Evapotranspiration and crop coefficient for sprinkler-irrigated

Agricultural Water Management 107 (2012) 86–93
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Agricultural Water Management
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Evapotranspiration and crop coefficient for sprinkler-irrigated cotton crop in
Apodi Plateau semiarid lands of Brazil
Bergson G. Bezerra a,d,∗ , Bernardo B. da Silva b , José R.C. Bezerra c , Valdinei Sofiatti c ,
Carlos A.C. dos Santos d
a
National Institute of Semi Arid (INSA), Campina Grande, Brazil
Federal University of Pernambuco, Department of Geographical Sciences, Recife, Brazil
c
Brazilian Agricultural Research Company (EMBRAPA) – National Center for Cotton Research, Campina Grande, Brazil
d
Department of Atmospheric Science, Federal University of Campina Grande, Campina Grande, Brazil
b
a r t i c l e
i n f o
Article history:
Received 18 August 2011
Accepted 17 January 2012
Available online 23 February 2012
Keywords:
Bowen ratio
FAO-56
Irrigation
Water management
Apodi Plateau
a b s t r a c t
During the twentieth century, the cotton crop was the main agricultural product in the semiarid regions of
Brazil, with over 3.2 million hectares planted. However, due to structural problems, this activity became
uncompetitive and economically unfeasible, being virtually wiped out in the eighties. The revival of
cotton growing in semiarid lands of Brazil is important to the regional economy. However, the adoptions
of new technologies mainly related to the water use efficiency are needed. Thus, accurate ETc estimates
are required for efficient irrigation management. The Kc method is a practical and reliable technique for
estimating ETc, and has been vastly applied by the farmers in the semiarid lands of Brazil. However, the
use of Kc values listed in FAO-56 can contribute to ETc estimates that are substantially different from
actual ETc. Hence the importance of determining Kc values experimentally. A field study on sprinklerirrigated cotton was carried out during the dry seasons of 2008 and 2009 years in the Apodi Plateau,
Brazilian semiarid lands. This study aims to determine ETc and the Kc curve values using the Bowen Ratio
Energy Balance (BREB) technique. The locally developed Kc curves are compared with generalized FAO Kc
values adjusted for local climate and management. The ETc values were 716 mm and 754 mm in 2008 and
2009, respectively. These values were higher than those observed in other areas of Brazilian semiarid.
These differences are attributed to weather heterogeneity in the region. The average of Kc values were
0.75, 1.09 and 0.80 for initial, middle and end, of growing season, respectively. These values were lower
than the Kc-FAO-Adjusted to local conditions. For this reason, ETc values obtained from Kc-FAO-Adjusted were
overestimated by 12% in both the years. The irrigation scheduling based on the Kc-FAO-Adjusted increases
production cost and yield loss.
© 2012 Elsevier B.V. All rights reserved.
1. Introduction
Cotton (Gossypium hirsutum L.) is the most important textile
fiber in the world. It accounts for more than 40% of the total
world fiber production and it is grown in more than 100 countries
(MacDonald and Vollrath, 2005; Esparza et al., 2007). During the
twentieth century, the cotton crop was the main agricultural product in the semiarid regions of Brazil, with over 3.2 million hectares
planted. As the production system was not equipped with modern technology, it resulted in low productivity and the plague of
boll weevil (Anthonomus grandis Boheman), which proliferated in
∗ Corresponding author at: Departamento de Ciências Atmosféricas, Av. Aprígio
Veloso, 882, Bairro Universitário, Campina Grande-PB, CEP 58109-970, Brazil.
Tel.: +55 83 2101 1202.
E-mail address: [email protected] (B.G. Bezerra).
0378-3774/$ – see front matter © 2012 Elsevier B.V. All rights reserved.
doi:10.1016/j.agwat.2012.01.013
that region in early eighties became unmanageable. This activity
became uncompetitive and economically unfeasible, being virtually wiped out in the eighties. Also contributed to its decline were
the subsidized prices in the international market and the opening
of the Brazilian market to imports of subsidized foreign fibers.
The revival of cotton growing in semiarid lands of Brazil is
important to the regional economy. According to Bezerra et al.
(2010) it is an agricultural activity of great social importance
because it adds a large number of manpower to the region. On the
other hand, the demand for raw material has been increased by
the Brazilian textile industry. Cotton growing revival in this region
depends on the adoption of new technologies mainly related to the
water use efficiency, which are very important to ensure its sustainability. In Brazilian semiarid lands, as in other semiarid lands
across the world, water became a scarce resource and its efficient
use is imperative. According to Perry et al. (2009) in these areas the
competition for scarce water resources is already widely evident.
B.G. Bezerra et al. / Agricultural Water Management 107 (2012) 86–93
Due to the annual rainfall irregularities in the semi-arid region the
rainfed cotton growing becomes unfeasible. Thus, irrigation may
provide higher yields without water stress, allowing its maximum
production. Because of the need to sustain water management in
cotton growth, several studies have been developed in the semiarid
of Brazil in order to improve water use efficiency in cotton (Azevedo
et al., 1993; Silva and Rao, 2005; Bezerra et al., 2008, 2010; Santos
et al., 2010).
In the semiarid lands of Brazilian Northeast region, about 10%
is available for agricultural practices. Inside this area appears the
Apodi Plateau area as an important pole of irrigated agricultural
production, especially horticulture. The Apodi Plateau is located in
the boundary between the Rio Grande do Norte and Ceará states, in
the Brazilian semiarid region. The groundwater is the main source
of water for irrigation, which is pumped out of Açu sandstone
through wells of about 1000 m depth, and from Jandaíra calcareous aquifer through wells of 100 m depth. Currently, the most
widely used type of wells is that exploiting the Jandaíra calcareous
aquifer.
The most fundamental requirement of scheduling irrigation
is the determination of crop evapotranspiration (ETc). The twostep crop coefficient (Kc ) versus reference evapotranspiration (ET0 )
method is a practical and reliable technique for estimating ETc, and
it is being widely used (Hunsaker et al., 2003, 2005; Allen et al.,
2005; Allen and Pereira, 2009). Besides the accuracy and reliability,
the advantage of this method is related to the fact that it is inexpensive, requiring only meteorological data to estimate ET0 which
is multiplied by a crop coefficient that represents the relative rate
of ETc and a specific condition (Allen et al., 1998; Allen and Pereira,
2009). Additionally, the knowledge of the Kc for each specific crop
growth stage is necessary. This inexpensive method makes it popular, accessible and vastly applied by the farmers in the semiarid
lands of Brazil which have restricted financial resources.
The Kc concept was introduced by Jensen (1968) and is widely
discussed and refined by the Food and Agricultural Organization
(FAO) in its Bulletin-56 (Irrigation and Drainage Paper; Allen et al.,
1998), which reports Kc values for the initial, middle and end
growth stages, Kc-ini , Kc-mid and Kc-end , respectively, for many crops
including cotton crop. However, the Kc values presented in Table
12 of FAO-56 Bulletin (Allen et al., 1998) are expected for a subhumid climate with average daily minimum relative humidity
(RHmin ) values of about 45% and calm to moderate wind speed
(u2 ) averaging 2 m s−1 . For humid, arid and semiarid climates it
has been suggested corrections to their values according to equations proposed in FAO-56 (Allen et al., 1998). However, the use of
these values can contribute to ETc estimates which are substantially different from actual ETc (Hunsaker et al., 2003), because
it has been demonstrated that Kc-ini , Kc-mid and Kc-end values for
cotton crop experimentally determined differ from those values
listed in the FAO-56 (Hunsaker, 1999; Grismer, 2002; Farahani
et al., 2008; Hribal, 2009). In the semiarid lands of Brazil some
studies have shown that Kc locally obtained was predominantly
lower than FAO Kc values (Azevedo et al., 1993; Bezerra et al.,
2010). Farahani et al. (2008) concluded that the use of the adjusted
FAO Kc values overestimate seasonal cotton crop evapotranspiration in Mediterranean climate conditions by 10–33%. Thus, to the
accurate application of this methodology, it is necessary to obtain
the Kc curve values experimentally, to represent the local weather
and water management conditions. Thus, the Kc values for cotton
crop has been experimentally determined for different climatic and
growth conditions (Azevedo et al., 1993; Ayars and Hutmacher,
1994; Hunsaker, 1999; Farahani et al., 2008; Ko et al., 2009; Hribal,
2009; Bezerra et al., 2010).
It is known that ETc data are derived from a range of measurement systems including lysimeters, eddy covariance, Bowen ratio,
soil water balance, sap flow, scintillometry and even satellite-based
87
remote sensing and direct modeling (Allen et al., 2011). The Bowen
Ratio Energy Balance (BREB) method is a practical and relatively
reliable micrometeorological approach. Allen et al. (2011) affirm
that the use of the BREB concept (Bowen, 1926) enable solving the
energy balance equation by measuring simple gradients of the air
temperature and vapor pressure in the near surface layer above the
evaporating surface. This method has been often used to estimate
the evapotranspiration from different soil–vegetation systems and
different climatic conditions (Steduto and Hsiao, 1998; Todd et al.,
2000; Azevedo et al., 2003, 2007; Inman-Bamber and McGlinchey,
2003; Teixeira et al., 2007; Zeggaf et al., 2008; Savage et al., 2009;
Hou et al., 2010; Bezerra et al., 2010). In some studies, ETc obtained
according to the BREB has been used to determine crop coefficient
curves (Inman-Bamber and McGlinchey, 2003; Hou et al., 2010;
Bezerra et al., 2010). The widespread application of this method is
attributed to its relative simplicity, practicality, robustness and precision (Todd et al., 2000; Silva et al., 2007; Gavilán and Berengena,
2007). The BREB requires measurements of air temperature and
water vapor pressure gradients, net radiation and soil heat flux in
order to obtain the latent heat flux and, consequently, the ETc.Given
the increasing competitiveness by the water use in Brazilian semiarid, and the importance of cotton in socio-economic plans for
Brazil and the world, this study aims to determine ETc and the Kc
curve values for sprinkler-irrigated cotton (cultivar BRS 187-8H)
in Apodi Plateau, semiarid land of Brazil. The locally developed Kc
curves are compared with generalized FAO Kc values adjusted for
local climate and management according to the methodology proposed in FAO-56 (Allen et al., 1998). The ETc values were obtained
using the BREB methodology while ET0 values were calculated
using weather data collected from the Apodi meteorological station
and method described in FAO-56 (Allen et al., 1998).
2. Materials and methods
2.1. Characteristics of the experimental area
Experimental campaigns were conducted in the Apodi Plateau,
west of Rio Grande do Norte State, at the experimental station of
EMPARN – Agricultural Research Company of Rio Grande do Norte,
located in Apodi County, Rio Grande do Norte State (5◦ 37 37 S,
37◦ 49 54 W, 138 m) (Fig. 1), northeastern Brazil, during the dry
seasons of 2008 and 2009 years.
The climate of the region according to Thornthwaite (1948) is
semiarid, DA’da type, with average annual precipitation of 920 mm,
concentrated in the summer and fall while the annual average of
potential evapotranspiration is equal to 2,146 mm. The average air
temperature ranges from 23.5 ◦ C in August to 28.3 ◦ C in December
while the average relative humidity ranges from 58% in October to
77% in April. Fig. 2 shows the climatological parameters observed
at the study area during last 30 years. Soil texture of experimental
area is sandy–clay–loam, with 56.8% of sand, 33.7% of clay and 9.5%
of silt.
2.2. Crop practices and irrigation
The experimental campaigns were carried out in an area of 5.0 ha
of cotton crop (G. hirsutum L., cultivar BRS 187 – 8H) under full irrigation condition. The crop was irrigated using a sprinkler system
three or four times a week. The irrigation system presented Christiansen’s uniformity coefficient (CU) equal to 84.7%. The irrigation
was scheduled using FAO-56 methodology and the total irrigation
water supplied during each irrigation event was shown in Fig. 3.
The crop was sown with a spacing of 0.9 m between rows and
the linear plant density was 10 plants m−1 , which is equivalent to
133,000 plants per ha. The fertilization in 2008 was 20.0 kg ha−1
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B.G. Bezerra et al. / Agricultural Water Management 107 (2012) 86–93
Fig. 3. Total irrigation water applied during each irrigation event.
2.3. Cotton evapotranspiration
The daily cotton ETc was estimated, from the latent heat flux
(LE) which was obtained through the BREB techniques (Perez et al.,
1999; Azevedo et al., 2003; Inman-Bamber and McGlinchey, 2003;
Silva et al., 2007; Hou et al., 2010) from the following equation:
Fig. 1. Location of study area in relation to Brazil (red rectangle) and elevation map
around Apodi Plateau. (For interpretation of the references to color in this figure
legend, the reader is referred to the web version of the article.)
of N, 60.0 kg ha−1 of P2 O5 , 40.0 kg ha−1 of K2 O and 2.0 kg ha−1 of B
at sowing and 90.0 kg ha−1 of N 40 days after emergence – DAE.
In 2009 campaign were applied 18 kg ha−1 of N, 100 kg ha−1 of
P2 O5 , 54 kg ha−1 K2 O and 2 kg ha−1 of B at sowing, 100 kg h−1 and
60 kg h−1 of N at 28 and 59 DAE, respectively.
LE =
Rn − G
1+ˇ
(1)
where Rn is the net radiation (W m−2 ), G is the soil heat flux
(W m−2 ) and ˇ is the Bowen ratio. According to the method proposed by Perez et al. (1999), for calculating the latent heat flux, for
the period of the day with positive energy available (Rn – G > 0), ˇ
was calculated from the following equation:
ˇ=
T e
(2)
where is the psychometric constant (kPa ◦ C−1 ), T and e above
canopy verticals gradients of air temperature (◦ C) and vapor pressure (kPa), respectively.
The micrometeorological tower was installed in the experimental area where the distance to the field boundary is approximately
200 m in the predominant wind direction in order to provide the
necessary fetch required by the above technique (Allen et al., 2011).
Rn measurements were obtained by a NR-LITE net radiometer
(Kipp & Zonen, Delft, The Netherland) installed at 2 m above canopy,
while G was measured by two soil heat flux plates, model HFP01SC
Self-Calibration Soil Heat Flux Plate (Hukseflux Thermal Sensors,
Delft, The Netherlands), burried at 0.02 m depth. The gradients
of the air temperature (◦ C) and vapor pressure (kPa) were measured using psychrometers constructed with thermocouples type T
(copper–constantan), installed at 0.5 and 2.0 m above canopy. The
height of psicrometers and net radiometer was adjusted weekly
following the change in plant height. Electrical signals from the
sensors used in the computation of LE were collected every 5 s and
averages extracted every 20 min, through a data acquisition system
CR3000 (Campbell Sci, Logan, UT, USA) with energy supplied by a
solar panel of 20 W.
2.4. Crop coefficient curve – Kc
To determine the Kc curve values, the four stages of crop growth
were identified based in the LAI or ground cover (see Table 2 and
Fig. 4), in accordance with the methodology proposed by FAO-56
(Allen et al., 1998), as follows:
Fig. 2. Climatic parameters such as precipitation (Prec), potential evaporation
(Evap), relative humidity (RH), and maximum (Max), average (Ave), and minimum
(Min) temperatures, and insolation for the study area during last 30 years.
• Initial-season: Period from emergence to approximately 10%
ground cover.
B.G. Bezerra et al. / Agricultural Water Management 107 (2012) 86–93
89
Fig. 5. Daily ETc for irrigated cotton in Apodi-RN in 2008 (green square) and 2009
(blue circle) years. (For interpretation of the references to color in this figure legend,
the reader is referred to the web version of the article.)
The Kc-ini-FAO was obtained graphically from the data of calculated ET0 in the period and irrigation frequency for medium
textured soils was taken from Figure 30 of the FAO-56 Bulletin
(Allen et al., 1998).
2.5. Reference evapotranspiration – ET0
Fig. 4. Temporal change of LAI and plant height of cotton in 2008 and 2009.
• Crop development: Period from 10% ground cover to effective full
cover or start of flowering.
• Middle-season: Period from start of flowering to start of maturity.
• Late-season: Period from the start of maturity to harvest or end
of water use.
The Kc curve is then constructed by knowing the duration of each
of the growth stages in addition to Kc values for the initial stage
(Kc-ini ), the middle-season (Kc-mid ) and the time of harvest (Kc-end ).
The Kc for each stage was calculated by the following equation,
defined as Kc-Local :
Kc-Local =
ETc
ET0
(3)
The Kc-ini-Local and Kc-mid-Local values match the averages of
initial and middle stages, respectively, while Kc-end Local , in turn,
corresponds to the value observed at full maturity. The results
obtained from the experimental data were compared with corresponding values of the FAO-56 Bulletin, adjusted to local conditions
through the following equations taken from Allen et al. (1998).
Kc-mid-FAO = Kc-mid(Tab) + [0.04(u2 − 2)
h 0.3
− 0.004(RHmin − 45)]
3
(4)
The ET0 was calculated by the FAO-56 method for grass (Allen
et al., 1998, 2006), based on meteorological data collected at
the meteorological station of Apodi-RN, from the automatic station network (INMET – National Institute of Meteorology), located
approximately 250 m south of cotton field, according to:
ET0 =
0.408(Rn − G) + (900/(T + 273))u2 (es − ea )
+ (1 + 0.034u2 )
(6)
where Rn is net radiation, G is soil heat flux (both in MJ m−2 d−1 ),
T is the average daily air temperature (◦ C), u2 is the wind speed
daily averaged at 2 m height (m s−1 ), es is the saturation vapor pressure (kPa), ea is the actual vapor pressure (kPa); es − ea is the vapor
pressure deficit (kPa), is the slope of the vapor pressure curve
(kPa ◦ C−1 ) and is the psychrometric constant (kPa ◦ C−1 ).
2.6. Leaf area index (LAI) and plant height
LAI and plant height were measured every 15 days from the 15th
DAE until the end of growing season totalizing six measurements
in 2008 and seven measurements in 2009. The plant height was
directly measured in field, while leaf area was measured using LI3100C Area Meter (LI-COR, Lincoln, NE, USA). The LAI was derived
from leaf area measurements and crop spacing.
3. Results and discussion
3.1. ETc, ET0 and irrigation
Kc-end-FAO = Kc-end(Tab) + [0.04(u2 − 2)
h 0.3
− 0.004(RHmin − 45)]
3
(5)
where Kc-mid(Tab) and Kc-end(Tab) are the cotton crop coefficients for
the middle and final stages, respectively, obtained from Table 12 of
FAO-56 Bulletin, u2 is the average daily wind speed at 2.0 m height;
RHmin is the average daily minimum relative humidity, h is plant
height in each period, which ranged from 0.46 m to 0.96 m on average growth stage while the end stage height observed was 1.12 m.
The weather data observed during the crop growth stage in
both the experimental campaigns are presented in Table 1. During the crop growth stages in 2008 the cumulative rainfall was
only 3.6 mm. In 2009 the cumulative rainfall was 25.8 mm concentrated in the last days of December when the crop was ready
for harvest. Observing the values of ET0 , it appears that the atmospheric water demand in the region is high according to FAO-56
(Allen et al., 1998), since these averages were about 7.0 mm d−1 in
both the campaigns. Analyzing and comparing the averages of all
the weather parameters it appears that during the experimental
90
B.G. Bezerra et al. / Agricultural Water Management 107 (2012) 86–93
Table 1
Average monthly solar radiation (Rad.), air temperature (Tair ), relative humidity (RH), wind speed at 2 m (u2 ), vapor pressure deficit (VPD), reference evapotranspiration
(ET0 ), and total monthly rainfall (Rainf.) observed during cotton growing season in both the years of study.
Month
Rad. (MJ m−2 d−1 )
Tair (◦ C)
RH (%)
u2 (m s−1 )
VPD (kPa)
ET0 (mm d−1 )
Oct/2008
Nov/2008
Dec/2008
Jan/2009
25.4
25.3
24.2
24.2
29.6
29.9
29.9
30.3
50.3
51.8
52.5
52.1
2.9
2.9
2.7
2.8
2.5
2.5
2.4
2.5
7.7
7.6
7.3
7.4
2.2
0.0
0.0
1.4
Average (2008)
Total rainfall (mm)
24.8
29.9
51.7
2.8
2.5
7.5
–
3.6
Sep/2009
Oct/2009
Nov/2009
Dec/2009
24.3
25.2
25.3
21.9
27.8
29.0
29.5
29.7
59.6
56.6
54.0
56.6
2.2
2.6
2.8
2.5
2.0
2.3
2.4
2.2
6.3
7.1
7.5
6.6
0.8
0.0
0.0
25.0
Average (2009)
Total rainfall (mm)
24.2
–
29.0
–
56.8
–
2.5
–
2.2
–
6.9
–
–
25.8
Rainf. (mm)
campaign of 2008 atmospheric water demand is higher than that
presented in 2009, as shown in Table 1. The difference shown by
the atmospheric water demand between the years of study can be
associated to the different sowing periods (see Table 3).
The growing season lengths of cotton crop in Apodi Plateau in
both the years of study are shown in Table 2. The definition of the
length of the growing season is based on field observation of the
ground cover according to the FAO-56 methodology (Allen et al.,
1998). The LAI average values, observed during each growing season, are shown in Table 3. The temporal change in LAI and plant
height observed during growing season was shown in Fig. 3. The
LAI is an important indicator of ground cover, because it has been
found high correlation between LAI and plant height (Juan et al.,
2011). The values of LAI >3 during the mid-season indicates full
ground cover provided by crop, according to Allen et al. (1998). Also
is shown in Table 2 the growing season length in terms of thermal
scale based on growing-degree-days (GDD). According to Howell
et al. (2004) the GDD scale has been reported to improve intersite
and interseasonal transferability of growing season length and Kc
curves. As can be seen in Table 1, the temperature was important
in establishing the length of the growing season, since the GDD
required by the crop in both the years was about 1500 ◦ C (Table 2).
The growing season length in 2009 was 7 days longer because the
average temperature observed during the experimental period was
almost 1 ◦ C less than in 2008 (Table 1). The average amount of GDD
obtained in this work (1503 ◦ C) was within the range presented
for many arid and semi-arid regions of cotton production, such
as Texas, Oklahoma, New Mexico (Peng et al., 1989; Howell et al.,
2004; Esparza et al., 2007; Ko et al., 2009) and Syria (Farahani et al.,
2008).
The extending increase in length of the growing season in 2009
is probably related to the differences in dates of sowing which was
anticipated by 21 days (Table 3) in this year. Thus, in 2008 the crop
has been developed in a period with higher temperature.
The higher atmospheric water demand in 2008 is evidenced by
cumulative ET0 and total irrigation water supplied (Table 4). The
cumulative ET0 was 12 mm higher in 2008, while the total irrigation
water supplied was 8 mm higher, and the growing season was 7
days shorter.
Accumulated cotton ETc was 716 and 754 mm in 2008 and 2009,
respectively (Table 4). The higher value of accumulated ETc in 2009
was due to the increase in the crop growth stage which presented
7 days more than that in 2008, as discussed previously.
Compared to literature, the 2-year average ETc value of 735 mm
is lower than those reported for the Menemen, in western Turkey
(Allen, 2000), in Bushland, Texas, USA (Grismer, 2002), in central Arizona, USA (Hunsaker et al., 2003), northern High Plains of
Texas, USA (Howell et al., 2004), in northern Syria (Farahani et al.,
2008) and for the region of Uvalde, Texas (Ko et al., 2009). However, it can be noted that the length of the growing season of
the cultivars used in all studies mentioned above have approximately 50 days longer growing season than that presented in this
study.
Moreover, it appears that the ETc obtained in this study is considerably higher than values observed in other areas of the Brazilian
semiarid such as the valleys of Sousa in the western part of Paraiba
(Azevedo et al., 1993) and the southern part of Ceará (Bezerra
et al., 2010). These results show the necessity of determining ETc
and its corresponding Kc locally, since in the Brazilian semiarid is
very heterogeneous in terms of weather, with considerable differences between the values of RH, wind speed and VPD. The weather
Table 3
Sowing, emergence and maturity dates in both the years.
Table 4
Accumulated ET0 , ETc and irrigation.
Table 2
The growing season lengths of cotton crop in Apodi Plateau in 2008 and 2009.
Cotton growth stages
2008
Initial
Crop-development
Mid-season
Late-season
Full-season
2009
Initial
Crop-development
Mid-season
Late-season
Full-season
Length
(days)
15
28
38
24
105
17
30
40
25
112
LAI
(cm2 cm−2 )
0.14
1.10
5.20
4.70
Cumulative
GDDa (◦ C)
211
396
556
336
–
1499
0.18
1.12
5.28
4.80
207
396
556
348
–
1507
◦
a
GDD was obtained using basal temperature of 15.6 C (Howell et al., 2004;
al., 2009) employing the standard method (Mavi and Tupper, 2004):
Ko et (Tmax − Tmin )/2 − 15.6.
GDD =
Sowing date
Emergence date
Full maturity date
2008
2009
22/sep/2008
29/sep/2009
12/jan/2009
01/sep/2009
08/sep/2009
28/dec/2009
Total ET0 (mm)
Total irrigation (mm)
Total ETc
2008
2009
Mean
789
892
716
777
884
754
783
899
735
B.G. Bezerra et al. / Agricultural Water Management 107 (2012) 86–93
Table 5
Mean values of energy used as latent heat flux (LE/Rn) and soil heat flux (G/Rn),
evaporative fraction () and Bowen ratio (ˇ) during each growth stage in 2008 and
2009 of the cotton crop in Apodi-RN.
Energy balance partitioning
2008
2009
a
(LE/Rn)a (%)
(G/Rn)a
ˇ
Initial-season
Crop-development
Mid-season
Late-season
58.2
74.5
81.5
75.1
13.1
14.3
7.8
9.4
0.68
0.83
0.87
0.75
0.32
0.27
0.13
0.15
Full growth season
72.3
11.2
0.78
0.22
Initial-season
Crop-development
Mid-season
Late-season
63.4
74.0
80.9
76.0
14.9
13.5
6.1
7.1
0.78
0.82
0.84
0.78
0.14
0.23
0.10
0.17
Full growth season
73.6
10.4
0.82
0.16
The LE/Rn and G/Rn were multiplied by 100%.
heterogeneity in the region is already known from literature (Silva,
2004).
The daily cotton ETc values ranged from 3.7 to 9.3 mm d−1 in
2008 and from 3.7 to 9.6 mm d−1 in 2009 (Fig. 5). The minimum
values were observed in the initial stage, while the maximum values were attained in the middle stage in both campaigns, that is,
79 DAE in 2008 and 45 DAE in 2009. These maximum values are
lower than those attained in Texas (Howell et al., 2004; Ko et al.,
2009). This difference can be attributed to the different climatic
conditions between them, i.e. Brazilian semiarid (this study) and
Texas (arid climates). On the other hand, these values are higher
than those obtained in the Brazilian semiarid such as the valleys
of Souza in the western part of Paraiba State (Azevedo et al., 1993)
and in the southern part of Ceará State (Bezerra et al., 2010). This
difference can be related to the orographic effects, which change
meteorological parameters, such as: humidity, temperature, and
wind speed.
The percentage of Rn used as LE and G other than evaporative fraction (), ratio between LE and available energy (Rn − G)
(Shuttleworth et al., 1989), and Bowen ratio (ˇ) were shown in
Table 5. The largest water consumption occurred during midseason whose percentage of Rn used as LE, as well as, was
exceeded 80%, while the ˇ and G/Rn values were lowest (Table 5).
The value reflects the soil moisture conditions in the root zone
(Scott et al., 2003). According to Teixeira et al. (2007) high values
reveal that crop is not water stressed and that the soil is wet.
The largest water consumption occurs in this stage because the
plant is in the prime of its development and its physiological and
metabolic functions, since it is the flowering and boll formation
stage, where the LAI reaches its maximum (Table 2 and Fig. 4). On
the other hand, the lowest percentages of Rn converted into LE
occurred during initial growth stage with values equal to 58.2% and
63.4% in both 2008 and 2009 years, respectively. The reasons for
largest percentage of Rn used as LE, higher , and lowest ˇ, during
the initial-stage in 2009, will be discussed later.
The percentage of Rn used as G presented values in accordance
with the growth stage, which means that the increase in the ground
cover reflects the decrease of G. During mid-season their values
were less than 10%, while highest values have been observed during
initial growth season. According to Allen et al. (2011) the accuracy
of ET depends substantially on the representativeness and accuracy
of G measurements. The average values observed in both experimental campaigns, about 10%, is similar to majority of values found
by Ham et al. (1991) for cotton crop at Texas and for other crops
in the Brazilian semiarid such as table and wine grapes and mango
(Teixeira et al., 2007; Silva et al., 2007).
91
Table 6
Comparison between cotton yield (Y) in Apodi-RN and other studies at Brazilian
semiarid under full irrigation conditions.
Source
Cultivar studied
Y (kg ha−1 )
In this study
Oliveira et al. (1999)
Bezerra et al. (2003)
Bezerra et al. (2008)
CNPA 187 8H
Acala del cerro
BRS 201
BRS 200 – Marrom
3517
3468
4472
3289
The cotton yield in Apodi-RN was 3448 kg ha−1 and 3586 kg ha−1
in 2008 and 2009, respectively. The average value obtained in this
study is compared with some previous results obtained in the
Brazilian semi-arid region. The value found in Apodi is similar to
those studies, whose difference was around ±10%, although the
cultivars are different and the details are shown in Table 6.
3.2. Kc-FAO-Adjusted versus Kc-Locally-Developed
The Kc-FAO-Adjusted and Kc-Locally-Developed values for the initial,
middle and end seasons of the sprinkler-irrigated cotton, in the
Brazilian semiarid are presented in Table 7 and Fig. 6a and b.
The Kc-FAO curve values differed considerably from the Kc-Local values, presented in Table 7 and Fig. 6b, with differences that varied
between 2.5 and 20%.
The Kc-ini-Local values were lower than the values of Kc-ini-FAO in
both the experimental campaigns, with an average difference about
6.0%. The average value of 0.75 is very similar to results obtained
by Ko et al. (2009) in Texas, but is about 40% higher than those
obtained by Azevedo et al. (1993) in the Brazilian semiarid and
almost three times higher than results obtained from other regions
such as Syria (Farahani et al., 2008) and Louisiana, USA (Hribal,
2009). These differences are attributed to the sensibility of Kc-ini
to irrigation management and systems.
The Kc-mid-Local values were practically the same in both the
years of observation (i.e. 1.08 and 1.09) and also showed similar differences in relation to Kc-mid-FAO in both the campaigns, i.e.
about 10% lower. The values of Kc-mid-Local obtained in this study
are quite similar to those found by Azevedo et al. (1993), Mohan
and Arumugam (1994) and Farahani et al. (2008). However, the
difference between Kc-mid-Local and Kc-mid-FAO found by Farahani
et al. (2008) was about 24%, showing higher values in comparison
with this study. Kc-mid-Local values found in other cotton productive regions, as Texas, California, Arizona and Louisiana, presented
differences ranging from 14 to 25% higher than those found here
(Hunsaker, 1999; Grismer, 2002; Hunsaker et al., 2003; Ko et al.,
2009; Hribal, 2009). These differences can be related to the climate
factors such as higher insolation, lower humidity and higher temperature, different cultivars studied, and irrigation management.
Probably the reason for the lower values of the Kc-mid-Local when
compared with Kc-mid-FAO is related to the possible overestimation of ET0 that occurs in seasons/climates very different from
the spring/summer values typical of the humid temperate regions
that served as the main basis to calibrate stomatal resistance value
Table 7
Kc-FAO-Adjusted and Kc-Local for the cotton crop sprinkler-irrigated in the Brazilian
semiarid.
Adjusted FAO Kc
Kc-ini-FAO
Kc-mid-FAO
Kc-end-FAO
Locally developed Kc
Kc-ini-Local
Kc-mid-Local
Kc-end-Local
2008
2009
Average
0.70
1.20
0.66
0.90
1.21
0.74
0.84
1.20
0.70
0.68
1.08
0.80
0.82
1.09
0.79
0.75
1.09
0.80
92
B.G. Bezerra et al. / Agricultural Water Management 107 (2012) 86–93
The Kc-ini sensitivity to irrigation management is known in literature, previously addressed by several authors (Jensen et al., 1990;
Allen et al., 1998; Farahani et al., 2008; López-Urrea et al., 2009).
Allen et al. (1998) argue that its value can vary from 0.10 to 1.15,
mainly influenced by the frequency and intensity of surface wetness (rain or irrigation). López-Urrea et al. (2009) and Cavero et al.
(2009) also attribute the frequent use of sprinkler irrigation system as a contributing factor to the high values of ETc during the
crop initial stage, because it causes intense wetting of the surface and consequently high soil evaporation due to its incomplete
ground cover provided by the crop. Typically, on the days after irrigation events, the ETc is often 20% higher than the ET0 (Doorenbos
and Kassam, 1979). Unlike the Kc-ini , the values of Kc-mid-Local and
Kc-end-Local were quite stable showing almost the same results in
both the experimental campaigns.
The use of the adjusted FAO Kc overestimated ETc in both the
years by about 12% corresponding to 95 mm. The overestimation of
ETc by using the Kc-FAO-Adjusted is remarkable, which requires about
10 h of additional irrigation. The irrigation scheduling based on the
Kc-FAO-Adjusted increases production cost and yield loss.
4. Summary and conclusions
Fig. 6. Curves of Kc locally developed during the experimental periods of 2008 (a)
and 2009 (b) and (c) its mean curve (blue line) compared with the curve of the
adjusted FAO Kc (green line). (For interpretation of the references to color in this
figure legend, the reader is referred to the web version of the article.)
(70 s m−1 ) adopted in FAO-56. Although the FAO-56 method, which
is recommended for ET0 calculations, it has been identified as overestimation in semi-arid climates (López-Urrea et al., 2006). In fact, it
is not physically credible that a rough crop with about 1.0 m height
(see Fig. 4), as presented in this study, has an evapotranspiration
rate only 8% (2008) and 9% (2009) higher than the grass surface with
0.12 m (see Table 7). Thus, the Kc-mid-Local represents the cotton crop
coefficient for the Brazilian semi-arid climate.
The Kc-end-Local was higher than Kc-end-FAO whose differences
were about 10%. The Kc-end-Local of 0.80 is about 18% higher than
values found by Azevedo et al. (1993) and Farahani et al. (2008),
0.65 and 0.66, respectively, and lower than those found by Grismer
(2002), with values of 0.87 for Sacramento and San Joaquin valleys,
0.95 for California desert counties and 0.90 for the Uvalde region,
Texas, USA (Ko et al., 2009).
Table 7 and Fig. 6a and b show that the Kc-ini-Local was very susceptible to local variations, especially the irrigation management.
During initial stage in 2009 there was an error in the irrigation
scheduling during 1 week, which was detected and corrected. This
error implies in an increment of 70 mm in the water supplied by
irrigation in 2009 compared to 2008 and resulted in a Kc-ini-Local
value of about 20% higher.
The excessive irrigation water supplied during initial stage in
2009 is detected by energy balance elements showed in Table 5.
The percentage of Rn used as LE in 2009 was 5% higher than 2008
while was 14% higher indicating an increase of ETc. In turn, the
ˇ value observed during the initial stage in 2009 was about 50%
lower than 2008. On the other hand, the percentage of Rn used
as G observed during the initial stage in 2009 was higher than its
corresponding value in 2008. The increase of the soil water content
caused the rise of soil heat flux values which in turn increase the
soil thermal conductivity (Abu-Hamdeh and Reeder, 2000).
This study aimed to determine experimentally the Kc curve and
ETc of sprinkler-irrigated cotton in the Brazilian semiarid lands.
The two-step crop coefficient (Kc ) versus reference evapotranspiration (ET0 ) method is widely applied due its simplicity and limited
data requirements for irrigation scheduling and water management. However, according to Hunsaker et al. (2003), the use of
generalized Kc values presented in FAO-56 can contribute to ETc
estimates that substantially differ from actual ETc. It is confirmed by
Kc-Local results which are lower than those of the FAO-56 adjusted
to local conditions. Mean differences were observed in the order
of 13, 18 and 10% for Kc-ini , Kc-mid and Kc-end , respectively. Using
the Kc-FAO-Adjusted curve values to estimate the cotton ETc led to
overestimation of ETc with differences exceeding 10% compared
with values obtained from Kc-Locally-developed in both the observation
years. This discrepancy corroborates with that found by Farahani
et al. (2008). The irrigation scheduling based on the Kc-FAO-Adjusted
implies excess water supply causing substantial increases in production costs and yield losses, as evidenced by literature.
The Kc-mid-Local and Kc-end-Local values did not differ in the two
observation years. However, the Kc-ini was highly susceptible to
variation of irrigation management, which corroborates with the
facts already known in the literature. The Kc values found for Kc-ini ,
Kc-mid and Kc-end were 0.75, 1.09 and 0.80, respectively. However,
the Kc-ini value is unreliable because of the problems occurred in
irrigation scheduling during the initial growth stage of 2009 season, as explained earlier. So it is recommended that one should be
careful in its use and that further studies should be conducted for
more reliable results.
The ETc obtained from BREB in Apodi Plateau was higher than
those values obtained in other regions of the Brazilian semiarid,
suggesting the weather heterogeneity of the region. These higher
values are attributed to atmospheric water demand in the study
area showing ET0 values classified by the FAO-56 (Allen et al., 1998)
as very high.
Acknowledgments
The authors gratefully acknowledge the CNPq/CT-HIDRO for
granting a PhD scholarship to the first author and CNPq for funding
the Generation and Transfer of Technologies for the Sustainability of Cotton in the Northeast Semiarid Project (Projeto Geração e
Transferência de Tecnologias para a Sustentabilidade do Algodoeiro
B.G. Bezerra et al. / Agricultural Water Management 107 (2012) 86–93
no Semiárido Nordestino), covenant ATECEL-FINEP-EMBRAPA, no.
591-07 and to INMET for providing the meteorological data used
during the experimental campaigns.
References
Abu-Hamdeh, N.H., Reeder, R.C., 2000. Soil thermal conductivity: effects of density, moisture, salt concentration, and organic matter. Soil Sci. Soc. Am. J. 64,
1285–1290.
Allen, R.G., 2000. Using the FAO-56 dual crop coefficient method over an irrigated
region as part of an evapotranspiration intercomparison study. J. Hydrol. 229,
27–41.
Allen, R.G., Clemmens, A.J., Burt, C.M., Solomon, K., O’Halloran, T., 2005. Prediction accuracy for projectwide evapotranspiration using crop coefficients and
reference evapotranspiration. J. Irrig. Drain. Eng. 131 (1), 24–36.
Allen, R.G., Pruitt, W.O., Wright, J.L., Howell, T.A., Ventura, F., Snyder, R., Itenfisu,
D., Steduto, P., Berengena, J., Yrisarry, J.B., Smith, M., Pereira, L.S., Raes, D., Perrier, A., Alves, I., Walter, I., Elliot, R., 2006. A recommendation on standardized
surface resistance for hourly calculation of reference ET0 by the FAO56 PenmanMonteith method. Agric. Water Manage. 81, 1–22.
Allen, R.G., Pereira, L.S., 2009. Estimating crop coefficients from fraction of ground
cover and height. Irrig. Sci. 28, 17–34.
Allen, R.G., Pereira, L.S., Howell, T.A., Jensen, M.E., 2011. Evapotranspiration information reporting. I. Factors governing measurement accuracy. Agric. Water
Manage. 98, 899–920.
Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop evapotranspiration: guidelines for computing crop water requirements. In: United Nations FAO, Irrigation
and Drainage Paper 56. FAO, Rome, Italy.
Ayars, J.E., Hutmacher, R.B., 1994. Crop coefficient for irrigating in the presence of
groundwater. Irrig. Sci. 15, 45–52.
Azevedo, P.V., Rao, T.V.R., Amorim Neto, M.S., Bezerra, J.R.C., Espínola Sobrinho,
J., Maciel, G.F., 1993. Necessidades hídricas da cultural do algodoeiro. Pesq.
Agropec. Bras. 28 (1), 863–870 (in Portuguese with English abstract).
Azevedo, P.V., Silva, B.B., Silva, V.P.R., 2003. Water requirements of irrigated mango
orchard in northeast Brazil. Agric. Water Manage. 58, 241–254.
Azevedo, P.V., Souza, C.B., Silva, B.B., Silva, V.P.R., 2007. Water requirements of
pineapple crop grown in a tropical environment, Brazil. Agric. Water Manage.
88, 201–208.
Bezerra, J.R.C., Azevedo, P.V., Silva, B.B., Dias, J.M., 2010. Evapotranspiração e coeficiente de cultivo do algodoeiro BRS-200 Marrom. Irrigado. Rev. Bras. Eng. Agric.
Ambient. 14 (6), 625–632 (in Portuguese with English abstract).
Bezerra, J.R.C., Azevedo, P.V., Dias, J.M., Silva, B.B., Luz, M.J.S., 2008. Efeito da lâmina
de irrigação na rentabilidade do algodoeiro BRS 200 – Marrom. Rev. Bras. Oleag.
Fibr. 12 (3), 97–106 (in Portuguese with English abstract).
Bezerra, J.R.C., Luz, M.J.S., Pereira, J.R., Dias, J.M., Santos, J.W., Santos, T.S., 2003. Rendimento e qualidade da fibra do algodoeiro herbáceo em diferentes épocas de
interrupção da irrigação. Rev. Bras. Oleag. Fibr. 7, 719–726 (in Portuguese with
English abstract).
Bowen, I.S., 1926. The ratio of heat losses by conduction and by evaporation from
any water surface. Phys. Rev. 27, 779–787.
Cavero, J., Medina, E.T., Puig, M., Martinez-Cob, A., 2009. Sprinkler irrigation changes
maize canopy microclimate and crop water status, transpiration, and temperature. Agron. J. 101, 854–864.
Doorenbos, J., Kassam, A.H., 1979. Yield response to water. In: FAO Irrigation and
Drainage Paper No. 33. FAO, Rome, Italy, 193 pp.
Esparza, A.M., Gowda, P.H., Baumhardt, R.L., Mareck, T.H., Howell, T.A., 2007. Heat
unit availability for cotton productions in the Ogallala Aquifer Region of the
United States. J. Cotton Sci. 11, 110–117.
Farahani, H.J., Oweis, T.Y., Izzi, G., 2008. Crop coefficient for drip-irrigated cotton in
a Mediterranean environment. Irrig. Sci. 26, 275–383.
Gavilán, P., Berengena, J., 2007. Accuracy of Bowen ratio-energy balance method for
measuring latent heat flux in a semiarid advective environment. Irrig. Sci. 25 (2),
127–140.
Grismer, M.E., 2002. Regional cotton lint yield, ETc, and water value in Arizona and
California. Agric. Water Manage. 54 (3), 227–242.
Ham, J.M., Heilman, J.L., Lascano, R.J., 1991. Soil and canopy energy balances of a row
crop at partial cover. Agron. J. 83, 744–753.
Hou, L.G., Xiao, H.L., Si, J.H., Zhou, M.X., Yang, Y.G., 2010. Evapotranspiration and
crop coefficient of Populus euphratica Olivi forest during the growin season in
the extreme arid region northwest China. Agric. Water Manage. 97 (2), 351–356.
Howell, T.A., Evett, S.R., Tolk, J.A., Schneider, A.D., 2004. Evapotranspiration of full-,
deficit-irrigated, and dryland cotton on the Northern Texas High Plains. J. Irrig.
Drain. Eng. 130 (4), 277–285.
Hribal, S.A., 2009. Crop Coefficients for Cotton in Northeastern Louisiana. Master
of Science Degree Thesis 60p – Agricultural and Mechanical College, Louisiana
State University, Baton Rouge.
93
Hunsaker, D.J., 1999. Basal crop coefficients and water for early maturity cotton.
Trans. ASAE 42 (4), 927–936.
Hunsaker, D.J., Barnes, E.M., Clarke, T.R., Fitzgerald, G.J., Printer Jr., P.J., 2005. Cotton
irrigation scheduling using remotely sensed and FAO-56 basal crop coefficients.
Trans. ASAE 48 (4), 1395–1407.
Hunsaker, D.J., Pinter Jr., P.J., Barnes, E.M., Kimball, B.A., 2003. Estimating cotton
evapotranspiration crop coefficients with a multispectral vegetation index. Irrig.
Sci. 22, 95–104.
Inman-Bamber, N.G., McGlinchey, M.G., 2003. Crop coefficients and water-use
estimates for sugarcane based on long-term Bowen ratio energy balance measurements. Field Crops Res. 83, 12–138.
Jensen, M.E., 1968. Water consumption by agricultural plants. In: Kozlowsky, T.T.
(Ed.), Water Deficits and Plant Growth, vol. II. Academic Press, New York, pp.
1–22.
Jensen, M.E., Burman, R.D., Allen, R.G., 1990. Evapotranspiration and the irrigation
water requirements. In: ASCE Manual No. 70. ASCE, New York.
Juan, W., Changzhou, W., Jinqiang, G., Yongwen, L., 2011. A method base on digital image analysis for estimating crop canopy parameters. In: Proceedings of
the International Conference on Computer Distributed Control and Intelligent
Environmental Monitoring, Changsha, Hunan, Chine, pp. 338–341.
Ko, J., Piccinni, G., Marek, T., Howell, T., 2009. Determination of growth-stagespecific crop coefficients (Kc ) of cotton and wheat. Agric. Water Manage. 96
(12), 1691–1697.
López-Urrea, R., Martín de Santa Olalla, F., Fabeiro, C., Moratalla, A., 2006. Testing evapotranspiration equations using lysimeter observations in a semiarid
climate. Agric. Water Manage. 85, 15–26.
López-Urrea, R., Montoro, A., González-Piqueras, J., López-Fuster, P., Fereres, E., 2009.
Water use of spring wheat to rise water productivity. Agric. Water Manage. 96,
1305–1310.
MacDonald, S., Vollrath, T., 2005. The forces of shaping world cotton consumption
after the multifiber arrangement. Outlook Report CWS-05c-01. USDA, Economic
Research Service.
Mavi, H.S., Tupper, G.J., 2004. Agrometeorology: Principles and Application of Climate Studies in Agriculture, 1st ed. Food Products Press, New York, 364 pp.
Mohan, S., Arumugam, N., 1994. Crop coefficient of major crops in south India. Agric.
Water Manage. 26 (1–2), 67–80.
Oliveira, F.A., Bezerra, J.R.C., Oliveira, B.C., 1999. Efeito do manejo da irrigação e de
população de plantas sobre o rendimento do algodoeiro herbáceo. Pesq. Agropec.
Bras. 34, 2185–2191 (in Portuguese with English abstract).
Peng, S., Krieg, D.R., Hicks, S.K., 1989. Cotton lint yield response to accumulated heat
units and soil water supply. Field Crops Res. 19, 253–262.
Perez, P.J., Castelvi, F., Ibañez, M., Rossel, J.I., 1999. Assessment of reliability of Bowen
ratio method for partitioning fluxes. Agric. Forest Meteorol. 97, 141–150.
Perry, C., Steduto, P., Allen, R.G., Burt, C.M., 2009. Increasing productivity in irrigated agriculture: agronomic constrains and hydrological realities. Agric. Water
Manage. 96, 1517–1524.
Santos, C.A.C., Bezerra, B.G., Silva, B.B., Rao, T.V.R., 2010. Assessment of daily actual
evapotranspiration with SEBAL and S-SEBI algorithms in cotton crop. Rev. Bras.
Meterol. 25 (3), 383–392.
Savage, M.J., Everson, C.S., Metelerkamp, B.R., 2009. Bowen ratio evaporation measurement in a remote montane grassland: data integrity and fluxes. J. Hydrol.
376, 249–260.
Scott, C.A., Bastiaanssen, W.G.M., Ahmad, M.D., 2003. Mapping root zone soil moisture using remotely sensed optical imagery. J. Irrig. Drain. Eng. 129, 326–335.
Shuttleworth, W.J., Gurney, R.J., Hsu, A.Y., Ormsby, J.P., 1989. FIFE: The Variation in
Energy Partition at Surface Flux Sites, vol. 186. IAHS Publication, pp. 67–74.
Silva, B.B., Rao, T.V.R., 2005. The CWSI variations of a cotton crop in a semi-arid
region of Northeast Brazil. J. Arid Environ. 62, 649–659.
Silva, V.P.R., 2004. On climate variability in Northeast of Brazil. J. Arid Environ. 58,
575–596.
Silva, V.P.R., Azevedo, P.V., Silva, B.B., 2007. Surface energy balance and evapotranspiration of a mango orchard grown in a semiarid environment. Agron. J. 99,
1391–1396.
Steduto, P., Hsiao, T.C., 1998. Maize canopies under two soil water regimes. IV.
Validity of Bowen ratio-energy balance techniques for measurements water
vapor and carbon dioxide fluxes at 5-min intervals. Agric. Forest Meteorol. 89,
215–228.
Teixeira, A.H., Bastiaanssen, W.G.M., Bassoi, L.H., 2007. Crop water parameters of
irrigated wine and table grapes to support water productivity analysis in the
São Francisco river basin, Brazil. Agric. Water Manage. 94, 31–42.
Thornthwaite, C.W., 1948. An approach toward a rational classification of climate.
Geogr. Rev. 38, 55–94.
Todd, R.W., Evett, S.R., Howell, T.A., 2000. The Bowen ratio-energy balance method
for estimating latent heat flux of irrigated alfalfa evaluated in a semi-arid, advective environment. Agric. Forest Meteorol. 130, 335–348.
Zeggaf, A.T., Takeuchi, S., Dehghaniasanij, H., Anyoji, H., Yano, T., 2008. A Bowen ratio
technique for partitioning energy fluxes between maize transpiration and soil
surface evaporation. Agron. J. 100, 988–996.