1.2 (Chiew and McMahon, 1991, Table A1),e0 constant for Blaney-Criddle formula = 0.81917 (Frevert et al., 1983, Table 1),e1 constant for Blaney-Criddle formula = -0.0040922 (Frevert et al., 1983, Table 1),e2 constant for Blaney-Criddle formula = 1.0705 (Frevert et al., 1983, Table 1),e3 constant for Blaney-Criddle formula = 0.065649 (Frevert et al., 1983, Table 1),e4 constant for Blaney-Criddle formula = -0.0059864 (Frevert et al., 1983, Table 1),e5 constant for Blaney-Criddle formula = -0.0005967 (Frevert et al., 1983, Table 1), epsilonMo Land surface emissivity in Morton’s procedure = 0.92,sigmaMo Stefan-Boltzmann constant in Morton’s procedure = 5.67e-08 W.m^-2.K^-4.Sourcevarious referencesSee AlsoconstantsET ET FormulationsET 7 DescriptionA generic function including 17 different specific methods that are all named following the format of ET.methodname. Once specific function is called the corresponding calculations are performed and a calculation summary is printed to screen.UsageET(data, constants, …)Argumentsdata A list of climate data required for estimating evapotranspiration which differs for each evapotranspiration formulations, see specific formulations for details.constants A list named constants consists of constants required for the ET models which mdiffer for specific ET models – refer to the manual for individual models for details…. Arguments to be passed to methods which differs for each evapotranspiration formulations, see specific formulations for details.DetailsIndividual ET methods can be called by substituting the ’methodname’ by the function name (e.g. ET.Penman to call the Penman model).When the ET model selection is not specified by users, this function determines the default model to use based on the availability of climate data presented. Wherever data are available, the more comprehensive, physically-based models are always preferred over the empirical models, in the fol- lowing hierarchy:- If all variables of Tmax/Tmin and RHmax/RHmin and either uz or u2, and either Rs of n or Cd are available, and short crop surface is specified in argument:Penman-Monteith FAO56 (ET.PenmanMonteith with crop = “short”);- If all variables of Tmax/Tmin and RHmax/RHmin and either uz or u2, and either Rs of n or Cd are available, and long crop surface is specified in argument:Penman-Monteith ASCE-EWRI (ET.PenmanMonteith with crop = “long”);- If all variables of Tmax/Tmin and RHmax/RHmin and either uz or u2, and either Rs of n or Cd are available, and no surface is specified:Penman (ET.Penman);- If all variables of Tmax/Tmin and RHmax/RHmin, and either Rs of n or Cd are available: Priestley-Taylor (ET.PriestleyTaylor);- If all variables of Tmax/Tmin and either Rs of n or Cd are available: Makkink (ET.Makkink);8ET.Abtew- If all variables of Tmax/Tmin are available: Hargreaves-Samani (ET.HargreavesSamani).Author(s)Danlu GuoExamples# Use processed existing data set from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call generic function ET() – leads to the use of Penman modelresults_default <- ET(data, constants)# Call generic function ET() – leads to the use of Penman-Monteith modelresults_crop <- ET(data, constants, crop = “short”)ET.Abtew Abtew FormulationDescriptionImplementing the Abtew formulation for estimating actual evapotranspiration.Usage## S3 method for class ‘Abtew’ET(data, constants, ts=”daily”, solar=”sunshine hours”,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data in class “Abtew” which contains the following items (climate vari- ables) required by Abtew formulation:Tmax, Tmin (degree Celcius), Rs (Megajoules per sqm) or n (hour) or Cd (okta)constants A list named constants consists of constants required for the calculation of Abtew 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,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-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,ET.Abtewts solarmessage9bs – difference between fracion of extraterrestrial radiation reaching full-sun days and that on sunless days.Must be either daily, monthly or annual, which indicates the disired time step that the output ET estimates should be on. Default is daily.Must be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.Must be either yes or no, indicating whether message should be printed for calculation summary including 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 minvalues.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.AdditionalStatssave.csv…DetailsThe alternative calculation options can be selected through argument solar, please see Arguments for details.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typeDaily aggregated estimations of Abtew actual evapotranspiration. Monthly aggregated estimations of Abtew actual evapotranspiration. Annually aggregated estimations of Abtew actual evapotranspiration. Monthly averaged estimations of daily Abtew actual evapotranspiration. Annually averaged estimations of daily Abtew actual evapotranspiration. Name of the formulation used which equals to Abtew.Type of the estimation obtained which is Actual Evapotranspiration.10message1ET.BlaneyCriddleA message to inform the users about how solar radiation has been calculated by using which data.Author(s)Danlu GuoReferencesAbtew, W. 1996. Evapotranspiration measurements and modeling for three wetland systems in south florida. Wiley Online Library.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.Abtew under the generic function ETresults <- ET.Abtew(data, constants,ts=”daily”, solar=”sunshine hours”,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.BlaneyCriddle Blaney-Criddle FormulationDescriptionImplementing the Blaney-Criddle formulation for estimating reference crop evapotranspiration.Usage## S3 method for class ‘BlaneyCriddle’ET(data, constants, ts=”daily”, solar=”sunshine hours”, height = F,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Blaney-Criddle formulation:Tmax, Tmin (degree Celcius), RHmin (per cent), n (hour) or Cd (okta), u2 or uz (meter per second)ET.BlaneyCriddleconstantsts solarheightmessage11A list named constants consists of constants required for the calculation of PenPan 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,z – height of wind instrument in m,e0,e1,e2,e3,e4 – recommended values of 0.81917, -0.0040922, 1.0705, 0.065649, -0.0059684, -0.0005967 respectively (Table 1 in Frevert et al., 1983).Must be either daily, monthly or annual, which indicates the disired time step that the output ET estimates should be on. Default is daily.Must be either sunshine hours or cloud: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.Default is sunshine hours.Must be T or F, indicating if adjustment for site elevation for arid and semi-arid regions is applied in Blaney-Criddle formulation (Allen and Brockway, 1983). Default is F for no adjustment.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- Evaporative surface- Option for calculating solar radiation (i.e. the value of argument solar)- If height adjustment has been applied on results (i.e. the value of argument height)- 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”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.AdditionalStatssave.csv …DetailsThe alternative calculation options can be selected through argument solar, please see Arguments for details.Height adjustment for the estimations is available through argument height, please see Arguments for details.12 ET.BlaneyCriddleValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1message3Author(s)Danlu GuoReferencesDaily aggregated estimations of Blaney-Criddle reference crop evapotranspira- tion.Monthly aggregated estimations of Blaney-Criddle reference crop evapotranspi- ration.Annually ggregated estimations of Blaney-Criddle reference crop evapotranspi- ration.Monthly averaged estimations of daily Blaney-Criddle reference crop evapo- transpiration.Annually averaged estimations of daily Blaney-Criddle reference crop evapo- transpiration.Name of the formulation used which equals to Blaney-Criddle.Type of the estimation obtained which is Reference Crop Evapotranspiration.A message to inform the users about how solar radiation has been calculated by using which data.A message to inform the users about if height adjustment has been applied to calculated Blaney-Criddle reference crop evapotranspiration.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Allen, R.G.Brockway, C.E. 1983, Estimating consumptive use on a statewide basis. Advances in Irrigation and Drainage@ sSurviving External Pressures, ASCE, pp. 79-89.Allen, R. & Pruitt, W. 1986. Rational Use of The FAO Blaney-Criddle Formula. Journal of Irrigation and Drainage Engineering, 112, 139-155.Frevert, D.K., Hill, R.W.Braaten, B.C. 1983, Estimation of FAO evapotranspiration coefficients, Journal of Irrigation and Drainage Engineering, vol. 109, no. 2, pp. 265-270.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)ET.BrutsaertStrickler 13# Call ET.BlaneyCriddle under the generic function ETresults <- ET.BlaneyCriddle(data, constants, ts=”daily”, solar=”sunshine hours”,height= FALSE, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.BrutsaertStrickler Brutsaert-Strickler FormulationDescriptionImplementing the Brutsaert-Strickler formulation for actual areal evapotranspirationUsage## S3 method for class ‘BrutsaertStrickler’ET(data, constants, ts=”daily”, solar=”sunshine hours”, alpha=0.23,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Brutsaert-Strickler formulation:Tmax, Tmin (degree Celcius), RHmax, RHmin (per cent), Rs (Megajoules per sqm) or n (hour) or Cd (okta), u2 or uz (meter per second)constants A list named constants consists of constants required for the calculation of Brutsaert-Strickler 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,z – height of wind instrument in m,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-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 evap- otranspiration;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;14alphamessageET.BrutsaertStricklermonthly precipitation indicates that solar radiation is to be calculated di- rectly from monthly precipitation.Default is sunshine hours.Any numeric value between 0 and 1 (dimensionless), albedo of the evaporative surface representing the portion of the incident radiation that is reflected back at the surface.Default is 0.23 for surface covered with short reference crop.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- Evaporative surface with values of albedo, surface resistance, crop height and roughness height- 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”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.DetailsAdditionalStatssave.csv…The alternative calculation options can be selected through argument solar, please see Arguments for details.User-defined evaporative surface is allowed through argument alpha, please see Arguments for details.ValueThe function also generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveDaily aggregated estimations of Brutsaert-Strickler actual areal evapotranspira- tion.Monthly aggregated estimations of Brutsaert-Strickler actual areal evapotranspi- ration.Annually aggregated estimations of Brutsaert-Strickler actual areal evapotran- spiration.Monthly averaged estimations of daily Brutsaert-Strickler actual areal evapo- transpiration.Annually averaged estimations of daily Brutsaert-Strickler actual areal evapo- transpiration.ET.ChapmanAustralianET_formulationET_typemessage1Author(s)Danlu GuoReferences15Name of the formulation used which equals to Brutsaert-Strickler.Type of the estimation obtained which is Actual Areal Evapotranspiration.A message to inform the users about how solar radiation has been calculated by using which data.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.BrutsaertStrickler under the generic function ETresults <- ET.BrutsaertStrickler(data, constants, ts=”daily”, solar=”sunshine hours”,alpha=0.23, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.ChapmanAustralian Chapman FormulationDescriptionImplementing the Chapman formulation for estimating potential evapotranspiration.Usage## S3 method for class ‘ChapmanAustralian’ET(data, constants, ts=”daily”, PenPan= T,solar=”sunshine hours”, alpha=0.23, message=”yes”, AdditionalStats=”yes”,save.csv=”yes”, …)16ArgumentsdataconstantsET.ChapmanAustralianA list of data which contains the following items (climate variables) required by Chapman formulation:Tmax, Tmin (degree Celcius), RHmax, RHmin (per cent), Rs (Megajoules per sqm) or n (hour) or Cd (okta), u2 or uz (meter per second)A list named constants consists of constants required for the calculation of Chapman 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,z – height of wind instrument in m,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1, lat – latitude in degrees,alphaA – albedo for Class-A pan,ap – a constant in PenPan = 2.4.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.Must be either daily, monthly or annual, which indicates the disired time step that the output ET estimates should be on. Default is daily.Must be T or F, indicating if the PenPan formulation is used for estimating Class- A pan evaporation required in Chapman formulation. If T PenPan will be used and if F the actual data of Class-A pan evaporation will be used. Default is T for using the PenPan formulation.Must be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.Any numeric value between 0 and 1 (dimensionless), albedo of the evaporative surface incident radiation that is reflected back at the surface.Default is 0.23 for surface covered with short reference crop.Must be either yes or no, indicating whether message should be printed for cal- culation summary including the following elements:- ET model name and ET quantity estimated, and the value of pan coefficient (only for when potential ET is estimated)- Evaporative surface with values of albedo- Option for calculating solar radiation (i.e. the value of argument solar)ts PenPansolaralphamessageET.ChapmanAustralianAdditionalStatssave.csv…Details17- If the PenPan formulation is used for estimating Class-A pan evaporation re- quired in Chapman formulation (i.e. the value of argument PenPan)- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.The alternative calculation options can be selected through arguments PenPan and solar, please see Arguments for details.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1message5Author(s)Danlu GuoReferencesDaily aggregated estimations of Chapman potential evapotranspiration. Monthly aggregated estimations of Chapman potential evapotranspiration.Annually aggregated estimations of Chapman equivalent Penmen-Monteith evap- otranspiration.Monthly averaged estimations of daily Chapman potential evapotranspiration.Annually averaged estimations of daily Chapman potential evapotranspiration.Name of the formulation used which equals to Chapman.Type of the estimation obtained which is Potential Evapotranspiration.A message to inform the users about how solar radiation has been calculated by using which data.A message to inform the users about if the Class-A pan evaporation is from actual data or from PenPan estimation.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.18 ET.GrangerGrayChapman, T. 2001, Estimation of evaporation in rainfall-runoff models, in F. Ghassemi, D. Post, M. SivapalanR. Vertessy (eds), MODSIM2001: Integrating models for Natural Resources Management across Disciplines, Issues and Scales, MSSANZ, vol. 1, pp. 293-298.See AlsoET,data,defaultconstants,constants,ET.PenPan Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.ChapmanAustralian under the generic function ETresults <- ET.ChapmanAustralian(data, constants, ts=”daily”, PenPan= TRUE,solar=”sunshine hours”, alpha=0.23, message=”yes”, AdditionalStats=”yes”,save.csv=”yes”)ET.GrangerGray Granger-Gray FormulationDescriptionImplementing the Granger-Gray formulation for estimating actual areal evapotranspiration.Usage## S3 method for class ‘GrangerGray’ET(data, constants, ts=”daily”,solar=”sunshine hours”, windfunction_ver=1948, alpha=0.23,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Granger-Gray formulation:Tmax, Tmin (degree Celcius), RHmax, RHmin (per cent), Rs (Megajoules per sqm) or n (hour) or Cd (okta), u2 or uz (meter per second)constants A list named constants consists of constants required for the calculation of Granger-Gray 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,z – height of wind instrument in m,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1. G – soil heat flux in MJ.m^-2.day^-1, = 0 when using daily time step.ET.GrangerGrayts solar19The 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.Must be either daily, monthly or annual, which indicates the disired time step that the output ET estimates should be on. Default is daily.Must be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.windfunction_veralphamessageThe version of Penman wind function that will be used within the Penman for- mulation. Must be either 1948 or 1956.1948 is for applying the Penman’s 1948 wind function (Penman, 1948);1956 is for applying the Penman’s 1956 wind function (Penman, 1956) Default is 1948.Any numeric value between 0 and 1 (dimensionless), albedo of evaporative sur- face representing the portion of the incident radiation that is reflected back at the surface.Default is 0.23 for surface covered with short reference crop.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- Evaporative surface with values of albedo- Option for calculating solar radiation (i.e. the value of argument solar)- The version of Penman wind function has been used (i.e. the value of argument windfunction_ver)- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.AdditionalStatssave.csv …20 ET.GrangerGray DetailsThe alternative calculation options can be selected through arguments solar and windfunction_ver, please see Arguments for details.User-defined evaporative surface is allowed through argument alpha, please see Arguments for de- tails.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1message2Author(s)Danlu GuoReferencesDaily aggregated estimations of Granger-Gray actual areal evapotranspiration.Monthly aggregated estimations of Granger-Gray actual areal evapotranspira- tion.Annually aggregated estimations of Granger-Gray actual areal evapotranspira- tion.Monthly averaged estimations of daily Granger-Gray actual areal evapotranspi- ration.Annually averaged estimations of daily Granger-Gray actual areal evapotranspi- ration.Name of the formulation used which equals to Granger-Gray.Type of the estimation obtained which is Actual Areal Evapotranspiration.A message to inform the users about how solar radiation has been calculated by using which data.A message to inform the users about which version of the Penman wind function has been used.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Penman, H. L. 1948. Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 193, 120-145.Penman, H. L. 1956. Evaporation: An introductory survey. Netherlands Journal of Agricultural Science, 4, 9-29See AlsoET,data,defaultconstants,constants,ET.PenmanET.Hamon 21 Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.GrangerGray under the generic function ETresults <- ET.GrangerGray(data, constants, ts=”daily”,solar=”sunshine hours”, windfunction_ver=1948, alpha=0.23,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.Hamon Hamon Formulation DescriptionImplementing the Hamon formulation for estimating potential evapotranspiration.Usage## S3 method for class ‘Hamon’ET(data, constants = NULL, ts=”daily”, message=”yes”, AdditionalStats=”yes”,save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Hamon formulation:Tmax, Tmin (degree Celcius), n (hour) constants Dummy argument with a NULL value.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.message Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:AdditionalStats- ET model name and ET quantity estimated- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.save.csv Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory…. Dummy for generic function, no need to define.22 ET.Hamon DetailsThis formulation provides a single calculation method with no alternatives available.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typeAuthor(s)Danlu GuoReferencesDaily aggregated estimations of Hamon potential evapotranspiration. Monthly aggregated estimations of Hamon potential evapotranspiration. Annually aggregated estimations of Hamon potential evapotranspiration. Monthly averaged estimations of daily Hamon potential evapotranspiration. Annually averaged estimations of daily Hamon potential evapotranspiration. Name of the formulation used which equals to Hamon.Type of the estimation obtained which is Potential Evapotranspiration.Hamon, W. R. 1961. Estimating potential evapotranspiration. Journal of the Hydraulics Division, 87, 107-120.Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andreassian, V., Anctil, F.Loumagne, C. 2005,Which potential evapotranspiration input for a lumped rainfall-runoff model?: Part 2-Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling. Journal of Hydrology, vol. 303, no. 1-4, pp. 290-306.See AlsoET,data Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.Hamon under the generic function ETresults <- ET.Hamon(data, ts=”daily”, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.HargreavesSamani 23ET.HargreavesSamani Hargreaves-Samani FormulationDescriptionImplementing the Hargreaves-Samani formulation for estimating reference crop evapotranspiration.Usage## S3 method for class ‘HargreavesSamani’ET(data, constants, ts=”daily”,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Hargreaves-Samani formulation: Tmax, Tmin (degree Celcius)constants A list named constants consists of constants required for the calculation of Hargreaves-Samani 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.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.message Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:AdditionalStats- ET model name and ET quantity estimated- Evaporative surface with values of albedo- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.save.csv Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory…. Dummy for generic function, no need to define.DetailsThis formulation provides a single calculation method with no alternatives available.24 ET.HargreavesSamaniValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typeAuthor(s)Danlu GuoReferencesDaily aggregated estimations of Hargreaves-Samani reference crop evapotran- spiration.Monthly aggregated estimations of Hargreaves-Samani reference crop evapo- transpiration.Annually aggregated estimations of Hargreaves-Samani reference crop evapo- transpiration.Monthly averaged estimations of daily Hargreaves-Samani reference crop evap- otranspiration.Annually averaged estimations of daily Hargreaves-Samani reference crop evap- otranspiration.Name of the formulation used which equals to Hargreaves-Samani.Type of the estimation obtained which is Reference Crop Evapotranspiration.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Hargreaves, G.H.Samani, Z.A. 1985, Reference crop evapotranspiration from ambient air temper- ature. American Society of Agricultural Engineers.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.HargreavesSamani under the generic function ETresults <- ET.HargreavesSamani(data, constants, ts=”daily”, message=”yes”,AdditionalStats=”yes”, save.csv=”yes”)ET.JensenHaise 25ET.JensenHaise Jensen-Haise Formulation DescriptionImplementing the Jensen-Haise formulation for estimating potential evapotranspiration.Usage## S3 method for class ‘JensenHaise’ET(data, constants, ts=”daily”, solar=”sunshine hours”,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)ArgumentsdataconstantsA list of data which contains the following items (climate variables) required by Jensen-Haise formulation: Tmax, Tmin, Rs or n or Cd Tmax, Tmin (degree Celcius), Rs (Megajoules per sqm) or n (hour) or Cd (okta)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.Must be either daily, monthly or annual, which indicates the disired time step that the output ET estimates should be on. Default is daily.Must be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- Option for calculating solar radiation (i.e. the value of argument solar)ts solarmessage26ET.JensenHaise- 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 minvalues.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.DetailsAdditionalStatssave.csv…This formulation provides a single calculation method with no alternatives available.ValueThe function also generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typeAuthor(s)Danlu GuoReferencesDaily aggregated estimations of Jensen-Haise potential evapotranspiration.Monthly aggregated estimations of Jensen-Haise potential evapotranspiration.Annually aggregated estimations of Jensen-Haise potential evapotranspiration.Monthly averaged estimations of daily Jensen-Haise potential evapotranspira- tion.Annually averaged estimations of daily Jensen-Haise potential evapotranspira- tion.Name of the formulation used which equals to Jensen-Haise.Type of the estimation obtained which is Potential Evapotranspiration.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 asso- ciated 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 calculat- ing evaporation., Hydrological Processes, vol. 14, no. 2, pp. 339-349.ET.Linacre 27 See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.JensenHaise under the generic function ETresults <- ET.JensenHaise(data, constants, ts=”daily”, solar=”sunshine hours”,message=”yes”,AdditionalStats=”yes”, save.csv=”yes”)ET.Linacre Linacre Formulation DescriptionImplementing the Linacre formulation for estimating actual evapotranspiration.Usage## S3 method for class ‘Linacre’ET(data, constants, ts=”daily”, message=”yes”, AdditionalStats=”yes”,save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Linacre formulation:Tmax, Tmin, Tdew (degree Celcius)constants A list named constants consists of constants required for the calculation of Linacre formulation which must contain the following items:Elev – ground elevation above mean sea level in m, lat – latitude in degrees.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.message Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- 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.28save.csv…ET.Linacre”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.DetailsAdditionalStatsThis formulation provides a single calculation method with no alternatives available.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typeAuthor(s)Danlu GuoReferencesDaily aggregated estimations of Linacre actual evapotranspiration. Monthly aggregated estimations of Linacre actual evapotranspiration. Annually aggregated estimations of Linacre actual evapotranspiration. Monthly averaged estimations of daily Linacre actual evapotranspiration. Annually averaged estimations of daily Linacre actual evapotranspiration. Name of the formulation used which equals to Linacre.Type of the estimation obtained which is Actual Evapotranspiration.Linacre, E. T. 1977. A simple formula for estimating evaporation rates in various climates, using temperature data alone. Agricultural meteorology, 18, 409-424.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.Linacre under the generic function ETresults <- ET.Linacre(data, constants, ts=”daily”,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.Makkink 29ET.Makkink Makkink Formulation DescriptionImplementing the Makkink formulation for estimating reference crop evapotranspiration.Usage## S3 method for class ‘Makkink’ET(data, constants, ts=”daily”, solar=”sunshine hours”,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)ArgumentsdataconstantsA list of data which contains the following items (climate variables) required by Makkink formulation:Tmax, Tmin (degree Celcius), Rs (Megajoules per sqm) or n (hour) or Cd (okta)A list named constants consists of constants required for the calculation of Makkink 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.Must be either daily, monthly or annual, which indicates the disired time step that the output ET estimates should be on. Default is daily.Must be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.Must be either yes or no, indicating whether message should be printed for calculation summary including 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)ts solarmessage30ET.Makkink- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.DetailsAdditionalStatssave.csv…The alternative calculation options can be selected through argument solar, please see Arguments for details.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1Author(s)Danlu GuoReferencesDaily aggregated estimations of Makkink reference crop evapotranspiration.Monthly aggregated estimations of Makkink reference crop evapotranspiration.Annually aggregated estimations of Makkink reference crop evapotranspiration.Monthly averaged estimations of daily Makkink reference crop evapotranspira- tion.Annually averaged estimations of daily Makkink reference crop evapotranspira- tion.Name of the formulation used which equals to Makkink.Type of the estimation obtained which is Reference crop evapotranspiration.A message to inform the users about how solar radiation has been calculated by using which data.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.De Bruin, H. 1981, The determination of (reference crop) evapotranspiration from routine weather data. Evaporation in relation to hydrology, pp. 25-37.ET.MattShuttleworth 31 See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.Makkink under the generic function ETresults <- ET.Makkink(data, constants, ts=”daily”, solar=”sunshine hours”,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.MattShuttleworth Matt-Shuttleworth FormulationDescriptionImplementing the Matt-Shuttleworth formulation for reference crop evapotranspirationUsage## S3 method for class ‘MattShuttleworth’ET(data, constants, ts=”daily”, solar=”sunshine hours”,alpha=0.23, r_s=70, CH=0.12, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list which contains the following items (climate variables) required by Matt- Shuttleworth formulation:Tmax, Tmin (degree Celcius), RHmax, RHmin (per cent), Rs (Megajoules per sqm) or n (hour) or Cd (okta), u2 or uz (meter per second)constants A list named constants consists of constants required for the calculation of Matt-Shuttleworth 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,z – height of wind instrument in m,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1, Roua – mean air density = 1.20 kg.m^-3,Ca – specific heat of air = 0.001013 MJ.kg^-1.oC^-1.The following constants are also required when argument solar has value of sunshine hours:32ts solaralphar_sCH messageET.MattShuttleworthas – 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.Must be either daily, monthly or annual, which indicates the disired time step that the output ET estimates should be on. Default is daily.Must be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.Any numeric value between 0 and 1 (dimensionless), albedo of evaporative sur- face representing the portion of the incident radiation that is reflected back at the surface.Default is 0.23 for surface covered with short reference crop, which is for the calculation of Matt-Shuttleworth reference crop evaporation.Any value (seconds per metre), surface resistance depends on the type of refer- ence crop.Default is 70 for short reference crop.Any value (metres), crop height depends on the reference crop. Default is 0.12 for short reference crop.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- Evaporative surface with values of albedo, surface resistance and crop height – 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 minvalues.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.DetailsAdditionalStatssave.csv…The alternative calculation options can be selected through argument solar, please see Arguments for details.ET.MattShuttleworth 33 User-defined evaporative surface is allowed through arguments alpha, r_s and CH, please seeArguments for details.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1Author(s)Danlu GuoReferencesDaily aggregated estimations of Matt-Shuttleworth reference crop evapotranspi- ration.Monthly aggregated estimations of Matt-Shuttleworth reference crop evapotran- spiration.Annually aggregated estimations of Matt-Shuttleworth reference crop evapo- transpiration.Monthly averaged estimations of daily Matt-Shuttleworth reference crop evapo- transpiration.Annually averaged estimations of daily Matt-Shuttleworth reference crop evap- otranspiration.Name of the formulation used which equals to Matt-Shuttleworth.Type of the estimation obtained which is Reference Crop Evapotranspiration.A message to inform the users about how solar radiation has been calculated by using which data.Shuttleworth, W. & Wallace, J. 2009. Calculating the water requirements of irrigated crops in Australia using the Matt-Shuttleworth approach. Transactions of the ASABE, 52, 1895-1906.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.MattShuttleworth under the generic function ETresults <- ET.MattShuttleworth(data, constants, ts=”daily”,solar=”sunshine hours”, alpha=0.23, r_s=70, CH=0.12,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)34 ET.McGuinnessBordneET.McGuinnessBordne McGuinness-Bordne FormulationDescriptionImplementing the McGuinness-Bordne formulation for estimating potential evapotranspiration.Usage## S3 method for class ‘McGuinnessBordne’ET(data, constants, ts=”daily”, message=”yes”,AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by McGuinness-Bordne formulation: Tmax, Tmin (degree Celcius)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.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.message Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:AdditionalStats- ET model name and ET quantity estimated- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.save.csv Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory…. Dummy for generic function, no need to define.DetailsThis formulation provides a single calculation method with no alternatives available.ET.McGuinnessBordne 35ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typeAuthor(s)Danlu GuoReferencesDaily aggregated estimations of McGuinness-Bordne potential evapotranspira- tion.Monthly aggregated estimations of McGuinness-Bordne potential evapotranspi- ration.Annually aggregated estimations of McGuinness-Bordne potential evapotran- spiration.Monthly averaged estimations of daily McGuinness-Bordne potential evapo- transpiration.Annually averaged estimations of daily McGuinness-Bordne potential evapo- transpiration.Name of the formulation used which equals to McGuinness-Bordne.Type of the estimation obtained which is Potential Evapotranspiration.Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andreassian, V., Anctil, F.Loumagne, C. 2005,Which potential evapotranspiration input for a lumped rainfall-runoff model?: Part 2-Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling. Journal of Hydrology, vol. 303, no. 1-4, pp. 290-306.Xu, C.Y.Singh, V.P. 2000, Evaluation and generalization of radiation-based methods for calculat- ing evaporation., Hydrological Processes, vol. 14, no. 2, pp. 339-349.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.McGuinnessBordne under the generic function ETresults <- ET.McGuinnessBordne(data, constants, ts=”daily”,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)36 ET.MortonCRAEET.MortonCRAE Morton CRAE Formulation DescriptionImplementing the Morton CRAE formulation for estimating potential evapotranspiration, wet-environment areal evapotranspiration and actual areal evapotranspiration.Usage## S3 method for class ‘MortonCRAE’ET(data, constants, ts=”monthly”, est=”potential ET”,solar=”sunshine hours”, Tdew= T, alpha = NULL, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Morton CRAE formulation:Tmax, Tmin, Tdew (degree Celcius) or va or RHmax and RHmin, Rs (Megajoules per sqm) or n (hour) or Cd (okta)constants A list named constants consists of constants required for the calculation of Morton CRAE formulation which must contain the following items:Elev – ground elevation above mean sea level in m,lat_rad – latitude in radians,PA – annual precipitation in mm, required when precipitation data is not avail- able,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1,lat – latitude in degrees,epsilonMo – surface emissivity = 0.92 (Morton, 1986),fz – A constant in Morton’s procedure = 28.0 Wm^-2.mbar^-1 for T >= 0 degree Celcius, and = 28.0*1.15 Wm^-2.mbar^-1 for T >= 0 degree Celcius for CRAE model (Morton, 1983),
b0 – a constants in Morton’s procedure, = 1 for CRAE model (Morton, 1983), b1 – a constant in Morton’s procedure, = 14 for CRAE model (Morton, 1983), b2 – a constant in Morton’s procedure, = 1.2 for CRAE model (Morton, 1983), gammaps – Produce of Psychrometric constant and atmospheric pressure as sea level, = 0.66 mbar. degree Celcius^-1 for T >= 0 degree Celcius, = 0.66/1.15 mbar. degree Celcius^-1 for T < 0 degree Celcius (Morton, 1983),alphaMo – a constant in Morton’s procedure, = 17.27 when T >= 0 degree Cel- cius, = 21.88 when T < 0 degree Celcius (Morton, 1983),betaMo – a constant in Morton’s procedure, = 237.3 degree Celcius when T >= 0 degree Celcius, = 265.5 degree Celcius, when T < 0 degree Celcius (Morton, 1983),sigmaMo – Stefan-Boltzmann constant in Morton’s procedure, = 5.67e-08 W.m^- 2.K^-4 (Morton, 1983),ET.MortonCRAEts solarestTdewalphamessage37lambdaMo – Latent heat of vaporisation in Morton’s procedure, = 28.5W.day.kg^- 1 when T >= 0 degree Celcius, = 28.5*1.15W.day.kg^-1 when T < 0 degree Cel- cius,Must be either monthly or annual, which indicates the disired time step that the output ET estimates should be on. Default is monthly.Must be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.Must be either potential ET, wet areal ET or actual areal ET: potential ET proceeds to estimating potential evapotranspiration;wet areal ET proceeds to estimating wet-environmental areal evapotranspira- tion;actual areal ET proceeds to estimating actual areal evapotranspiraion. Default is potential ET.Must be T or F, indicating if real data of dew point temperature is used for calculating the radiation in Morton’s formulations, if T the data will be used and if F the dew point temperature will be calculated from data of daily vapour pressure. Default is T for using actual dew point temperature data.Only needed if argument solar has value of data.Any numeric value between 0 and 1 (dimensionless), albedo of evaporative sur- face representing the portion of the incident radiation that is reflected back at the surface.Default is NULL in line with the default use of sunshine hours to estimate solar radiation (i.e. argument solar is sunshine hours.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated (i.e. the value of argument est)- Option for calculating solar radiation (i.e. the value of argument solar)- If the actual dew point temperature data are used (i.e. the value of argument Tdew)- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.AdditionalStats38save.csv…ET.MortonCRAEMust be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.DetailsThe type of evapotranspiration calculated can be selected through argument est, please see Arguments for details. The alternative calculation options can be selected through argument solar and Tdew, please see Arguments for details.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1message6Author(s)Danlu GuoReferencesDaily aggregated estimations of Morton CRAE potential evapotranspiration, wet-environment areal evapotranspiration or actual areal evapotranspiration.Monthly aggregated estimations of Morton CRAE potential evapotranspiration, wet-environment areal evapotranspiration or actual areal evapotranspiration.A zoo object containing annually aggregated estimations of Morton CRAE po- tential evapotranspiration, wet-environment areal evapotranspiration or actual areal evapotranspiration.A zoo object containing monthly averaged estimations of daily Morton CRAE potential evapotranspiration, wet-environment areal evapotranspiration or actual areal evapotranspiration.A zoo object containing annually averaged estimations of daily Morton CRAE potential evapotranspiration, wet-environment areal evapotranspiration or actual areal evapotranspiration.Name of the formulation used which equals to MortonCRAE.Type of the estimation obtained which is either Potential Evapotranspiration,Wet-environment Areal Evapotranspiration and Actual Areal Evapotranspiration. A message to inform the users about how solar radiation has been calculated byusing which data.A message to inform the users about if actual dew point temperature has been used in the calculations or alternative calculations has been performed without dew point temperature data.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Morton, F.I. 1983, Operational estimates of areal evapotranspiration and their significance to the science and practice of hydrology. Journal of Hydrology, vol. 66, no. 1-4, pp. 1-76.ET.MortonCRWE 39 See Alsodata,defaultconstants,constants,ET.MortonCRWE Examples# Use processed existing data set and constants from# kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.MortonCRAE under the generic function ETresults <- ET.MortonCRAE(data, constants, ts=”monthly”,est=”potential ET”, solar=”sunshine hours”, Tdew= TRUE,alpha = NULL, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.MortonCRWE Morton CRWE FormulationDescriptionImplementing the Morton CRWE formulation for estimating potential evapotranspiration or shallow lake evaporation.Usage## S3 method for class ‘MortonCRWE’ET(data, constants, ts=”monthly”, est=”potential ET”,solar=”sunshine hours”, Tdew= T, alpha = NULL, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Morton CRWE formulation:Tmax, Tmin, Tdew (degree Celcius) or va or RHmax and RHmin, Rs (Megajoules per sqm) or n (hour) or Cd (okta)constants A list named constants consists of constants required for the calculation of Morton CRWE formulation which must contain the following items:Elev – ground elevation above mean sea level in m,lat_rad – latitude in radians,PA – annual precipitation in mm, required when precipitation data is not avail- able,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1,lat – latitude in degrees,epsilonMo – surface emissivity = 0.92 (Morton, 1986),fz – A constant in Morton’s procedure = 25.0 Wm^-2.mbar^-1 for T >= 0 de- gree Celcius, and = 28.75 Wm^-2.mbar^-1 for T >= 0 degree Celcius for CRWE

40
ET.MortonCRWE
model (Morton, 1986),
b0 – A constants in Morton’s procedure, = 1.12 for CRWE model, (Morton, 1986) b1 – A constant in Morton’s procedure, = 13 for CRWE model (Morton, 1986),
b2 – A constant in Morton’s procedure, = 1.12 for CRWE model (Morton, 1986), gammaps – Produce of Psychrometric constant and atmospheric pressure as sea level, = 0.66 mbar. degree Celcius^-1 for T >= 0 degree Celcius, = 0.66/1.15 mbar. degree Celcius^-1 for T < 0 degree Celcius (Morton, 1983),alphaMo – a constant in Morton’s procedure, = 17.27 when T >= 0 degree Cel- cius, = 21.88 when T < 0 degree Celcius (Morton, 1983),betaMo – a constant in Morton’s procedure, = 237.3 degree Celcius when T >= 0 degree Celcius, = 265.5 degree Celcius, when T < 0 degree Celcius (Morton, 1983),sigmaMo – Stefan-Boltzmann constant in Morton’s procedure, = 5.67e-08 W.m^- 2.K^-4 (Morton, 1983),lambdaMo – Latent heat of vaporisation in Morton’s procedure, = 28.5W.day.kg^- 1 when T >= 0 degree Celcius, = 28.5*1.15W.day.kg^-1 when T < 0 degree Cel- cius,Must be either monthly or annual, which indicates the disired time step that the output ET estimates should be on. Default is monthly.Must be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.Must be either potential ET or shallow lake ET:potential ET proceeds to estimating potential evapotranspiration; shallow lake ET proceeds to estimating shallow lake evaporation. Default is potential ET.Must be T or F, indicating if real data of dew point temperature is used for calculating the radiation in Morton’s formulations, if T the data will be used and if F the dew point temperature will be calculated from data of daily vapour pressure. Default is T for using actual dew point temperature data.Only needed if argument solar has value of data.Any numeric value between 0 and 1 (dimensionless), albedo of evaporative sur- face representing the portion of the incident radiation that is reflected back at the surface.Default is NULL in line with the default use of sunshine hours to estimate solar radiation (i.e. argument solar is sunshine hours.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:ts solarestTdewalphamessageET.MortonCRWE41- ET model name and ET quantity estimated (i.e. the value of argument est)- Option for calculating solar radiation (i.e. the value of argument solar)- If the actual dew point temperature data are used (i.e. the value of argument Tdew)- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.AdditionalStatssave.csv…DetailsThe type of evapotranspiration calculated can be selected through argument est, please see Arguments for details. The alternative calculation options can be selected through argument solar and Tdew, please see Arguments for details.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1message6Daily aggregated estimations of MortonCRWE potential evapotranspiration or shallow lake evaporation.Monthly aggregated estimations of MortonCRWE potential evapotranspiration or shallow lake evaporation.Annually aggregated estimations of MortonCRWE potential evapotranspiration or shallow lake evaporation.Monthly averaged estimations of daily MortonCRWE potential evapotranspira- tion or shallow lake evaporation.Annually averaged estimations of daily MortonCRWE potential evapotranspira- tion or shallow lake evaporation.Name of the formulation used which equals to MortonCRWE.Type of the estimation obtained which is either Potential Evapotranspirationor Shallow Lake Evaporation.A message to inform the users about how solar radiation has been calculated byusing which data.A message to inform the users about if actual dew point temperature has been used in the calculations or alternative calculations has been performed without dew point temperature data.42 ET.Penman Author(s)Danlu GuoReferencesMcMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Morton, F.I. 1983, Operational estimates of lake evaporation. Journal of Hydrology, vol. 66, no. 1-4, pp. 77-100.See Alsodata,defaultconstants,constants,ET.MortonCRWE Examples# Use processed existing data set and constants from# kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.MortonCRWE under the generic function ETresults <- ET.MortonCRWE(data, constants, ts=”monthly”,est=”potential ET”, solar=”sunshine hours”, Tdew= TRUE,alpha = NULL, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.Penman Penman FormulationDescriptionImplementing the Penman formulation for estimating open-water evaporation or potential evapo- transpirationUsage## S3 method for class ‘Penman’ET(data, constants, ts=”daily”, solar=”sunshine hours”,wind=”yes”, windfunction_ver=1948, alpha=0.08, z0=0.001, message=”yes”,AdditionalStats=”yes”, save.csv=”yes”, …)ET.PenmanArguments43data A list which contains the following items (climate variables) required by Pen- man formulation:Tmax, Tmin, RHmax, RHmin, Rs or n or Cd, u2 or uzconstants 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, lat_rad – latitude in radians,Gsc – solar constant = 0.0820 MJ.m^-2.min^-1,z – height of wind instrument in m,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1.The following constants are also required when argument solar has value of sunshine hours:as – only for when cloud data is used for calculating radiation i.e. solar = “cloud” – fraction of extraterrestrial radiation reaching earth on sunless days,bs – only for when cloud data is used for calculating radiation i.e. solar = “cloud” – 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 evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.wind Must be either yes or no.yes indicates that the calculation will use real data of wind speed;no indicates that the alternative calculation without using wind data will be used in Penman formulation (Valiantzas 2006, Equation33).Default is yes.windfunction_veralphaThe version of Penman wind function that will be used within the Penman for- mulation. Must be either 1948 or 1956.1948 is for applying the Penman’s 1948 wind function (Penman, 1948);1956 is for applying the Penman’s 1956 wind function (Penman, 1956) Default is 1948.Any numeric value between 0 and 1 (dimensionless), albedo of evaporative sur- face representing the portion of the incident radiation that is reflected back at the surface.Default is 0.08 for open-water surface which is for the calculation of Penman44z0messageET.Penmanopen-water evaporation, all other values will trigger the calculation of Penman potential evapotranspriation.Any value (metres), roughness height of the evaporative surface.Default is 0.001 for open-water surface which is for the calculation of Penman open-water evaporation, all other values will trigger the calculation of Penman potential evapotranspriation.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- Evaporative surface with values of albedo and roughness height- Option for calculating solar radiation (i.e. the value of argument solar)- If actual wind data has been used for calculation (i.e. the value of argument wind) and which version of Penman wind function has been used (i.e. the value of argument windfunction_ver)- 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”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.DetailsAdditionalStatssave.csv…The alternative calculation options can be selected through arguments solar, wind and windfunction_ver, please see Arguments for details.User-defined evaporative surface is allowed through arguments alpha and z0, please see Argumentsfor details.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveDaily aggregated estimations of Penman open-water evaporation or potential evapotranspiration.Monthly aggregated estimations of Penman open-water evaporation or potential evapotranspiration.Annually aggregated estimations of Penman open-water evaporation or potential evapotranspiration.Monthly averaged estimations of daily Penman open-water evaporation or po- tential evapotranspiration.ET.PenmanET.AnnualAveET_formulationET_typemessage1message2Author(s)Danlu GuoReferences45Annually averaged estimations of daily Penman open-water evaporation or po- tential evapotranspiration.Name of the formulation used which equals to Penman.Type of the estimation obtained which is either Open-water Evaporation orPotential Evapotranspiration.A message to inform the users about how solar radiation has been calculated byusing which data.A message to inform the users about if actual wind data has been used in the calculations or alternative calculations has been performed without wind data, and which version of the Penman wind function has been used.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Penman, H. L. 1948. Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 193, 120-145.Valiantzas, J. D. 2006. Simplified versions for the Penman evaporation equation using routine weather data. Journal of Hydrology, 331, 690-702.Penman, H. L. 1956. Evaporation: An introductory survey. Netherlands Journal of Agricultural Science, 4, 9-29.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from# kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.Penman under the generic function ETresults <- ET.Penman(data, constants, ts=”daily”,solar=”sunshine hours”, wind=”yes”,windfunction_ver = “1948”, alpha = 0.08, z0 = 0.001,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)46 ET.PenmanMonteithET.PenmanMonteith Penman-Monteith Formulation DescriptionImplementing the Penman-Monteith formulation (including the method for FAO-56 hypothetical short grass and the method for ASCE-EWRI Standardised crop) for estimating reference crop evap- otranspirationUsage## S3 method for class ‘PenmanMonteith’ET(data, constants, ts=”daily”, solar=”sunshine hours”,wind=”yes”, crop=”short”, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list which contains the following items (climate variables) required by Penman- Monteith formulation:Tmax, Tmin, RHmax, RHmin, Rs or n or Cd, u2 or uzconstants A list named constants consists of constants required for the calculation of Penman-Monteith 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,z – height of wind instrument in m,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1.G – soil heat flux in MJ.m^-2.day^-1, = 0 when using daily time step.The following constants are also required when argument solar has value of sunshine hours:as – only for when cloud data is used for calculating radiation i.e. solar = “cloud” – fraction of extraterrestrial radiation reaching earth on sunless days,bs – only for when cloud data is used for calculating radiation i.e. solar = “cloud” – 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 evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.ET.PenmanMonteithwind Must be either yes or no.yes indicates that the calculation will use real data of wind speed;47no indicates that the alternative calculation without using wind data will be used in Penman formulation (Valiantzas 2006, Equation33).Default is yes.crop Must be either short or tall.short indicates that the method for FAO-56 hypothetical short grass will be ap- plied (Allen et al., 1998, Equation 6);tall indicates that the method for ASCE-EWRI Standardised crop will be ap- plied (ASCE, 2005, Equation 1, Table 1).Default is short.message Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:AdditionalStats- ET model name and ET quantity estimated- Evaporative surface with values of albedo, surface resistance, crop height and roughness height- Option for calculating solar radiation (i.e. the value of argument solar)- If actual wind data has been used for calculation (i.e. the value of argument wind)- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.save.csv Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory…. Dummy for generic function, no need to define. DetailsThe alternative calculation options can be selected through arguments solar and wind, please see Arguments for details.User-defined evaporative surface is allowed through arguments crop, please see Arguments for details.ValueThe function generates a list containing the following components:ET.Daily Daily aggregated estimations of Penman-Monteith rerference crop evapotran- spiration.ET.Monthly Monthly aggregated estimations of Penman-Monteith rerference crop evapo- transpiration.48ET.PenmanMonteithAnnually aggregated estimations of Penman-Monteith rerference crop evapo- transpiration.Monthly averaged estimations of daily Penman-Monteith rerference crop evap- otranspiration.Annually averaged estimations of daily Penman-Monteith rerference crop evap- otranspiration.Name of the formulation used which equals to either Penman-Monteith FAO56 or Penman-Monteith ASCE-EWRI Standardised.A character string containing the type of the estimation obtained which is Reference Crop Evapotranspi A message to inform the users about how solar radiation has been calculated byusing which data.A message to inform the users about if actual wind data has been used in the calculations or alternative calculations has been performed without wind data.ET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1message2Author(s)Danlu GuoReferencesMcMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Allen, R. G., Pereira, L. S., Raes, D. & Smith, M. 1998. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage. paper 56. FAO, Rome, 300, 6541.Allen, R. G. 2005. The ASCE standardized reference evapotranspiration equation. Amer Society of Civil Engineers.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.PenmanMonteith under the generic function ETresults <- ET.PenmanMonteith(data, constants, ts=”daily”, solar=”sunshine hours”,wind=”yes”, crop = “short”, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.PenPan 49ET.PenPan PenPan FormulationDescriptionImplementing the PenPan formulation for Class-A pan evaporation.Usage## S3 method for class ‘PenPan’ET(data, constants, ts=”daily”, solar=”sunshine hours”,alpha=0.23, est=”potential ET”, pan_coeff=0.71, overest= F, message=”yes”,AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by PenPan formulation:Tmax, Tmin (degree Celcius), RHmax, RHmin (per cent), Rs (Megajoules per sqm) or n (hour) or Cd (okta), u2 or uz (meter per second)constants A list named constants consists of constants required for the calculation of PenPan 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,z – height of wind instrument in m,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1, lat – latitude in degrees,alphaA – albedo for Class-A pan,ap – a constant in PenPan = 2.4.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 evap- otranspiration;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;50alphaoverestestpan_coeffmessageET.PenPanmonthly precipitation indicates that solar radiation is to be calculated di- rectly from monthly precipitation.Default is sunshine hours.Any numeric value between 0 and 1 (dimensionless), albedo of surface sur- rounding the evaporation pan representing the portion of the incident radiation that is reflected back at the surface.Default is 0.23 for surface covered with short reference crop.Must be T or F, indicating if adjustment for the overestimation (i.e. divided by 1.078) of Class-A pan evaporation for Australian data is applied in PenPan formulation.Default is F for no adjustment.Must be either pan or potential ET to specify if estimation for the Class-A pan evaporation or potential evapotranspriation is performed.Default is potential ET for estimating potential evapotranspriation.Only required if argument est has value of potential ET, which defines the pan coefficient used to adjust the estimated pan evaporation to the potential ET required.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated (i.e. the value of argument est), and the value of pan coefficient (only for when potential ET is estimated)- Evaporative surface with values of albedo- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.DetailsAdditionalStatssave.csv…The alternative calculation options can be selected through argument solar, please see Arguments for details.User-defined evaporative surface is allowed through argument alpha, please see Arguments for de- tails.Adjustment for overestimation on the estimations are available through argument height, please see Arguments for details.ET.PenPan 51ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1Author(s)Danlu GuoReferencesDaily aggregated estimations of PenPan Class-A pan evaporation/potential evap- otranspiration.Monthly aggregated estimations of PenPan Class-A pan evaporation/potential evapotranspiration.Annually aggregated estimations of PenPan Class-A pan evaporation/potential evapotranspiration.Monthly averaged estimations of daily PenPan Class-A pan evaporation/potential evapotranspiration.Annually averaged estimations of daily PenPan Class-A pan evaporation/potential evapotranspiration.Name of the formulation used which equals to PenPan.Type of the estimation obtained which is Class-A Pan Evaporation or Potential Evapotranspiratiodepending on the value of est.A message to inform the users about how solar radiation has been calculated byusing which data.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Rotstayn, L. D., Roderick, M. L. & Farquhar, G. D. 2006. A simple pan-evaporation model for analysis of climate simulations: Evaluation over Australia. Geophysical Research Letters, 33.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from# kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.PenPan under the generic function ETresults <- ET.PenPan(data, constants, ts=”daily”,solar=”sunshine hours”, alpha=0.23,est=”potential ET”, pan_coeff=0.71, overest= FALSE,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)52 ET.PriestleyTaylorET.PriestleyTaylor Priestley-Taylor FormulationDescriptionImplementing the Priestley-Taylor formulation for potential evaporationUsage## S3 method for class ‘PriestleyTaylor’ET(data, constants, ts=”daily”, solar=”sunshine hours”, alpha=0.23,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list which contains the following items (climate variables) required by Priestley- Taylor formulation:Tmax, Tmin (degree Celcius), RHmax, RHmin (per cent), Rs (Megajoules per sqm) or n (hour) or Cd (okta)constants A list named constants consists of constants required for the calculation of Priestley-Taylor 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,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-1, alphaPT – Priestley-Taylor coefficient = 1.26 for Priestley-Taylor model (Priest- ley and Taylor, 1972)G – soil heat flux in MJ.m^-2.day^-1, = 0 when using daily time step.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 evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.ET.PriestleyTayloralphamessage53Any numeric value between 0 and 1 (dimensionless), albedo of evaporative sur- face representing the portion of the incident radiation that is reflected back at the surface.Default is 0.23 for surface covered with short reference crop, which is for the calculation of Priestly-Taylor reference crop evaporation.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- Evaporative surface with values of albedo- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.AdditionalStatssave.csv…DetailsThe alternative calculation options can be selected through argument solar, please see Arguments for details.User-defined evaporative surface is allowed through argument alpha, please see Arguments for details.ValueThe function generates a list containing the following components, which is saved into a csv file named as ET_PriestleyTaylor.csv in the working directory:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1Daily aggregated estimations of Priestley-Taylor potential evaporation.Monthly aggregated estimations of Priestley-Taylor potential evaporation.Annually aggregated estimations of Priestley-Taylor potential evaporation.Monthly averaged estimations of daily Priestley-Taylor potential evaporation.Annually averaged estimations of daily Priestley-Taylor potential evaporation.A character string containing the name of the formulation used which equals to Priestley-Taylor.Type of the estimation obtained which is Potential Evaporation.A message to inform the users about how solar radiation has been calculated by using which data.54 ET.Romanenko Author(s)Danlu GuoReferencesMcMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Priestley, C. & Taylor, R. 1972, On the assessment of surface heat flux and evaporation using large- scale parameters’. Monthly Weather Review, vol. 100, no. 2, pp. 81-92.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.PriestleyTaylor under the generic function ETresults <- ET.PriestleyTaylor(data, constants, ts=”daily”, solar=”sunshine hours”, alpha=0.23, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.Romanenko Romanenko FormulationDescriptionImplementing the Romanenko formulation for estimating potential evapotranspiration.Usage## S3 method for class ‘Romanenko’ET(data, constants = NULL, ts=”daily”,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Romanenko formulation:Tmax, Tmin (degree Celcius), RHmax, RHmin (per cent) constants Dummy argument with a NULL value.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.ET.RomanenkomessageAdditionalStatssave.csv…Details55Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.This formulation provides a single calculation method with no alternatives available.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typeAuthor(s)Danlu GuoReferencesDaily aggregated estimations of Romanenko potential evapotranspiration.Monthly aggregated estimations of Romanenko potential evapotranspiration.Annually aggregated estimations of Romanenko potential evapotranspiration.Monthly averaged estimations of daily Romanenko potential evapotranspiration.Annually averaged estimations of daily Romanenko potential evapotranspira- tion.Name of the formulation used which equals to Romanenko.Type of the estimation obtained which is Potential Evapotranspiration.Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andreassian, V., Anctil, F.Loumagne, C. 2005,Which potential evapotranspiration input for a lumped rainfall-runoff model?: Part 2-Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling. Journal of Hydrology, vol. 303, no. 1-4, pp. 290-306.See AlsoET,data56 ET.SzilagyiJozsa Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.Romanenko under the generic function ETresults <- ET.Romanenko(data, ts=”daily”, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.SzilagyiJozsa Szilagyi-Jozsa FormulationDescriptionImplementing the Szilagyi-Jozsa formulation for estimating actual evapotranspirationUsage## S3 method for class ‘SzilagyiJozsa’ET(data, constants, ts=”daily”, solar=”sunshine hours”, wind=”yes”, windfunction_ver=1948, alpha=0.23, z0=0.2, message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Szilagyi-Jozsa formulation:Tmax, Tmin (degree Celcius), RHmax, RHmin (per cent), Rs (Megajoules per sqm) or n (hour) or Cd (okta), u2 or uz (meter per second)constants A list named constants consists of constants required for the calculation of Szilagyi-Jozsa 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,z – height of wind instrument in m,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-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.ET.SzilagyiJozsasolarwind57Must be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.Must be either yes or no.yes indicates that the calculation will use real data of wind speed;no indicates that the alternative calculation without using wind data will be used in Penman formulation (Valiantzas 2006, Equation33), which is required in the Szilagyi-Jozsa model.Default is yes.windfunction_veralphaz0 messageThe version of Penman wind function that will be used within the Penman for- mulation. Must be either 1948 or 1956.1948 is for applying the Penman’s 1948 wind function (Penman, 1948);1956 is for applying the Penman’s 1956 wind function (Penman, 1956) Default is 1948.Any numeric value between 0 and 1 (dimensionless), albedo of evaporative sur- face representing the portion of the incident radiation that is reflected back at the surface.Default is 0.23 for short reference crop.Any value (metres), roughness height of the evaporative surface. Default is 0.23 for short reference crop.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- Evaporative surface with values of albedo, as well as the roughness height- Option for calculating solar radiation (i.e. the value of argument solar)- If actual wind data has been used for calculation (i.e. the value of argument wind) and which version of Penman wind function has been used (i.e. the value of argument windfunction_ver)- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.AdditionalStatssave.csv …58 ET.SzilagyiJozsa DetailsThe alternative calculation options can be selected through arguments solar, wind and windfunction_ver, please see Arguments for details.User-defined evaporative surface is allowed through arguments alpha and z0, please see Argumentsfor details.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualET.MonthlyAveET.AnnualAveET_formulationET_typemessage1message2Author(s)Danlu GuoReferencesDaily aggregated estimations of Szilagyi-Jozsa actual evapotranspiration.Monthly aggregated estimations of Szilagyi-Jozsa actual evapotranspiration.Annually aggregated estimations of Szilagyi-Jozsa actual evapotranspiration.Monthly averaged estimations of daily Szilagyi-Jozsa actual evapotranspiration.Annually averaged estimations of daily Szilagyi-Jozsa actual evapotranspira- tion.Name of the formulation used which equals to Szilagyi-Jozsa.A character string containing the type of the estimation obtained which is Actual Evapotranspiration.A message to inform the users about how solar radiation has been calculated by using which data.A message to inform the users about if actual wind data has been used in the calculations or alternative calculations has been performed without wind data, and which version of the Penman wind function has been used.Szilagyi, J. 2007. On the inherent asymmetric nature of the complementary relationship of evapo- ration. Geophysical Research Letters, 34, L02405.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Penman, H. L. 1948. Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 193, 120-145.Valiantzas, J. D. 2006. Simplified versions for the Penman evaporation equation using routine weather data. Journal of Hydrology, 331, 690-702.Penman, H. L. 1956. Evaporation: An introductory survey. Netherlands Journal of Agricultural Science, 4, 9-29.See AlsoET,data,defaultconstants,constants,ET.PenmanET.Turc 59 Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.SzilagyiJozsa under the generic function ETresults <- ET.SzilagyiJozsa(data, constants, ts=”daily”,solar=”sunshine hours”, wind=”yes”, windfunction_ver=1948, alpha=0.23, z0=0.2,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ET.Turc Turc FormulationDescriptionImplementing the Turc formulation for estimating reference crop evapotranspiration.Usage## S3 method for class ‘Turc’ET(data, constants, ts=”daily”, solar=”sunshine hours”, humid= F,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”, …)Argumentsdata A list of data which contains the following items (climate variables) required by Turc formulation:Tmax, Tmin (degree Celcius), Rs (Megajoules per sqm) or n (hour) or Cd (okta)constants A list named constants consists of constants required for the calculation of Turc 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,sigma – Stefan-Boltzmann constant = 4.903*10^-9 MJ.K^-4.m^-2.day^-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.60solarhumidmessageET.TurcMust be either data, sunshine hours, cloud or monthly precipitation: data indicates that solar radiation data is to be used directly for calculating evap- otranspiration;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 di- rectly from monthly precipitation.Default is sunshine hours.Must be T or F, indicating if adjustment for non-humid conditions is applied in Turc formulation (Alexandris et al., 2008, Equation 5b).Default is F for no adjustment.Must be either yes or no, indicating whether message should be printed for calculation summary including the following elements:- ET model name and ET quantity estimated- Evaporative surface- Option for calculating solar radiation (i.e. the value of argument solar)- if adjustment for non-humid conditions has been applied (i.e. the value of argument humid)- 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.”yes” or “no” indicating whether monthly averaged and annual averaged ET should be calculated.Must be either yes or no, indicating whether a .csv of ET estimates should be saved to working directory.Dummy for generic function, no need to define.DetailsAdditionalStatssave.csv…The alternative calculation options can be selected through argument solar, please see Arguments for details.Humidity adjustment for the estimations is available through argument humid, please see Arguments for details.ValueThe function generates a list containing the following components:ET.DailyET.MonthlyET.AnnualDaily aggregated estimations of Turc reference crop evapotranspiration. Monthly aggregated estimations of Turc reference crop evapotranspiration. Annually aggregated estimations of Turc reference crop evapotranspiration.ETComparisonET.MonthlyAveET.AnnualAveET_formulationET_typemessage1message4Author(s)Danlu GuoReferences61Monthly averaged estimations of daily Turc reference crop evapotranspiration.Annually averaged estimations of daily Turc reference crop evapotranspiration.Name of the formulation used which equals to Turc.Type of the estimation obtained which is Reference Crop Evapotranspiration.A message to inform the users about how solar radiation has been calculated by using which data.A message to inform the users about if adjustment for non-humid conditions has been applied to calculated Turc reference crop evapotranspiration.McMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Turc, L. 1961, Estimation of irrigation water requirements, potential evapotranspiration: a simple climatic formula evolved up to date. Ann. Agron, vol. 12, no. 1, pp. 13-49.Alexandris, S., Stricevic, R.Petkovic, S. 2008, Comparative analysis of reference evapotranspira- tion from the surface of rainfed grass in central Serbia, calculated by six empirical methods against the Penman-Monteith formula. European Water, vol. 21, no. 22, pp. 17-28.See AlsoET,data,defaultconstants,constants Examples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.Turc under the generic function ETresults <- ET.Turc(data, constants, ts=”daily”, solar=”sunshine hours”, humid= FALSE,message=”yes”, AdditionalStats=”yes”, save.csv=”yes”)ETComparison Compare esimtated evapotranspiration among multiple sets of result DescriptionProduce comparison plots for results and statistics from different estimations produced by using different formulations and/or different input data. The number of different sets of results can be between 2 and 7. Plotting type can be selected among daily aggregation, monthly aggregation, annual aggregation, monthly average and annual average. For each type three comparison plots will be produced including time series, non-exceedance probability and box plot.62 ETComparison UsageETComparison(results1, results2, results3 = NULL, results4 = NULL, results5 = NULL, results6 = NULL, results7 = NULL, labs, Sdate = NULL, Edate = NULL,type = “Monthly”, ylim = rep(NA,2))Argumentsresults1results2results3results4results5results6results7labs SdateEdateylimtypeA list named results which has been derived from function ET which can be from any model such as Penman, Penman-Monteith or Priestley-Taylor.A list named results which has been derived from function ET which can be from any model such as Penman, Penman-Monteith or Priestley-Taylor.A list named results which has been derived from function ET which can be from any model such as Penman, Penman-Monteith or Priestley-Taylor. The default is NULL if the user requires the comparison between only two sets of results.A list named results which has been derived from function ET which can be from any model such as Penman, Penman-Monteith or Priestley-Taylor. The default is NULL if the user requires the comparison among only three sets of results.A list named results which has been derived from function ET which can be from any model such as Penman, Penman-Monteith or Priestley-Taylor. The default is NULL if the user requires the comparison among only four sets of results.A list named results which has been derived from function ET which can be from any model such as Penman, Penman-Monteith or Priestley-Taylor. The default is NULL if the user requires the comparison among only five sets of results.A list named results which has been derived from function ET which can be from any model such as Penman, Penman-Monteith or Priestley-Taylor. The default is NULL if the user requires the comparison among only six sets of results.A character vector with the length equal to the number of sets of results to com- pare, defining the labels for the comparison plotsOnly used when argument type is Daily, Monthly or Annual to define the start date for the plotting windows, which can be defined by user in the format YYYY- MM-DD; if missing the default is the first day of data is used.Only used when argument type is Daily, Monthly or Annual to define the end date for the plotting windows, which can be defined by user in the format YYYY- MM-DD; if missing the default is the last day of data is used.A numeric vector of length 2 defining the lower and upper limit of the y-axis for plotting, if missing the default is from 0 to 1.5 times of maximum value from the first set of result that is used to compare with others.A character string indicating the type of plot produced, can be one of the fol- lowing:ETForcingsValue63Daily – comparison plots of estimated daily evapotranspiration;Monthly – comparison plots of monthly aggregated evapotranspiration; Annual – comparison plots of annually aggregated evapotranspiration; MonthlyAve – comparison plots of monthly averaged daily evapotranspiration; AnnualAve – comparison plots of annually averaged daily evapotranspiration.Three plots are generated for each type of comparison plot selected, including:1) time series plot of the estimated/aggregated/averaged values from each set of result;2) non-exceedance plot of the distribution of estimated/aggregated/averaged values from each set of result;3) box plot of the distribution of estimated/aggregated/averaged values from each set of result.Author(s)Danlu GuoSee AlsoETPlotExamples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.Penman under the generic function ETresults_Penman <- ET.Penman(data, constants, ts=”daily”, solar=”sunshine hours”,wind=”yes”, windfunction_ver = “1948”, alpha = 0.08, z0 = 0.001)# Call ET.PenmanMonteith under the generic function ETresults_PenmanMonteith <- ET.PenmanMonteith(data, constants, ts=”daily”, solar=”sunshine hours”, wind=”yes”, crop = “short”)# Plot the estimated Penman open-water evaporation against average temperatureETComparison(results_Penman, results_PenmanMonteith, type = “Monthly”, ylim=c(0,400),labs=c(“Penman”,”PenmanMonteith”))ETForcings Plot esimtated evapotranspiration with climate variablesDescriptionProduce plot of daily, monthly and annual averaged estimated evapotranspiration with selected climate variables of the same time step.64 ETForcings UsageETForcings(data, results, forcing)ArgumentsdataresultsforcingA list of data named data which must contain a component with the name of a climate variable that the estimated evapotranspiration should be plotted against, see forcing.A list named results which has been derived from function ET.A character string as the name of a climate variable that the estimated evapo- transpiration should be plotted against, can be any of:Tmax – maximum temperature,Tmin – minimum temperature,u2 – average wind speed at 2m, uz – average wind speed,Rs – solar radiation,n – daily sunshine hours, Precip – precipitation,Epan – Class-A pan evaporation, RHmax – maximum relative humidity, RHmin – minimum relative humidity, Tdew – average dew point temeprature.ValueThree plots are generated for the response of calculated evapotranspiration to each climate variable, including:1) daily evapotranspiration estimate vs. daily average temperature;2) monthly mean daily evaporationion estimate vs. monthly average temperature;3) annual mean daily evaporationion estimate vs. annual average temperature.Author(s)Danlu GuoSee AlsoETPlotExamples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.Penman under the generic function ETresults <- ET.Penman(data, constants, ts=”daily”, solar=”sunshine hours”,wind=”yes”, windfunction_ver = “1948”, alpha = 0.08, z0 = 0.001)ETPlot 65# Plot the estimated Penman open-water evaporation against average temperatureETForcings(data, results, forcing = “Tmax”)ETPlot Plot the daily, monthly and annual aggregations of esimtated evapo- transpirationDescriptionProduce plot of aggregated estimations of evapotranspiration in daily, monthly and annual steps, or averaged daily estimations in monthly or annual steps.UsageETPlot(results, type = “Aggregation”, OBS, OBSplot, Sdate = time(results$ET.Daily)[1], Edate = time(results$ET.Daily)[length(results$ET.Daily)])Argumentsresults typeOBS OBSplotSdateEdateValueA list named results which has been derived from function ET..().A character string of either Aggregation or Average to indicate the type of plot required. The default is Aggregation. For aggregation plot the user can define the start and end date of plotting or by default using the calculation period for plotting. For average plot the plotting period equals to the calculation period.A list named OBS which has been derived from function ReadOBSEvaporation.Must be eith TRUE or FALSE. TRUE indicates that the observed evaporation will be plotted together with the estimations and FALSE indicates that the ob- servations will not be shown on the plots.Only used when type = Aggregation to define the start date for the plotting windows, the default is the first day for the estimate evapotranspiration, but can be defined by user in the format YYYY-MM-DD.Only used when type = Aggregation to define the end date for the plotting windows, the default is the last day for the estimate evapotranspiration, but can be defined by user in the format YYYY-MM-DD.If argument type is Aggregation, three plots are displayed in the following order (the next one appears after pressing enter):1) Daily evapotranspiration estimates;2) Monthly evapotranspiration estimates aggregated from daily estimates;3) Annual evapotranspiration estimates aggregated from daily estimates.If argument type is Average, two plots are displayed in the following order66E_OBS1) Monthly averaged daily estimations of evapotranspiration; 2) Annually averaged daily estiamtions of evapotranspriation.Author(s)Danlu GuoSee AlsoETComparisonExamples# Use processed existing data set and constants from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Call ET.Penman under the generic function ETresults <- ET.Penman(data, constants, ts=”daily”, solar=”sunshine hours”,wind=”yes”, windfunction_ver = “1948”, alpha = 0.08, z0 = 0.001)# Read evaporation datadata(“E_OBS”)OBS <- ReadOBSEvaporation(E_OBS, data)# Plot the aggregation of estimated Penman open-water evaporation with observed evaporation ETPlot(results, type = “Aggregation”, OBS, OBSplot = TRUE, Sdate = “2001-05-01”,Edate = “2004-05-01”)E_OBS Observed Class-A Pan Evaporation DescriptionThis data set contains the Class-A pan evaporation observed over the period between 1/3/2001 and 31/8/2004 at the Kent Town station in Adelaide, Australia.UsageclimatedataFormatA list containing 48 obserations of 5 variablesSourceBureau of Meteorology, Kent Town, Adelaide, AustraliaReadInputs 67ReadInputs ReadInputs raw date and climate dataDescriptionLoad raw date and climate data, perform pre-processing, check for missing and error entries and then compile data list of daily time step.UsageReadInputs(varnames, climatedata, constants, stopmissing, timestep = “daily”,interp_missing_days = FALSE,Argumentsvarnames interp_missing_entries = FALSE, interp_abnormal = FALSE, missing_method = NULL, abnormal_method = NULL, message = “yes”)A character vector with length equals to the number of climate variables to be processed. Can include any element from: Tmax, Tmin, Temp, Tdew, RHmax, RHmin, RH, Rs, n, Cd, Precip, uz, u2, Epan, va, vs.Each variable is detailed as below:Tmax – daily maximum temperature in degree Celcius,Tmin – daily minimum temperature in degree Celcius,Temp – subdaily temperature in degree CelciusTdew – dew point temperature in degree Celcius, either daily or subdaily ac- cepted,RHmax – daily maximum relative humidity in percentage,RHmin – daily minimum relative humidity in percentage,RH – subdaily relative humidity in degree Celcius,Rs – incoming solar radiation in Megajoules per square metres per day, either daily or subdaily accepted,n – daily sunshine hour in hours,Cd – daily cloud cover in oktas,Precip – precipitation in millimitres, either daily or subdaily accepted,u2 – wind speed measured at 2 metres from the ground surface in metres per second, either daily or subdaily accepted,uz – wind speed in metres per second, either daily or subdaily accepted,Epan – daily Class-A pan evaporation in millimitres,va – average vapour pressure in KPa, either daily or subdaily accepted,vs – saturated vapour pressure in KPa, either daily or subdaily accepted.68ReadInputsA data frame named “climatedata” containing the raw data of date and climate variables.The data frame must have objects named as Year, Month and Day to indicate the date.The climate variables to include should be consistent with varnames.In order to determine which variables are needed for ET estimation, please see ET for the specific data requirements for different formulations.Should be either daily or subdaily to specify the time step of raw climate data used.A list named “constants” consists of constants required for data pre-processing which may contain the following items:a_0, b_0, c_0, d_0.These four constants which are constants required to calculate daily sunshine hours from daily cloud cover (see Equation S3.10 in McMahon et al., 2012) – if the user requires such calculation these constants must be included in “con- stants”.The suggested values for various Australian locations are presented in Chiew and McMahon (1991), in which the four constants are named as a0, b0, c0, d0.A numeric vector of length 3:- the first value represents the maximum percentage of missing data that the user can tolerate;- the second value represents the maximum percentage of the duration of missing data to the total data duaration that the user can toleratre;- the third value represents the maximum percentage of missing days (within the date data, as a fraction of the total number of days) that the user can tolerate. All values should be numbers between 1 and 99.The percentages of the number and duration of missing data in the date data and each input variable are compared to the corresponding threshold; if any of the threshold is exceeded the program will be terminated due to unsatisfactory data quality.climatedatatimestepconstantsstopmissinginterp_missing_daysT or F, indicating if missing days (within the date data) should be interpolated, with a default of F which assigns NA to data at the missing days.interp_missing_entriesT or F, indicating if missing data entries within individual climate variables should be interpolated, with a default of F which assigns NA to the missing en- tries.interp_abnormalT or F, if abnormal values within individual climate variables should be interpo- lated, with a default of F which leaves the abnormal values unchanged. Abnormal values are defined differently according to the input variable, as fol- lowing:- Tmax > 100 or < -50 degree Celcius- Tmin > Tmax or < -50 degree Celcius – Temp > 100 or < -50 degree Celcius- Tdew > 100 or < -50 degree CelciusReadInputs69missing_methodA character string for the name of the interpolated methods chosen for filling in missing days and missing data entries. Can be either:monthly average – replacement with same-month average (adapted from Nara- pusetty et al., 2009);seasonal average – replacement with same-season average (adapted from Narapusetty et al., 2009);DoY average – replacement with same day-of-the-year average (Narapusetty et al., 2009);neighbouring average – interpolation between the two bounding values, which is only suitable for time increments in which values are available at adjacent in- crements (McMahon et al., 2013). When there is more than one consecutive missing entry, this interpolation fails, with a warning given.A character string for the name of the interpolated methods chosen for replacing data entries with abnormal values. Can be either:monthly average – replacement with same-month average (adapted from Nara- pusetty et al., 2009);seasonal average – replacement with same-season average (adapted from Narapusetty et al., 2009);DoY average – replacement with same day-of-the-year average (Narapusetty et al., 2009);neighbouring average – interpolation between the two bounding values, which is only suitable for time increments in which non-abnormal values are available at adjacent increments (McMahon et al., 2013). When there is more than one consecutive abnormal entry, this interpolation fails, with a warning given.”yes” or “no” indicating whether checking messages should be printed on screen.abnormal_methodmessageValue- RHmax > 100 or < 0 per cent- RHmin > RHmax or < 0 per cent – RH > 100 per cent
– Rs < 0 MJ.m^2- n < 0 hour- Cd < 0 Okta- Precip < 0 mm- uz < 0 m/s- u2 < 0 m/s- Epan < 0 mm- vs < 0 KPa- va < 0 KPaThis function returns a list with all components of class zoo which have been processed from the raw data, including:Date.daily A zoo object containing the date in daily step in the format of yyyy-mm-dd.70indaysTmaxTminu2uzRsnCdPrecipEpanRHmaxRHminTdewReadInputsA zoo object containing the date in daily step in the format of mmm-yyyy.A zoo object containing the Julian Day for every day during the period that thedata spans.A zoo object containing the month number for every day during the period that the data spans.A zoo object containing the number of days for every month during the period that the data spans.A zoo object containing the daily maximum temperatures in degree Celcius.A zoo object containing the daily minimum temperatures in degree Celcius.A zoo object containing the daily wind speed at 2m from the ground in m/s.A zoo object containing the daily wind speed measured at the height of wind instrument in m/s.A zoo object containing the daily solar radiation in MJ/m^2/day. A zoo object containing the daily sunshine hours.A zoo object containing the daily cloud cover in oktas.A zoo object containing the daily precipitation in mm.A zoo object containing the daily Class-A pan evaporation in mm.A zoo object containing the daily maximum relative humidity in percentage. A zoo object containing the daily minimum relative humidity in percentage. A zoo object containing the average daily dew temperatures in degree Celcius.Date.monthlyJNote that the components might have value of NULL when the corresponding input variable cannot be found in the raw data (i.e. “climatedata”).Author(s)Danlu GuoReferencesMcMahon, T., Peel, M., Lowe, L., Srikanthan, R. & McVicar, T. 2012. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences Discussions, 9, 11829-11910.Chiew, F. H. & McMahon, T. A. 1991. The applicability of Morton’s and Penman’s evapotranspi- ration estimates in rainfall-runoff modeling1. JAWRA Journal of the American Water Resources Association, 27, 611-620.Narapusetty, B., DelSole, T.Tippett, M.K. 2009, Optimal Estimation of the Climatological Mean. Journal of Climate, vol. 22, no. 18, pp. 4845-4859.See AlsoET,climatedata,dataReadOBSEvaporations 71 Examples# ReadInputs climate datadata(“climatedata”)data(“constants”)data <- ReadInputs(varnames = c(“Temp”,”Tdew”,”n”,”RH”,”uz”), climatedata, constants, stopmissing=c(10,10,3), timestep = “subdaily”, interp_missing_days = FALSE, interp_missing_entries = FALSE, interp_abnormal = FALSE, missing_method = NULL, abnormal_method = NULL)ReadOBSEvaporations Read Raw Data of Observed Evaporation from fileDescriptionLoad raw date and evaporation data and then compile data list of daily time step.UsageReadOBSEvaporation(E_OBS, data)ArgumentsE_OBS A list of evaporation data named E_OBS which must contain the following columns: Year, Month, Day as the date and,EVAP.Obs as the observed evaporation in mm.The observations can be of daily and monthly time steps and must match with the corresponding dates recorded.data A list of data named data which contains data of climate variables over the same period as the evaporation dataValueThis function returns a list with all components of class zoo which have been processed from the raw data, including:Date.OBSE_obs.DailyE_obs.MonthlyE_obs.AnnualA zoo object containing the date data with time step consistent with the raw evaporation data in E_OBS.A zoo object containing the daily evaporation data.A zoo object containing the monthly aggregaated observed evaporation in mm. A zoo object containing the annually aggregated observed evaporation in mm.72ReadOBSEvaporationsE_obs.MonthlyAveA zoo object containing the monthly averaged daily evaporation from observa- tion in mm/day.E_obs.AnnualAveA zoo object containing the annually average daily evaporation from observation in mm/day.Note that the components might have value of NULL when the corresponding raw data cannot be found in E_OBS.Author(s)Danlu GuoExamples# Get the time period from “data”# Use processed existing data set from kent Town, Adelaidedata(“processeddata”)data(“constants”)# Reading obsevations of evaporation within specified time perioddata(“E_OBS”)OBS <- ReadOBSEvaporation(E_OBS, data)Index∗Topic ASCE ET.PenmanMonteith, 46∗Topic Abtew ET.Abtew, 8∗Topic BlaneyCriddle ET.BlaneyCriddle, 10∗Topic Brutsaert-Strickler ET.BrutsaertStrickler, 13∗Topic Chapman ET.ChapmanAustralian, 15∗Topic Class-A pan evaporation ET.PenPan, 49∗Topic FAO-56 ET.PenmanMonteith, 46∗Topic Granger-Gray ET.GrangerGray, 18∗Topic Hamon ET.Hamon, 21∗Topic Hargreaves-Samani ET.HargreavesSamani, 23∗Topic Jensen-Haise ET.JensenHaise, 25∗Topic Linacre ET.Linacre, 27∗Topic Makkink ET.Makkink, 29∗Topic Matt-Shuttleworth ET.MattShuttleworth, 31∗Topic McGuinness-Bordne ET.McGuinnessBordne, 34∗Topic MortonCRAE ET.MortonCRAE, 36∗Topic MortonCRWE ET.MortonCRWE, 39∗Topic PenPan ET.PenPan, 49∗Topic Penman-Monteith ET.PenmanMonteith, 46∗Topic PenmanET.Penman, 42∗Topic Priestley-TaylorET.PriestleyTaylor, 52 ∗Topic ReadInputsReadInputs, 67 ∗Topic ReadingReadOBSEvaporations, 71 ∗Topic Reference cropevapotranspirationET.PenmanMonteith, 46 ∗Topic RomanenkoET.Romanenko, 54 ∗Topic Szilagyi-JozsaET.SzilagyiJozsa, 56 ∗Topic TurcET.Turc, 59 ∗Topic actual arealevapotranspirationET.BrutsaertStrickler, 13ET.MortonCRAE, 36∗Topic actual evapotranspirationET.Abtew, 8 ET.Linacre, 27 ET.SzilagyiJozsa, 56∗Topic climate ETComparison, 61ETForcings, 63∗Topic data pre-processingReadInputs, 67 ∗Topic datasetsclimatedata, 2 constants, 3data, 5 defaultconstants, 5 E_OBS, 66∗Topic evapotranspiration ET, 6ET.Abtew, 8 ET.BlaneyCriddle, 107374INDEXET.BrutsaertStrickler, 13 ET.ChapmanAustralian, 15 ET.GrangerGray, 18 ET.Hamon, 21 ET.HargreavesSamani, 23 ET.JensenHaise, 25 ET.Linacre, 27 ET.MattShuttleworth, 31 ET.McGuinnessBordne, 34 ET.MortonCRAE, 36 ET.Penman, 42 ET.PenmanMonteith, 46 ET.PenPan, 49 ET.PriestleyTaylor, 52 ET.Romanenko, 54 ET.SzilagyiJozsa, 56 ET.Turc, 59ETComparison, 61 ETForcings, 63ETPlot, 65ReadInputs, 67 ReadOBSEvaporations, 71ET.PenPan, 49ET.Romanenko, 54 ∗Topic reference cropevapotranspirationET.BlaneyCriddle, 10 ET.HargreavesSamani, 23 ET.Makkink, 29 ET.MattShuttleworth, 31 ET.Turc, 59∗Topic shallow lake ET.MortonCRWE, 39∗Topic wet-environment areal evapotranspirationET.MortonCRAE, 36∗Topic forcing ETComparison, 61ETForcings, 63 ∗Topic observationReadOBSEvaporations, 71 ∗Topic open-water evaporationET, 6 ET.GrangerGray, 18 ET.MortonCRWE, 39 ET.Penman, 42∗Topic plot ETComparison, 61ETForcings, 63ETPlot, 65∗Topic potential evaporationET.PriestleyTaylor, 52∗Topic potential evapotranspirationET, 6 ET.ChapmanAustralian, 15 ET.GrangerGray, 18 ET.Hamon, 21 ET.JensenHaise, 25 ET.McGuinnessBordne, 34 ET.MortonCRAE, 36 ET.MortonCRWE, 39 ET.Penman, 42climatedata, 2, 70constants, 3, 6, 10, 12, 15, 18, 20, 24, 27, 28,31, 33, 35, 39, 42, 45, 48, 51, 54, 58, 61data, 5, 10, 12, 15, 18, 20, 22, 24, 27, 28, 31, 33, 35, 39, 42, 45, 48, 51, 54, 55, 58,61, 70defaultconstants, 5, 5, 10, 12, 15, 18, 20,24, 27, 28, 31, 33, 35, 39, 42, 45, 48, 51, 54, 58, 61E_OBS, 66ET, 2, 3, 5, 6, 10, 12, 15, 18, 20, 22, 24, 27, 28,31, 33, 35, 45, 48, 51, 54, 55, 58, 61,68, 70 ET.Abtew, 8ET.BlaneyCriddle, 10 ET.BrutsaertStrickler, 13 ET.ChapmanAustralian, 15 ET.GrangerGray, 18 ET.Hamon, 21 ET.HargreavesSamani, 8, 23 ET.JensenHaise, 25 ET.Linacre, 27 ET.Makkink, 7, 29 ET.MattShuttleworth, 31 ET.McGuinnessBordne, 34 ET.MortonCRAE, 36 ET.MortonCRWE, 39, 39, 42 ET.Penman, 7, 20, 42, 58 ET.PenmanMonteith, 7, 46 ET.PenPan, 18, 49 ET.PriestleyTaylor, 7, 52INDEX 75ET.Romanenko, 54 ET.SzilagyiJozsa, 56 ET.Turc, 59 ETComparison, 61, 66 ETForcings, 63 ETPlot, 63, 64, 65ReadInputs, 67 ReadOBSEvaporation(ReadOBSEvaporations), 71 ReadOBSEvaporations, 71