PR-ET Version 1.0

 

Puerto Rico EvapoTranspiration Estimation Computer Program

 

 

USER’S MANUAL

 

 

 

 

 

 

 

 

 

 

 

 

 

University of Puerto Rico-Mayagüez Campus

Department of Agricultural and Biosystems Engineering

and

University of Puerto Rico Experiment Station-Rio Piedras

 

 

 

 

 

 

July 2002


 

 

PR-ET Version 1.0

 

Puerto Rico EvapoTranspiration 

Estimation Computer Program

 

 

USER’S MANUAL

 

 

 

 

Prepared by

 

Eric W. Harmsen[1] and Antonio Luis González Pérez[2]

 

 

 

 

 

 

 

 

University of Puerto Rico-Mayagüez Campus

Department of Agricultural and Biosystems Engineering

and

University of Puerto Rico Experiment Station-Rio Piedras

 

 

 

July 2002


 

Acknowledgements

 

Funding Support

Funding support for the Puerto Rico EvapoTranspiration (PR-ET) Estimation Computer Program (Version 1.0) code development was provided by University of Puerto Rico Experiment Station Grant SP-347. 

 

Disclaimer of Warranty

 

The PR-ET (Version 1.0) computer code is provided without any warranty.  We make no warranties, express or implied, that the PR-ET code is free of errors or whether it will meet your need for solving a particular problem.  You use the code at your own risk.  The authors disclaim all liability for direct or consequential damage resulting from the use of the code.

 

For Other Information Please Contact:

 

Eric Harmsen, Ph.D., P.E.

Assistant Professor of Agricultural and Biosystems Engineering

P.O. Box 9030

University of Puerto Rico-Mayagüez Campus

Mayagüez, PR 00681-9030

Telephone: (787)834-2575

Email: eric_Harmsen@cca.uprm.edu


ABSTRACT

 

Puerto Rico EvapoTranspiration (PR-ET) Estimation Computer Program calculates the mean monthly average crop evapotranspiration at any location in Puerto Rico.  With only the site latitude and elevation, and specification of the Climate Division, the program calculates all the climate data necessary as input to the Penman Monteith reference evapotranspiration method.  Alternatively, the user can enter monthly average climate data manually into the Windows-based computer program.  In this mode the program can be used anywhere in the world.  The program currently included crop coefficient data for fifteen vegetable crops. 

 

 

 


TABLE OF CONTENTS

 

 

Acknowledgements. 3

Funding Support 3

Disclaimer of Warranty. 3

ABSTRACT. 4

TABLE OF CONTENTS. 5

LIST OF FIGURES. 6

1. INTRODUCTION.. 7

2. THEORY AND CALCULATIONS. 8

2.1 Evapotranspiration. 8

2.2 Climate Parameter Estimation. 8

2.2.1 Minimum and Maximum Air Temperature. 9

2.2.2 Dew Point Temperature. 9

2.2.3 Wind Speed. 10

2.2.4 Solar Radiation. 11

2.3 Crop Coefficients. 12

2.4 Crop Evapotranspiration. 12

3. INPUTTING DATA.. 13

4. OUTPUTTING DATA.. 19

5. EXAMPLE PROBLEMS. 22

5.1 Example 1 - Manual Entry of Climate Data. 22

5.2 Example 2 - Automatic Calculation of Climate Data. 33

6. HELP. 38

7. LIMITATIONS. 39

8. REFERENCES. 40

 


LIST OF FIGURES

Figure 1.  Climate Divisions of Puerto Rico:  1, North Coastal; 2, South Coastal; 3, Northern Slopes; 4, Southern Slopes; 5, Eastern Interior; and 6, Western Interior. 10

Figure 2. The PR-ET computer program introductory page. 13

Figure 3. Initial data input page. 15

Figure 4. Selection of data input method. 16

Figure 5. Manual input table for minimum air temperature. 17

Figure 7. Climate Division selection screen. 18

Figure 8. Screen printout of monthly average climate data and reference evapotranspiration. 19

Figure 9. Output screen for daily average crop coefficient, reference evapotranspiration, and crop evapotranspiration. 20

Figure 10. Graph of crop coefficient, reference evapotranspiration, and crop evapotranspiration versus time. 21

Figure 11. Initial input page for Example 1. 22

Figure 12. Selection of data input method for Example 1. 23

Figure 13. Manual input table for minimum air temperature for Example 1. 24

Figure 14. Manual input table for maximum air temperature for Example 1. 25

Figure 15. Manual input table for solar radiation for Example 1. 26

Figure 16. Manual input table for wind speed for Example 1. 27

Figure 17. Manual input table for relative humidity for Example 1. 28

Figure 18. Screen printout of monthly average climate data and reference evapotranspiration for Example 1. 29

Figure 19. Output screen for daily average crop coefficient, reference evapotranspiration, and crop evapotranspiration for Example 1. 30

Figure 20. Graph of crop coefficient, reference evapotranspiration, and crop evapotranspiration versus time for Example 1. 31

Figure 21. Saving output data to a file. 32

Figure 22. Initial input screen for Example 2. 33

Figure 23. Selection of data input method for Example 2. 34

Figure 24. Climate Division selection screen for Example 2. 35

Figure 25. Screen printout of monthly average climate data and reference evapotranspiration for Example 2. 36

Figure 26. Output screen for daily average crop coefficient, reference evapotranspiration, and crop evapotranspiration for Example 2. 37

Figure 27. Graph of crop coefficient, reference evapotranspiration, and crop evapotranspiration versus time for Example 2. 38

 

LIST OF TABLES

 

Table 1. Relationships among temperatures (T) and elevations (Z) for 9

Table 2. Temperature correction Factor Kcorr used in Equation 2 for Climate Divisions1 within Puerto Rico. 10

Table 3. Average Daily Wind Speeds (U2) by Month and Climate Division1 within Puerto Rico. 11

 


1. INTRODUCTION

 

       This document provides information about the PR-ET computer program.  The purpose of the program is to estimate mean daily values of evapotranspiration for fifteen vegetable crops in Puerto Rico.  The program utilizes the Penman Monteith method for estimating reference evapotranspiration (ETo).  Crop coefficients (Kc) are provided internally for the fifteen vegetable crops.  Additional crops can be evaluated if the user provides values of the crop coefficient. 

 

       Estimates of crop evapotranspiration are useful for planning irrigation systems and scheduling irrigation applications.  In Puerto Rico, irrigation is needed to supplement rainfall during certain months of the year.  This is especially true in the southwest Puerto Rico where the climate is considered to be semi-arid and evapotranspiration greatly exceeds rainfall.  Estimation of the evapotranspiration is also important for hydrologic and environmental studies.    

 

       PR-ET provides estimates of potential evapotranspiration.  Potential evapotranspiration is the estimated evapotranspiration for a crop that does not experience water stress at any time during the crop season.  Allen et al. (1998) provide a method for incorporating the effects of crop water stress that could be used in combination with estimates of crop evapotranspiration derived from the PR-ET computer program.

 

       The program operates in two modes: manual climate data input and automatic estimation of the climate input data.  In the first case the user enters average monthly data.  In the second case the program estimated long-term average monthly climate data based on procedures described in Harmsen et al. (2002).  The procedures are described in the following section. 

 

        

 

 


2. THEORY AND CALCULATIONS

 

2.1 Evapotranspiration

 

Evapotranspiration (ETc) is defined as the combination of evaporation from soil and plant surfaces, and transpiration from plant leaves.  Evaporation is the process whereby liquid water is converted to water vapor and removed from the evaporating surface (Allen et al., 1998).  Transpiration is the vaporization of liquid water contained in plant tissues and its subsequent removal to the atmosphere.  Crops predominately loss water through small openings in their leaves called stomata.  Evapotranspiration estimates from PR-ET are expressed in units of mm/day. 

 

Crop evapotranspiration (ETc) can be defined as the product of a reference evapotranspiration (ETo) and crop coefficient (Kc):

 

ETc = Kc ETo                                                                                                              (1)

 

       The crop coefficient (Kc) accounts for the effects of characteristics that distinguish the field crop from the grass reference crop (Allen et al., 1998).  The reference evapotranspiration is defined as the evapotranspiration from an extended surface of 0.08 to 0.15 m tall, green grass cover of uniform height, actively growing, completely shading the ground and not short of water (Doorenbos and Pruitt, 1977).  Numerous mathematical expressions have been developed for ETo.  One such expression, which has been shown to have global validity and is recommended by the United Nations Food and Agriculture Organization (FAO) is the Penman-Monteith equation (Allen et al., 1998):

                         (2)

 

where D = slope of the vapor pressure curve, Rn = net radiation, G= soil heat flux density, g = psychrometric constant, T = mean daily air temperature at 2 m height, u2 = wind speed at 2 m height, es is the saturated vapor pressure and ea is the actual vapor pressure.  Equation 4 applies specifically to a hypothetical reference crop with an assumed crop height of 0.12 m, a fixed surface resistance of 70 sec/m and an albedo of 0.23.  PR-ET uses equation 2 to estimate reference evapotranspiration.

 

2.2 Climate Parameter Estimation

 

       Estimation procedures are presented below for long-term average daily climate parameters on a monthly basis for Puerto Rico.  The FAO recommends using the Penman-Monteith method over all other methods even when local data is missing.  Studies have shown that using estimation procedures for missing data with the Penman-Monteith equation will generally provide more accurate estimates of ETo than will other available methods requiring less input data (Allen et al., 1998).  Climate data include: minimum air temperature (Tmin), maximum air temperature (Tmax) , dew point temperature (Tdew), solar radiation (Rs) and wind speed (U).  A more detailed description of the method background and a validation of the methodology can be in Harmsen et al. (2002), Harmsen and Torres Justiniano (2001a and 2001b), and Harmsen et al. 2001. 

 

2.2.1 Minimum and Maximum Air Temperature

 

Goyal et al. (1988) developed regression equations for minimum and maximum long-term average daily air temperatures for Puerto Rico based on surface elevation.  Table 1 lists the regression coefficients for the daily average minimum and maximum air temperatures in Puerto Rico by month.  The regression equations have the following general form: 

 

T = A – (B.10-5 ).Z                                                                                                      (3)

 

where T is temperature (oC), A and B are regression coefficients and Z is elevation (m) above mean sea level. 

 

Table 1. Relationships among temperatures (T) and elevations (Z) for

Puerto Rico (Goyal et al., 1988)1

 

Mean Daily Maximum Temperatures, oC

Mean Daily Minimum Temperatures, oC

Month

A

B

r2

A

B

r2

Jan.

29.24

770

0.73

18.58

544

0.44

Feb.

29.37

752

0.72

18.37

558

0.46

Mar.

30.08

711

0.71

18.71

590

0.48

Apr.

30.59

687

0.71

19.9

686

0.63

May

31.16

707

0.76

21.23

608

0.63

Jun.

31.76

686

0.73

21.92

577

0.59

Jul.

32.07

717

0.64

22.14

591

0.58

Aug.

32.12

682

0.75

22.21

585

0.58

Sep.

32.12

696

0.79

21.95

586

0.62

Oct.

31.84

705

0.79

21.48

553

0.59

Nov.

30.89

706

0.75

20.68

562

0.55

Dec.

29.83

744

0.73

19.52

547

0.47

1 T = A – (B. 10-5 ) Z, where T = temperature, oC; Z = elevation above mean sea level, m; and A and

B are regression coefficients and r2 is the coefficient of determination.

 

 

2.2.2 Dew Point Temperature

 

The FAO  (Allen et al., 1998) has reported that Tdew can be estimated on the basis of the daily minimum air temperature.  A correction factor based on local conditions should be added to the minimum temperature as follows:

 

Tdew = Tmin + Kcorr                                                                                                (4)

 

where Kcorr is a temperature correction factor in degrees oC, listed in Table 2.  Correction factors (Kcorr) were calibrated for three of the six Climate Divisions of Puerto Rico as defined by the U.S. National Oceanic and Atmospheric Administration (NOAA), and are presented in Table 2.  Figure 1 shows the Climate Divisions for Puerto Rico.  A climate division is defined as region possessing similar climatic characteristics.  Long-term average Tdew data were not available for Climate Divisions 3, 5 and 6, therefore, these Divisions were assigned a value of 0 oC similar to that of Division 4 (humid conditions). 

 

Table 2. Temperature correction Factor Kcorr used in Equation 2 for Climate Divisions1 within Puerto Rico.

Climate Division1

1

2

3,4,5,6

Kcorr (oC)

1.0

-2.9

0

1 See Figure 1 for Climate Divisions

 

Figure 1.  Climate Divisions of Puerto Rico:  1, North Coastal; 2, South Coastal; 3, Northern Slopes; 4, Southern Slopes; 5, Eastern Interior; and 6, Western Interior.

 

2.2.3 Wind Speed

 

The Penman-Monteith method is based on a wind speed measured 2 m above the ground and is referred to as U2.  Wind speeds that are collected at heights other than 2 m above the ground were adjusted to the U2 value using an exponential relationship.  Table 3 presents U2 values for Puerto Rico.  These wind speeds were estimated by averaging station data within the Climate Divisions established by the NOAA. 

 

 

Table 3. Average Daily Wind Speeds (U2) by Month and Climate Division1 within Puerto Rico.

 

Average Daily Wind Speeds at 2 m Above the Ground (m/s)2

Climate Division1

Jan

Feb

Mar

Apr

May

June

July

Aug

Sept

Oct

Nov

Dec

1

2.7

2.8

3.0

2.9

2.6

2.6

2.9

2.7

2.1

1.9

2.2

2.6

2

1.8

2.0

2.2

2.1

2.2

2.4

2.4

2.1

1.7

1.5

1.4

1.5

3

2.2

2.4

2.6

2.4

2.2

2.4

2.7

2.5

2.0

1.8

2.0

2.3

4

1.8

2.0

2.1

2.1

2.0

2.0

2.0

1.8

1.6

1.6

1.6

1.6

5

1.1

1.3

1.4

1.5

1.6

1.7

1.6

1.3

1.1

0.9

0.9

0.9

6

1.3

1.5

1.5

1.5

1.6

1.8

1.8

1.5

1.2

1.1

1.0

1.0

1 See Figure 1 for Climate Divisions

2 Averages are based on San Juan and Aguadilla for Div. 1; Ponce, Aguirre, Fortuna and Lajas, for Div. 2; Isabela and Río Piedras for Div. 3; Mayagüez, Roosevelt Rd. and Yabucoa for Div. 4; Gurabo for Div. 5; and Corozal and Adjuntas for Div. 6.  Measured wind speeds were adjusted to the wind speed 2 m above the ground (U2) using the following equation: U2 = (4.87Uz)/[ln(67.8z-5.42)], where Uz  in m/sec is the wind speed at height z  in meters above the ground. 

 

2.2.4 Solar Radiation

 

The FAO recommends that solar radiation be estimated by using the following equation for islands:

 

Rs = (0.7 Ra - b)                                                                                                         (5)

 

where Rs is solar radiation, b is an empirical constant equal to 4 mega-joules per meter squared per day (MJ m-2 day-1) and Ra is the incoming extraterrestrial radiation given by the following equation:

 

Ra = (24*60/π) Gsc dr [ωssin(φ) sin(δ) + cos(φ) cos(δ) sin(ωs)]                                    (6)

 

 

where Gsc is a solar constant equal to 0.0820 MJ m-1 min-1, and dr is the inverse relative distance Earth-Sun equal to

 

dr = 1 + 0.033 cos(2π J / 365)                                                                                    (7)

where J is a number of the day in the year between 1 (1 January) and 365 or 366 (31 December).  For estimating the long-term average daily reference evapotranspiration by month, J is equal to 15 for January, 45 for February, 75 for March, and so on.   The sunset hour angle ωs is give by

 

ωs = arccos[-tan(φ)tan(δ)]                                                                                           (8)

 

The solar declination (radians) is given by

 

δ = 0.409 sin[(2π J / 365) – 1.39]                                                                               (9)

 

In the above equations, the latitude φ  must be in radians.  The conversion from decimal degrees to radians is

 

[Radians] =  (π/180) [decimal degrees]                                                                        (10)

 

It should be noted that the only input required to use equation 6 is the day of the year (J) and the site latitude (φ).  For a more detailed discussion of the calculation of Ra, the reader is referred to Allen et al. (1998).

 

Equation 5 is limited to elevations of less than 100 m above sea level.  Therefore, for higher elevations, in the interior areas of Puerto Rico, where the ocean does not moderate air temperatures as much as along the low altitude coastal areas, the Hargreaves radiation formula should be used:

 

Rs = kRs (Tmax – Tmin)1/2 Ra                                                                                   (11)

 

where kRs is an adjustment factor equal to 0.19. 

 

2.3 Crop Coefficients

 

Crop coefficients (Kc) for fifteen vegetable crops are provided within the PR-ET computer program.  These crop coefficients were obtained from the United Nations Food and Agriculture Organization (FAO) Paper No. 56 (Allen et al., 1998). 

 

       In the program, the value of Kc,ini is adjusted to account for  type of irrigation used, soil type and depth of irrigation applied.  A description of this adjustment is provided in Allen et al. (1998).  If drip irrigation is used, 40 percent of the surface is assumed to be wetted by the drip emitter.  With flood and sprinkler irrigation, 100% of the surface is assumed to be wet.  Values of Kc,mid and Kc,end are adjusted for the monthly minimum relative humidity and wind speed as described in Allen et al. (1998).

 

2.4 Crop Evapotranspiration

 

       PR-ET calculates the crop evapotranspiration using equation 1.  Monthly average values of ETo are interpolated to obtain the daily values throughout the crop season.  The adjusted values of Kc,ini and Kc,mid are used during the initial and mid crop growth stages, respectively.  The Kc values used between the last day of the initial stage and the first day of the mid stage is a linear interpolation between the Kc,ini and Kc,mid values.  The Kc values used between the last day of the mid stage and the last day of the crop season is a linear interpolation between the Kc,mid and Kc,end values.    Daily values of Kc and ETo are multiplied to obtain daily values of ETc throughout the crop season.

 


3. INPUTTING DATA

 

       The program can be started by double clicking on the program icon (PR-ET.EXE).  After the program is started the introductory page will appear on the screen (Figure 2). 

 

Figure 2. The PR-ET computer program introductory page.

 

 

 

       By clicking on the OK button on the introductory page, the first input page will appear. 

 

Crop:      In this menu you can select from fifteen vegetable crops.  If your crop is not shown in the list select Other.

 

Location:       Enter the location of your site (e.g., Juana Diaz)

 

Latitude:       Enter the site latitude in decimal format.  The value of site latitude can be obtained from maps commonly available (e.g., topographical map). To convert a latitude from degrees and minutes to degrees decimal, divide the minutes part by 60 and add to the degree part.  For example 18o30’ is 18 + 30/60 =18.5o. 

 

Elevation:  Enter the average site elevation in meters above mean sea level.

 

Interval Between Irrigations:   This is the average number of days between irrigation applications.  For example if you typically irrigate once every four days you would enter 4.  This number is used in determining the amount of water that evaporates from the soil early in the season before the crop fully shades the soil.

 

Depth of Irrigation:  The is the equal to the total volume of irrigation water divided  by the field area. 

 

Type of Soil:                Select either fine or course textured soil.

 

Planting Date:             Enter the date that the crop will be planted.

 

Type of Irrigation:      Select drip, spray or surface irrigation.

 

Length of Initial Crop Stage:    Enter the length of initial crop stage in days.  The initial crop stage starts at planting and ends as soon as the crop enters the development crop stage.  The initial crop stage is characterized by little to no crop growth. 

 

Length of Development Crop Stage:  Enter the length of development crop stage in days.  The development crop stage is characterized by rapid growth.  This stage terminates when the mid crop stage is reached.

 

Length of Mid Crop Stage:  Enter the length of mid crop stage in days.  The mid crop stage is occurs when the plants are at maximum height and transpiration is maximum.  This stage terminates when the end crop stage is reached.

 

Length of End Crop Stage: Enter the length of end crop stage in days.  The end crop stage is characterized by a reduction in plant area as the plant.  This stage terminates at the end of the crop season.

 

If site-specific data are not available for the length of the initial, development, mid and end crop stages, estimates can be obtained from Allen et al. (1998).

 

 

 

 

 

 

Figure 3. Initial data input page.

 

      


After entering the data shown in Figure 3 and clicking on the Next button, the screen shown in Figure 4 will appear.  By selecting Enter Climate Data it will be necessary to enter the monthly values for minimum and maximum air temperature, relative humidity, wind speed and solar radiation.  Figure 5 shows the manual input screen for the Minimum Air Temperature.  Input for other climate parameters are similar to Figure 5.

 

 

 

Figure 4. Selection of data input method.

 

 

Figure 5. Manual input table for minimum air temperature.

 

 

 

 

      


It is possible to have the program estimate all of the climate input data by selecting Have Program Calculate Climate Data (Figure 4).  If this approach is selected the user must specify the Climate Division in Puerto Rico where the site is located. This screen is shown in Figure 7. 

 

 

 

 

 

Figure 7. Climate Division selection screen.

 

 

 

After clicking the Next button on the screen shown in Figure 7, the program will calculate the daily crop coefficient, reference evapotranspiration and crop evapotranspiration. 

 

 


4. OUTPUTTING DATA

 

Figure 8 shows the first output screen, which includes the average monthly minimum air temperature, maximum air temperature, relative humidity, wind speed, solar radiation and the estimated reference evapotranspiration.  If desired the data can be saved to a text file for post-processing in another program (e.g., Microsoft Excel).

 

 

 

Figure 8. Screen printout of monthly average climate data and reference evapotranspiration.

 

The next screen gives the estimated crop coefficient, reference evapotranspiration and crop evapotranspiration.  The data can be saved to a file if desired.  Note that these data, unlike those shown in Figure 8, are daily average values.  By clicking on the Graph button a graph will appear on the screen showing crop coefficient, reference evapotranspiration and crop evapotranspiration versus time.  From this screen the user may terminate the program by clicking on the End Program button or perform another analysis by clicking on the Restart Program button.

 

 

 

 

 

 

 

Figure 9. Output screen for daily average crop coefficient, reference evapotranspiration, and crop evapotranspiration.

 

 

 

Figure 10. Graph of crop coefficient, reference evapotranspiration, and crop evapotranspiration versus time.

 

 

 

 

 

 

 

 


5. EXAMPLE PROBLEMS

 

       Two example problems are provided that illustrate the use of PR-ET.  Example 1 shows how to enter input data manually.  In this mode, the evapotranspiration can be estimated at any location in the world.  Example 2 shows how to use the computer program to automatically calculate the climate input data.  In this mode, estimation of evapotranspiration is limited to Puerto Rico.

 

5.1 Example 1 - Manual Entry of Climate Data

 

       In this example input data for San Juan, PR was used.  This initial input data screen is shown in Figure 11.  In this example the daily evapotranspiration will be determined for a sweet pepper crop starting on January 20th.

 

Figure 11. Initial input page for Example 1.

 


       In this example climate data will be entered manually.  Therefore, Enter Climate Data icon was selected (Figure 12). 

 

 

 

Figure 12. Selection of data input method for Example 1.

 


Figures 13 through 17 show the climate data input screens.  Minimum and maximum air temperature, wind speed, solar radiation and dew point temperature were obtained from the International Station Meteorological Climate Summary (National Climate Data Center, 1992) for San Juan.  Dew point temperatures were converted to relative humidity for entry into the computer program.  The manual data entry approach utilizes relative humidity instead of dew point temperature because it is usually more readily available.  Note that the Height of the Wind Speed Measurement in Figure 16 was set to 10 meters (San Juan Airport weather station height).  Within program, the wind speed values are converted to the wind speed at 2 m above the ground (u2) for use in the Penman-Monteith equation (Equ. 2). 

 

 

 

 

Figure 13. Manual input table for minimum air temperature for Example 1.

 

 

Figure 14. Manual input table for maximum air temperature for Example 1.

 

 

Figure 15. Manual input table for solar radiation for Example 1.

 

 

 

Figure 16. Manual input table for wind speed for Example 1.

 

 

 

 

Figure 17. Manual input table for relative humidity for Example 1.

 


Figure 18 shows the monthly climate data and the estimated reference evapotranspiration (ETo) for Example 1.  Figure 19 shows the daily estimated values of crop coefficient, reference evapotranspiration, and crop evapotranspiration.  For convenience, definitions of the variables can be found by clicking on the Definitions icon.  Note that the date column uses the international format for date (i.e., day/month).  Although the initial input screen (Figure 11) allows the user to enter the year, it has no influence on the results and therefore is not shown in Figure 19.  By clicking on the Graph icon the estimated crop coefficient, reference evapotranspiration, and crop evapotranspiration versus time graph can be seen (Figure 20).   Alternatively the output data can be saved to a file by clicking on the Save icon (Figure 21).

 

 

Figure 18. Screen printout of monthly average climate data and reference evapotranspiration for Example 1.

 

 

 

Figure 19. Output screen for daily average crop coefficient, reference evapotranspiration, and crop evapotranspiration for Example 1.

 

 


 

 

 

 

 

 

Figure 20. Graph of crop coefficient, reference evapotranspiration, and crop evapotranspiration versus time for Example 1.

 

 

 

Figure 21. Saving output data to a file.

 

 

 

 


5.2 Example 2 - Automatic Calculation of Climate Data

 

In this example input data for Ponce, PR was used.  This initial input data screen is shown in Figure 22.  In this example the daily evapotranspiration will be determined for a watermelon crop starting on November 20th.

 

 

Figure 22. Initial input screen for Example 2.

 


       In this example climate input data will be estimated automatically.  Therefore, the Have Program Calculate Climate Data icon was selected (Figure 23). 

 

 

 

 

Figure 23. Selection of data input method for Example 2.

 

 


In this mode (automatic climate data estimation) it is necessary to select the Climate Division that the site is located within.  Ponce is located within Climate Division 2 (Figure 24).

 

 

Figure 24. Climate Division selection screen for Example 2.

 


Figure 25 shows the monthly climate data and the estimated reference evapotranspiration (ETo) for Example 2.  Figure 26 shows the daily estimated values of crop coefficient, reference evapotranspiration, and crop evapotranspiration.  For convenience, definitions of the variables can be found by clicking on the Definitions icon.  By clicking on the Graph icon the estimated crop coefficient, reference evapotranspiration, and crop evapotranspiration versus time graph can be seen (Figure 27).  

 

 

Figure 25. Screen printout of monthly average climate data and reference evapotranspiration for Example 2.

 

 

 

 

Figure 26. Output screen for daily average crop coefficient, reference evapotranspiration, and crop evapotranspiration for Example 2.

 

 

 

 

 

Figure 27. Graph of crop coefficient, reference evapotranspiration, and crop evapotranspiration versus time for Example 2.

 

 

 

 

6. HELP

      

       Help is available while running the program by clicking on the Help command located in the upper left corner of the screen.  An Adobe Acrobat Reader version of this manual will appear, which can be referred to for help in understanding and running the program.  If you do not have Adobe Acrobat Reader on your computer you can download a free copy from the following website: 

 

http://www.adobe.com/products/acrobat/readstep2.html

 

Note that by consulting the online help document you can click on any item of interest in the table and contents and the get to that section of the text.

 

       In additional to the Help command, the Definitions icon on the output screens can be clicked to view definitions of variables used in the program.  Units of the variables are also provided.

 

 

7. LIMITATIONS

 

The climate estimation procedure presented in Section 2.2 should be considered only approximate for estimating reference evapotranspiration.  Some potential limitations include:

 


8. REFERENCES

 

Allen, R. G., L. S. Pereira, Dirk Raes and M. Smith, 1998. Crop Evapotranspiration Guidelines for Computing Crop Water Requirements.  FAO Irrigation and Drainage Paper 56, Food and Agriculture Organization of the United Nations, Rome.

Capiel, M. and R. J. Calvesbert, 1976. On the climate of puerto rico and its agricultural water balance.  J. of Agric. Univ. P.R. 60(2):139-153.

Doorenbos, J. and W.O. Pruitt, 1977. Guidelines for Predicting Crop Water Requirements. FAO Irrigation and Drainge Paper 24, Revised.  United Nations, Rome.

Goyal, M. R., E. A. Gonzalez and C. Chao de Baez,  1988. Temperature versus elevation relationships for Puerto Rico, J. of Agric. Univ. P.R. 72(3):440-467.

Harmsen, E. W., M. R. Goyal, and S. Torres Justiniano, 2002. Estimating Evapotranspiration in Puerto Rico. Puerto Rico Journal of Agriculture. In Press

Harmsen, E. W. and S. Torres Justiniano, 2001a. Estimating Island-Wide Reference Evapotranspration for Puerto Rico Using the Penman-Monteith Method.  ASAE Paper No. 01-2174. 2001 ASAE Annual International Meeting, Sacramento Convention Center, Sacramento, CA, July 30-August 1.

Harmsen, E. W. and S. Torres Justiniano, 2001b. Evaluation of prediction methods for estimating climate data to be used with the Penman-Monteith method in Puerto Rico.  ASAE Paper No. 01-2048. 2001 ASAE Annual International Meeting, Sacramento Convention Center, Sacramento, CA, July 30-August 1.

Harmsen, E. W., J. Caldero and M. R. Goyal, 2001. Consumptive Water Use Estimates for Pumpkin and Onion at Two Locations in Puerto Rico.  Proceedings of the Sixth Caribbean Islands Water Resources Congress.  Editor: Walter F. Silva Araya. University of Puerto Rico, Mayagüez, PR 00680.

National Climate Data Center, 1992. International Station Meteorological Climate Summary (ISMCS), Version 2.

 



[1] Assistant Professor, Department of Agricultural and Biosystems Engineering, University of Puerto Rico; phone: (787)832-4040 ext. 3112; email: eric_Harmsen@cca.uprm.edu.

 

[2] Undergraduate Research Assistant, Department of Agricultural and Biosystems Engineering, University of Puerto Rico.