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American Journal of  Life Science and 
Innovation (AJLSI)

Validations of  CROPWAT Based Irrigation Practice for Tomato Productivity in Lowland 
Hot Humid Area of  Ethiopia 

Temesgen F. Adamtie1*, Demeke T. Mitku1 and Abeba Hassen1

Volume 1 Issue 1, Year 2022
ISSN: 2833-1397 (Online)

DOI: https://doi.org/10.54536/ajlsi.v1i1.426
https://journals.e-palli.com/home/index.php/ajlsi

Article Information ABSTRACT

Received: July 20, 2022

Accepted: July 23, 2022

Published: July 24, 2022

The efficient management of  applied water volume and wise water application is accom-
plished by irrigation scheduling. Microclimate is the most important factor affecting the 
irrigation schedule, which determines when and how much irrigation water will be used. 
The objective of  this experiment was to validate the experimental effects of  CROPWAT 
irrigation practice compared to farmer’s practice on crop and water productivity of  tomato. 
The CROPWAT Penman–Monteith method was used to calculate crop water requirement 
and irrigation scheduling of  tomato as compared to farmers irrigation practice. The total 
water applied were 1087.5mm and 1275.5mm for 2020 and 895.3mm and 1242.6mm for 
2021 respectively for CROPWAT and farmers’ practice. The obtained validated result re-
vealed that farmers’ irrigation practices for marketable tomato fruit were 25.8% lower when 
based on CROPWAT irrigation practice, while those for unmarketable tomato fruit were 
46.18% lower. In contrast to farmers’ irrigation practices, the CROPWAT irrigation system 
can reduce loss by 46.1 percent for the production of  tomato fruit. Similarly for tomato 
water productivity, CROPWAT-based irrigation systems received an incremental 37.5 per-
cent advantage over farmers’ practices. As a result, this study came to the conclusion that 
CROPWAT-based irrigation practices are crucial for field crop irrigation scheduling and 
crop water requirements. The study will contribute to bettering tomato fruit productivity and 
water resource management. This study might serve as a guide for making choices regarding 
upcoming planning.

INTRODUCTION
The FAO created the decision-support software 
CROPWAT 8.0 to compute reference evapotranspiration 
(ET0), crop water requirements (CWR), irrigation 
scheduling, and irrigation water requirements (IR) using 
rainfall, soil, crop, and climate data (Ewaid et al., 2019). 
Irrigation scheduling is a water management strategy 
to prevent over-application of  water while minimizing 
yield loss due to water shortage or drought stress area 
(Marković et al., 2014; Jones, 2006; Jha et al., 2016; 
Adametie and Mitku, 2021). The efficiency of  water use 
in agriculture is low with poor management and improper 
designs of  water application systems (Evans and Sadler, 
2008; Sharma and Bhambota, 2022).The irrigation 
schedule which determines the timing and amount of  
irrigation water is governed by many complex factors, 
but microclimate plays the most vital role (Stevens, 2007; 
Nikolaou et al., 2020; Raine et al., 2007). High water loss 
results in lesser yield and reduced irrigated areas that are 
linked to ineffective water use (Ewaid et al., 2019). But 
the improved irrigation practices lead to more uniform 
water distribution, minimize water application, irrigation 
costs, nutrient leaching, and result in the economic 
viability of  irrigated agriculture (Ismail and Ozawa, 
2009; Jones, 2006). However, in Ethiopia traditionally 
anyone understood that irrigating more water for the 
crops means getting more yield (Adametie and Mitku, 
2021). In addition to this, in Ethiopia, poor irrigation 
scheduling practices have been considered as the major 
challenge for the sustainability of  irrigation schemes 

Keywords

Crop water requirement, 
Irrigation Scheduling, 
CROPWAT, Tomato 

because of  the lack of  simple and practical scheduling 
techniques, cost, inaccessibility of  soil water monitoring 
tools, lack of  local climate data and soil–water parameters 
(Yohannes et al., 2019; Eshete et al., 2020). Therefore, it 
is important to develop irrigation scheduling techniques 
under prevailing vital conditions to utilize scarce and 
expensive water efficiently and effectively for crop 
production. To tackle those problem Several studies were 
carried out in the past on the development and evaluation 
of  irrigation scheduling techniques under a wide range of  
irrigation systems and management, soil crop and climate 
conditions. Software modeling with programs such as 
AQUACROP and CROPWAT 8.0 is a significant practice 
used by scientists for crop evapotranspiration, CWR, 
and irrigation scheduling. The Food and Agriculture 
Organization (FAO) created those software programs 
as tools to assist irrigation engineers and agronomists in 
performing the standard calculations for water irrigation 
studies, as well as in the management and design of  
irrigation schemes (Ewaid et al., 2019; Poornima et 
al., 2020). For this study CROPWAT model was used 
to investigate the irrigation water requirements and 
irrigation scheduling tomato  in lowland hot humid area 
of  Ethiopia. Because of  this model a lot of  previous tests 
showed locally applicable and satisfactory performance 
in number of  worldwide locations under varying climate 
circumstances including Ethiopia (Allen et al., 1998a; 
Eshete et al., 2020; Ewaid et al., 2019; Yohannes et al., 
2019; Adametie and Mitku, 2021). 
Tomato (Lycopersicon esculentum) is an important 

1 Department of  Irrigation and Drainage, Pawe Agricultural Research Center, Ethiopian Institute of  Agricultural Research, Ethiopia.
* Corresponding author’s e-mail: temesgenfentahun09@gmail.com

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horticultural crop used by many for stew like in Amharic 
(Wote) and other recipes in Ethiopia. As the population 
continues to increase the demand for tomato in Ethiopia is 
also increasing; however, the yield is far below expectation 
that observed in some other countries and the fruits are 
with poor quality (Yeshiwas et al., 2016). The reason 
showed  farmers still practice traditional irrigation system 
in Pawe district lowland hot humid area of  Ethiopia’s. For 
such condition, well managed and scheduled irrigation 
practice with respective crop stage is very necessary. The 
irrigator needs knowledge of  the efficient use of  water 
resources with crop management practices and irrigation 
scheduling techniques. These traditional practice needs 
improved technology like validation and demonstration 
for applicability of  CROPWAT8. So, the objectives of  
this study were (1) To determine tomato crop water 
requirement and irrigation scheduling for local climate 
condition (2) To validate the experimental effects of  
CROPWAT irrigation scheduling compared to farmer’s 
practice on crop and water productivity in area.

METHODOLOGY 
Study Area description 
This study was conducted on Pawe district it is located 
in the lowland hot humid area of  Northwest Ethiopia 
(Figure 1). It lays between 360 151 and 360 301 and 110 
231 north longitude and latitude respectively. The altitude 
ranges from 1000-1220 m.a.s.l. it is characterized by long 
rain season (from May to October). According to long 
term rainfall and climate data the mean annual rainfall is 
1586 mm and amount are reliable from year to year and 
its average minimum and maximum temperature is 16.5 
c0 and 32.66 c0 respectively. However, variation ranges 
from 8 co in the coolest period especially in July and 
August and around 40 c0 in the hottest period, March 
and April. 
Pawe district also part of  Beles basin included two main 
rivers namely Main and Gilgel Beles. The head water 
of  Beles River starts from the area close to the western 
periphery of  Lake Tana. Along its way it collects many 
major and minor tributaries. Gezhig, Burzhi and Chankur, 
Bula (keteb) and Giligile Beles are the major tributaries. 
All of  the tributary also located on Pawe district each 

Figure 1: Study Area of  experiment

of  them have annually flow water that farmers used 
irrigation for dry season crops like tomato, onion, pepper, 
maize, soyabean and perennial crops. 
According Dieci and Viezzoli (1992) as cited by (Mariyea 
et al.)Pawe district are broadly categorized as vertisols 
soil (black clay soils), and account for 40–45% of  the 
area; Nitisols (red or reddish-brown laterite soils) which 
account for 25–30%; and intermediate soils of  a blackish-
brown color, which account for 25–30%. This experiment 
was conducted on Vertisols (black clay soils) of  Pawe 
district lowland hot humid area of  Ethiopia humid area 
of  Ethiopia 

Experimental setup 
The experiment was laid out a paired t-design to validate 
tomato productivity using CROPWAT 8 model crop 
water requirement and irrigation schedule as compared 
to farmer’s practice. The paired t-test is mathematically 
powerful in comparing two-paired measurements that 
have intrinsic relationships and allows good control of  
individual differences without necessarily having a large 
sample size (Eng, 2003). De Winter (2013) proved the 
applicability of  paired t-test as low as two replicates. 
Several studies including Assefa et al. (2021) Yimam et 
al. (2020),  Belay et al. (2020), and Assefa et al. (2019) 
have used paired-t design for comparation purposes. So, 
in this experiment CROPWAT 8 model is the treatment 
to validated with farmer’s practice for the productivity of  
tomato. 
Furrow irrigation system was used for both CROPWAT 
8  irrigation water management versus farmers irrigation 
practice. In farmer’s irrigation practice, the farmers use  
their own irrigation scheduling system, with irrigation 
water management for tomato. Whereas in irrigation 
scheduling practice, we use the CROPWAT version 
8 model to calculate irrigation water requirement and 
irrigation scheduling. 
Calibrated two-inch throat width Parshall flume was 
used to measured irrigation water for both CROPWAT 
8 irrigation scheduling and farmers’ irrigation scheduling 
practice. The water discharge measured with partial 
flume. For each irrigation, the amounts of  watering date 
and amount of  watering were recorded in both farmer’s 
irrigation practice and CROPWAT 8  irrigation scheduling 
practice.

CROPWAT 8.0 Model Description
CROPWAT for Windows version 8.0 is a decision 
support system developed by the Water Resources 
Development and Management Service of  based on 
a number of  equations, developed by the FAO to 
calculate reference evapotranspiration (ET0), crop water 
requirement (CWR), irrigation scheduling, and irrigation 
water requirement (IR), using rainfall, soil, crop, and 
climate data (Ewaid et al., 2019; Gabr, 2021; Kuo et al., 
2001; Smith, 1992). The model is important at worldwide 
including Ethiopia (Bokke and Shoro, 2020; Adametie 
and Mitku, 2021). 

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Data Requirement
Four types of  data are required for using the CROPWAT 
software, namely, rainfall data, climatic data, soil data, and 
crop data (Smith, 1992).
Climatic data for thirty-two years (1987–2019) were 
gathered from the Ethiopian National Meteorological 
Agency (ENMA) at Pawe meteorology station (Table 3). 
These parameters are monthly maximum and minimum 
temperature (°C), wind speed (km/h), mean relative 
humidity (%), sunshine hours (h), rainfall data (mm), and 
effective rainfall (mm).
The crop data for tomatoes was obtained from the FAO 
Manual 56 details and were added to the CROPWAT 
program, including rooting depth, crop coefficient, 
critical depletion, yield response factor, and length of  
plant growth stages (Allen et al., 1998b). Planting dates 
was decided accordingly effective rainfall of  Pawe area.
The soil parameters obtained from the FAO CROPWAT 
8.0 model include detailed information on the soil 
experimental site was sampled, such as field capacity (FC 
), permanent welting point (PPT)  and total available 
moisture content were done from Pawe agricultural 
research center (PARC) soil innovated laboratory. The 
rest specification initial moisture depletion, maximum 
rain infiltration rate, and maximum rooting depth were 
taken from FAO irrigation and drainage paper 56. 

Estimations of  Reference Evapotranspiration (ETo)
Transpiration (water lost from the plant surface) and 
evaporation (water lost from the soil surface) occur at 
the same time and, when combined, are referred to as 
evapotranspiration (ET). The CROPWAT 8 model was 
used to estimate the reference evapotranspiration (ETo) 
using the Penman-Monteith method (Zotarelli et al., 
2010). The Windows CROPWAT model uses the FAO 
Penman–Monteith equation for the calculation of  the 
ET0 where most of  the parameters are measured from 
the weather data.
The Penman–Monteith equation form is as follows:

Where:
ETo = reference evapotranspiration [mm day-1], Rn = 
net radiation at the crop surface [MJ m-2 day-1], G = 
soil heat flux density [MJ m-2 day-1], T = mean daily air 
temperature [°C], U2 = wind speed at 2 m height [m s-1], 
es = saturation vapour pressure [kPa], ea = actual vapour 
pressure [kPa], es-ea = saturation vapour pressure deficit 
[kPa], ∆ = slope vapour pressure curve [kPa °C-1], γ = 
psychrometric constant [kPa °C-1]

Rainfall Data and estimation of  effective rainfall
Similarly, climate data 32 years for monthly rainfall data 
was collected from the Ethiopian National Meteorological 
Agency (ENMA)  at Pawe meteorology station. Effective 
rainfall (Pe) was determined using the United States 
Department of  Agriculture Soil Conservation Service 
(USDA-SCS) method (Bos et al., 2008) and (Allen et al., 

1998a) as shown in (Equation 2). The effective rainfall 
was used to determine irrigation water requirement for 
tomatoes. 
(Pe=0.8P-25 P>75 mm/month)
(Pe=0.6P-10 P<75 mm/month) (2)
Where Pe and P are effective rainfall and precipitation in 
mm/month, respectively

Crop Water Requirement (CWR)
Crop water requirement refers to the amount of  water 
that needs to be supplied, while crop evapotranspiration 
refers to the amount of  water that is lost through 
evapotranspiration. For the determination of  crop 
water requirement, the effect of  climate on crop 
water requirement,  which  is  the  reference  crop  
evapotranspiration (ETo)  and  the  effect  of   crop 
characteristics (Kc) are important (Doorenbos and pruitt, 
1977). As estimated reference evapotranspiration of  the 
study area, crop data like crop coefficient, growing season 
and development stage, effective root depth, critical 
depletion factor of  tomato and maximum infiltration rate 
and total available water of  the soil was determined to 
calculate crop water requirement using cowpat model. 
(ETc=Kc×ETo )                             (3)
where Kc is the crop coefficient. It is the ratio of  the 
crop ETc to the ET0, and it represents an integration of  
the effects of  four essential qualities that differentiate 
the crop from reference grass, and it covers albedo 
(reflectance) of  the crop–soil surface, crop height, canopy 
resistance, and evaporation from the soil. Due to the ET 
differences during the growth stages, the Kc for the crop 
will vary over the developing period which can be divided 
into four distinct stages: initial, crop development, mid-
season, and late season (Allen et al., 1998b).

Irrigation Water Requirement (IR)
The irrigation requirement (IR) is the main parameter 
for the planning, design, and operation of  irrigation 
and water resources systems. According to Savva and 
Frenken (2002), irrigation water requirement is  the 
optimal allocation of  water resources for policy and 
decision-makers during the operation and management 
of  irrigation systems. Missed management of  irrigation 
requirements may lead to inappropriate capacities storage 
reservoirs, low water uses efficiency, reduction of  the 
irrigated area, and increased development costs. The 
CROPWAT Model can compute the water balance of  the 
root zone as far as root zone depletion by the following 
equation (Ewaid et al., 2019).     
 
IRn = ETc - (Pe + Ge +Ws) + LR (4)
Where, IRn = Net irrigation requirement (mm), ETc = 
Crop evapotranspiration (mm), Pe = Effective dependable 
rainfall (mm), Ge = Groundwater contribution from 
water table (mm), Ws = Water stored in the soil at the 
beginning of  each period (mm) and LR = Leaching 
requirement (mm)

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Irrigation Scheduling
Irrigation scheduling determines the correct measure 
of  water to irrigate and the correct time for watering. 
The CROPWAT model calculates the ETo, CWR, and 
IRs to develop the irrigation schedules under different 
administration conditions and water supply plans 
(Poornima et al., 2020). 

Crop parameter Data
For both treatment, tomato (melkashote) variety was 
cultivated two consecutive years in the 2020 and 2021 
dry season (November to April). For tomato production 
recommended spacing is 30cm between plants and 70 cm 
between row was used (Markos and Mekonen; Salau et al., 
2019). For both treatments blanket recommended Urea 

(46: N) fertilizer at a rate of  100 kg ha-1 were applied. 
Crop characteristics such as plant height and crop yield 
were recorded. Plant height was monitored at harvesting. 
The measuring tape was used to measure plant height. 
The digital balance was used to determine the weight of  
the fruit yield of  tomato. 

RESULT AND DISCUSSION 
Soil physical characteristics 
The soil sample was taken before the planting of  tomato 
takes place and analyzed using laboratory procedure. 
Hydrometer method to determine particle size of  the 
sample (Bouyoucos, 1962). The result as shown the soil 
texture was varied in the study site (Table 1).
Table 1. Soil physical characteristics texture, field capacity 

Table 1: Soil physical characteristics texture, field capacity (FC %), permanent wilting point (PWP %) and soil water 
availability (SWA %) of  experimental site
Depths(cm) Sand (%) Silt (%) Clay (%) Soil class FC ( % ) PWP ( %) AWS (%)
15 22 10 68 Heavy Clay 45.61 27.66 17.95
30 14 18 68 Heavy Clay 36.8 25.11 11.69
60 18 14 68 Heavy Clay 39.04 26.37 12.67
90 24 12 64  Clay 39.9 26.94 12.96
120 22 12 66 Clay 44.18 27.39 16.79

(FC %), permanent wilting point (PWP %) and soil water 
availability (SWA %) of  experimental site 
The obtained soil physical characteristics is similar for 
pervious work of   (Tefera and Mitku, 2017) (Table 2). 
Who was reported that the soil type of  the study area is 

characterized by heavy clay soil with initial available soil 
moisture depletion level 111-129 (mm/meter depth) and 
total available soil moisture level was 222-259 (mm/meter 
depth) varying with soil depth? Hence; the soil is heavy 
clay; a mean infiltration rate was recorded 70 mm/day 

Table 2: Source (Tefera and Mitku, 2017) soil physical characteristics of  bleak Klay soil in Metekele zone  
Soil texture Heavy Clay to clay loam 
Total available soil moisture  222.30-259.15 (mm/meter depth) 
Percentage of  initial soil moisture depletion 50% 
Initial available soil moisture depletion  111.15-129.575(mm/meter depth) 
Maximum infiltration rate 50-90 (mm/day) 
Maximum rooting depth  Up to 1.5m 
Bulk density 1.12-1.31gm/cm3 

and the bulk density was varying from 1.12-1.31gm/cm3 
across the depth of  1.2 meter 3.2. 

Monthly Rainfall, Effective rainfall and 
Evapotranspiration of  Pawe 
From long term mean monthly rainfall data Pawe district 
showed they have rainfall for each month (Table 3). The 
maximum rainfall Contrary minimum evapotranspiration 
(Eto) month June to October (Figure 2). However, the 

rainfall to be effectively used for crop production is only 
May to October the rest (November to April) there is no 
effective rainfall so that the irrigation is required. In this 
area May to October is wet season or rainfall season that 
applies rainfall system agriculture and also November to 
April is dry season known as irrigation time. This was 
used to guide the experiment conducted time depending 
on the effective rainfall and reference evapotranspiration 
to compute irrigation water requirement and irrigation 

Table 3: Monthly rainfall and effective rainfall of  Pawe
Pawe meteorology setation
 Month Rain (mm) Eff  rain (mm) Eto (mm/month)
January 0.7 0 116.4
February 0.6 0 122.96
March 7.8 0 154.51
April 27.8 6.68 161.46
May 93.2 49.56 155.65

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June 289.8 206.84 125.14
July 361.4 264.12 106.23
August 396.3 292.04 106.57
September 261.1 183.88 111.98
October 132.6 81.08 115.69
November 14.4 0 110.71
December 0.7 0 114.54
Note: Eff  rain and mm were effective rain fall and millimeter respectively.

Figure 2: Mean monthly distributions of  rainfall, effective rainfall and evapotranspiration of  Pawe 
scheduling of  dry season

Crop water requirement and irrigation scheduling of  
tomato in the study area of  Pawe
The input of  crop, rainfall and reference evapotranspiration 

(ETo) were used as input data of  CROPWAT to 
simulates  crop water requirement (ETc), and irrigation 
water requirement with respective crop growth stages of  
tomatoes (Table 4). Hence, this simulated tomato crop 
water requirement with respect to growth stage was used 

Table 4: Tomatoes cultivated season growth stage, crop coefficient (KC), crop evapotranspiration (ETc), effective 
rainfall and irrigation requirements 
Month Decade Stage Kc Coeff ETc mm/day ETc mm/dec Eff  rain mm/dec Irr. Req. mm/dec
Nov 2 Init 0.6 2.15 12.9 0 12.9
Nov 3 Init 0.6 2.14 21.4 0 21.4
Dec 1 Init 0.6 2.12 21.2 0 21.2
Dec 2 Deve 0.63 2.21 22.1 0 22.1
Dec 3 Deve 0.77 2.7 29.7 0 29.7
Jan 1 Deve 0.91 3.24 32.4 0 32.4
Jan 2 Deve 1.05 3.75 37.5 0 37.5
Jan 3 Mid 1.15 4.34 47.7 0 47.7
Feb 1 Mid 1.16 4.58 45.8 0 45.8
Feb 2 Mid 1.16 4.81 48.1 0 48.1
Feb 3 Mid 1.16 5.04 40.3 0 40.3
Mar 1 Late 1.16 5.26 52.6 0 52.6
Mar 2 Late 1.08 5.13 51.3 0 51.3
Mar 3 Late 0.96 4.67 51.4 0.1 51.2
Apr 1 Late 0.84 4.23 33.8 0.3 33.5
Total 548.2 0.4 547.7

to validate farmers applied water to each growth stage.  

CROPWAT system Irrigation scheduling of  Tomato 
Accordingly, FAO recommendation in this study 

irrigation scheduling was worked out using CROPWAT 
8.0 windows by selecting  without yield reduction and 
water loss; and the 100% readily available soil moisture 
depletion the simulated was follow (Table 5 and 6) as 

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Table 5: Tomatoes irrigation scheduling, net irrigation requirement, gross irrigation requirement and flow speed  of  
irrigated water in 2020
Day Stage Rain (mm) Net Irr (mm) Gr. Irr (mm) Flow (l/s/ha)
1 Init 0 27.7 46.1 5.34
7 Init 0.1 19.7 32.9 0.63
15 Init 0 26.6 44.3 0.64
25 Init 0 33.8 56.4 0.65
36 Dev 0 40.5 67.5 0.71
48 Dev 0 52.8 88 0.85
61 Dev 0 69.6 115.9 1.03
75 Mid 0 81.7 136.2 1.13
90 Mid 0 83.1 138.6 1.07
105 Mid 0 82 136.7 1.05
125 End 0 88.2 146.9 0.85
End End 0

Table 6: Tomatoes irrigation scheduling, net irrigation requirement, gross irrigation requirement and flow speed  of  
irrigated water in 2021
Day Stage Rain (mm) Net Irr (mm) Gr. Irr (mm) Flow (l/s/ha)
1 Init 0 22.4 37.3 4.32
6 Init 0 15.1 25.2 0.58
13 Init 0 21 34.9 0.58
21 Init 0 23.6 39.3 0.57
31 Dev 0 29.9 49.9 0.58
43 Dev 0 40.3 67.2 0.65
56 Dev 0 51 85 0.76
70 Dev 0.1 64.7 107.8 0.89
85 Mid 0 66.5 110.9 0.86
99 Mid 0 66.8 111.4 0.92
112 Mid 0 65.5 109.2 0.97
126 End 0 70.3 117.2 0.97

compared with farmer’s practice.

Validations of  CROPWAT versus farmer practice 
for gross irrigation water applied and irrigation 
scheduling 
Irrigation scheduling is handling the amount of  water 
applied and sensible application of  water efficiently. 
For this study gross irrigation depth was estimated 
considering field irrigation application efficiency of  60% 
for CROPWAT whereas for farmers practice their own 
traditional practice. As (figure 3) showed gross irrigation 
applied of  each stage of  tomato production CROPWAT 
versus farmer’s practice. Thus, obtained result showed 
that applied water for initial stage CROPWAT irrigation 
system 179.7mm and 137.7mm whereas farmers practice 
462 mm and 447.2mm for 2020 and 2021 respectively. 
Farmers practice at initial stage 61.1%  for 2020 and 
69% for 2021 more water applied than CROPWAT. The 
remaining development, mid and late stage also 7.7%, 
-33.9% and -36.4% for 2020 and 29.2%, -17.0% and -46.5 
for 2020 and 2021 respectively. This result told farmers 
water application system were not careful when to irrigate 
much water and when to irrigate minimum water time. 

For this two-year consecutive experiment farmers were 
applied water deficit at mid and late stage. Studies showed 
mid stage of  tomato is fruit initiation stage thus stage 
is sensitive to water stress (Kuşçu et al., 2014) it might 
be affects quality of  marketable fruit. Even though, 
the total water applied were 1087.5mm and 1275.5mm 
for 2020 and 895.3mm and 1242.6mm for 2021 were 
CROPWAT and farmers practice respectively. It shows 
farmers practice was more water for 14.7 % in 2020 
and 27.9% in 2021 as compared to CROPWAT. This 
finding indicates farmers scheduling and watering system 
is still under way. The main problem for this area was 
not shortage of  water resource but misunderstanding 
of  crop, water and soil relationship. i.e., soil infiltration 
rate when we observed practically at initial stage or 
transplanting time the soil infiltration rate was high 
farmers also supply high flow rate of  water. However, 
the rest stage of  the soil is stable it decreases  infiltration 
rate that crates high speed of  water or runoff  hear the 
farmers understand plenty. Similarly, a lot of  report have 
shown Ethiopian irrigation in field water management 
system is traditional. e.g., as reported by Beyene (2018) 
the farmers applied over irrigation (applied irrigation was 

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50 to 80% higher than CWR at early stage) during early 
growth stages and under irrigation (CWR was 12 to 40% 
higher than applied irrigation at mid stage. Consequently, 
also the overall  farmers’ seasonal irrigation application 
was comparable (seasonal applied irrigation was about 
10% higher than seasonal CWR) with the seasonal CWR 
estimated by CROPWAT model. This validation showed 
that CROPWAT irrigation scheduling system at initially 
minimum water applied and then increased depends 
on root depth, vegetative, soil water holding as well as 
climate conditions. 

Validations of  CROPWAT versus Farmers practice 
for Fruit of  tomato
This article compares the impact of  farmers’ irrigation 
practices and CROPWAT-based irrigation scheduling on 
tomato fruit yield and water use efficiency (Table 6). The 
effects of  tomato fruit on farmers’ irrigation practices 
for the CROPWAT irrigation system were examined 
using a one-tailed paired t-test. The combined analysis 
result for 2020 and 2021 revealed that CROPWAT and 
farmers’ practices were responsible for the marketable 
fruit of  tomato yields of  15.3 tons/ha and 11.35 tons/
ha, respectively. While tomato unmarketable fruit 
showed 5.25 and 9.75 ton/ha for CROPWAT and 
farmers’ practices, respectively. According to the results, 
CROPWAT irrigation was 25.8% more effective than 
farmers’ practices for marketable tomato fruit, while it 
was 46.1 percent less effective for unmarketable fruit. 
This demonstrates that, when compared to farmers’ 
irrigation practices, a CROPWAT-based irrigation system 
can increase marketable tomato fruit yield by 25.8% 
while reducing non-marketable fruit yield by 46.1%. In 
contrast to farmers’ irrigation practices, the CROPWAT 
irrigation system can reduce loss by 46.1 percent for 
the production of  tomato fruit. The variations of  
tomato fruit for CROPWAT and farmers’ practices were 
unplanned, i.e., excess at the beginning and development 
deficit at the middle and end stages. Water stress in the 
middle of  tomato production has an impact on the fruit’s 
quality. Studies have shown that the tomato’s mid-stage 
is the fruit-initiation stage, making this stage sensitive to 

Figure 3: Initial, development, mid, and late-stage gross 
water applied in 2020 and 2021 for CROPWAT and 
farmers practice respectively

water stress(Kuşçu et al., 2014) This could have an impact 
on the tomato’s marketable fruit’s quality. While for 
CROPWAT based system water applied was dependent 
on soil, crop, and climate relationship i.e., when and how 
much to be applied water with respective growth stage 
was applied this is the advantage to increase quality of  
tomato fruit. As a result, this validation output indicated 
that CROPWAT-based irrigation water management is 

Table 6: t-Test: Paired Two Sample for means of  
marketable and unmarketable tomato fruit  
t-Test: Paired Two Sample for means of  tomato fruit  
Marketable fruit (t/ha) Unmarketable  fruit (t/ha)
CROPWAT Farmers CROPWAT Farmer
Mean 15.3 11.35 5.25 9.75
Variance 8 14.045 1.125 0.125
t Stat 6.0 -4.5
P(T<=t) 
one-tail

0.051 0.06

suitable for this region.

Validations of  CROPWAT versus Farmers practice 
for water productivity of  tomato
A one-tailed paired t-test analysis result showed that the 
CROPWAT irrigation system was significantly affected 
for water productivity of  tomato fruit as compared to 
farmers irrigation practice at a 95 percent confidence 
level (Table 7). For CROPWAT and farmer irrigation 
practices, respectively, the obtained combined analysis 
result of  tomato water productivity was 14.42 kg/m3 
and 9.01 kg/m3. This demonstrated that CROPWAT-
based irrigation systems received an incremental 37.5 
percent advantage over farmers’ practices. Similarly, a 
lot of  studies reported that CROPWAT based irrigation 
practice and water resource management system is can 
increases water productivity of  crops and wisely use of  
water for agricultural fields (Ewaid et al., 2019; Poornima 

Table 7: t-Test: Paired Two Sample for means tomato 
fruit water productivity
t-Test: Paired Two Sample for Means of  Tomato water 
productivity

CROPWAT Farmers practice
(Kg/m3) (Kg/m3)

Mean 14.42 9.014733
Variance 18.31 8.860042
t Stat 5.87
P(T<=t) one-tail 0.053

et al., 2020; Roja et al., 2020; Savva and Frenken, 2002).

CONCLUSION AND RECOMMENDATION
This study confirmed the effectiveness of  the FAO 
CROPWAT-based irrigation system for tomato fruit 
production as well as crop water requirements and 

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Am. J. Life Sci. Innov. 1(1) 27-35, 2022

irrigation scheduling when compared to local farmers’ 
irrigation practices. The total water applied were 1087.5mm 
and 1275.5mm for 2020 and 895.3mm and 1242.6mm for 
2021 were CROPWAT and farmers practice respectively. 
It shows farmers practice was more water for 14.7 % in 
2020 and 27.9% in 2021 as compared to CROPWAT. 
For farmers irrigation practice  water applied system for 
crop was not careful when to irrigate much water and 
when to irrigate minimum water time the result shows 
excess water in stage of  initial and development deficit 
at mid and late stage consequently affected marketable 
fruit of  tomato. Even if  farmers’ seasonal irrigation water 
application was 10% greater than their seasonal CWR for 
CROPWT. The obtained validated result revealed that 
farmers’ irrigation practices for marketable tomato fruit 
were 25.8% lower when based on CROPWAT irrigation 
practice, while those for unmarketable tomato fruit were 
46.18% lower. In contrast to farmers’ irrigation practices, 
the CROPWAT irrigation system can reduce loss by 46.1 
percent for the production of  tomato fruit. Similar results 
were obtained for tomato water productivity, which were 
14.42 kg/m3 for CROPWAT and 9.01 kg/m3 for farmers’ 
irrigation practices. This demonstrated that CROPWAT-
based irrigation systems received an incremental 37.5 
percent advantage over farmers’ practices. As a result, 
this study came to the conclusion that CROPWAT-based 
irrigation practices are crucial for field crop irrigation 
scheduling and crop water requirements. The study will 
contribute to bettering tomato fruit productivity and 
water resource management. In areas with limited water 
resources, the CROPWAT tool can assist in determining 
the crop water requirements and irrigation scheduling for 
field crops. This study might serve as a guide for making 
choices regarding upcoming planning.

ACKNOWLEDGEMENTS
Before anything else, we would like to thank the 
omnipotent GOD for giving us the courage to complete 
this work and for preserving our courage. We appreciate 
the Ethiopian Meteorological Service Agency’s (EMSA) 
and Pawe Agricultural Research Center’s (PARC) soil 
laboratory’s contributions of  meteorological and soil 
parameter data, respectively. Last but not least, we 
would like to thank Ms. Aster Beyene and Ms. Mentamer 
Alemew for collecting the data. 

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