LESSON 25 Evapotranspiration

25.1 Evaporation and Transpiration

Evapotranspiration is one of the major components of the hydrologic cycle and affects crop water demand. Therefore, its quantification is necessary for proper irrigation planning. The term evapotranspiration refers to combination of two processes, namely, evaporation and transpiration (Fig. 25.1). Evaporation is a process by which water is lost in the form of vapour from natural surfaces, such as freewater surface, bare soil, from live or dead vegetation. Transpiration is a process by which water is lost in the form of vapour through plant leaves. Therefore evapotranspiration is a combined loss of water from the soil (evaporation)and plant (transpiration) surfaces to the atmosphere through vaporization of liquid water, and is expressed in depth per unit time (for example mm/day).

Consumptive use (CU) – CU is used to designate the losses due to ET and water that is used for its metabolic activities of plants thus CU exceed ET by the amount of water used for digestion, photosynthesis, transport of minerals and photosynthates, structural support and growth. Since this difference is usually less than 1%, ET and CU are normally assumed to be equal. But both (CU &ET) terms are used simultaneously.

 

251.png

Fig.25.1.Evapotranspiration process.

(Source:http://toolboxes.flexiblelearning.net.au/demosites/series6/605/html/resources/visitor_centre/fact_sheets/text_evap_trans.htm: accessed on June 3, 2013)

 

ET can be either directly measured for a given crop, soil and climatic conditions or computed using the reference crop ET, which is generally estimated by various methods depending upon availability of data for a particular case.

 

25.2 Concept of Reference Crop Evapotranspiration

Reference Crop ET – is the potential ET for a specific crop (usually either grass or alfalfa) and set of surrounding (advective) conditions. According to Doorenbos and Pruitt (1977) ”ET from an extensive surface of 8 10 15 cm tall, green grass covers of uniform height, actively growing, completely shading the ground and not short of water”. Allen et al. (1998) modified the above definition to represent hypothetical grass surface. Reference crop evapotranspiration from an extensive surface of green grass of uniform height(0.12m), actively growing, completely shading the ground with an albedo of 0.23 and having ample water supply is called reference crop evapotranspiration and is denoted by ETo (Fig. 25.2).

252.png

Fig. 25.2.Estimation of reference crop evapotranspiration.

(Source: http://moreprofitperdrop.files.wordpress.com : accessed on June 3, 2013)

 

Climatic parameters are the only factors affecting ETo and it can be computed from weather data. ET for specific crop can be estimated using reference crop ET and crop coefficients. Typical ranges for ETo values for different agro-climatic regions are given in Table 25.1.

 

Table 25.1. Average ETo for different agro-climatic regions in mm/day

Regions

Mean daily temperature (°C)

Cool (~10°C)

Moderate (20°C)

Warm (> 30°C)

Tropics and subtropics

Humid and Sub-humid

2 – 3

3 - 5

5 – 7

Arid and Semi-arid

2 – 4

4 - 6

6 – 8

Temperate region

Humid and Sub-humid

1 – 2

2 - 4

4 – 7

Arid and Semi-arid

1 – 3

4 - 7

6 – 9

(Source:http://www.angrau.ac.in/media/7380/agro201.pdf: accessed on June 3, 2013)

 

25.3 ET Estimation Methods

Due to wide application of evapotranspirtaion data, various indirect ET estimation methods have been developed over the years. These methods can be grouped into four major categories. Although there is large number of methods developed in each category, a few examples are given below:

  1. Temperature based (Thornwaite, SCS BlaineyCriddle, FAO24 BlaneyCriddle, Hargreaves)
  2. Radiation based (Turc, Preistly Taylor, Jensen-Haise, and FAO 24 Radiation)
  3. Pan evaporation based ( Pan evaporation, FAO 24 Pan)
  4. Combination (Penman, Penman Moneith, FAO 56 Penman Monteith)

 

Data requirement as well as performance of each of these methods varies. In order to help user with ETo estimation, A Decision Support System for ETo estimation is developed at IIT Kharagpur (Bandopadhyaya et al. 2012), which estimates ETo by 22 well established method and ranks them based on their ETo estimation performance.

 

25.3.1 Hargreaves Methods

Hargreaves method is a temperature based method and it was derived to overcome non availability of solar radiation data at many locations. Hargreaves and Samani (1985) recommended estimating solar radiation from extraterrestrial radiation and proposed the following equation for estimating ETo in mm/day

       253.png     (25.1)

 

Where,

TD = difference between mean monthly maximum and minimum temperatures in °C,

 RA= extraterrestrial solar radiation in MJ m-2 d-1,

 Tmean = mean monthly air temperature in °C.

 

25.3.2 ThornthwaiteMethod

The relationship is expressed as:

        254.png     (25.2)

 

Where,

ETo = Monthly potential evapotranspiration (cm) or reference crop ET (i.e., ETo)

T= Mean monthly temperature (°C)

I = A heat index for a given area which is the sum of 12 monthly index values i

i is derived from mean monthly temperatures using the following formula:

  255.png         (25.3)

a = an empirically derived exponent which is a function of I

256.png     25.4       

 25.3.3 Pan Method

The amount of water evaporating from a pan is determined by measuring change in water level in the pan and correcting from precipitation (assuming that water loss due to wind action, animals, birds etc., has been prevented or is negligible). USBR Class A Pan evporometer is most commonly used for estimation of pan evaporation and is shown in Fig. 25.3. It is relatively inexpensive and simple way of assessing the evaporative capabilities of the atmosphere.

 257.png

Fig. 25.3. Pan evaporimeter. (Source: http://www.polylabindia.com/open-panevaporimeter-1622575.html, accessed on August 29, 2013)

 

Reference Crop ET (ETo) is related to Epas follows:

ETo = Ep .kp                                                (25.5)

 

Where,

ETo = Reference crop ETo in mm/day

Ep = pan evaporation (mm/day)

Kp = pan coefficient

 

Kp accounts for differences in pan type and conditions upwind of the pan, and for dissimilarities between plants and evaporation pans. Kp values for USBR class a Pan can be chosen from Table 25.2.

 

Table 25.2.PanCoefficient for USBR Class a pan at varying location of fetch, mean RH and wind run

Wind

Windward side distance of green crop

RH mean %

low

medium 40-70

high > 70

km/day

m

< 40

Light

1

0.55

0.65

0.75

< 175

10

0.65

0.75

0.85

100

0.7

0.8

0.85

1000

0.75

0.85

0.85

Moderate

1

0.5

0.6

0.65

175-425

10

0.6

0.7

0.75

100

0.65

0.75

0.8

1000

0.7

0.8

0.8

Strong

1

0.45

0.5

0.6

425-700

10

0.55

0.6

0.65

100

0.6

0.65

0.7

1000

0.65

0.7

0.75

Very strong

1

0.4

0.45

0.5

> 700

10

0.45

0.55

0.6

100

0.5

0.6

0.65

1000

0.55

0.6

0.65

(Source: FAO 24)

 

25.3.4 FAO-56 Penman – MonteithMethod

Allen et al. (1998) modified the Penman–Monteith equation for estimation of grass reference crop evapotranspiration (ETo). The mathematicalrelationship is as follows:

 

  258.png                              (25.6)

 

Where,

ETo = Reference crop evapotranspiration (mm/day)

Rn = Net radiation at the crop surface (MJ/m2/day)

G = Soil heat flux density (MJ/m2/day)

T = Air temperature at 2 m height (°C)

U2 = Wind speed at 2 m height (m/s)

es = Saturation vapour pressure (kPa)

ea = Actual vapour pressure (kPa)

(es – ea) = Saturation vapour pressure deficit (kPa)

Δ = Slope vapour pressure curve (kPa/°C)

γ = Psychrometric constant (kPa/°C)

Details of parameter estimation for the above ETo methods can be found in Allen et al. (1998) and Michael (2008). 

Application & Limitations

  • Method requires all weather data, i.e., minimum and maximum temperature, minimum and maximum RH, wind speed, Solar radiation or sunshine hour
  • Wide applicability i.e., in arid, semi-arid, humid, sub-humid conditions
  • Gives a very satisfactory estimate of ETo
  • Can provide basis for developing consistent crop coefficients

 

25.4 Crop Evapotranspiration

Estimation of evapotranpiration for a specific crop (ETc) requires first calculating the reference evapotranspiration (ET0) and then multiplying the crop coefficients (Kc) to estimate actual:

ETc = ETo x Kc                                                        (25.7)

Where, ETc is the ET of a specific crop,ETo is the grass-reference ET, and Kc is the crop coefficient for a given crop.

 

25.4.1 Crop Coefficient Concept

While ETo accounts for variations in weather and is used as an indicator of atmospheric demand for water, Kc values account for the difference between EToand ETc and link them. Kc is the crop coefficient for a given crop and growth stage, and is usually determined experimentally. Each agronomic crop has a set of specific crop coefficients used to predict water use rates at different growth stages.

 

There are four main crop growth stages: initial, crop development, mid-season, and late season:

a) Initial period – planting to 10% ground cover

b) Crop development – 10% ground cover to effective cover i.e., flowering

c) Mid-season – Effective cover to start of maturity i.e., senescence of leaves

d) Late season – Start of maturity to harvest.

 

These crop development stages along with crop coefficient variation for a typical crop are depicted in Fig. 25.3.Tables 25.3 presents length of growth stages of some of the representative crops whereas Table 25.4 shows values of crop coefficient during different stages. Crop coefficient values vary with the development stage of the crop. In the case of annual crops, Kc is typically low at seedling, emergence and establishment stage, increaseswith increase in ground cover and attains maximum value at mid-season stage andthereafter decreases towards ripening and maturity stage.

259.png 

Fig. 25.3.Variation of crop coefficient with crop growth stages. (Source: Allen et al. 1998)

Table 7.7.Length of crop growth stages (days)

Crop

Initial

(Lini)

Development

(Ldev)

Mid

 

(Lmid)

Late

 

(Llat)

Panting date

Region

Bean, green

20

30

30

10

Feb/Mar

Calif., Mediterrian

Cabbage

40

60

50

15

Sept

Calif. Desert, USA

Cauliflower

35

50

40

15

Sept

Calif. Desert, USA

Tomato

35

40

50

30

Apr/May

Calif., USA

Cucumber

20

30

40

15

Jun/Aug

Arid region

Potato

30

35

50

30

Apr

Europe

Groundnut

35

35

35

35

May

High Latitudes

Lentil

25

35

70

40

Oct/Nov

Arid region

Soybeans

20

30/35

60

25

May

Central USA

Cotton

30

50

60

55

Mar-May

Egypt; Pakistan; Calif.

Sesame

20

30

40

20

Jun

China

Sunflower

25

35

45

25

Apr/May

Medit.; Calif.

Wheat

15

25

50

30

Nov

Central India

Maize (grain)

20

35

40

30

Oct

India (dry, cool)

Rice

30

30

60

30

Dec; May

Tropics; Medit

Sugarcane, ratoon

30

50

180

60

 

Tropics

Banana, Istyr

120

90

120

60

Mar

Mediterranean

Grapes

20

40

120

60

Apr

Low Latitudes

Citrus

60

90

120

95

Jan

Mediterranean

(Source: Allen et. al, 1998)

 

Table 7.8.Single crop coefficients for grass reference crop and mean maximum plant heights for well managed no stressed condition in sub-humid regions (RHmin = 45% and u2 = 2 ms-1)

Crop

Kc_ini

Kc_mid

Kc_end

Maximum crop height, h (m)

Bean, green

0.5

1.05

0.90

0.4

Cabbage

0.7

1.05

0.95

0.4

Cauliflower

0.7

1.05

0.95

0.4

Tomato

0.6

1.15

0.70 – 0.90

0.6

Cucumber

0.5

1.00

0.90

0.3

Potato

0.5

1.15

0.75

0.6

Groundnut

0.4

1.15

0.60

0.4

Lentil

0.4

1.10

0.30

0.5

Soybeans

0.4

1.15

0.50

0.5-1.0

Cotton

0.35

1.15-1.20

0.70-0.50

1.2-1.5

Sesame

0.35

1.10

0.25

1.0

Sunflower

0.35

1.0-1.15

0.35

2.0

Wheat

0.3

1.15

0.25 – 0.40

1.0

Maize (grain)

0.3

1.20

0.60, 0.35*

2.0

Rice

1.05

1.20

0.90-0.60

1

Sugarcane

0.40

1.25

0.75

3

Banana, Istyr

0.50

1.10

1.00

3

Grapes

0.30

0.85

0.45

2

Citrus**

0.65

0.60

0.65

3

(Source: Allen et. al., 1998)

 

* First and second values correspond to harvest at high grain moisture and at complete field dry conditions, respectively.

** No ground cover, 50% canopy

 

Example 25.1:

Determine ETo for March from pan evaporation data of Palakkad, Kerala. Daily mean pan evaporation for the month of March = 7.01mm, Average relative humidity = 63.45 %, Average wind speed at 2m height = 1.157 m/s. At Palakkad, evaporation pan is placed in an area surrounded by green crops. The windward side distance of green crops is about 100 m.

 

Solution:

For the given conditions, Kp from Table 25.2 is 0.8

          ETo = Kp x Epan

                  = 0.8 x 7.01

                  = 5.61 mm. Ans

 

Example 25.2:

Determine monthly water requirements and total water requirement of a groundnut crop grown in the rice fallows at Palakkad, Kerala.

Month

January

February

March

April

Kc Values

0.51

0.93

1.14

0.82

ETo mm/day

4.60

5.00

5.59

5.20

 

Solution:

For the month of January:

Kc =0.51

No of days =31

ETo = 4.60

 

Therefore, ETc = ETo x Kc x No of days

                    = 4.60 x 0.51 x 31

                    = 72.725 mm

 

For the month of February:

Kc =0.93

No of days =28

ETo = 5.00

 

Therefore, ETc = ETo x Kc x No of days

                    = 5.00 x 0.93 x 28

                    = 130.2 mm

 

For the month of March:

Kc =1.14

No of days =31

ETo = 5.59

 

Therefore, ETc = ETo x Kc x No of days

                    = 5.59 x 1.14 x 31

                    = 197.47 mm

 

For the month of April:

Kc =0.82

No of days =30

ETo = 5.20

 

Therefore, ETc = ETo x Kc x No of days

                    = 5.20 x 0.82 x 30

                    = 85.2 mm

 

Total water requirement = Jan +Feb+Mar+Apr = 485.72 mm Ans.

 

Irrigation requirement for the above months are calculated by subtracting monthly effective rainfall from ETc of respective months.

 

Key Words: Evapotranspiration, Crop coefficient

 

References

Allen R, G.,Pereira, L.S., Raes, D. and Smith, M. (1998). Crop evapotranspiration guidelines for computing crop water requirements. Irrigation and Drainage Paper 56, Food and Agriculture Organization of the United Nations (FAO), Rome, Italy.(www.kimberly.uidaho.edu/ref-et/fao56.pdf‎)

Doorenbos, J. and Pruitt, W. O.(1977). Guidelines for predicting crop water requirements.Irrig.and Drain. Paper No. 24, FAO, Rome, Italy.

Michael, A.M. (2008). Irrigation Theory and Practice. Vikas Publishing House PvtLtd. New Delhi.

Murty, V.V.N. (2002).Land and Water Management Engineering(Fourth Edition).Kalyani Publisher, New Delhi.

 

Internet References

http://www.angrau.ac.in/media/7380/agro201.pdf

http://gilley.tamu.edu/BAEN464/Handout%20Items/Cuenca%20Book%20Chapter%203%20Soil%20Physics.pdf

http://ilri.org/InfoServ/Webpub/fulldocs/IWMI_IPMSmodules/Module_3.pdf

ftp://ftp.wcc.nrcs.usda.gov/wntsc/waterMgt/irrigation/NEH15/ch1.pdf

 

Suggested Reading

Michael, A.M. (2008). Irrigation Theory and Practice. Vikas Publishing House Pvt.Ltd. New Delhi.

Murty, V.V.N. (2002).Land and Water Management Engineering(Fourth Edition).Kalyani Publisher, New Delhi.

http://www.angrau.ac.in/media/7380/agro201.pdf

http://gilley.tamu.edu/BAEN464/Handout%20Items/Cuenca%20Book%20Chapter%203%20Soil%20Physics.pdf

http://ilri.org/InfoServ/Webpub/fulldocs/IWMI_IPMSmodules/Module_3.pdf

ftp://ftp.wcc.nrcs.usda.gov/wntsc/waterMgt/irrigation/NEH15/ch1.pdf

 

 

Last modified: Saturday, 15 March 2014, 6:25 AM