paper -see

First International Conference on Science & Environment,Tsu City, Nov. 19-21, 2015, ISBN: 978-4-9905958-3-8 C3051

EXAMINING THE SIX WELL KNOWN EQUATIONS FOR ESTIMATING REFERENCE EVAPOTRANSPIRATION IN

HERAT, AFGHANISTAN

Homayoon Ganji1 Takamitsu Kajisa1 Masaaki Kondo1 Behroze Rostami1

1Graduate School of Bioresources, Mie University, 514-8507 Kurima-machiya-cho 1577, Tsu, Japan

ABSTRACT

Herat province as a semi-arid area, having strong winds which are known as “120-day winds” needs to be investigated with aim for discovering the best method for estimating the reference evapotranspiration (ET0) which has the most accuracy and is adaptable in the area. In this research, an examining has been done between six well known methods based on their performances under the given climatic condition in the Herat provinces. Pan evaporation (Epan) is considered as indicator to compare with Penman-Monteith, which is the only method that includes a variable of wind, Thornthwaite, and Hargreaves, and Hamon, Net radiation and solar radiation methods. 8 years data from 2006 to 2013 is used to show the seasonal climatic variations as well the year 2009 data is used to compare the six methods between each other. The ET0 estimated values by six methods have been correlated with Epan estimated value, using Pearson’s correlation (R) methods. Based on p-value, all of the six methods are found significant to be used for measuring the ET0. The Penman-Monteith method is showing the highest R. Hence, by considering the standard error estimation (SEE) calculation, the Penman-Monteith method has the lowest value which suggests the best measuring of the ET0. The secondary smallest SEE was shown for Hargreaves. The yearly ET0 of Hargreaves was larger than the Epan, while the yearly ET0 of Penman-Monteith was smaller than Epan. Therefore, in a case the aim is not accuracy but design, the Hargreaves might not be ignored.

Keyword: 120-day winds, Pan Evaporation, Reference Evapotranspiration, Herat, Afghanistan

INTRODUCTION

Evapotranspiration (ET) is defined as physical processes whereby liquid water vaporized into the atmosphere from evaporating surfaces [2], [11] and [15]

ET is the most significant component of the hydrologic budget, apart from precipitation [7]. Accordingly, in arid and semi-arid areas, ET is important as well. The ET varies according to weather and wind conditions. Because of this variability, water managers who are responsible for planning and adjudicating the distribution of water resources need to have a thorough understanding of the ET process, and knowledge about the spatial and temporal rates of it.

ET is defined in different concepts as one of the concepts is called potential or reference evapotranspiration (ET0). The concept of the ET0 is used to introduce the evaporative demand of the atmosphere apart from the crop type, crop development and management practice [2].

Many different methods for measuring the ET0

have been developed based on their daily

performances under the given climatic condition in the world. In this study, only six models are selected to estimate the ET0 for Herat, Afghanistan.

Penman-Monteith, the United Nations Food and Agriculture Organization (FAO) has introduced a model for estimating of the standard ET0 which is known as Penman-Monteith model Eq. (1) Table 1 [2]. The accuracy of the FAO model is as high as recommended sole method of calculating ET0, if the requirement set of data are available [2]. The only limitation to the Penman family of models, they require many meteorological inputs, thereby limiting their utility in data-sparse areas [7], [4].

Thornthwaite (1944) defines ET0 as “the water loss which will occur if at no time there is a deficiency of water in the soil for use of vegetation” [16]. As this method requires only monthly average temperature, is considered to be popular method [13] According to the Mintz and Walker (1993), the Thornthwaite method has been developed to temperature measured under potential conditions and in only overestimate the potential evaporation in arid regions if air surface temperature is applied Eq. (2) Table 1.

1


The Hargreaves-Samani (1985) is one of the older ET models which are introduced by Allen and Hargreaves Eq. (3) [9] Table 1. The requirement component for this model is simpler than the Penman-Monteith. The Hargreaves’s ET0 model requires only measured temperature data. This model is seen to be less impacted than Penman-type methods when data are collected from arid or semi-arid and non-irrigated sites.

A method was described by Doorenbos and Pruitt (1977) through which evaporation is converted to ET0. This method described by Allen et al. (1991), known as FAO 24 Pan Evaporation (24PAN). In order to estimate ET0, the measured pan evaporation is adjusted by a coefficient Kp Eq. (4).

This method is the basic form of the 24PAN model, which is also described by Fontenot, R. L. (2004) Table 1.

Homan Method is also known as one of the simplest methods that are applicable for estimating the ET0 in monthly base or yearly bases. According to the Haith and Shoemaker (1987), this method requires only average number of daylight hours per day and saturated vapor pressure. The Eq. (5) is used for this method which was given by [8] Table 1.

Finally, FAO-56PM was simplified by Irmak et al. (2003) as expressing a multi-linear regression function that only net radiation (Rn) and solar radiation (Rs) are needed as requires input parameters for estimation Eq. (6)-(7) Table 1.

Table 1 Deferent model’s equations

Model Equation NoFAO Penman-Monteith

(56PM)ET 0=

0.408 ( Rn−G )+ 900T+273

u2(es−ea)

+(1+0.34 u2)

1

ThornthwaiteET 0=16 ×(10 Ti

I )a

( N12 )( I

30 )I=∑

i=1

12

(Ti5 )

1.514

a=( 492390+17920 I−77.1 I2+0.675 I 3 )× 10−6

2

Hargreaves-Samani 1985 (H-S)

ET 0=0.0023¿ 3

Pan Evaporation ET 0=K p × Epan 4

Homan MethodET 0=

2.1× H t2 es

(T¿¿mean+273.3)¿

5

Net radiation (Rn) ET 0=0.489+0.289 Rn+0.023 T mean 6

Solar radiation (Rs) ET 0=0.611+0.149 R s+0.079T mean 7

Where:ET0 is grass reference evapotranspiration (mm day-1), Rn is net radiation (MJ m-2 day-1), G is soil heat flux (MJ m-2 day-1), γ is the psychometric constant (kPa °C-1), es is the saturation vapor pressure (kPa), ea is the actual vapor pressure (kPa), ∆ is the slope of the saturation vapor pressure - temperature curve (kPa °C-1), T is the average daily air temperature (°C), u2

is the mean daily wind speed at 2 m (m s -1) [2]. Ti is the mean monthly temperature (°C); N is the mean monthly sunshine hour, Tmax is the daily maximum temperature (°C), Tmin is the daily minimum temperature (°C), Ra is the daily extraterrestrial radiation (mm day-1), KP is the pan coefficient, Epan

is the pan evaporation (mm day-1), Ht is

2


average number of daylight hours per day [day], Rs is solar shortwave radiation (MJ m-2 day-1).

The available ET0 date with different organization in Herat province is calculated through software developed by FAO, called CLIMWAT and CROPWAT software. Except that, there is no any method has been recommended for estimating the ET0 in Herat province yet, it means that, still no any research has been done to compare different methods in this regards so far. Thus, in order to establish a common method which can provide a more accurate ET0, this research has been done with following hypothesis:

1) Epan can be a good indicator for ET0

estimation through different methods.

2) The ET0 estimation value is more accurate with the methods those require wind factor than the dose do not require wind factor.

ESTIMITION METHODS For estimating the ET0 rate, six well known

methods are used as shown in Table 1. Climatic parameters that is important for estimation of the six different methods, shown in Table 2.

Table 2 Metrological parameters for different methods.

MethodsVariables

Temperature Humidity Wind speed Radiation No. of

Daylight hoursSaturated

vapour pressureFAO56-PM necessary necessary necessary necessary necessaryThornthwait

enecessary - - necessary

Hargreaves necessary - - necessary - -Hamon necessary - - necessary -

Rs- based radiation

necessary necessary - necessary necessary -

Rn- based radiation

necessary necessary - necessary necessary -

Due to lack of enough Epan data, only the data from year 2009 is used to estimate the ET0.

Collecting the metrological data is still a challenge in Afghanistan, but recently the ministry of Agriculture and livestock with support of FAO organization could reestablish the metrological stations in each province of Afghanistan.

There is a metrological station in Herat province which belongs to the department of Agriculture and livestock. This station is called Urdu Khan Research Center.

Urdu khan Regional Agricultural Research Station with a total area of 225 hectares is located in latitude of 39° 11' N and a longitude of 68° 13' E with an elevation of 964 meters in Urdu khan village, at 5.8 kilometers southeast of Herat city. The maximum mean annual temperature is around 28.9°C and minimum mean temperature -0.6 °C. Precipitation is reported 220 mm in average base yearly. The first frost almost occurs around November 4th whereas the last frost is seen about March 28th. The total frost-free days are 226 day during the summer season [14]. A strong wind which is called the “120-day winds” persists from early June until late September with a strong average

force (7.01 m/sec) [6].

RESULT AND DISCUSSION

Strong winds as a metrological factor, influences the ET0 which is estimated by different methods. The ET0 rate is shown different according to the different methods because all applied methods require different metrological factors in estimation of the ET0.

Among the applied methods in this study, Penman-Monteith is the only method which requires wind factor directly for estimating the ET0 including of the temperature, relative humidity and sun shine hours. Epan which is measured directly from A-class pan and Hargreaves methods, which requires temperature only, are influenced by wind speed whereas the other methods are seemed not influenced by wind factor.

1. Daily difference among the metrological variables is shown in Fig. 1. The monthly average variation of temperature, wind speed, humidity, solar radiation and net radiation which are necessary for ET0 estimation has been measured for 8 years.

3


23-Mar 23-Apr 23-May 23-Jun0

10

20

30

40

50

60

70

80

Spring

Tmen (°C) Wind Speed (m/s) Humidity (%)

23-Mar 23-Apr 23-May 23-Jun0

5

10

15

20

25

30

35

Spring

Rn Rs

(Jm-2

s-1)

24-Jun 24-Jul 23-Aug 22-Sep0

10

20

30

40

50

60

70

80

Summer

Tmen (°C) Wind Speed (m/s) Humidity(%)

24-Jun 24-Jul 24-Aug 24-Sep0

5

10

15

20

25

30

35

Summer

Rs Rn

(Jm-

2 s-1)

25-Sep 25-Oct 25-Nov 25-Dec0

10

20

30

40

50

60

70

80

Fall


25-Sep 25-Oct 25-Nov 25-Dec0

5

10

15

20

25

30

35

Fall

Rs Rn

(Jm-

2 s-1)

26-Dec 26-Jan 26-Feb 26-Mar0

10

20

30

40

50

60

70

80

Winter


26-Dec 26-Jan 26-Feb 26-Mar0

5

10

15

20

25

30

35

Winter

Rs Rn

(Jm-

2 s-1)

Fig 1 Daily average temperature, wind speed and humidity of four seasons

4


Humidity is seen high in the early spring, entire the winter and late fall whereas the summer season is characterized with low humidity, due to low precipitation.

The entire of the summer season, wind speed is seen faster, almost more than 5 m/s averagely than the other seasons. Similarly, temperature is high in the summer, but since early of fall the temperature drops till medal of spring.

Net radiation is decreasing by early of fall and again increasing from late winter on.

2. Compression of the daily average ET0

value, estimated through the different six methods such as; Thornthwaite, Hargreaves, Hamon, Solar radiation and Net radiation, Epan and FAO-56PM between each other is shown by (Fig. 2 to 7),using data of year 2009. All methods show a higher rate of ET0 from the early summer until late fall.

The Penman-Monteith and Hargreaves methods show closer ET0 value to the Epan entire of the year, especially at early of summer until late fall seasons (Fig 2 and 3). The reason might be referred to the strong wind “120-day winds” which blows all the summer season with high speed. This is why the ET0

estimated through penman-Monteith, which requires wind velocity and Hargreaves method, which is recommended at the arid area are closer in volume with Epan.

1-Jan

14-Jan

27-Jan9-F

eb

22-Feb7-M

ar

20-Mar2-A

pr

15-Apr

28-Apr

11-May

24-May

6-Jun

19-Jun

2-Jul

15-Jul

28-Jul

10-Aug

23-Aug

5-Sep

18-Sep

1-Oct

14-Oct

27-Oct

9-Nov

22-Nov

5-Dec

18-Dec

31-Dec

0

5

10

15

20

25

Epan Penman-Montieth

ET

0 (m

m/d

ay)

Fig. 2 Daily average estimated ET0 through Epan and Penman-Monteith methods

1-Jan

14-Jan

27-Jan9-F

eb

22-Feb

7-Mar

20-Mar

2-Apr

15-Apr

28-Apr

11-May

24-May

6-Jun

19-Jun

2-Jul

15-Jul

28-Jul

10-Aug

23-Aug

5-Sep

18-Sep

1-Oct

14-Oct

27-Oct

9-Nov

22-Nov

5-Dec

18-Dec

31-Dec

0

5

10

15

20

25

Epan Hargreaves

ET

0 (m

m/d

ay)

Fig. 3 Daily average estimated ET0 through Epan and Hargreaves methods

It is shown in Fig. 2 that, there is deference between Penman-Monteith ET0 value and Epan value

since early of summer until end of summer season; as well, the deference is seen between Hargreaves ET0 value and Epan value from January until June shown in Fig. 3.

The other four methods show lower ET0 value than the Epan, as there is a big deference between each method and Epan, especially form around May until late November (Fig. 4 to 7).

1-Jan

14-Jan

27-Jan9-F

eb

22-Feb

7-Mar

20-Mar2-A

pr

15-Apr

28-A

pr

11-May

24-May

6-Jun

19-Jun

2-Jul

15-Jul

28-Jul

10-Aug

23-Aug

5-Sep

18-Sep

1-Oct

14-Oct

27-Oct

9-Nov

22-Nov

5-Dec

18-Dec

31-Dec

0

5

10

15

20

25

Epan Hamon

ET0

(mm

/day

)

(C)

Fig. 4 Daily average estimated ET0 through Epan and Hamon methods

1-Jan

14-Jan

27-Jan9-F

eb

22-Feb7-M

ar

20-Mar

2-Apr

15-Apr

28-Apr

11-May

24-May

6-Jun

19-Jun

2-Jul

15-Jul

28-Jul

10-Aug

23-Aug

5-Sep

18-Sep

1-Oct

14-Oct

27-Oct

9-Nov

22-Nov

5-Dec

18-Dec

31-Dec

0

5

10

15

20

25

Epan Thoranthwait

ET

0 (m

m/d

ay)

Fig. 5 Daily average estimated ET0 through Epan and Thornthwaite methods

1-Jan

14-Jan

27-Jan9-F

eb

22-Feb7-M

ar

20-Mar

2-Apr

15-Apr

28-Apr

11-May

24-May

6-Jun

19-Jun

2-Jul

15-Jul

28-Jul

10-Aug

23-Aug

5-Sep

18-Sep

1-Oct

14-Oct

27-Oct

9-Nov

22-Nov

5-Dec

18-Dec

31-Dec

0

5

10

15

20

25

Epan Solar radiation (Rs) based method

ET

0 (m

m/d

ay)

Fig. 6 Daily average estimated ET0 through Epan and Solar radiation methods

1-Jan13-Jan

25-Jan6-Feb

18-Feb2-M

ar

14-Mar

26-Mar7-Apr

19-Apr

1-May

13-May

25-May6-Jun18-Jun

30-Jun12-Jul

24-Jul

5-Aug

17-Aug

29-Aug

10-Sep

22-Sep4-Oct

16-Oct

28-Oct9-Nov

21-Nov3-Dec

15-Dec

27-Dec

0

5

10

15

20

25

Epan Net radiation (Rn)based Method

ET

0 (m

m/d

ay)

5


Fig. 7 Daily average estimated ET0 through Epan and Net radiation methods

3. Yearly estimated ET0 value by using the six well known methods is shown by Fig. 8. The Hargreaves, Epan and Penman- Monteith show higher total annual ET0 value than the four others. Variations in the ET0 estimation reflect the differences in the variables applied in each method.

According to the Fig. 8, Hargreaves shows the highest total annual ET0 value that is 3500 mm/year, whereas the Thornthwaite, Homan, Solar radiation based method and Net radiation based methods show the lower value of total annual ET0 of which Thornthwaite method shows the lowest total annual value that is 1000 mm/year.

Hargrea

ves Epan

Penman-M

ontieth

Irmak sim

plified (R

s)

Irmak sim

plified (R

n Hamon

Thoranthwait

0

500

1000

1500

2000

2500

3000

3500

4000

ET0 (mm/year)

)

Fig. 8 Total annual ET0 estimates given by different methods covering 2009 year metrological data

As the Epan is considered as indicator, the estimated ET0 through Penman-Monteith and Hargreaves methods are closer to the Epan value. Therefore, the Penman-Monteith methods can be considered the most accurate method, whereas the Hargreaves methods as the second accurate method is useful to apply for designing of irrigation plan.

4. Brutsaert and Parlange (1998) indicated that, Epan is often taken as a good indicator of ET0. Therefore Fig. 4 shows a strong correlation between penman-Monteith method and Epan. This correlation is found by Zhang et al., 2007. Zhang considered Epan as indicator for reference evapotranspiration and potential evapotranspiration.

Fig. 9 Relationships between yearly Penman-Monteith ET0 and evaporation Epan [17]

Therefore, The Hargreaves, Thornthwaite, Hamon, solar radiation and net radiation-based methods, Penman-Monteith are correlated with Epan

as the value of (R2), (a) coefficients and Total yearly ET0 is shown by Table 4. By considering the (R2) and (a) value, in a case if the (R2) value is the same between two methods, the most accurate and significant method is the one which has the (a) nearest to the 1.

The Penman-Monteith method with having (R2 = 0.8817& a = 0.6962) is shown the highest correlation with Epan as well as shows the closest ET0

value to the Epan.

Table 3 Correlated coefficient and standard error estimation of six well known methods

Models

coefficients

SEE

P-

valu

eR2 a b n

Hargreaves0.

8

0.

8

3.

6

36

53.32 0.00

FAO-56PM0.

8

0.

6

0.

7365

2.70 0.00

Solar-

radiation

0.

8

0.

2

1.

4365

5.70 0.00

Net

radiation

0.

6

0.

2

1.

9365

6.11 0.00

Hamon0.

8

0.

3

0.

5365

5.71 0.00

Thornthwai

te

0.

8

0.

3

0.

0365

5.97 0.00

The relationship between the six methods is shown in Fig. 5. Based on P-value all the methods have significant correlation with Epan, but by considering the (a) value, except the Hargreaves which has (R2 = 0.8067 & a = 0.8037), all the others have the low value of (a) coefficient. Furthermore, Penman–Monteith requires the wind as a main factor for estimating the ET0 and in other hand, Herat is characterized with strong wind velocity, the Penman–Monteith is recommended as the most accurate model for estimating the ET0.

In a case if the requirement factors for penman-Monteith is not available, the Hargreaves with (R2 = 0.8067 & a = 0.8037) method, which only requires

6

ETpan (mm/y)

ET0 (mm/y)


temperature and radiation for calculation, is recommended for estimating the ET0 as it shows high correlation with Epan .

0 2 4 6 8 10 12 14 16 18 200

5

10

15

20

25

f(x) = 0.696239236957202 x + 0.784195927831097R² = 0.881745667907131

Epan (mm/day)

Penm

an-M

ontie

th (m

m/d

ay)

Fig. 10 Relationships between daily average Epan evaporation and Penman-Monteith methods

0 2 4 6 8 10 12 14 16 18 200

5

10

15

20

25

f(x) = 0.803739869591839 x + 3.62086763504771R² = 0.806736607593331

Epan (mm/day)

Har

grea

ves (

mm

/day

)

Fig. 11 Relationships between daily average Epan evaporation and Hargreaves methods

0 2 4 6 8 10 12 14 16 18 200

5

10

15

20

25

f(x) = 0.375706291398811 x − 0.074874542579169R² = 0.817685662311951

Epan (mm/day)

Thor

anth

wai

t (m

m/d

ay)

Fig. 12 Relationships between daily average Epan evaporation and Thornthwaite methods

0 2 4 6 8 10 12 14 16 18 200

5

10

15

20

25

f(x) = 0.349026096991041 x + 0.559678393283104R² = 0.830599038087421

Epan (mm/day)

Ham

on (m

m/d

ay)

Fig. 13 Relationships between daily average Epan evaporation and Hamon methods

0 2 4 6 8 10 12 14 16 18 200

5

10

15

20

25

f(x) = 0.277543812855955 x + 1.46854606789203R² = 0.825612015188045

Epan (mm/day)

Sola

r ra

diat

ion

(Rs)

bas

ed m

etho

d (m

m/d

ay)

Fig. 14 Relationships between daily average Epan evaporation and Solar-radiation methods

0 2 4 6 8 10 12 14 16 18 200

5

10

15

20

25

f(x) = 0.20102015162287 x + 1.92724577434028R² = 0.655552763097268

Epan (mm/day)

Net

rad

iatio

n (R

n) b

ased

met

hod

(mm

/day

)

Fig. 15 Relationships between daily average Epan evaporation and Net radiation Methods

CONCLUSION

In Herat province, the ET0 rate is shown different according to the different methods because all applied methods require different metrological factors for estimation of the ET0. Among the applied methods in this study, Penman-Monteith is the only method which requires wind factor directly for estimating the ET0 including the temperature, relative humidity and sun shine hours.

Epan evaporation which is measured directly from A-class pan and Hargreaves methods, which requires

7


temperature only, is also influenced by wind factor whereas the other methods are not influenced.

1. Humidity is high in the early spring, entire the winter and late fall whereas the summer season is characterized with low humidity due to low precipitation.

The entire of the summer season, wind speed is seen faster almost more than 5 m/s averagely than the other seasons. Similarly, temperature also is high in the summer, but since early of fall season the temperature decreases till middle of spring.

Net radiation is decreasing by early of fall and again increasing from late winter on.

2. All methods show a higher rate of ET0 from the early summer until late fall. The Penman-Monteith and Hargreaves show closer ET0 to the Epan

entire of the year, whereas the other four methods are different especially at early of summer until late fall seasons. The reason is referred to the strong wind “120-day winds” which blows all the summer season with high speed. This is why the estimated ET0 through penman-Monteith, which requires wind velocity and Hargreaves method, which is recommended at the arid area, are closer to the measured evaporation through Epan.

3. Hargreaves, Penman-Monteith and Epan

methods show the higher value of ET0 as the Hargreaves shows the highest total annual value of ET0 3500 mm/year, whereas the Thornthwaite, Homan, Solar radiation based method and Net radiation based methods, show the lower value of ET0 as Thornthwaite has the lowest total annual value of 1000 mm/year.

4. As the Epan is considered as indicator, the estimated ET0 through Penman-Monteith and Hargreaves methods are closer to the Epan value. Therefore, those methods are applicable than the other four methods in Herat, Afghanistan.

ACKNOWLEDGEMENT

REFERENCES

[1] Allen, Richard G., and William O. Pruitt. "FAO-24 reference evapotranspiration factors." J. of irrigation and drainage engineering, Vol. 117(5), Sep. 1991, pp. 758-773.

[2] Allen, Richard G., et al. "Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56" FAO, Rome , Vol. 300(9), year 1998.

[3] Brutsaert, W., and M. B. Parlange. "Hydrologic cycle explains the evaporation paradox", J. of Nature, Vol. 396.6706, Nov. 1998, pp. 30-30.

[4] Dingman, S.L.1994. Physical Hydrology. Upper Saddle River, NJ: Prentice Hall

[5] Fontenot, R. L., An evaluation of reference evapotranspiration models in Louisiana. Diss. Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Master of Natural Sciences In The Interdepartmental Program of Natural Sciences by Royce Landon Fontenot BS, Louisiana State University, 2004.

[6] Ganji H, Rahmany Ab. S, Kajisa T, Kondo M, Hajime N, “Comparison of the Crop Water Need between Actual Wind Condition and Zero Wind Simulation; Wind Velocity within 24-Hour Interval in Herat, Afghanistan”. In Tokyo University of Agriculture. 20th Int. Conf. on ISSAAS, 2014, pp. 91.

[7] Hanson, Ronald L. "Evapotranspiration and droughts." Paulson, RW, Chase, EB, Roberts, RS, and Moody, DW, Compilers, National Water Summary (1988), pp. 99-104.

[8] Haith, Douglas A., and Leslie L. Shoenaker. "Generalized Watershed Loading Functions for Stream Flow Nutrients1", J. JAWRA, Vol. 23(3), Jun. 1987, pp. 471-478.

[9] Hargreaves, George H., and Richard G. Allen. "History and evaluation of Hargreaves evapotranspiration equation." J. of Irrigation and Drainage Engineering, Vol. 129(1), Feb. 2003, pp. 53-63.

[10] Irmak, S., et al. "Solar and net radiation-based equations to estimate reference evapotranspiration in humid climates", J. of irrigation and drainage engineering, Vol. 129(5), Oct. 2003, pp. 336-347.

[11] Li, F., Lyons, T.J., 1999. Estimation of regional evapotranspiration through remote sensing. J. Appl. Meteorol.38, 1644-1654.

[12] Mintz, Y., and Walker, G. K. “Global fields of soil moisture and land surface evapotranspiration derived from observed precipitation and surface air temperature.” J. of Meteorology, Vol. 32, Aug. 1993, pp. 1305-12334.

[13] O. Alkaeed, C. Flores, K. Jinno and A. Tsutsumi. 2006. Comparison of Several Reference Evapotranspiration Methods for Itoshima Peninsula Area, Fukuoka, Japan. Kyushu University, Vol. 66, No.1.

[14] Osmanzai, M. 2009. Annual Report. CIMMYT, Afghanistan.

[15] Penman, H.L. 1948. Natural evapotranspiration from open-water, bare soil and grass. Proc. R. Soc. Acad., 193: 120-145.

[16] Thornthwaite, C. W. 1948. “An approach toward a rational classification of climate.” Geography. Rev. 38.

8


[17] Zhang, Yongqiang, et al. "Trends in pan evaporation and reference and actual evapotranspiration across the Tibetan Plateau", J. of Geophysical Research: Atmospheres, Vol. 112.D12. Jun. 2007.

9

paper -see

Documents