Microsoft Word - 32-3777_s_ETASR_V10_N5_pp6335-6343


Engineering, Technology & Applied Science Research Vol. 10, No. 5, 2020, 6335-6343 6335  
  

www.etasr.com Khalifa et al.: Farm-Based Environmental and Economic Impacts of Drip Irrigation System 

 

Farm-Based Environmental and Economic Impacts 
of the Drip Irrigation System 
 

Walid M. A. Khalifa 

Civil Engineering Department 
Hail University, Saudi Arabia and  

Fayoum University, Egypt 
khalifawalid@yahoo.com  

Hatem Gasmi 

Civil Engineering Department 
Hail University, Saudi Arabia and  
Tunis El-Manar University, Tunisia 

gasmi_hatem@yahoo.fr  

Tayyab A. Butt 

Civil Engineering Department 
Hail University  
Hail, Saudi Arabia 

tayyebishfaq@yahoo.com  
 

 

Abstract-Drip irrigation has received considerable attention from 

policy makers, researchers, and economists for its ability to 
contribute significantly improvements to water resource 

development, agricultural productivity, economic growth, and 

environmental sustainability. In this paper, the impact of drip 

irrigation has been studied on a farming system in terms of 

environmental and economic conditions using the developed 

Trickle Irrigation System Design Modeling (TISD). The 

environmental conditions included soil type, land topography, 

climate zones, water sources, their quality, and the farm 

dimensions. The economic conditions comprised of real and 

nominal interest rates, raw land price, and the energy and labor 

escalation rates. The study considered only the Benefit-Cost Ratio 

(BCR) to indicate the impact of environmental and economic 

parameters on the use of the drip irrigation system. The study 

used tomato-sesame as a crop rotation (line-source) and citrus as 
a long-life tree (point-source). Some parameters such as soil type, 

land topography, and water quality had a significant impact on 
the BCR. 

Keywords-trickle irrigation; system configuration; economics; 

environmental changes; citrus; tomato-sesame rotation   

I. INTRODUCTION  

Developing infrastructure for water resources and their 
management is a common policy agenda in many developing 
economies, particularly in arid and semi-arid tropical countries 
like Egypt. A study by the International Water Management 
Institute (IWMI) has shown that around 50% of the increase in 
water demand by the year 2025 can be met by improving the 
efficacy of irrigation [1]. Drip irrigation systems require a 
general understanding of the economic and environmental site 
conditions. Lack of consideration of economic conditions could 
lead to the failure of a system that may environmentally appear 
to be well designed. Some of the environmental conditions that 
must be considered are: crops and cultural practices, farm size 
and shape, topography, soil type, climate, water supply, and 

water quality [2-11]. Economic efficiency is paramount to the 
system selection process. The data required for economic 
analysis fall into two general categories, site-dependent and 
system-dependent [3]. Site-dependent economic parameters 
include: interest rate, labor cost, energy cost, energy inflation 
factor, general inflation factor, property taxes (on equipment), 
water cost, land value, and the return to irrigation for each crop. 
Interest rates are categorized as real or nominal. Nominal rate 
is the current rate of interest charged by the lending institution 
that will provide the credit and includes an inflationary 
component and a risk management and profit component. The 
real rate (inflation-free and ranges from 5 to 7%) is used to 
determine the annualized cost of capital expenditures that tend 
to appreciate, such as land values and permanent improvement 
to the land, like land-leveling. Nominal rate is used to 
determine the annualized cost of capital expenditures that 
depreciate or reach technical obsolescence with little or no 
salvage value. The energy inflation factor is the expected 
inflation rate for energy over the system’s economic life and is 
important for balancing capital and operating costs. Inflation 
factors should be included for other input costs, such as for 
labor and water. System-dependent parameters include: system 
component costs, system component lifetimes, and labor, 
energy and maintenance costs. The economic impacts of Drip 
Method of Irrigation (DMI) had been studied in [12] for 
sugarcane cultivation. The cost of cultivation was reduced in 
operations like weeding, intercultural and irrigation cost (both 
labor and other costs). The benefit-cost ratio varied from 1.98 
to 2.02 (without subsidy condition) and from 2.07 to 2.10 (30% 
subsidy at different discount rates). Further, the net present 
worth indicated that the entire capital cost was recovered from 
the income of the very first year itself even without subsidy. 
The measures of zero sales tax were suggested to bring down 
the cost of drip set. The effect of planting distance on guava 
yield, quality and economic return under DMI was conducted 
experimentally in [13]. The guava had been planted at 6m×6m 

Corresponding author: Walid M. A. Khalifa 



Engineering, Technology & Applied Science Research Vol. 10, No. 5, 2020, 6335-6343 6336  
  

www.etasr.com Khalifa et al.: Farm-Based Environmental and Economic Impacts of Drip Irrigation System 

 

(I) and 5m×5m (II). The results produced 8.31t/ha and 15.0t/ha 
(I) and 12.0t/ha and 21.60t/ha (II) after the 3rd and 4th year of 
plantin, respectively. The highest Benefit-Cost Ratio (BCR or 
B/C) (2.20) was at (II). The effect of salt-affected land 
production under DMI was reclaimed using a 1-3yr. field 
experiment in [14] to investigate changes in soil’s physical, 
chemical, and biological properties with cropping maize. The 
results indicated that the soil physical environment and 
nutrients status were both improved. Author in [15] used a 
Subsurface Drip Irrigation (SDI) system to examine the 
convenient streams of irrigation water in uncovered domains 
and greenhouses. Authors in [15] examined and analyzed 
pipeline materials, emitters spacing, and soil texture. The study 
investigated the impacts of soil sort and climate on 
consumption of water. Soil moisture was measured by two 
Enviroscan sensors. In addition, the climate parameters were 
measured by two weather stations. Software, based on 
Penman–Monteith approach, was used to estimate the crop 
evapotranspiration and the amount of irrigation water 
according to the FAO guidelines as a reference. The outcomes 
manifested a significant increase in crop productivity by 18% 
when the proposed SDI system was used over the normal DMI. 
Authors in [16] studied the effect of DMI of cultivation in 
terms of cropping pattern, resource use and yield. The DMI has 
been found to get an important effect on saving resources, 
cultivation cost, crops yield and farm profitability. Authors in 
[17] studied the adaptability of the DMI with the aid of solar 
power. Although the recurring cost for energy was waived due 
to the use of freely available solar energy, the initial investment 
for the solar powered drip system is high. Further, the BCR 
was 2.64 for using solar operated drip rather than the diesel 
operated system which had BCR equal to 1.30. The study in 
[18] aimed to assess the techno-economic feasibility of solar 
and wind based pumping irrigation systems. In the first stage of 
the study, the irrigation water requirements were determined by 
using the CROPWAT software to assess two different crop 
patterns that represent existing feasible alternatives for small 
farmers. For 1ha, the pumping systems powered by solar, wind 
and diesel energy were sized based on the crop water 
requirements. The costs of irrigation due to the three 
technologies, the two crop patterns and the three methods of 
irrigation (surface, sprinkler and drip) were estimated and 
compared. The economic analysis was complemented by a 
cost-benefit analysis spanning over 20 years. The economic 
analysis showed that windmills are the most cost effective 
solution, with solar pumping systems in second place. Diesel 
pumping systems are the least cost effective. To study the 
climate effect on the tomato yield under DMI, authors in [19] 
investigated three different combination levels (100, 75 and 
50% of crop water requirement) and two mulches (black 
polyethylene sheet and paddy straw). The highest yield for each 
mulch was obtained when the 50% of water requirement was 
applied. The yield results were 81.12t/ha for polyethylene and 
79.49t/ha for straw. With 100% water application, the straw-
mulched treatment produced higher yield than polyethylene-
mulched treatment. The highest water use efficiency of 
592kg/ha/mm was acquired with 50% water application under 
polyethylene mulch. The highest net return (US$ 7098/ha), 
incremental net return (US$ 1556/ha), and incremental benefit-
cost ratio (7.03) were found for 50% water application with 

straw mulch. Authors in [20] studied the economic and 
resource impacts of drip irrigation including its benefit–cost 
pattern using survey data in okra cultivation. The study results 
revealed that the drip irrigation usage can reduce about 15% of 
cultivation cost, save about 47% of water resources and 
electrical energy, and increase okra productivity by 49% for the 
same cultivated area under traditional methods of irrigation. 
Farmers cultivating okra under the usage of drip irrigation 
acquired an extra farm trade income of RS 72,711 per acre over 
the non-drip adopters. Author in [21] conducted economic 
analysis on seven crops and nine vegetables using the Trickle 
Irrigation System Design (TISD) developed in a hypothetical 
field in Egypt based on local environmental and economic 
conditions [22]. Economic B/C analysis and net returns 
amounts were calculated. The results of the study showed that 
high values of net return were attained for most crop rotations. 
Further, most B/C for crop rotations ranged from 1.5 to up to 
more than 2.0. Authors in [23] used the TISD [22] linked with 
the measures of the economic analysis in [21] to study the 
effects of system configuration and lateral directions for long-
life fruit trees on the selected economic bases. The study was 
conducted on eleven long-life fruit trees based on 
environmental, crop, and economic conditions. The results 
revealed that the drip irrigation system with configurations and 
lateral directions has a very small effect on BCR, annual net 
return, total annual costs, and net cultivated area. The used 
system has significance on initial capital cost and annual 
energy cost. Moreover, the drip irrigation system 
configurations and lateral directions have a considerable effect 
on annual maintenance cost. The objective of this study was to 
assess the impact of environmental and economic parameters in 
drip irrigation systems in farms using the TISD. The 
considered environmental conditions were: soil type, land 
topography, climate conditions, and water source conditions. 
The economic conditions were: real and nominal interest rates, 
raw land price, and energy and labor escalation rates. 

II. MATERIALS AND METHODS  

This study used the TISD [22] to design the trickle 
irrigation system with the economic analysis detailed in [21] to 
estimate the impacts of farm conditions under drip irrigation 
system on the BCR. Figure 1 shows the flowchart of the TISD. 
The conditions considered are the environmental and economic 
data and suitable crop rotations. The environmental site data 
are soil type [24-29], land shape and topography [30-31], water 
source position and type, irrigation water quantity and quality 
[32-34], and climate zone [35-37]. The economic data include: 
land price [38], real and nominal interest rates [12, 39], energy 
source type and fuel cost [40-43], energy inflation factor, labor 
availability and cost, labor inflation factor, and system 
components’ availability and costs. Crop rotations are either 
long-life trees or combination of winter and summer field crops 
or vegetables. The crop rotations should be compatible against 
soil type, irrigation methods, climate zone, water quality, and 
agricultural recommendations. After designing the concerned 
system, TDIS calculates the different system costs and returns 
to determine the different selection bases. The system costs 
include: installation, operation, maintenance, land, water (if 
any), and crop production (land preparation, seeding and 
planting, fertilization, weeding, pest control, harvesting, and 



Engineering, Technology & Applied Science Research Vol. 10, No. 5, 2020, 6335-6343 6337  
  

www.etasr.com Khalifa et al.: Farm-Based Environmental and Economic Impacts of Drip Irrigation System 

 

transportation). To analyze this methodology, a farm with 
certain environmental and economic parameters was proposed 
as the base farm (base run). This base run will be used in 
comparison with the following runs. In this study, one crop 
rotation (tomato-sesame) and one long-life tree (citrus) 
cultivation were selected. The TISD model runs by using the 
environmental and economic data of the base run for tomato-
sesame and citrus with the drip irrigation system configurations 
and lateral directions. This step was repeated for different 
parameter values, by changing one parameter while keeping the 
others to the value of the base run. Then, the effect of each 
environmental and economic parameter on the BCR as the only 
selection basis could be discussed. 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Fig. 1.  Flowchart of the TISD program. 

A. Proposed Data for Base Farm (Run) 

Figure 2 shows the proposed farm’s shape and topography. 
The proposed data to complete the analysis procedures for the 
base run include environmental and economic conditions 
(Table I). Further, crop rotations are considering the 
environmental site data (Table I) and the agricultural statistics 
in Egypt [44] based on the required information of the 
concerned crop rotations (tomato-sesame) and long-life fruit 
trees (citrus) in 2018 (Table II). The TISD model proposes the 
suitable crop rotations and their average production costs, 
expected average crop productions, and average crop prices as 
in [21] and [23]. 

 

 

Fig. 2.  Farm dimension, slopes, and North direction of the base run. 

TABLE I.  CASE STUDY’S SITE DATA 

Environmental Conditions 

Soil type: 
Coarse texture (coarse or fine or loamy sands), Code 

number=2 

Climatic conditions: 
Hot climate (Middle Egypt), CLZ (Code No.) = 3 

Wind speed (WS)=3.0mph 

Farm shape: Figure 2 

Farm topography: Figure 2 

Crop conditions: 

[24, 45-48] 

Plant spacing, plant root depth, shaded area (%), 
average rate of water use, seasonal water 
requirements, leaching requirement ratio 

Obstructions: No 

Water source: 

Surface water 
Suction head, Hs =6.0m 

Water quantity = no restriction 
Frequency = continuous 

Water quality, Electrical Conductivity, EcW= 

640.0ppm=1.0dS/m 
Water price=0.0US$/m

3
 

Economic Conditions 

Raw land value: RAW=1000 US$/ha 

Real interest rate: RIR=6.0% 

Nominal interest rate: NIR=10.0% 

Electric energy: 

[49] 

Energy cost=0.10 US$/kWh (2018 prices) 
Energy escalation rate=27.0% (2018) 

Labor: 

[50] 

Available and reliable 
Labor cost=4.5 US$/man-hr (2018 prices) 
Labor escalation rate=5.0%. (2018 prices) 

Construction elements: 

Available for drip irrigation system 
Available maintenance supports 

PVC specification = DIN (Germany) 

PVC price=15US$/kg of PVC (2018) 
Aluminum and steel pipe [3], outlets’ prices [51] 

 

B. Proposed Changes in Base Run’s Data 

The proposed changes of the base run environmental and 
economic data are listed in Tables III and IV. To study the 

READ the environmental crop conditions, and 
CALCULATE the preliminary irrigation design factors 

according to the crops chosen 

READ the farm dimensions, land slopes and static head, 

desired rate of interest, equivalent annual rate of energy 
escalation, pump efficiency, pipe specification type 

DESIGN the main pipe network for (line-source and point 
source) according to the pipe material, the required pressure 
head, and the critical uphill/downhill reaches due to the 
pressure head difference generated by the pump 

DESIGN the critical uphill/downhill reaches, inlet reaches 

of uphill and downhill rows of configurations [1] & [2], the 
composed reaches according to the velocity and adjacent 
sizes  

Draw the neat sketch for the system showing the area 
dimensions and slopes, total number of subunits, 
dimensions of different subunits, and pump station position 

CHOOSE the lateral shape (single or double) using the 
required system configuration, CALCULATE the subunits 
number, emitter conditions, lateral length and diameter, 
lateral discharge, lateral pressure head variation, inlet-exit 

lateral pressure head, best lateral inlet position on the 
manifold, manifold length and diameter, manifold 
discharge, manifold pressure head variation, inlet-exit 

manifold pressure head, best manifold inlet position on the 
mainline, uniformity and application rate 

END 

START 

ESTIMATE THE COSTS according to the configurations 



Engineering, Technology & Applied Science Research Vol. 10, No. 5, 2020, 6335-6343 6338  
  

www.etasr.com Khalifa et al.: Farm-Based Environmental and Economic Impacts of Drip Irrigation System 

 

effect of farm area and dimensions on system costs and returns, 
the base farm was divided into two, four, six, and eight equal 
parts. This partition was made by dividing the farm length 
and/or width and introduces dimension ratios (L/B) of (1.179, 
1.272, 1.696, 1.769, 2.358, 3.39, 4.716, 5.089, 6.785, 7.075, 
and 9.433). Other farm dimension ratios with constant farm 
area were also studied. The considered farm dimension ratios 
with the same farm area are: 1.0, 1.5, 2.0, 2.5, and 3.0. Figure 3 
shows the methodology flowchart. 

TABLE II.  ECONOMIC INFORMATION FOR THE CASE STUDY [44, 2018] 

Crop 

Rotations 

Fruit production 

price (US$/ha) 

Average fruit 

production ton/ha) 

Average fruit 

price US$/ton)
* 

Tomato 4064.11 40.9689 99.2 

Sesame 1183.84 1.2941 914.8 

Citrus 3726.2 24.11 154.55 
*[44, 2017] 

 

 
Fig. 3.  Flowchart of the methodology analysis. 

TABLE III.  PROPOSED CHANGES ON BASE RUN ENVIRONMENTAL 
PARAMETERS 

Crop 

rotation 

Environmental conditions 

Soil texture Land topography 
Climate 

conditions 

Water 

source 

(1)
 

DZ% DZ1% (2)
 
WS mph. EcW Hs 

Tomato-

sesame 
4,5 2,4,8,16 1.5,3,6,12 5 3,6,12 2,8 30 

Citrus 4,6 2,4,8,16 1.5,3,6,12 2,5 3,6,12 2,4 30 

 (1) Text code: Code 4: very fine sandy loams, loams, and silt loams, Code 5: clay loams, silty 
clay loams, and sandy clay loams, Code 6: sandy clays, silty clays, and clays,(2) CLZ Code: 

Code 2: Moderate climate, Code 5: High desert climate 

TABLE IV.  PROPOSED CHANGES ON BASE RUN ENVIRONMENTAL 
PARAMETERS 

Crop 

Rotations 

Economic conditions 

Land value 
Real and nominal 

interest rates 
Energy escalation 

RAW US$/ha
 Real

% 
Nominal

% 
ESCR 
% 

LASCR
% 

Tomato-

sesame 
2000, 4000, 8000 4,8,10 8,12,14 3,5,9 2,6,8 

Citrus 2000, 4000, 8000 4,8,10 8,12,14 3,5,9 2,6,8 

 

III. RESULTS AND DISCUSSION 

The TISD model was run for the preselected crop rotation 
(tomato-sesame) and long-life trees (citrus) under the drip 
irrigation system and configuration by using the environmental 
and economic data of the base run according to Tables III and 
IV. For tomato-sesame rotation, the laterals must be 
perpendicular to the North direction. For citrus trees, the 
laterals may be arranged parallel or perpendicular to the North. 
As in [22], if the laterals are parallel to the North direction, the 
configuration is either #1 (with pump at the farm center [DP1], 
with pump on the big side [DP11], with pump on the small side 
[DP12]) or #2 [DP2]. If the laterals are perpendicular on the 
North direction, the configuration is either #1 (with pump at the 
farm center [DN1], with pump on the big side [DN11], with 
pump on the small side [DN12]) or #2 [DN2]. 

A. Effect of Different Environmental Conditions on the BCR 

1) Soil Type 

The effects of different soil types on the BCR of tomato-
sesame crop rotation and citrus trees are shown in Figure 4. 
The Figure shows the BCR (stated as B/C) of the base run 
(coarse texture, Text = 2) with different configurations. Figure 
4 shows the changes of the base run BCR due to changes to the 
soil texture from coarse to medium and moderately fine (Text = 
4 and 5, tomato-sesame) and from coarse to medium and fine 
texture (text = 4 and 6, citrus). 

 

 
Fig. 4.  Effect of soil texture and climate condition on the BCR. 

It could be noted that the effect of soil type on the BCR of 
line-source is considerable (about 15.0%) and for point-source 
is negligible (within 2.0%). The best B/C is obtained with 
medium soil. For point-source and line-source drip systems, the 
soil type has a negligible effect on the selection of system 
configuration and laterals’ direction (less than 0.5%). For line-
source drip system, the improvement in the BCR due to the 
change to the soil texture from coarse to medium is 
considerable and due to this change the soil texture from coarse 



Engineering, Technology & Applied Science Research Vol. 10, No. 5, 2020, 6335-6343 6339  
  

www.etasr.com Khalifa et al.: Farm-Based Environmental and Economic Impacts of Drip Irrigation System 

 

to medium to moderately fine is negligible. For the point-
source drip system, the improvement in the BCR due to change 
of the soil texture from coarse to medium or fine is negligible. 
So, it is preferable to use the point source drip system on the 
coarser soil textures. 

2) Uniform Land Topography 

The effects of different uniform land slopes on the BCR of 
tomato-sesame crop rotation and long-life citrus plantation are 
shown in Figure 5. This figure shows the B/C of the base run 
(DZ=DZ1=0.0%) under the drip irrigation system 
configurations. The Figure shows the resulting changes in the 
BCR of the base run due to changes in the farm slopes. From 

Figure 5, it could be noted that the effect of land slope on the 
BCR depends on the slope value and direction, and the pump 
position. The negative effect of the land slope on the BCR 
could be avoided by putting the pump unit on the upper farm 
side (if possible). Also, for the point-source drip system, it is 
better to arrange the lateral lines on the small slope direction. 
Land slopes have a considerable effect on the configuration 
selection, especially for high slopes. Configuration #1 with the 
pump on the upper farm side may improve B/C. Configuration 
#2 improves the B/C due to increase in the land slope up to 
2.0%. Therefore, Configuration #1 with the pump station at the 
farm’s center is not always the optimum configuration for 
inclined lands. 

 

 
Fig. 5.  Effect of land topography on the BCR.

3) Climate and Wind Conditions 

The effects of different Climate Zones (CLZ) and Wind 
Speeds (WS) on the BCR of tomato-sesame crop rotation and 
long-life citrus trees are shown in Figure 4. It should be noted 
that there is no effect of WS on the BCR of drip irrigation 
systems. In addition, the effect of climate on the B/C is 
negligible for line-source, and small (3.0%) for point-source. 
Climate has a negligible effect on the configuration’s selection. 
Therefore, it is preferable to use drip systems in hot climate and 
high wind speeds. 

4) Water Source Quality Conditions 

The effects of water source quality and type on the BCR of 
tomato-sesame crop rotation and citrus trees long-life 
plantation are shown in Figure 6. 

 

 

Fig. 6.  Effect of water source quality on BCR. 

It can be noted that the effect of water quality on the BCR 
of line-source and point-source drip systems depends on the 
salt concentration in the irrigation water. This effect is 
negligible if the salt concentration approaches the lower limit 
of the crop salt tolerance range, ECemin, (2.5dS/m for tomato 
and 1.7dS/m for citrus, [52-55]). When the salt concentration 

increases to approach the upper limit of the crop salt tolerance 
range, ECemax, (12.5dS/m for tomato and 8.0dS/m for citrus, 
[52- 55]), the system costs increase and the crop yield 
decreases [56-59]. The reduction in the BCR may be more than 
45% with EcW = 8.0dS/m for tomato-sesame and more than 
30% with EcW = 4.0dS/m for citrus trees. The BCR reduces 
about 5% to 35% due to increase in the suction head from 6.0 
(base run) to 30.0m. Water source quality and type have a 
negligible effect on the selection of system configurations or 
laterals’ direction. 

5) Farm’s Size and Shape 

The effects of different farm areas and dimensions on the 
B/C of long-life citrus trees are shown in Figure 7. It can be 
noted that the effects of farm area and dimension ratio on the 
BCR of point-source drip system are small. The resulting 
changes in the BCR due to the farm partition are not bigger 
than 4.0%. The best improvement in the BCR was obtained 
with L/B ratio within 1.18-1.27 (L/2×B/2 and L/3×B/2) and 
farm area within 8.82-13.23ha. Further, farm partition has a 
small effect on the selection of system configurations and 
laterals’ direction. For the same farm dimension ratio, L/B, 
(L×B/2 and L/2×B/4) and different farm areas (26.46 and 
6.615ha, respectively), B/C improves by less than 1.0%. 
Therefore, the farm area has a negligible effect on the BCR of 
the point-source drip system. Further, the base run farm area 
remained constant (52.92ha) and the L/B ratio changed. The 
used dimension ratios, L/B, are 1, 1.5, 2.0, 2.5, and 3.0. The 
effects of L/B ratio on the base run B/C of tomato-sesame and 
citrus are shown in Figure 8. It can be noted that the effect of 
farm dimension on the BCR is negligible. The BCR changes by 
less than 2.0%. The best L/B ratio is less or equal to 1.5. Also, 
the farm dimension ratio has a negligible effect on the selection 
of system configuration and laterals’ direction. 



Engineering, Technology & Applied Science Research Vol. 10, No. 5, 2020, 6335-6343 6340  
  

www.etasr.com Khalifa et al.: Farm-Based Environmental and Economic Impacts of Drip Irrigation System 

 

 

Fig. 7.  Effect of farm partitioning on the BCR of long-life citrus trees.

 
Fig. 8.  Effect of farm dimensions on the BCR. 

B. Effect of Different Economic Conditions on the BCR 

1) Real and Nominal Interest Rates 

Interest rates are often categorized as real or nominal. 
Nominal rates are the current rates of interest charged by the 
lending institution that will provide credit [60-61]. The rate 
includes an inflationary component and a risk, management, 
and profit component. The real rate is inflation-free, therefore, 
it is less than the nominal by the long-term inflation rate. The 
real rate is used to determine the annualized cost of capital 
expenditures such as land value and permanent land 
improvements (land-leveling). Nominal rate is used to 
determine the annualized cost of capital expenditures that 
depreciate or reach technical obsolescence with little or no 
salvage value. The effects of real and nominal rates on the B/C 
of tomato-sesame and citrus are shown in Figure 9.  

 

 
Fig. 9.  Effect of real and nominal interest rates on the BCR.

It can be seen that the effects of real and nominal interest 
rates on the BCR of the drip irrigation system depend on their 
values. The effects of real and nominal interest rates on the 
selection of system configuration and laterals’ direction are 
negligible for the drip systems. The BCR increases as the real 
and nominal interest rates decrease. The nominal interest rate 
has a higher effect on the BCR than the real rate due to the high 
values of construction elements compared with the land price. 

2) Raw Land Price 

The effects of raw land price on the BCR of tomato-sesame 
crop rotation and long-life citrus trees plantation are shown in 
Figure 10. It can be noted that the effect of raw land value on 
the B/C depends on the land price. The BCR increases as the 
raw land price decreases. There is no effect for raw land price 
on the selection of system configuration or lateral lines’ 
direction. The effect of raw land price on the BCR of line-
source and point-source systems is approximately the same 
(about 2.6% for every 1000US$/ha increase). 

3) Energy and Labor Escalation Rates 

The effects of energy and labor inflation factors on the 
BCR of tomato-sesame crop rotation and long-life citrus trees 

are shown in Figure 11. It can be seen that the effect of energy 
and labor inflation rates on the BCR depends on their values. 
The BCR increases as the inflation rates decrease. There is no 
effect for the energy and labor inflation rates on the drip system 
configuration or laterals’ direction. There is no effect for labor 
inflation rate on the BCR of drip systems. The effect of energy 
inflation rate on the BCR of the line-source and point-source 
drip systems is small and approximately the same (1.0% for 
every 1.0% inflation rate). 

 

 
Fig. 10.  Effect of raw land value on BCR. 



Engineering, Technology & Applied Science Research Vol. 10, No. 5, 2020, 6335-6343 6341  
  

www.etasr.com Khalifa et al.: Farm-Based Environmental and Economic Impacts of Drip Irrigation System 

 

 

Fig. 11.  Effect of energy and labor escalation rates on BCR.

The conducted analyses through the present study for 
different environmental and economic parameters (Tables III 
and IV) are summarized in Table V. Environmental and 
economic analyses were conducted based on the BCR for 
tomato-sesame crop rotation and long-life citrus trees 
cultivation. 

IV. CONCLUSION 

The outcome of this study is based on the environmental 
and economic parameters of cultivating farms using the TISD 
software to fulfill the needs of the irrigation agencies and 
engineers. The TISD model was used to select the drip 
system’s configuration type that could potentially meet the 
desired economic goal of BCR. The effect of the soil type on 
the BCR and the configuration selection and laterals’ direction 
are considerable for line-source and negligible for point-source. 
The soil type has a negligible effect on the selection of system 
configuration for all drip systems. The effect of land slopes on 
the BCR depends on the slope direction with laterals and pump 
position. For the same slopes, it is preferable to arrange the 
point-source’s laterals on the small slope and put the pump on 
the upper farm side. Also, the land slope has a considerable 
effect on the configuration’s selection of drip systems, 
especially with high slopes. The effect of high wind speeds on 
the B/C is negligible for the drip systems. The effect of climate 
on the BCR and the selection of configuration and lateral’s 
direction is negligible for line-source and small for point-
source. The effect of irrigation water on the BCR and 
configuration’ selection of drip systems is negligible up to the 
lower limit of the crop salt tolerance. The effect of water source 
type on the BCR and selection of configuration and laterals’ 
direction is small for drip systems. So, it is preferable to use 
drip systems with groundwater sources. The effect of farm 
partition on the BCR and configuration selection of the drip 
systems is very small. The effects of real and nominal interest 
rates on the BCR and configuration’ selection depend on their 
values. The nominal rate has a higher effect than the real rate 
on the B/C due to the higher installation cost. Also, the nominal 
rate has a higher effect on the BCR of drip systems due to their 
initial installation cost. The effect of raw land value on the 
BCR depends on the land price. The effect of land value on the 
B/C of drip is negligible on the selection of system 
configuration or laterals’ direction. The effect of energy and 
labor inflation rates on the BCR depends on their values. There 
is no effect for the energy and labor inflation rates on the 
selection of system configuration or laterals’ direction. There is 
no effect for the labor inflation rate on the BCR of drip 
systems. The effect of energy inflation rate on the BCR of the 

line-source and point-source drip systems is small and 
approximately the same (about 1.0% for every 1.0% inflation 
rate). 

TABLE V.  EFFECT OF DIFFERENT ENVIRONMENTAL AND ECONOMIC 
CONDITIONS ON BCR 

No. Parameters 
Drip sys. 

type 

Drip sys. 

effect 

Configuration 

effect 

Lateral direction 

effect 

1 Soil texture 
L-source High No - 

P-source Very small Negligible - 

2 
Land 

topography 

L-source Small Small - 

P-source High High High 

3 Climate zone 
L-source Negligible Negligible - 

P-source Small Negligible Small 

4 Wind speed 
L-source No No - 

P-source No No - 

5 Water quality 
L-source Very small No - 

P-source Very small Negligible Negligible 

6 
Water source 

type 

L-source Small No No 

P-source Small Negligible Negligible 

7 Farm Area 
L-source Very small Negligible  

P-source Small Very small Small 

8 
Farm 

dimension 

L-source Negligible Negligible - 

P-source Very small Negligible Negligible 

9 Interest rates 
L-source Small No - 

P-source Considerable Negligible Negligible 

10 
Raw land 
cost 

L-source Small No - 

P-source Considerable Negligible Negligible 

11 
Energy 
escalation 

L-source Small Negligible - 

P-source Small Negligible Negligible 

12 
Labor 

escalation 

L-source Very small Negligible - 

P-source Negligible Negligible Negligible 
Negligible 0.0 < Effect < 1.0 % Considerable 5.0 < Effect < 10.0 % 

Very small 1.0 < Effect < 2.0 % High 10.0 < Effect < 20.0 % 
Small 2.0 < Effect < 5.0 % Very high Effect > 20.0 % 

ACKNOWLEDGMENT 

The authors are thankful to the Deanship of Scientific 
Research at the University of Hail, Saudi Arabia for the 
financial support under the contract (RG-191313). 

REFEFRENCES 

[1] D. Seckler, U. Amarasinghe, D. Molden, R. de Silva, and R. Barker, 
World water demand and supply, 1990 to 2025: Scenarios and issues. 
Colombo, Sri Lanka: International Water Management Institute, 1998. 

[2] M. E. Jensen, R. D. Burman, and R. G. Allen, Evapotranspiration and 
Irrigation Water Requirements. New York, NY, USA: American Society 
of Civil Engineers, 1990. 

[3] J. Keller and R. D. Bliesner, Sprinkle and trickle irrigation. New York, 
NY, USA: Springer, 1990. 

[4] C. M. Burt, A. J. Clemmens, R. Bliesner, J. L. Merriam, and L. Hardy, 
Selection of Irrigation Methods for Agriculture. New York, NY, USA: 
American Society of Civil Engineers, 2000. 



Engineering, Technology & Applied Science Research Vol. 10, No. 5, 2020, 6335-6343 6342  
  

www.etasr.com Khalifa et al.: Farm-Based Environmental and Economic Impacts of Drip Irrigation System 

 

[5] M. Stubbs, “Irrigation in U.S. Agriculture: On-Farm Technologies and 
Best Management Practices,” Congressional Research Service, 7–5700, 
Oct. 2016. 

[6] J. Seyedmohammadi, L. Esmaeelnejad, and H. Ramezanpour, “Land 
suitability assessment for optimum management of water consumption 
in precise agriculture,” Modeling Earth Systems and Environment, vol. 
2, no. 3, Sep. 2016, doi: 10.1007/s40808-016-0212-9, Art. No. 162. 

[7] W. R. Adams and K. T. Zeleke, “Diurnal effects on the efficiency of drip 
irrigation,” Irrigation Science, vol. 2, no. 35, pp. 141–157, Nov. 2016, 
doi: 10.1007/s00271-016-0529-1. 

[8] X. Chen, K. R. Thorp, Z. Ouyang, Y. Hou, B. Zhou, and Y. Li, “Energy 
consumption due to groundwater pumping for irrigation in the North 
China Plain,” Science of The Total Environment, vol. 669, pp. 1033–
1042, Jun. 2019, doi: 10.1016/j.scitotenv.2019.03.179. 

[9] C. Wei et al., “Effects of Irrigation Water Salinity on Soil Properties, 
N2O Emission and Yield of Spring Maize under Mulched Drip 
Irrigation,” Water, vol. 11, no. 8, Aug. 2019, doi: 10.3390/w11081548, 
Art. No. 1548. 

[10] I. Fernandez Garcia et al., “Trends and Challenges in Irrigation 
Scheduling in the Semi-Arid Area of Spain,” Water, vol. 12, no. 3, Mar. 
2020, doi: 10.3390/w12030785, Art. No. 785. 

[11] A. Y. Yimam, T. T. Assefa, N. F. Adane, S. A. Tilahun, M. K. Jha, and 
M. R. Reyes, “Experimental Evaluation for the Impacts of Conservation 
Agriculture with Drip Irrigation on Crop Coefficient and Soil Properties 
in the Sub-Humid Ethiopian Highlands,” Water, vol. 12, no. 4, Apr. 
2020, doi: 10.3390/w12040947, Art. No. 947. 

[12] A. Narayanamoorthy, “Economics of Drip Irrigation in Sugarcane 
Cultivation: Case Study of a Farmer from Tamil Nadu,” Indian Journal 
of Agricultural Economics, vol. 60, no. 2, pp. 235–248, 2005. 

[13] G. Mandal, S. Kumar, R. Kumar, and R. Singh, “Effect of drip irrigation 
and plant spacing on yield, quality and economic return of guava 
(Psidium guajava L.) grown in saline soil,” Acta horticulturae, vol. 735, 
no. 60, pp. 427–432, 2007, doi: 10.17660/ActaHortic.2007.735.60. 

[14] J. Tan and Y. Kang, “Changes in Soil Properties Under the Influences of 
Cropping and Drip Irrigation During the Reclamation of Severe Salt-
Affected Soils,” Agricultural Sciences in China, vol. 8, no. 10, pp. 
1228–1237, Oct. 2009, doi: 10.1016/S1671-2927(08)60333-8. 

[15] H. K. Soussa, “Effects of Drip Irrigation Water Amount on Crop Yield, 
Productivity and Efficiency of Water Use in Desert Regions in Egypt,” 
Nile Basin Water Science& Engineering Journal, vol. 3, no. 2, pp. 96–
109, 2010. 

[16] D. S. Kumar and K. Palanisami, “Impact of drip irrigation on farming 
system: evidence from Southern India,” Agricultural Economics 
Research Review, vol. 23, no. 2, pp. 265–272, 2010. 

[17] S. Halder, D. Sadhukhan, and R. Verma, “Adaptability of drip irrigation 
in coastal and hard rock terrain of west bengal, India,” presented at the 
International Ground Water Conference 2012, Maharashtra India, Jan. 
2012. 

[18] J. A. C. Bolanos, W. Ortiz, and R. Bhandari, “Techno-economic 
feasibility study of solar and wind based irrigation systems in Northern 
Colombia,” presented at the The 4th World Sustainability Forum, Basel, 
Switzerland, 2014, pp. 1–20. 

[19] S. K. Biswas, A. R. Akanda, M. S. Rahman, and M. A. Hossain, “Effect 
of drip irrigation and mulching on yield, water-use efficiency and 
economics of tomato,” Plant, Soil and Environment, vol. 61, no. 3, pp. 
97–102, Mar. 2015, doi: 10.17221/804/2014-PSE. 

[20] A. Narayanamoorthy and N. Devika, “Economic and Resource Impacts 
of Drip Method of Irrigation on Okra Cultivation: An Analysis of Field 
Survey Data,” Journal of Land and Rural Studies, vol. 6, no. 1, pp. 15–
33, Jan. 2018, doi: 10.1177/2321024917731840. 

[21] W. M. A. Khalifa, “An Economic Analysis of crops Production using a 
Trickle Irrigation System,” International Transaction Journal of 
Engineering, Management, & Applied Sciences & Technologies, vol. 11, 
no. 8, 2020, Art. No. 11A8J. 

[22] W. M. A. Khalifa, “Computer Model for Trickle Irrigation System 
Design,” International Transaction Journal of Engineering, 
Management, & Applied Sciences & Technologies, vol. 11, no. 7, 2020, 
Art. No. 11A07U. 

[23] W. M. A. Khalifa and N. A. A. Mahmoud, “Effects of Drip Irrigation 
System for Long-Life Fruit Trees on Different Economic Bases,” 
International Transaction Journal of Engineering, Management, & 
Applied Sciences & Technologies, vol. 11, no. 11, 2020, Art. No. 
11A11P. 

[24] “Irrigation Water Requirements,” in Part 623 National Engineering 
Handbook, Washington DC, USA: United States Department of 
Agriculture, Soil Conservation Service, 1993. 

[25] Technical Guidelines for Irrigation Suitability Land Classification. 
Denver, CO, USA: U.S. Department of the Interior Bureau of 
Reclamation Technical Service Center Land Suitability and Water 
Quality Group, 2005. 

[26] H. M. A. Ragheb, M. A. Gameh, S. M. Ismail, and N. A. Abou Al-Rejal, 
“Water Distribution Patterns of Drip Irrigation in Sandy Calcareous Soil 
as Affected by Discharge Rate and Amount of Irrigation Water,” 
Journal of King Abdulaziz University: Meteorology, Environment & 

Arid Land Agriculture Sciences, vol. 22, no. 3, pp. 141–161, 2011. 

[27] I. R. Kareem, H. A. Omran, and R. S. Hassan, “Operating a drip 
irrigation system in different types of soil,” in First International 
Symposium on Urban Development: Koya as a Case Study, vol. 17, WIT 
Press, 2013, pp. 105–116. 

[28] K. Khaskhoussy, B. Kahlaoui, B. M. Nefzi, O. Jozdan, A. Dakheel, and 
M. Hachicha, “Effect of Treated Wastewater Irrigation on Heavy Metals 
Distribution in a Tunisian Soil,” Engineering, Technology & Applied 
Science Research, vol. 5, no. 3, pp. 805–810, Jun. 2015. 

[29] Y.-W. Fan, N. Huang, J. Zhang, and T. Zhao, “Simulation of Soil 
Wetting Pattern of Vertical Moistube-Irrigation,” Water, vol. 10, no. 5, 
May 2018, doi: 10.3390/w10050601, Art. No. 601. 

[30] A. Phocaides, “CHAPTER 19: An outline for engineering investigation 
for a pressurized irrigation system,” in Pressurized Irrigation 
Techniques, 2nd ed., Rome, Italy: FAO, 2007. 

[31] M. D. Dukes, D. Z. Haman, F. Lamm, J. R. Buchanan, and C. R. Camp, 
“Site Selection for Subsurface Drip Irrigation Systems in the Humid 
Region,” presented at the World Water and Environmental Resources 
Congress 2005, Apr. 2012, doi: 10.1061/40792(173)558. 

[32] L. Karlberg, “Irrigation with saline water using low-cost drip-irrigation 
systems in sub-Saharan Africa,” Ph.D. dissertation, KTH Royal Institute 
of Technology, Stockholm, Sweden, 2005. 

[33] A. M. Al-Omran, A. R. Al-Harbi, M. A. Wahb-Allah, M. Nadeem, and 
A. Al-Eter, “Impact of irrigation water quality, irrigation systems, 
irrigation rates and soil amendments on tomato production in sandy 
calcareous soil,” Turkish Journal of Agriculture and Forestry, vol. 34, 
no. 1, pp. 59–73, Feb. 2010. 

[34] S. J. Oad, H. Maqsood, A. L. Qureshi, S. Ahmed, I. A. Channa, and M. 
I. Ali, “Farm-based Evaluation of Sustainable Alternative Irrigation 
Practices,” Engineering, Technology & Applied Science Research, vol. 
9, no. 3, pp. 4310–4314, Jun. 2019. 

[35] G. P. Mengu, E. Akkuzu, S. Anac, and S. Sensoy, “Impact of Climate 
Change on Irrigated Agriculture,” Fresenius Environmental Bulletin, 
vol. 20, no. 3a, pp. 823–830, 2011. 

[36] S. Mohan and N. Ramsundram, “Climate Change and its Impact on 
Irrigation Water Requirements on Temporal Scale,” Irrigation & 
Drainage Systems Engineering, vol. 3, no. 1, pp. 1–8, 2014, doi: 
10.4172/2168-9768.1000118. 

[37] Y. Liu, H. Yang, J. Li, Y. Li, and H. Yan, “Estimation of irrigation 
requirements for drip-irrigated maize in a sub-humid climate,” Journal 
of Integrative Agriculture, vol. 17, no. 3, pp. 677–692, Mar. 2018, doi: 
10.1016/S2095-3119(17)61833-1. 

[38] P. Polak, B. Nanes, and D. Adhikari, “A Low Cost Drip Irrigation 
System for Small Farmers in Developing Countries,” Journal of the 
American Water Resources Association, vol. 33, no. 1, pp. 119–124, 
1997, doi: 10.1111/j.1752-1688.1997.tb04088.x. 

[39] C. Wilde, J. Johnson, and J. P. Bordovsky, “Economic analysis of 
subsurface drip irrigation system uniformity,” Applied Engineering in 
Agriculture, vol. 25, no. 3, pp. 357–361, 2009. 

[40] S. Amosson et al., Economics of Irrigation Systems. Texas A&M 
AgriLife Communications, 2011. 



Engineering, Technology & Applied Science Research Vol. 10, No. 5, 2020, 6335-6343 6343  
  

www.etasr.com Khalifa et al.: Farm-Based Environmental and Economic Impacts of Drip Irrigation System 

 

[41] S. K. Deshmukh, “Improving the water and energy efficiency for food 
production through drip irrigation in India,” Water and Energy 
International, vol. 58, no. 1, 2015. 

[42] R. Akhila, Y. Sai Manohar, J. Bangarraju, and V. Rajagopal, “Wind-
Solar Hybrid Energy Powered for Drip Irrigation System,” in 
Proceedings of XI Control Instrumentation System Conference, 
Bangalore, India, Jan. 2014, pp. 148–153. 

[43]  M. A. Pardo Picazo, J. M. Juarez, and D. Garcia-Marquez, “Energy 
Consumption Optimization in Irrigation Networks Supplied by a 
Standalone Direct Pumping Photovoltaic System,” Sustainability, vol. 
10, no. 11, Nov. 2018, doi: 10.3390/su10114203, Art. No. 4203. 

[44] FAOSTAT. http://www.fao.org/faostat/en/#home (accessed Oct. 03, 
2020). 

[45] J. Doorenbos and W. O. Pruitt, Crop Water Requirements. Rome, Italy: 
FAO, 1992. 

[46] A. P. Savva and K. Frenken, Irrigation Manual: Planning, Development 
Monitoring and Evaluation of Irrigated Agriculture with Farmer 
Participation. Rome, Italy: FAO, 2002. 

[47] P. Steduto, T. C. Hsiao, E. Fereres, and D. Raes, Crop Yield Response to 
Water. Rome, Italy: FAO, 2012. 

[48] K. H. N. Reddy, K. A. Kumar, and M. V. Ramana, “Design and 
Development of Drip Irrigation System Software in Visual Basic,” 
International Journal of Agricultural Science and Research, vol. 7, no. 
4, pp. 339–346, 2017. 

[49] “Electricity Facts 2017/2018 Price hikes continue | Egyptian Initiative 
for Personal Rights.” https://eipr.org/en/publications/electricity-facts-
20172018-price-hikes-continue (accessed Oct. 03, 2020). 

[50] Central Agency for Public Mobilization and Statistics. 
https://www.capmas.gov.eg/HomePage.aspx (accessed Oct. 03, 2020). 

[51] Landscape Irrigation Price List. Rain Bird, 2020. 

[52] R. S. Ayers and D. W. Westcott, Water quality for agriculture. Rome, 
Italy: FAO, 1985. 

[53] E. V. Maas, “Salinity and citriculture,” Tree Physiology, vol. 12, no. 2, 
pp. 195–216, Mar. 1993, doi: 10.1093/treephys/12.2.195. 

[54] G. Fipps, Irrigation Water Quality Standards and Salinity Management 
Strategies. Texas Agricultural Extension Service, Texas A&M 
University System, 1996. 

[55] B. Lamsal and V. Jindal, “Variation in Electrical Conductivity of 
Selected Fruit Juices During Continuous Ohmic Heating,” International 
Journal of Applied Science and Technology, vol. 7, no. 1, pp. 47–56, 
Feb. 2014, doi: 10.14416/j.ijast.2014.01.008. 

[56] J. Doorenbos and A. H. Kassam, Yield response to water. Rome, Italy: 
FAO, 1979. 

[57] M. Dorai, A. Papadopoulos, and A. Gosselin, “Influence of electric 
conductivity management on greenhouse tomato yield and fruit quality,” 
Agronomie, vol. 21, no. 4, pp. 367–383, 2001, doi: 10.1051/agro: 
2001130. 

[58] A. A. Murkute, S. Sharma, and S. K. Singh, “Citrus in terms of soil and 
water salinity: A review,” Journal of Scientific & Industrial Research, 
vol. 64, no. 6, pp. 393–402, Jun. 2005. 

[59] M. A. Akanji, S. O. Oshunsanya, and A. Alomran, “Electrical 
conductivity method for predicting yields of two yam (Dioscorea alata) 
cultivars in a coarse textured soil,” International Soil and Water 
Conservation Research, vol. 6, no. 3, pp. 230–236, 2018. 

[60] “Interest Rate - Calculate Simple and Compound Interest Rates,” 
Corporate Finance Institute. https://corporatefinanceinstitute.com/ 
resources/knowledge/finance/interest-rate/ (accessed Oct. 03, 2020). 

[61] C. Banton, “Interest Rate: What the Lender Gets Paid for the Use of 
Assets,” Investopedia. https://www.investopedia.com/terms/i/interest 
rate.asp (accessed Oct. 03, 2020). 

 

AUTHORS PROFILE 
 

Walid M. A. Khalifa is an Assistant Professor at Hail University, Saudi 
Arabia, and Fayoum University, Egypt. He received his B.S. in Civil 
Engineering from Cairo University, and his Ph.D. in Water Resources and 
Environmental Hydrology from Cairo University. His research interests 

include water quality and hydrodynamics modeling, pressurized irrigation 
modeling, and design of RC water structures. 

 

Dr. Hatem Gasmi is an Assistant Professor at Hail University, Saudi Arabia. He 

received his B.S. in Civil Engineering and his Ph.D. in Geotechnical and Soil Risks 

Evaluation from the National Engineering School of Tunis. His research interests 

include ground improvement and soil reinforcement, evaluation of soil risks, and 

innovation system and strategies. 

 

Dr. Tayyab A. Butt is an Assistant Professor at Hail University, Saudi Arabia. He 

received his B.S. in Civil Engineering from University of the Engineering & 

Technology, Lahore, Pakistan and hid Ph.D. in Environmental Engineering from 

KAIST, South Korea. His research interests include energy & environment, 

adsorption engineering, and wastewater treatment technologies.