Bioscience Journal | 2022 | vol. 38, e38012 | ISSN 1981-3163
1
Lucas Maltoni ANDRADE1 , Jean Carlos Coelho PACHECO1 , Giovanna Lyssa Lacerda COSTA1 ,
Carlos Augusto Brasileiro de ALENCAR2 , Fernando França da CUNHA2
1 Agricultural and Environmental Engineering, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil.
2 Department of Agricultural Engineering, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil.
Corresponding author:
Fernando França da Cunha
Email: fernando.cunha@ufv.br
How to cite: ANDRADE, L.M., et al. Uniformity of water distribution by a sprinkler irrigation system on a soccer field. Bioscience Journal. 2022,
38, e38012. https://doi.org/10.14393/BJ-v38n0a2022-57028
Abstract
Soccer field grass can be compared to highly sensitive crops regarding water deficit and must be irrigated
throughout the year to provide decent conditions for use. For this, efficient irrigation systems are necessary
to save water and energy, and this is possible, provided that they are evaluated. Therefore, this paper
evaluated the water distribution uniformity, by different methodologies, for an irrigation system installed in
a grass soccer field. Also, the influences of multiple spacings between sprinklers and meteorological factors
on the final results were assessed. The irrigation system had Falcon 6504 sprinklers, operating at the
pressure of 320 kPa. Six field essays were conducted considering overlaying water depths originated from
the same irrigation system considering spacings between sprinklers varying from 6 m x 6 m, 6 m x 9 m, 9 m
x 9 m, 9 m x 12 m, 12 m x 12 m, 12 m x 15 m, 15 m x 15 m, 15 m x 18 m, 18 m x 18 m, 18 m x 21 m, 21 m x
21 m, 21 m x 24 m, 24 m x 24 m, 24 m x 27 m, 27 m x 27 m, 27 m x 30 m and 30 m x 30 m. The uniformity
coefficients used were: Christiansen uniformity coefficient (CU), distribution uniformity coefficient (DU),
absolute uniformity coefficient (UA), statistical uniformity coefficient (US), Hart uniformity coefficient (UH)
and HSPA standard efficiency (UHSPA). Meteorological data were obtained during the essays. Wind speed
caused reduction in the length of the water jet applied by the sprinkler and also caused a bigger effect on
the water distribution uniformity. Both CU and UH showed higher values compared to the other coefficients.
The increase in the spacing between the sprinklers resulted in reduced water distribution coefficients. To
comply with technical and economic criteria, an arrangement of 12 m x 15 m between the Falcon 6504
sprinklers, operating at a 320 kPa pressure, is recommended.
Keywords: CU. Grass Field Irrigation. Irrigation Efficiency. Sprinkler Spacing.
1. Introduction
The grass for soccer fields, golfing, gardens and many others occupies large expanses of land and are
highly sensitive to water deficit, requiring an appropriate irrigation management throughout the year. The
water, when supplied in the right moment and quantity, guarantees that the grass field will be maintained
in ideal conditions for proper practice of sports and aesthetic purposes (García-González et al. 2015; Siqueira
et al. 2018). Thus, an adequate irrigation system presents itself as a relevant strategy to achieve these goals.
Irrigation is the world’s major consumer of water, accounting for, on average, 70% of all its use (FAO-
WWC 2015). In Brazil, this use reaches 68.4%, according to recent studies (Ana 2019). In 2050, it is expected
that irrigation will remain the world’s major water user, representing more than half of all abstractions from
UNIFORMITY OF WATER DISTRIBUTION BY A SPRINKLER
IRRIGATION SYSTEM ON A SOCCER FIELD
https://orcid.org/0000-0003-0715-8989
https://orcid.org/0000-0001-6120-6369
https://orcid.org/0000-0002-4588-9013
https://orcid.org/0000-0001-9866-6254
https://orcid.org/0000-0002-1671-1021
Bioscience Journal | 2022 | vol. 38, e38012 | https://doi.org/10.14393/BJ-v38n0a2022-57028
2
Uniformity of water distribution by a sprinkler irrigation system on a soccer field
rivers, lakes and aquifers. Therefore, it is of increasing relevance that these water users worry about such
vital resource and adopt irrigations systems that can perform with high efficiency, so the water will not be
wasted, and the crops can perform their best, under the given conditions.
The conventional sprinkler irrigation system is largely used in Brazil (Alves et al. 2017). However,
under adverse meteorological conditions, such as high temperatures, low air humidity and increased wind
speed, this system does not perform in its full capacity, causing considerable losses of water, fertilizer, and
electricity due to its lower efficiency (Molle et al. 2012; Sheikhesmaeili et al. 2016; Araújo et al. 2020).
Siqueira et al. (2018) affirm that, although modern systems make use of advanced technologies to reduce
water and energy consumption, it is not possible to reduce their wastes to zero.
Irrigation efficiency can be defined as the amount of water applied by irrigation that is, in certain
quantity, absorbed by crops, being a fine indicator related to irrigation efficiency, water management and
recent technologies in irrigation (Wu et al. 2019). Such efficiency is a result of application, distribution, and
conduction efficiencies (Filgueiras et al. 2020).
The distribution efficiency can be obtained by the distribution uniformity, which consists in a
measurable capacity of an irrigation system to apply an equal amount of water in the irrigated perimeter
(Keller and Bliesner 1990; Mohamed et al. 2019). The distribution uniformity for different irrigation types is
also influenced by different factors, related to each technique of irrigation (Andrade et al. 2015). Particularly
for sprinkler systems, the uniformity is related not only to its mechanical aspects (flow rate, operating
pressure, spacing, nozzle diameter, etc.), but also to meteorological conditions, especially wind direction
and speed (Keller and Bliesner 1990; Faria et al. 2016). Its estimate is frequently evaluated based on the
uniformity coefficients.
Among the coefficients used to express water distribution variability, the first was proposed by
Christiansen (1942) and uses the absolute average deviation as a dispersion measurement (Christiansen
uniformity coefficient - CU). Additionally, Wilcox and Swailes (1947) proposed a uniformity coefficient using
the standard deviation as a dispersion measurement, for which only values above 75% are accepted
(statistical uniformity coefficient - US). Criddle et al. (1956) introduced another uniformity parameter, this
time considering the ratio between the lowest quartile average and the average water depth that was
collected (distribution uniformity coefficient - DU). Hart (1961) also proposed a uniformity coefficient using
the standard deviation as a dispersion measurement (Hart uniformity coefficient - UH). Consequently, when
the applied water depth has a normal distribution, CU and UH will be equaled. Hart (1961) also proposed
another coefficient related to the distribution uniformity, known as HSPA standard efficiency (HSPA standard
efficiency - UHSPA). Similar to UH, when the applied water depth shows a normal distribution, UHSPA and DU
will be equaled. Karmeli and Keller (1975) proposed a uniformity measurement that includes the ratio of the
maximum and minimum flows with the average (absolute uniformity coefficient - UA).
Many studies have been conducted aiming to evaluate and define projects of irrigation systems based
on their water distribution uniformity (Mohamed et al. 2019; Rodrigues et al. 2019; Araújo et al. 2020;
Filgueiras et al. 2020). However, studies evaluating irrigation systems for soccer fields are insufficient in the
literature. Therefore, this study evaluated, using different methodologies, the distribution uniformity of an
irrigation system designed for a soccer field, and verified the influence of different spacings between
sprinklers and meteorological factors on the final results.
2. Material and Methods
Study location
The essays of uniformity were conducted in a soccer field, during October and November 2019,
located at “Clube Campestre de Viçosa” (Figure 1), situated in the city of Viçosa, Minas Gerais State, Brazil,
with the following coordinates: latitude 20.7408º S, longitude 42.8629º W and altitude of 706 m, in the
region known as “Zona da Mata Mineira”. Its local climate, according to the Köppen-Geiger classification is
Cwa, consisting in a humid subtropical climate, with dry winters and hot summers (Alvares et al. 2013).
Bioscience Journal | 2022 | vol. 38, e38012 | https://doi.org/10.14393/BJ-v38n0a2022-57028
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ANDRADE, L.M., et al.
Figure 1. A – experimental area in relation to “Clube Campestre” in the city of Viçosa-MG; B – the sketch of
the pluviometers’ arrangement for the essays of uniformity.
This work consisted of the evaluation of an irrigation system composed of rotor sprinklers, Falcon
6504 model (nozzle 14), made by Rain Bird company. This sprinkler is retractable, especially recommended
for grass fields destined for sports practices or green spaces. The manufacturer’s recommendations estimate
an ideal operating pressure within the interval from 250 to 550 kPa. Figure 2A represents the operating
pressure versus flow rate function and in the Figure 2B the water jet length applied by the sprinklers. It is
important to highlight that the adjusted models are only relevant to the operating pressure between 250
and 550 kPa. The field essays were carried out with an average pressure of 320 kPa, with an average flow
rate of 2.835 m3 h-1.
Figure 2. Technical features of Falcon 6504 (nozzle 14) sprinkler: A – flow versus operating pressure curve;
B – water jet length as a function of operating pressure.
Sprinklers evaluation in the field
To evaluate the distribution uniformity, water collectors produced by Fabrimar® were used. The
collectors were arranged around a single sprinkler, at a uniform spacing of 3 m x 3 m (Figure 1D). With such
arrangement, each water collector represented a 9 m2 squared area, complying with Brazilian regulation
ABNT-NBR: 14244 (ABNT 1998). 12 columns and 12 rows of collectors were installed, resulting in a total of
144 water collectors around the single sprinkler, with a total coverage area of 1,296 m2. The maximum
distance between a collector and the sprinkler was 23.3 m, to make sure that the water depths would be
zero at the extremities. All collectors were placed 0.70 m above ground, according to the methodology of
Merriam and Keller (1978).
Six field essays were conducted, each one of them lasting for 40 min, under distinct meteorological
conditions. During the essays, average air temperature, humidity, wind speed, solar radiation and vapor
pressure deficit (es-ea) data were collected, as shown in Table 1. The average air temperature, relative
humidity, wind speed and solar radiation data were measured by an automated meteorological station
during the irrigation system experiments. These data were used to determine the actual vapor pressure and
1
A
B
2
y = 1.5643 + 0.0040x
r² = 0.9972
2,4
2,6
2,8
3,0
3,2
3,4
3,6
3,8
250 300 350 400 450 500 550
S
p
ri
n
k
le
r
fl
o
w
(
m
3
h
-1
)
Operating pressure (kPa)
y = 11.8286 + 0.0255x - (0.0049x)2
R² = 0.9865
16,7
17,0
17,3
17,6
17,9
18,2
18,5
18,8
250 300 350 400 450 500 550
S
p
ri
n
k
le
r
re
a
c
h
r
a
d
iu
s
(
m
)
Operating pressure (kPa)
Bioscience Journal | 2022 | vol. 38, e38012 | https://doi.org/10.14393/BJ-v38n0a2022-57028
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Uniformity of water distribution by a sprinkler irrigation system on a soccer field
saturation vapor pressure using the average values obtained in the experiments. Thus, the saturation vapor
pressure deficit was obtained by the difference between the two pressures mentioned.
Table 1. Average values of meteorological factors during the irrigation system’s essays.
Date Time
Air temperature Air humidity Wind speed Solar radiation es-ea
(°C) (%) (m s-1) (MJ m-2) (hPa)
10/25/2019 2:45 pm 31.3 37.1 0.78 2.06 28.7
10/30/2019 6:20 pm 23.4 71.3 0.76 0.05 8.2
11/14/2019 2:20 pm 26.6 59.3 1.77 1.57 14.2
11/14/2019 3:40 pm 26.8 59.3 1.87 1.38 14.3
11/14/2019 8:05 pm 20.6 94.2 0.44 0.00 1.4
11/14/2019 9:25 pm 20.7 95.0 0,42. 0.00 1.2
At the end of each essay, the water depths contained in each collector were obtained, using a
graduated cylinder with a maximum capacity of 15 mm, produced by Fabrimar®. Water evaporation was
quantified by a pluviometer with an already known initial water volume. Also, at the end of the essays, the
remaining volume was measured once again, so the variation obtained with this deduction represented the
water evaporation occurred during the essays. This variation was added to all water collectors within the
sprinkler’s radius of throw, following the recommendations of Bernardo et al. (2019).
Distribution uniformity evaluation
Once all data were collected from the field essays, the readings were overlapped, simulating
irrigation systems with sprinklers spaced by 6 m x 6 m, 6 m x 9 m, 9 m x 9 m, 9 m x 12 m, 12 m x 12 m, 12 m
x 15 m, 15 m x 15 m, 15 m x 18 m, 18 m x 18 m, 18 m x 21 m, 21 m x 21 m, 21 m x 24 m, 24 m x 24 m, 24 m
x 27 m, 27 m x 27 m, 27 m x 30 m and 30 m x 30 m, according to Bernardo et al. (2019). To analyze the spatial
distribution of the water depths for each sprinkler arrangement, weighted interpolations (weight = 2) were
carried out by the inverse of the distance (IDW). Afterwards, the water distribution uniformity was calculated
using the following uniformity coefficients: Christiansen uniformity coefficient (CU), distribution uniformity
coefficient (DU), absolute uniformity coefficient (UA), statistical uniformity coefficient (US), Hart uniformity
coefficient (UH) and HSPA standard efficiency (UHSPA), obtained by equations 1, 2, 3, 4, 5 and 6, respectively.
𝐶𝑈 = 100[1 −
∑ |𝑋𝑖−𝑋|
𝑛
𝑖=1
𝑛𝑋
] (1)
𝐷𝑈 = 100
𝑋25%
𝑋
(2)
𝑈𝐴 = 50[
𝑋25%
𝑋
+
𝑋
𝑋12.5%
] (3)
𝑈𝑆 = 100[1 −
𝑆
𝑋
] (4)
𝑈𝐻 = 100{1 − √
2
𝜋
(
𝑆
𝑋
)} (5)
𝑈𝐻𝑆𝑃𝐴 = 100(1 − 1.27
𝑆
𝑋
) (6)
Where CU means Christiansen uniformity coefficient (Christiansen 1942), in %; Xi, the observed
precipitation, in mm; 𝑋, average precipitation, in mm; n, the number of collectors; DU, Distribution
uniformity coefficient (Criddle et al. 1956), in %; X25%, the average of 25% of the lower readings among all
collectors, in mm; UA, Absolute uniformity coefficient, (Karmeli and Keller 1975), in %; X12.5%, the average of
12.5% of the highest readings among all collectors, in mm; US, Statistical uniformity coefficient (Wilcox and
Swailes 1947), in %; S, the standard deviation of the precipitation data, in mm; UH, Hart uniformity coefficient
(Hart 1961), in %; UHSPA, HSPA standard efficiency (Hart 1961), in %.
Once all uniformity coefficients were obtained for each essay, the accumulated uniformity coefficient
was also determined. For such purpose, the six values of the accumulated water depth were summed for
Bioscience Journal | 2022 | vol. 38, e38012 | https://doi.org/10.14393/BJ-v38n0a2022-57028
5
ANDRADE, L.M., et al.
each collector. Afterwards, the uniformity coefficients were determined using these accumulated values,
making use of the same procedures for the non-accumulated water depth, following Equations 1 to 6.
Influence of climatic variables on the distribution uniformity
After determining the best spacing between the sprinklers for the irrigation system, the uniformity
coefficients values for each experiment were plotted as a function of the meteorological variables, using
scatter plots. In sequence, polynomial and linear regression models were fitted, selecting those the highest
values of determination coefficient (r²).
3. Results and Discussion
Figure 3 represents the distribution uniformity in different simulations of spacings between Falcon
6504 (nozzle 14) sprinklers, while operating at an average pressure of 320 kPa. Using the same average water
depths allowed a better visual comparison among the different sprinkler spacings. It is convenient to
mention that the application intensities, for each spacing configuration, were not the same. For example,
the 30 m x 30 m configuration had an application intensity of 3.15 mm h-1, so, with an average gross water
depth of 10 mm, the irrigation system would have to operate for 3 h and 10 min. For the 6 m x 6 m
configuration, however, the application intensity is 78.75 mm h-1. So, for the same average gross water depth
of 10 mm, this irrigation system would operate for 8 min only.
Bioscience Journal | 2022 | vol. 38, e38012 | https://doi.org/10.14393/BJ-v38n0a2022-57028
6
Uniformity of water distribution by a sprinkler irrigation system on a soccer field
Figure 3. Distribution uniformity for the application of an average water depth of 10 mm for multiple
simulations with different arrangements of Falcon 6504 (nozzle 14) sprinklers with an operating pressure
of 320 kPa.
The increase in spacing between the sprinklers led to a greater irregularity in water depth distribution
(Figure 3). It occurred due to the lower overlapping between the water depths, compared to smaller
spacings. Consequently, in theory, with spacings above 24 m x 27 m it would not be possible to irrigate the
central region of the squared area of 9 m2 relative to the four sprinklers. A solution for such obstacle would
be to employ a triangular configuration, so the central region could be well covered by the three sprinklers.
This triangular setting, however, poses a considerable challenge for the project and operation for rectangular
areas.
During the tests, wind speed led to reduction in the water jet length applied by the sprinkler. Figure
4 shows that the wind speed caused a linear reduction in the length of the jet applied by the Falcon 6504
Bioscience Journal | 2022 | vol. 38, e38012 | https://doi.org/10.14393/BJ-v38n0a2022-57028
7
ANDRADE, L.M., et al.
(nozzle 14) sprinkler, operating at an average pressure of 320 kPa. According to the regression equation, a
2.5 m s-1 wind speed led to a water jet length of 14.3 m. Therefore, besides the increase in sprinkler spacing,
wind speed also causes reduction in the overlapping of the applied water depths and, consequently,
reduction in the irrigation distribution uniformity. Reduced wind speed values are vital to ensure an
adequate irrigation efficiency, especially for sprinkler systems, since such variable might result in major
impacts on water application and distribution (Keller and Bliesner 1990; Faria et al. 2016). A strategy to
overcome such problem is the practice of overnight irrigations since it might be a way to reduce the effects
of high wind speed. According to Munhoz and Garcia (2008), night periods have lower thermal gradients,
resulting in reduced wind speed.
Figure 4. Maximum water jet length applied by the Falcon 6504 (nozzle 14) sprinkler, operating at a
pressure of 320 kPa, as a function of wind speed.
Despite the existence of a numerical disparity, the uniformity coefficients indicated similar behaviors
between the different spacing simulations using the Falcon 6504 (nozzle 14) sprinklers, operating at an
average pressure of 320 kPa (Figure 5A). It can also be observed that the Christiansen (CU) and Hart (U H)
coefficients showed nearly equal values. Such occurrence was already expected, since Hart (1961), the
developer of UH, reported that when the applied water depth has normal distributions, CU can be equaled
to UH.
y = 17.0205 - 1.0949x
r² = 0.9418
14.0
14.5
15.0
15.5
16.0
16.5
17.0
0.0 0.5 1.0 1.5 2.0 2.5
S
p
ri
n
k
le
r
re
a
c
h
r
a
d
iu
s
(
m
)
Wind speed (m s-1)
Bioscience Journal | 2022 | vol. 38, e38012 | https://doi.org/10.14393/BJ-v38n0a2022-57028
8
Uniformity of water distribution by a sprinkler irrigation system on a soccer field
Figure 5. Water distribution uniformity coefficients as a function of multiple arrangements of the Falcon
6504 (nozzle 14) sprinkler, operating at a pressure of 320 kPa: A – collected average water depths; B –
collected and overlapped water depths.
CU and UH values were higher than those of the other evaluated coefficients. Generally, the lowest
values were observed for the distribution uniformity coefficient (DU), absolute uniformity coefficient (UA)
and the HSPA standard efficiency (DH), in this sequence. Cunha et al. (2009), working with the same
uniformity coefficients to evaluate a conventional sprinkler irrigation system, verified that CU had higher
values, followed by US, UA, UH, DU and UHSPA. DU is more restrictive and will usually be lower compared to
CU, once DU calculation will only consider 25% of the water collectors with the smallest amount of water.
Keller and Bliesner (1990) also affirmed it and added that DU can be related to CU by the expression: DU =
100 - 1.59 (100 - CU). After obtaining CU with this equation, it was possible to note an underestimation of
only 0.48% when compared to DU, obtained based on the collected water depths.
Mantovani (2001) ranked CU as “excellent” (CU > 90%), “good” (80 < CU < 90), “reasonable” (70 < CU
< 80), “poor” (60 < CU < 70) and “unacceptable” (CU < 60). In accordance with Figure 5A, it can be noted that
the Falcon 6504 (nozzle 14) sprinkler arranged with the 9 m x12 m spacing led to a distribution uniformity
ranked as “excellent”. It can also be noted regarding Figure 5A that the 12 m x12 m and 18 m x21 m spacings
resulted in “good” distribution uniformity, according to Mantovani (2001). On the other hand, the 30 m x 30
m arrangement led to a distribution uniformity ranked as “poor”.
Regarding Figure 5B, the water depths collected from the same pluviometers were overlapped for
each one of the six essays, and their uniformity coefficients were also calculated with these values. It was
found that the coefficients with the accumulated water depths (Figure 5B) showed higher values compared
to the average uniformity coefficients (Figure 5A). These uniformity increments were 5.7, 7.2, 6.6, 6.9, 5.6
and 8.7% for CU, DU, UA, US, UH and UHSPA, respectively.
A
B
50
55
60
65
70
75
80
85
90
95
100
0
8
16
24
32
40
48
56
64
72
80
6
x
6
6
x
9
9
x
9
9
x
1
2
1
2
x
1
2
1
2
x
1
5
1
5
x
1
5
1
5
x
1
8
1
8
x
1
8
1
8
x
2
1
2
1
x
2
1
2
1
x
2
4
2
4
x
2
4
2
4
x
2
7
2
7
x
2
7
2
7
x
3
0
3
0
x
3
0
U
n
if
o
rm
it
y
c
o
e
ff
ic
ie
n
ts
(%
)
Ir
ri
g
a
ti
o
n
in
te
n
s
it
y
(m
m
h
-1
)
Sprinkler spacing (m x m)
Good
Moderate
Poor
Excellent
Unacceptable
50
55
60
65
70
75
80
85
90
95
100
0
8
16
24
32
40
48
56
64
72
80
6
x
6
6
x
9
9
x
9
9
x
1
2
1
2
x
1
2
1
2
x
1
5
1
5
x
1
5
1
5
x
1
8
1
8
x
1
8
1
8
x
2
1
2
1
x
2
1
2
1
x
2
4
2
4
x
2
4
2
4
x
2
7
2
7
x
2
7
2
7
x
3
0
3
0
x
3
0
U
n
if
o
rm
it
y
c
o
e
ff
ic
ie
n
ts
(%
)
Ir
ri
g
a
ti
o
n
in
te
n
s
it
y
(m
m
h
-1
)
Sprinkler spacing (m x m)
IA (mm/h) CUC CUD CUA CUE CUH UDH
Good
Moderate
Poor
Excellent
Unacceptable
Bioscience Journal | 2022 | vol. 38, e38012 | https://doi.org/10.14393/BJ-v38n0a2022-57028
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ANDRADE, L.M., et al.
Araújo et al. (2020) overlapped water depths originated from ten sprinkler irrigation systems and
observed a 7.1% increase in CU values. The water distribution along the irrigated area varies with time, which
promotes a significant difference in uniformity, considering multiple irrigations. Due to the random pattern
related to precipitation variation, caused by meteorological parameters such as wind speed, a specific point
in the irrigated area might receive in different irrigation events an equal, higher or lower water depth
compared to the average water depth. Thus, the same specific point which might have received a deficit
water depth and consequently reached a deficit state regarding the surrounding points, could also receive a
water depth above the average in the following irrigation event, partially or completely supplying the initial
deficit related to the first irrigation. Hence, when the average CU is assumed, it is not taken into
consideration that a given region which received different water depths might, over time, have a CU value
that is higher and more representative of the area.
Considering the water depth overlapping strategy for the distribution uniformity calculation (Figure
5B), it was observed that the systems arranged in a maximum distance of 12 m x15 m were classified as
“excellent”, according to Mantovani (2001). It is well known that the lower the water distribution uniformity,
the lower the irrigation efficiency, and consequently, the higher the gross water depth. For this reason,
aiming at a reduced water and energy consumption, an arrangement between the Falcon 6504 (nozzle 14)
sprinklers of 12 m x15 m is recommended for irrigation of soccer fields and the like. Smaller spacings could
also be recommended considering the technical aspects of the system engineering; however, under an
economic view, these arrangements would require more sprinklers, increasing the project’s final cost.
The irrigation system associated with the Falcon 6504 sprinklers, spaced by 12 m x15 m and operating
with a pressure of 320 kPa, will promote an application intensity of 15.75 mm h-1. So, this specific
arrangement can be considered as ideal and can be recommended exclusively to areas with a basic
infiltration rate (BIR) equal to or higher than the system’s application intensity, according to Bernardo et al.
(2019). In areas with a BIR above 15.75 mm h-1, the spacings between sprinklers will have to be increased,
so the application intensity is lower compared to the area’s BIR, in order to prevent surface runoff and
promote water and energy saving.
Despite the recommending the spacing between sprinklers through the overlapped water depth
methodology, additional studies are required to consolidate and make this procedure practicable. In these
future studies, it is recommended to evaluate the number of experiments required to overlap the water
depths and calculate distribution efficiency using a uniformity coefficient.
It can also be verified in Figure 5B that irrigation systems with spacings between 15 m x15 m and 24
m x 24 m have “good” distribution uniformity, according to Mantovani (2001). It is worth mentioning that
the 15 m x 15 m to 24 m x 24 m arrangements could also be recommended for irrigation systems in
commercial crops. Sheikhesmaeili et al. (2016) suggest that, regarding sprinkler irrigation, a minimum value
for CU of 80% is acceptable to employ these configurations in commercial crops. However, it is known that
the lower the water distribution uniformity, the higher the difference between irrigation depths and the
average water depth. Such lower distribution uniformity results in a decreased irrigation efficiency;
therefore, an increased gross water depth will be required, compared to the net water depth. In fact, the
smaller the irrigation efficiency, the more time it will take for the irrigation systems to apply the same net
water depth. Thus, the inner areas that received smaller water depths will be partially corrected, due to an
increase in water application caused by a longer irrigation time. At the same time, these inner areas that
would already receive higher water depths, due to the increased irrigation time, will receive an even larger
water depth. A direct consequence will be an excessively moist soil, not being able to provide reasonable
conditions for an extended sport activity. Thus, it can also lead the cultivated crops to hypoxia, besides
leaching of nutrients and increased energy and water expenditure.
In agriculture, commercial crops show certain plasticity, and such effects are not easily noticeable in
the results, such as reduction in overall productivity. For soccer field grass irrigation, however, these
problems are more easily found since they result in a more relevant visual outcome. This fact was verified
by Silva et al. (2010) in a work with grass (Paspalum notatum), conducted in Viçosa, Minas Gerais State,
Brazil. The authors performed a sensory analysis regarding this specific grass and verified that applied water
depths equivalent to 100% of crop evapotranspiration led to “good” and “very good” classifications. For the
other conditions, however, the classifications were “poor” and “very poor”.
Bioscience Journal | 2022 | vol. 38, e38012 | https://doi.org/10.14393/BJ-v38n0a2022-57028
10
Uniformity of water distribution by a sprinkler irrigation system on a soccer field
Besides the increase in sprinkler spacing, the meteorological factors also affected the water
distribution uniformity (Figure 6). The increase in relative humidity caused a linear increase in CU (Figure
6B), for the 12 m x15 m arrangement. The remaining factors caused a decreasing linear effect. The best fit,
based on r2, was found for wind speed (Figure 6C), followed by air relative humidity (Figure 6B) and solar
radiation (Figure 6D). Regarding wind speed, its increase reduces the water jet length, also reducing the
water distribution uniformity, as verified by Figure 4. Robles et al. (2017), studying the wind speed effect on
distribution uniformity, found a CU of 89% for low wind speed and 67% for high wind speed conditions.
Figure 6. Values of Christiansen uniformity coefficient (CU) as a function of the average values of: A – air
temperature; B – relative humidity; C – wind speed; D – solar radiation; E – vapor pressure deficit during
the essays with the Falcon 6504 (nozzle 14) sprinkler, spaced by 12 m x 15 m.
Through r2, it is also possible to attest that wind speed is the variable with highest correlation (r) with
the distribution uniformity given by CU. Siqueira et al. (2018) also found similar results when evaluating a
sprinkler system for a soccer field, in Brazil. These authors verified that wind speed was the variable with the
strongest effect on distribution uniformity. According to Rodrigues et al. (2019), both water depth intensity
and wind direction affects the destination of particles. Therefore, the wind has a considerable influence on
the area’s water distribution. So, to promote an increase in water distribution uniformity, it is necessary to
perform the irrigations during nighttime, when wind speed has its lowest values. Overnight, the irrigation
will also have a higher application efficiency due to reduced rates of evaporation and drift of water droplets.
1
A 2
3
B C 4
5
D E 6
7
y = 96.16 - 0.3506x
r² = 0.49
85
86
87
88
89
90
91
20 22 24 26 28 30 32
C
U
(
%
)
Air temperature (ºC)
y = 82.66 + 0.0689x
r² = 0.55
85
86
87
88
89
90
91
35 50 65 80 95
C
U
(
%
)
Relative humidity (%)
y = 90.21 - 2.7618x
r² = 0.75
85
86
87
88
89
90
91
0,4 0,7 1,0 1,3 1,6 1,9
C
U
(
%
)
Wind speed (m s-1)
y = 88.77 - 1.5865x
r² = 0.51
85
86
87
88
89
90
91
0,0 0,3 0,6 0,9 1,2 1,5 1,8 2,1
C
U
(
%
)
Solar radiation (MJ m-2)
y = 88.87 - 0.1265x
r² = 0.39
85
86
87
88
89
90
91
0 5 10 15 20 25 30
C
U
(
%
)
Vapor pressure deficit (hPa)
Bioscience Journal | 2022 | vol. 38, e38012 | https://doi.org/10.14393/BJ-v38n0a2022-57028
11
ANDRADE, L.M., et al.
The reason behind the reduced evaporation overnight is related to the lower vapor pressure deficit and air
temperature. For the reduced drift of water droplets, however, it is a result of lower wind speed values.
4. Conclusions
Wind speed reduced the water jet length applied by the Falcon 6504 sprinkler, and it was the
meteorological factor that showed the strongest influence on water distribution uniformity.
The Christiansen (CU) and Hart (UH) uniformity coefficients showed similar values and were also
higher than the other coefficients. Generally, the lowest values were associated with the distribution (DU),
absolute (UA) and HSPA standard efficiency uniformity coefficients, in this sequence.
The increase in spacing between the Falcon 6504 sprinklers led to reduction in water distribution
uniformity. To meet both economic and technical criteria, the 12 m x 15 m arrangement, operating at a
pressure of 320 kPa, is recommended.
Due to the random pattern regarding the water distribution by the sprinklers, the accumulated CU
showed higher values compared to the average CU, presenting itself as an alternative to determine the
irrigation efficiency. However, additional studies are required to consolidate such procedure.
Authors' Contributions: ANDRADE, L.M.: acquisition of data, analysis and interpretation of data; PACHECO, J.C.C.: acquisition of data, analysis
and interpretation of data; COSTA, G.L.L.: acquisition of data, analysis and interpretation of data; ALENCAR, C.A.B.: acquisition of data, analysis
and interpretation of data; CUNHA, F.F.: conception and design, analysis and interpretation of data, drafting the article. All authors have read
and approved the final version of the manuscript.
Conflicts of Interest: The authors declare no conflicts of interest.
Ethics Approval: Not applicable.
Acknowledgments: The authors would like to thank the funding for the realization of this study provided by the Brazilian agency CAPES
(Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil), Finance Code 001.
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Received: 29 August 2020 | Accepted: 21 October 2021 | Published: 16 February 2022
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