The benefit of changing to Variable Rate Irrigation (VRI) from uniform application methods needs to be assessed for technology adoption. Precision irrigation involves water application in optimum amounts. Results indicate that feasibility of precision irrigation depends on field variability, crop value, economies of scale, and useful life of the equipment.Land Economics/Use,

Almas, Lal K.

Amosson, Stephen H.

Colette, W. Arden

Marek, Thomas H.

English

Research Papers in Economics

 
 
 
Economic Feasibility of Precision Irrigation 
in the Northern Texas High Plains 
 
 
 
 
 
Lal K. Almas 
West Texas A&M University, Division of Agriculture, 
WTAMU Box 60998, Canyon, Texas 79016 
 
Steve H. Amosson 
Texas Cooperative Extension 
Texas A&M Research and Extension Center 
6500 Amarillo Blvd West, Amarillo, Texas 79106 
 
Thomas Marek 
Texas Agricultural Experiment Station 
Texas A&M Research and Extension Center 
6500 Amarillo Blvd West, Amarillo, Texas 79106 
 
W. Arden Colette 
West Texas A&M University; Division of Agriculture 
WTAMU Box 60998, Canyon, Texas 79016 
 
 
 
Selected Paper prepared for presentation at the Southern Agricultural 
Economics Association Annual Meeting, Mobile, Alabama, February 1-5,2003 
 
 
 
 
 
 
 
 
Copyright 2003 by [authors].  All rights reserved.  Readers may make verbatim copies of this document for non-
commercial purposes by any means, provided that this copyright notice appears on all such copies. 
 
   2
Economic Feasibility of Precision Irrigation in the Northern Texas High Plains 
 
 
Abstract: 
  The benefit of changing to Variable Rate Irrigation (VRI) from uniform application 
methods needs to be assessed for technology adoption.   Precision irrigation involves water 
application in optimum amounts.  Results indicate that feasibility of precision irrigation depends 
on field variability, crop value, economies of scale, and useful life of the equipment.   
   3
Introduction: 
Production agriculture is facing significant challenges such as escalating production cost, 
limited irrigation water, and increased public concern about possible adverse impacts of 
agricultural production on the environment.  Farmers continue to strive to produce high-quality 
products by using farm technologies that are profitable and environmentally friendly.   
Precision farming recognizes variability in soil fertility, water availability, pest 
concentrations, and crop characteristics within fields and seeks to optimize variable input use to 
enhance enterprise profitability and minimize environmental impacts.  Economic benefits of 
switching to variable rate application (VRA) from uniform application methods depend on the 
economic value of assessing and treating within-field variability.  Several variables might be 
responsible for yield variation in a specific field.  These variables could include water, especially 
for water sensitive crops such as corn, fertility, as well as tillage practices.  Marek and Cox 
(2000) assessed potential and future implementation of precision agriculture technologies in the 
Northern Texas High Plains.  Water was assessed to be the most significant factor in production 
of corn, with plant population and depth of soil also responsible for significant variation in yield.   
In the past the emphasis in precision farming research has been on VRA of fertilizers 
when assessing the profitability of VRA.  Swinton and Lowenberg-DeBoer (1998) compared 
estimates for VRA of fertilizers for 54 sites in nine studies.  Babcock and Pautsch (1998) 
evaluated the profitability of VRA of nitrogen fertilization relative to uniform rate application.  
Watkins et al. (1998) also performed an economic and environmental analysis of VRA of 
nitrogen fertilizers for production of seed potatoes.  Research on VRA of water is limited.  
However, in their economics of precision agriculture study, Yu et al. (2000) included a fertilizer 
and water interaction term in a yield estimation model of irrigated cotton production in the   4
Southern High Plains of Texas.  Results indicated that the interaction of fertilizer and water 
significantly affected yield.  Marek and Cox (2000) in their assessment of VRI potential 
determined that irrigation water was the most significant factor in the production of corn in the 
Northern Texas High Plains.  
  A producer seeking to invest in VRA equipment is faced with the questions, “How much 
will it cost?  How much will yield potential be increased?  Will additional returns offset the 
investment cost?”  Knowledge of spatial variability and yield increase can help a farmer make 
appropriate economic decisions about adopting VRA.  In the semi-arid region of the Texas High 
Plains, research indicates that water is an important production input.  In an earlier precision 
farming study by Marek et al. (2001), analyses of producer yield maps revealed that yield was 
variable enough to justify investment in precision irrigation technology.  
Objectives: 
  The goal of this research was to assess economic feasibility of alternative VRI controller 
technology.  The specific objectives were to: 
-  identify and analyze the investment cost of VRI technology in Texas 
-  evaluate the breakeven variability in the field and estimate the breakeven yields of 
grain crops to offset the cost of technology. 
Methodology: 
  Studies of site-specific management have often focused on changes in crop input cost, 
such as fertilizer or herbicide, while ignoring fixed investment costs.  Fixed costs represent 
annualized costs associated with durable capital investment required for VRA and other 
necessary equipment.  The cost estimate data for most of the equipment and technology used in 
precision irrigation is collected from manufacturers and suppliers.  Evaluating the feasibility of   5
investing in a new farm technology can be very complicated because of all the factors involved.  
However, methodology involved in making the decision is relatively simple.  First, the gross 
investment cost should be estimated.  Gross investment indicates the amount of capital that will 
be required.  However, net investment that adjusts gross investment by considering tax savings, 
future salvage value and opportunity cost of investment provides an estimate of the “true” 
economic cost. 
The annual cost of using site-specific tools depends on the useful life of that equipment, 
software and skill.  If site-specific management tools are obsolete in three to four years, the 
annual cost of use can be expensive.   Because a dollar five years from now is not worth the 
same as a dollar today, all annual costs and benefits need to be discounted to today’s dollar.  This 
will allow direct comparison of the costs and benefits of a site-specific management technology.  
The fundamental analysis for the economic cost of investing in VRI technology and the benefits 
generated from an increase in potential yield is conducted by applying a standard cost benefit 
analysis.  A farmer will break even if the expected additional returns above the input costs are 
equal to the cost of VRI depending upon the spatial variability in the field.   
To assess the economic feasibility of VRI, investments of $10,000, 15,000 and 20,000 are 
assumed as possible bases for a VRI control setup on a center pivot systems.  These values are 
assumed for irrigation systems ¼, 3/8 and ½ mile long, respectively, and correspond to 125, 284 
and 500-acre systems, respectively.  Life expectancy of the system is assumed to be 5 years with 
a discount factor of 4.2124 at the discount rate of 6%.  This yields an additional investment cost 
of $69.89, $46.30 and $34.94 per acre for each of the systems, respectively.  (As new generation 
control systems are developed, a 10- to 15- year life could be expected, improving the feasibility 
prediction.)   6
Prices used in the economics portion of the analysis were based on 5-year average values 
obtained from local markets.  The average prices for the respective crops within the region are as 
follows: corn - $2.78/bushel, sorghum - $4.36/cwt, soybeans- $5.66/bushel and wheat -
$3.51/bushel.  Yield variability used in the respective economic analyses varied from 20 to 50%. 
The future streams of returns over five years were discounted to present value (PV) using 
a discount rate of six percent and compared with the initial cost for investing in the technology.  
If PV is greater than the investment, adopting precision agriculture will be profitable.  However, 
if PV were less than the investment, precision agricultural technology would not be feasible to 
implement.  Given the average prices of the major crops grown in the area, corn, sorghum, 
soybean, and wheat, and field variability assumption, breakeven additional yields were also 
estimated for three center pivot irrigation systems. 
Results and Discussion: 
  Before investing in variable rate irrigation technology, yield maps for each crop in each 
field under each crop need to be reviewed carefully because not all fields are suitable for 
implementation of variable rate irrigation on center pivot systems.  A field with a center pivot 
not suitable for VRI is presented in Figure 1.  It indicates a nozzling problem rather than yield 
deviation problem down the lateral and the problem could be corrected without using VRI.  
However, the field represented by Figure 2 is considered more appropriate for use of VRI.  
Figure 3 exhibits a corn yield map illustrating a production system that is a good candidate for 
VRI.  Such a field shows a potential for improvement with VRI.  However, Figure 2 is 
considered the best candidate for VRI because sectoring alone cannot fully solve the variable 
yield problem.  As an example, the breakeven requirement procedure using yield maps for center 
pivot field can be illustrated in Figure 3 by outlining the sub level production area(s) within the   7
histogram bins by using the polygon tool available with most yield mapping software packages.  
These tools compute the respective sub area(s) and associated yield.  The 82-acre area 
represented in Figure 3 is outlined by the black line polygon and indicates the improvement area 
required for breakeven by using a VRI system.  The outlined region, which is relatively small, 
would require only 15 bushels per acre gain to breakeven with a VRI system cost of $20,000.  
This improvement would have to be sustained for five years. 
Breakeven additional yield levels required for justifying additional investment in VRI for 
corn ranged from 12-30 bushels per acre for the ¼-mile and 6-15 bushels per acre for ½-mile 
center pivot system depending on the variability in the field (Table 1).  For soybean, the 
breakeven yield ranged from 3-15 bushels per acre for the various systems (Table 2).  For 
irrigated wheat, the expected breakeven yield ranged from 5-24 bushels per acre for the three 
sizes of center pivot systems (Table 3).  For sorghum, additional yield ranged from 380-1,900 
pounds per acre for the three center pivot systems at various levels of field variability (Table 4).  
The sensitivity analyses were conducted for each crop by varying the output prices.  The 
breakeven yield results at those output prices were also included in the respective tables. 
Additionally, greater yields might be obtained from fields with much variability in 
amounts of irrigation applied to different areas than from fields where irrigation was uniform.  
Also, VRI would be feasible for crops of high value but low-value crops require substantially 
greater yields to breakeven.   Hence, substantial field variability and high crop prices are 
required for VRI to be profitable. 
Variable rate irrigation could be feasible and represent an important tool in the 
technologies associated with precision agriculture in the northern Texas High Plains.  This   8
feasibility is more apparent with higher value and more water-use sensitive crops.  It seems that 
VRI would be feasible for most crops grown in the region. 
References: 
Babcock, Bruce A. and Gregory R. Pautch.  “Moving from Uniform to Variable Fertilizer Rates 
in Iowa Corn: Effects on Rates and Returns.”  Journal of Agricultural and Resource 
Economics, 23, 2 (1998): 385-400. 
    
Marek, T. and E. Cox.  “Assessment of Variable Rate Irrigation Potential in the Northern Texas 
High Plains.”  Society for Engineering in Agriculture Conference in Australia.  Adelaide, 
Australia.  April 2000. 7 pp. 
 
Marek, T., L. Almas, E. Cox, and S. Amosson.  “The Feasibility of Variable Rate Irrigation with 
Center Pivot Systems in the Northern Texas High Plains.”  2001 ASAE Annual 
International Meeting Paper No.01-1117, St. Joseph, MI: American Society for 
Agricultural Engineers. 
 
Swinton, S. M. and J. Lowenberg-DeBoer.  “Evaluating the Profitability of Site-Specific 
Farming”.  Journal of Production Agriculture, 11, 4 (1998): 439-446 
 
Watkins, K. B., Yao-chi Lu, and Wen-yuan Huang.  “Economic and Environmental Feasibility 
of Variable Rate Nitrogen Fertilizer Application with Carry-Over Effects.”  Journal of 
Agricultural and Resource Economics, 23, 2 (1998): 401-426. 
 
Yu, M., E. Segarra, H. Li, R. J. Lascano, C. Chilcutt, L. T. Wilson, K. Bronson, and S. Searcy.  
“The Economics of Precision Agricultural Practices in Cotton Production.”  2000 
Beltwide Cotton Conferences Proceedings, National Cotton Council, Memphis, TN: 201-
208.  
 
 
 
 
 
 
 
 
   9
 
 
 
 
 
 
 
 
 
 
 
 
Figure 1.  Corn yield map illustrating a center pivot irrigation system that is not a 
suitable candidate for VRI. 
   10
 
 
Figure 2.  Corn yield map illustrating a center pivot irrigation system that is an excellent 
candidate for VRI   11
 
 
 
 
 
 
 
 
 
 
 
 
Figure 3.  Corn yield map illustrating a center pivot irrigation system that is a 
good candidate for variable rate irrigation. 
   12
Table 1.  Corn breakeven yield required for implementation of VRI on various lengths 
of center pivot irrigation systems assuming different output prices and field variability. 
 
Field Variability (%)  10  20  30  40 
Output Price ($/bu)  System Length (mile)  Breakeven Yield (bushels/acre) 
¼   33.18  22.12  16.59  13.27 
3/8   21.98  14.66  10.99  8.79 
 
2.50 
½   16.59  11.06  8.29  6.64 
¼   29.84  19.89  14.92  11.94 
3/8   19.77  13.18  9.88  7.91 
 
2.78 
½   14.92  9.95  7.46  5.97 
¼   27.65  18.43  13.83  11.06 
3/8   18.32  12.21  9.16  7.33 
 
3.00 
½   13.82  9.22  6.91  5.53   13
Table 2.  Soybeans breakeven yield required for implementation of VRI on various lengths 
of center pivot irrigation systems assuming different output prices and field variability. 
 
Field Variability (%)  10  20  30  40 
Output Price ($/bu)  System Length (mile)  Breakeven Yield (bushels/acre) 
¼   15.59  10.40  7.80  6.24 
3/8   10.33  6.89  5.17  4.13 
 
5.32 
½   7.80  5.20  3.90  3.12 
¼   14.66  9.77  7.33  5.86 
3/8   9.71  6.47  4.85  3.88 
 
5.66 
½   7.33  4.88  3.66  2.93 
¼   13.83  9.22  6.91  5.53 
3/8   9.16  6.11  4.58  3.66 
 
6.00 
½   6.91  4.61  3.46  2.76   14
Table 3.  Wheat breakeven yield required for implementation of VRI on various lengths 
of center pivot irrigation systems assuming different output prices and field variability. 
 
Field Variability (%)  10  20  30  40 
Output Price ($/bu)  System Length (mile)  Breakeven Yield (bushels/acre) 
¼   25.53  17.02  12.76  10.21 
3/8   16.91  11.27  8.45  6.76 
 
3.25 
½   12.76  8.51  6.38  5.10 
¼   23.63  15.76  11.82  9.45 
3/8   15.66  10.44  7.83  6.26 
 
3.51 
½   11.82  7.88  5.91  4.73 
¼   22.12  14.75  11.06  8.85 
3/8   14.66  9.77  7.33  5.86 
 
3.75 
½   11.06  7.37  5.53  4.42   15
Table 4.  Sorghum breakeven yield required for implementation of VRI on various lengths 
of center pivot irrigation systems assuming different output prices and field variability. 
 
Field Variability (%)  10  20  30  40 
Output Price ($/cwt)  System Length (mile)  Breakeven Yield (cwt/acre) 
¼   20.74  13.83  10.37  8.30 
3/8   13.74  9.16  6.87  5.50 
 
4.00 
½   10.37  6.91  5.18  4.15 
¼   19.03  12.68  9.51  7.61 
3/8   12.60  8.40  6.30  5.04 
 
4.36 
½   9.51  6.34  4.76  3.80 
¼   17.58  11.72  8.79  7.03 
3/8   11.64  7.76  5.82  4.66 
 
4.72 
½   8.79  5.86  4.39  3.51 
 

Assessment of Variable Rate Irrigation Potential in the Northern Texas High Plains.” Society for Engineering

Evaluating the Profitability of Site-Specific Farming”.

Moving from Uniform to Variable Fertilizer Rates in Iowa Corn: Effects on Rates and Returns.”

The Feasibility of Variable Rate Irrigation with Center Pivot Systems in the Northern Texas High Plains.”

ECONOMIC FEASIBILITY OF PRECISION IRRIGATION IN THE NORTHERN TEXAS HIGH PLAINS

ECONOMIC FEASIBILITY OF PRECISION IRRIGATION IN THE NORTHERN TEXAS HIGH PLAINS

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