Research of Current and Potential Subsurface Irrigation Methods for 

United States Department of Agriculture (USDA) 

Federal Crop Insurance Corporation (FCIC) Program 

Final Research Report 

Solicitation: RFQ1396983 

July 24, 2020 

Prepared For: 

Deputy Administrator for Product Management 

USDA/RMA/Room 403 

6501 Beacon Drive 

Kansas City, MO 64133-4675 

DeputyAdministrator@rma.usda.gov 

ATTENTION: 

shawn.beach@usda.gov 

Person’s Authorized to Sign on Offeror’s Behalf: 

S. Clifton Parks 

President & CEO 

1700 Research Parkway, Suite 290 

College Station, TX 77845 

913-982-2441 (p) 

512-548-7511 (f) 

cparks@agrilogic.com 

TIN # 26-4731702 

DUNS # 830444944 

NAICS Code: 524298 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

CONTENTS 

OVERVIEW _____________________________________________________________________________________ 1 

Introduction ________________________________________________________________________________ 1 

Background _________________________________________________________________________________ 1 

SDI ADOPTION AND WATER EFFICIENCY COMPARISONS ______________________________________________________ 5 

SDI Adoption in the High Plains _________________________________________________________________ 5 

SDI vs. Center Pivot Irrigation System Performance _________________________________________________ 8 

TX COTTON YIELDS WITH ALTERNATIVE IRRIGATION SYSTEMS (SDI, LEPA, ETC.)____________________________________ 10 

Mean Yield of Cotton on SDI vs. Other Common Irrigation Systems ___________________________________ 10 

Cotton Yield Variability with SDI vs. Other Common Irrigation Systems ________________________________ 19 

USDA RMA T-Yields vs. County Average NASS and RMA Annual Data __________________________________ 20 

CONCLUSION___________________________________________________________________________________ 26 

RECOMMENDATIONS _____________________________________________________________________________ 29 

REFERENCES ___________________________________________________________________________________ 30 

APPENDIX A: LISTENING SESSION REPORT_______________________________________________________________ 34 

Lubbock, TX Meetings – February 11, 2020_______________________________________________________ 34 

Amarillo, TX Meetings - February 12, 2020 _______________________________________________________ 37 

SDI Webinar – March 10, 2020 ________________________________________________________________ 38 

Additional Contacts Made During Project Period __________________________________________________ 39 

Handout for HPWD Board Meeting _____________________________________________________________ 42 

Webinar Flyer ______________________________________________________________________________ 43 

Webinar Slides _____________________________________________________________________________ 44 

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LIST OF TABLES 

TABLE 1. BASIC ASSUMPTIONS FOR FIVE IRRIGATION DISTRIBUTION SYSTEMS (AMOSSON, ET AL, 2011) 9 

TABLE 2. COTTON YIELDS AND WATER EFFICIENCY BY IRRIGATION TECHNOLOGY, 2005-2013 (TAWC, 

2015).................................................................................................................................................... 11 

TABLE 3. HELMS FARM REPORT – COTTON YIELD AND IRRIGATION DELIVERED BY SDI AND LEPA, 2002-

2012 ..................................................................................................................................................... 14 

TABLE 4. SDI WEBINAR ATTENDEES.......................................................................................................... 39 

LIST OF FIGURES 

FIGURE 1. TEXAS HIGH PLAINS..................................................................................................................... 2 

FIGURE 2. WATER-LEVEL CHANGES IN THE OGALLALA AQUIFER, 1950-2015............................................ 3 

FIGURE 3. TASS CROP REPORTING DISTRICTS (CRDS)............................................................................... 4 

FIGURE 4. PROBABILITY DISTRIBUTION FUNCTION (PDF) OF SDI ANNUAL MEAN COTTON YIELD RELATIVE TO CENTER PIVOT IRRIGATED 

COTTON (2005 TO 2018) BASED ON TAWC OBSERVATIONS...........................................................................................12 

FIGURE 5. EXCERPT OF TEXAS HIGH PLAINS FROM TEXAS AGRICULTURAL EXPERIMENT STATION, TEXAS 

A&M UNIVERSITY, GENERAL SOIL MAP OF TEXAS 1973 (GODFREY, ET AL, 1973)........................... 13 

FIGURE 6. INCHES OF IRRIGATION WATER APPLIED AND RESULTING YIELDS, SDI VS. LEPA ................. 16 

FIGURE 7. TOTAL WATER APPLIED (IRRIGATION & PRECIPITATION OF MARCH – OCTOBER) SDI VS. LEPA 

COTTON YIELDS................................................................................................................................... 16 

FIGURE 8. TOTAL WATER APPLIED (IRRIGATION & PRECIPITATION OF MARCH – OCTOBER WITH MEAN 

STORM DURATION ASSUMED OF 1 HR. FOR INFILTRATION PURPOSES) SDI VS. LEPA COTTON YIELDS 

............................................................................................................................................................. 17 

FIGURE 9. ACTUAL AND PREDICTED YIELDS – SDI VS. LEPA 2002 - 2012 ............................................... 17 

FIGURE 10. PROBABILITY DISTRIBUTION FUNCTION (PDF) OF COTTON YIELDS FROM THE MEAN 

IRRIGATION SYSTEM OBSERVED YIELDS TAWC FROM 2005-2018 FOR SDI AND CENTER PIVOT 

SYSTEMS .............................................................................................................................................. 19 

FIGURE 11. PROBABILITY DISTRIBUTION FUNCTION (PDF) OF COTTON YIELDS FROM THE MEAN 

IRRIGATION SYSTEM OBSERVED YIELDS HELMS FARM FROM 2002-2012 FOR SDI AND CENTER PIVOT 

SYSTEMS .............................................................................................................................................. 20 

FIGURE 12. USDA RMA T-YIELDS VS. NASS AND RMA 10-YR MOVING AVERAGE COUNTY YIELDS, 

SOUTHERN HIGH PLAINS 2001-2018 ................................................................................................... 22 

FIGURE 13. USDA RMA T-YIELDS VS. NASS AND RMA 10-YR MOVING AVERAGE COUNTY YIELDS, 

NORTHERN HIGH PLAINS 2001-2018................................................................................................... 23 

FIGURE 14. USDA RMA T-YIELDS VS. NASS AND RMA 10-YR MOVING AVERAGE COUNTY YIELDS, HALE 

COUNTY, TX 2001-2018...................................................................................................................... 24 

FIGURE 15. USDA RMA T-YIELDS VS. NASS AND RMA 10-YR MOVING AVERAGE COUNTY YIELDS, 

OCHILTREE COUNTY, TX 2001-2018 .................................................................................................. 24 

FIGURE 16: AREA SERVED BY PLAINS COTTON GROWERS, INC. .............................................................. 35 

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OVERVIEW 

INTRODUCTION 

AgriLogic Consulting, LLC (hereafter referred to as AgriLogic) has written the following report to 

address the objectives detailed in the United States Department of Agriculture (USDA) Risk 

Management Agency (RMA) Solicitation RFQ 1396983 - Research of Current and Potential Limited 

and Subsurface Irrigation Methods for USDA Crop Insurance Program. 

Per the requirement of the Food, Conservation, and Energy Act of 2018 (2018 Farm Bill): 

The contractor shall research the feasibility of creating a separate irrigation 

practice for SDI including the establishment of a separate transitional yield 

within a county that is reflective of the average gain in productivity and yield 

associated with the installation of a subsurface drip irrigation system. 

During the solicitation process, a follow up question regarding the scope (area) and crops to be 

included in the report was asked. The contracting officer’s response clarified that the scope was 

for cotton. Additional discussions with USDA further narrowed the scope of work to the eight 

counties surrounding Lubbock, Texas. Therefore, all subsequent research and analyses found in 

this report focuses on areas where irrigated cotton overlaps with ground water restrictions and 

where efficiencies of sub surface drip irrigation (SDI) are being studied by academic research 

personnel and utilized by producers in the Texas High Plains. 

AgriLogic has worked with industry experts, producers, and state officials during the contract 

period to develop a comprehensive recommendation regarding the potential and perceived need 

for a separate practice (and potentially separate cotton T-yields) for the SDI production practice 

in the High Plains. 

BACKGROUND 

For this report AgriLogic Consulting focused on the feasibility of creating a separate irrigation 

practice in the Texas High Plains where the SDI practice has been most widely adopted for cotton 

production. However, recommendations made in this study could also be applicable in similar 

areas where cotton is being grown with SDI in western Oklahoma and western Kansas. First, it is 

important to define the Texas High Plains as the area from roughly Midland, TX to the top of the 

Texas Panhandle as illustrated in Figure 1. 

The Ogallala Aquifer is the largest in the United States (U.S.) and one of the largest in the world. 

It underlies eight states (Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, 

Texas, and Wyoming) and spans 111.8 million acres. From wheat and cows to corn and cotton, 

the regional economy depends almost exclusively on agriculture dependent on Ogallala 

groundwater. However, according to the Fourth National Climate Assessment, producers are 

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extracting water faster than it is being replenished, which means that parts of the Ogallala 

Aquifer should be considered a nonrenewable resource. (California Agriculture, 2016) 

The characteristics of the aquifer vary greatly in different parts of the region. The Ogallala Aquifer 

in Nebraska is deeper in its saturated thickness and recharges more readily than other areas such 

as western Kansas and Texas. According to the Texas Water Resource Institute at Texas A&M 

University, Texas and Kansas together have used close to 40 percent of the total water in the 

Ogallala Aquifer, as compared to Nebraska which has only used 1 percent (TWRI, 2018). The steep 

decline in parts of Texas has caused concern for some time as demonstrated in Figure 2, which 

shows a reduction in water levels of over 150 feet in many areas of the Texas High Plains between 

1950 and 2015. 

Figure 1. Texas High Plains 

According to the United States Geological Society (Stanton et al., 2011), Texas has exhausted 

nearly 30 percent of its water allocation from the aquifer. On average, the aquifer in Texas is 

dropping at a rate of almost one foot per year. The most significant decline in the Ogallala in the 

Texas High Plains has been in the southern part of this region. The Texas Water Development 

Board (TWDB) provided funding for Texas Tech University to perform long-term research on the 

best ways to improve irrigation management and to evaluate the decline in the aquifer in an area 

covering 97,000 acres in Hale and Floyd counties. The study estimated the volume of water in 

storage was 1,748,630 acre-feet in January 2003 and declined to 1,329,740 acre-feet by January 

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2014. The rate of decline averaged 3.3 percent per year and the most significant drop was not 

surprisingly during the catastrophic drought of 2011; in fact, there were many anecdotal reports 

of the evapotranspiration rates off irrigated crops in specific days and areas surpassing the 

amount of water that could be added by the irrigation systems as a result of the severe conditions 

during that year. 

Figure 2. Water-level Changes in the Ogallala Aquifer, 1950-2015 

Source: United States Geological Survey, 2020 

The Texas Field Office of the USDA National Agricultural Statistics Service (NASS) provides data 

for two crop reporting districts (CRDs) that are most relevant to this study, the Northern High 

Plains - District 11 (red) and Southern High Plains – District 12 (blue) as illustrated in Figure 3. 

Cotton is king in the Texas High Plains. NASS reports there were 7 million planted acres of cotton 

resulting in 6.4 million bales of production in 2019. Of that total, the Texas High Plains accounts 

for 63% of the planted acres and 51% of the total production, making this area the dominant 

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cotton-producing area in the state. The Southern High Plains reported 2.3 million bales from 3.1 

million planted acres while the Northern High Plains produced 940,000 bales on 1.3 million acres. 

Figure 3. TASS Crop Reporting Districts (CRDs) 

Source: USDA NASS, Texas Field Office, 2020 

While the Southern High Plains region remains, the primary cotton producing region in Texas, 

there has also been a notable increase in cotton production in recent years in the Northern High 

Plains. The migration of cotton north has been a result of improved cotton varieties for the 

northern areas and ongoing water restrictions which have caused producers in these areas to 

seek more drought tolerant crop alternatives. Dr. Jourdan Bell, Texas A&M agronomist in 

Amarillo, observed that in the last five years cotton acreage in the 22 northernmost counties of 

the Texas High Plains has almost tripled. In 2013, producers in this area planted 300,000 acres of 

cotton which increased to 850,000 acres by 2018. Of that 550,000-acre increase, 350,000 acres 

have been north of Amarillo. Producers applied supplemental irrigation to less than a third of the 

cotton acres in 2013, and by 2018 nearly half of the acreage was being irrigated. Sixty percent of 

the farms south of Lubbock remain in dryland production. 

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SDI ADOPTION AND WATER EFFICIENCY COMPARISONS 

Our first objective was to develop an in-depth understanding of 1) the extent that SDI irrigation 

is being utilized in the Texas High Plains on cotton, and 2) the benefits of SDI in terms of yield and 

water use efficiency. This task was carried out by: 

1) Reviewing published literature from credible sources on SDI; 

2) Consulting with extension offices/universities that have researched SDI; 

3) Collecting all available data from commercial agricultural scale field-level trials comparing 

yields of SDI to other common irrigation methods in the region; 

4) Conducting listening sessions with producers, water officials and industry experts. 

The objective in evaluating the feasibility of a separate irrigation practice for SDI is to enable 

growers to obtain a more representative guarantee for their acreage when they transition from 

an alternative irrigation practice to SDI. The critical questions that must be addressed are: 

1) Is cotton yield performance for SDI statistically different enough from other commonly 

used irrigation methods in the region to merit segregation of the alternative irrigation 

production practices? This could lead to the potential of establishing alternative T-yields 

for the irrigation practices. 

2) Is there significantly different risk presented by the SDI irrigation method compared to 

other commonly used methods (e.g. Low Energy Precision Application (LEPA)) in the 

region? This could lead to the establishment of different premium rates for the 

production practice. 

3) Do irrigated cotton T-yields in the Texas High Plains appropriately represent actual 

producer performance, who are using advanced irrigation methods? 

The first two questions address whether there is a need to establish a separate SDI production 

practice in the crop insurance programs for cotton. The final question addresses if there is just a 

need for a more rigorous update of yield expectations for irrigated yields for the areas in 

question. 

SDI ADOPTION IN THE HIGH PLAINS 

The decline in the Ogallala aquifer has motivated scientists and irrigation engineers to develop 

new types of irrigation with improved efficiency compared to furrow irrigation, a type of flood 

irrigation. Furrow irrigation was the dominant type of irrigation in the Texas High Plains until 

1994, with only an approximate 60% water application efficiency, at which time center pivot 

sprinkler irrigation overtook flood irrigation in utilization (Evett, et al, 2014; Amosson, et al, 

2011). The center pivot was recognized in a 1976 Scientific American article which called the 

center pivot irrigation “perhaps the most significant mechanical innovation in agriculture since 

the replacement of draft animals by the tractor” (California Agriculture, 2016). That is quite a 

statement, but there is no doubt that center pivot irrigation had an enormous impact on 

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agriculture in the Texas High Plains. The early center pivots were an improvement over furrow 

irrigation in many respects, but their use can also result in significant loss to evaporation, 

especially with the early high pressure high-elevation nozzle styles. The next step in center pivot 

development was the introduction of the mid-elevation spray application (MESA) center pivots, 

which improved application efficiency to 78% while the low-elevation spray application (LESA1) 

continued the improvement to a mean 88% efficiency (Amosson, et al, 2011). Bill Lyle, a Texas 

A&M University agricultural engineer, is credited with pioneering the next major irrigation 

revolution by developing the low energy precision application (LEPA) system. It was so named 

because it used lower pressure and less energy than the traditional center pivot systems. LEPA 

type systems have continued to improve since that time, partly by lowering the droplines to 

reduce evaporation that has resulted in a 95% water application efficiency (Amosson, et al, 2011). 

Currently, approximately 80 percent of the producers in the Texas High Plains use center pivot 

systems with LEPA being one of the more advanced systems (Porter, 2020). LEPA is well suited 

to the high plains region with large fields that allow the use of extended pivots which reduces 

producer cost on a per acre basis (Porter, 2020). However, it is not an ideal application method 

for all situations as soil type, producer’s equipment capabilities (e.g. precision planting 

equipment, furrow diking, and application equipment to farm in a circular pattern, etc.), that lead 

a mixtures of systems being more preferable in different applications (Sides, 2020). 

The next innovation in water application efficiency for specific applications is SDI with a mean 

water application efficiency of approximately 97%. SDI is only marginally more efficient 

compared to LEPA and other newer pivot type systems; moreover, it requires a significantly 

greater investment to install. SDI also requires a higher level of management to utilize its full 

capabilities. SDI is currently on approximately 18%2 of irrigated acreage in the Texas High Plains 

region, which is a relatively minor percentage of the irrigated cotton acres in the region currently, 

but its adoption rate has been steadily rising. SDI started catching on in commercial agriculture 

in the 1980s, and initially on high-value fruit, vegetable and orchard crops. Cotton was one of the 

first large scale row crops to begin to make extensive use of SDI. SDI is gaining in popularity, 

especially in areas with limited irrigation well capacities and where water application efficiency 

is paramount, a common problem particularly in the southern part of the High Plains. SDI also 

works well on small or irregularly shaped fields not well suited for pivots where a relatively small 

percentage of it can be cost effectively irrigated. 

1 A subset of the LESA classification which is very popular in the Texas High Plains is the low pressure in canopy (LPIC) system 

that was noted by the USDA Natural Resource Conservation Service (NRCS) as being one of the most popular systems they fund 

through the EQIP program. It is estimated by Keith Sides, the NRCS Texas State Irrigation Engineer that there is an even split 

between traditional LESA and LPIC systems in the classification given their worked with Texas producers (Sides, 2020). The 

water use efficiency is estimated as being the same for the LESA and LPIC systems by the Texas Water Development Board hence 

suggesting the LPIC is a sub-classification of the LESA category (TWDC, 2013). 

2 The 18% SDI assumption is the average of the SDI acreage reported by Sosebee and Dr. Porter of 600,000 acres times 85% (an 

average of the 90% estimate from Sosebee and the 80% estimate from Porter) in the high plains divided by the 2,912,500 irrigated 

acreage reported by USDA NASS for the Texas High Plains in 2018 for cotton, corn, and sorghum irrigated acreage combined. 

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One of the impediments of SDI adoption is the cost to install the system, particularly for cotton 

in tight market conditions as the industry is currently experiencing. According to an article in the 

American Society of Farm Managers and Ranch Appraisers, a LEPA system cost approximately 

$600 per acre for a quarter mile machine, while a typical SDI system costs approximately $1,200 

per acre for the equipment not counting the cost of the well or pump (Guerrero, et al, 2016; 

DuBois, 2020). (The LEPA per acre cost advantage over SDI increases as the field size increases.) 

The study concludes that savings in pumping costs by themselves are not enough to off-set the 

increase in the investment cost of SDI compared to LEPA. However, when the potential for yield 

increases as well as reduced pumping costs are factored into the analysis, the total benefits may 

be enough over time to justify the additional cost of SDI. 

It is estimated that between 500,000 to 700,000 acres in Texas are irrigated with SDI, and 

approximately 85%3 of those acres, which equates to approximately 510,000 acres assuming the 

mean of this range, are in the High Plains (Sosebee, 2020). There are significant differences in 

cotton production and irrigation practices between the Southern and Northern High Plains. For 

the Southern High Plains, cotton is generally planted continuously year after year without 

rotating to other crops, in part because cotton uses less water than some other crops including 

corn. Another reason the producers in this area do continuous cotton is because of the sizable 

investment they have in the equipment necessary to be a competitive cotton producer. 

Conversion of some or even all of a producer’s acreage to dryland production is also common in 

this area. The availability of an adequate amount of water is generally more important in 

determining potential yields than the type of irrigation system used to produce the cotton. 

According to Dr. Jourdan Bell, the northern area has a shorter growing season that is being 

addressed by new cotton varieties. Producers are also becoming more concerned about their 

water situation and since cotton requires less water than corn, a rotation between the two is 

becoming more common. Dr. Bell noted that corn in this region requires about 24 to 30 inches 

of total water (irrigation and rainfall) while cotton only uses 12 to 24 inches in a typical year to 

make a crop. As noted earlier, SDI is not as common in this area as it is further south. SDI does 

have benefits over LEPA and other alternatives in certain areas but there are certainly challenges 

that the practice presents as well with a special emphasis on seed germination and emergence 

in dry years at planting. It is much more challenging to “water the crop up” with SDI, if the soil 

moisture is inadequate for germination without irrigation. This is particularly the case on soil 

types with high concentrations of sand. 

It must be concluded then that many producers are finding that SDI has enough benefits to justify 

the higher initial investment. In summary, there is no question that SDI is a proven irrigation 

practice for cotton production in this region and it should be expected that the adoption of SDI 

will continue to increase over time. 

3 Dr. Porter suggested 80% of SDI was in the Texas High Plains but she deferred to Sosebee to have the most accurate information 

as they are the principle manufacturer of the technology (Porter, 2020). 

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SDI VS. CENTER PIVOT IRRIGATION SYSTEM PERFORMANCE 

Benefits of SDI are described in scientific literature, but it is also useful to learn about producers’ 

perspectives of SDI and the anecdotal evidence associated with their observations. The following 

section highlights several stories from farmers about their experiences with SDI: 

• Jamey Duesterhaus, Lamb County - Farms 1,900 acres of mostly minimum-till cotton. 260 

of the 500 irrigated acres of cotton are on SDI. He likes that he can directly spoon feed the 

root zone with nitrogen and zinc and have less evaporation. In 2015 he produced 2,340 

pounds per acre on a 60-acre field. (Cotton Farming, 2016) 

• Jeffrey Kitten, Lubbock - Kitten says the biggest factor in his excellent yields are because 

of the way SDI allows him to apply fertilizer. This improved method of feeding nutrients to 

cotton makes it possible to generate some phenomenal yields. In 2013 their drip fields 

produced more than 4 bales per acre (each bale is 500 pounds) and some even made 5 

bales. (Wolfshohl, 2014) 

• Glenn Schur and son Layton, Hale County - Installed 60 acres of SDI on some of their best 

land but it had “weak water.” In 2018 he planted at the beginning of May and replanted 

at the end of May and the cotton yielded about 3 bales per acre. (Huguley, 2019) 

A 2016 article in MyFarmLife.com summed up the comparison of SDI and LEPA and raises the 

question of whether SDI saves water in field crops. The answer, it turns out, is complicated. Ricky 

James, a producer in the Plainview area, said water scarcity is the biggest issue. He stated that 

they must “work at it to get water out of the wells compared to times past when water was under 

pressure and it flowed more freely”. He stated that today the water situation is very different, 

“The water is just not as clean as before and can cause emitters to become clogged.” Also 

mentioned in the article was a field trial on Eddie Teeter’s farm 65 miles north of Lubbock that 

was designed by Rick Kellison, project manager for the Texas Alliance for Water Conservation at 

Texas Tech University. The experiment involved six different fields with three on SDI and the 

other three on LEPA with bubblers (a feature in some of the newer pivots). The conclusion of this 

test was that SDI did not save much water, but Teeter was able to water more acres with about 

the same amount of water. 

In addition to the above examples, a review of the literature on SDI summarizes some of the 

benefits of SDI compared to LEPA which are: 

• Potential for higher yields 

• Works well with lower capacity wells (system can be designed with multiple zones to 

accommodate low well capacity) 

• Less water lost to evaporation and runoff 

• More uniform application of water over entire field 

• Ability to place water and the fertilizer directly into the root zone and do so frequently 

• Fewer weed seeds germinate because the soil is dry 

• Other farming operations can take place concurrently because the irrigation system is 

underground 

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TX COTTON YIELDS WITH ALTERNATIVE IRRIGATION 

SYSTEMS (SDI, LEPA, ETC.) 

MEAN YIELD OF COTTON ON SDI VS. OTHER COMMON IRRIGATION SYSTEMS 

In addressing the principle question, “Is cotton yield performance for SDI statistically different 

enough from other commonly used irrigation methods in the region to merit establishment of a 

separate irrigation production practice?” several studies that have been conducted in the region 

were considered. 

The first study reviewed was conducted by the Texas Alliance for Water Conservation (TAWC), 

which collected data for cotton yields and irrigation efficiencies in Floyd and Hale counties. The 

data was collected on the primary irrigation systems utilized in the region from multiple farm 

fields between 2005 and 2013. The results are presented in Table 2 (TAWC, 2015). The cumulative 

results across all years of the study suggests cotton yields from the SDI systems were 16% higher 

than LEPA and approximately 29% higher than other types of center pivot irrigation systems used 

in the region. The total water consumed was higher on SDI in this study than the other alternative 

methods. Total water (both precipitation and irrigation) consumption must be the metric of 

comparison as that is what it took to make the crop. However, the water use efficiency was 

certainly improved with the SDI method over alternative methods. 

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Figure 4. Probability Distribution Function (PDF) of SDI Annual Mean Cotton Yield Relative to Center 

Pivot Irrigated Cotton (2005 to 2018) Based on TAWC Observations 

In evaluating this information, it is beneficial to understand the distribution of the irrigation 

methods represented by the data, particularly the center pivot category that SDI is compared to 

in Figure 4. The irrigated acreage represented by the TAWC study as of 2018 comprises 

approximately 2% furrow, 19% MESA, 43% LESA, 22% LEPA and 13% SDI. This distribution is not 

an ideal representation of the Texas High Plains but is generally representative of the principle 

areas of focus. A rough estimate of the pivot irrigated acreage in the Texas High Plains overall is 

approximately 80% (Porter, 2020); therefore, the distribution presented by this study is not that 

dissimilar from the overall expectations. 

The concentration of different irrigation systems varies across the Texas High Plains. In the 

northern portion of the Texas panhandle, north of Amarillo, the North Plains Groundwater 

Conservation District (NPGCD) contains very little SDI. The estimates from the Master Irrigator 

NPGCD program from 2016 to 2019 includes approximately 263,000 acres of irrigation which 

were considered a good cross section of the farmers in the region with MESA systems 

representing 9%, LESA 58%, LEPA 32%, furrow 0.1%, and SDI 1.3% of the irrigated acreage 

(Amosson, 2020). Hence SDI was a very minor player in the northern portion of the Texas 

Panhandle. As you examine the southern portions of the plains where soils have a higher sand 

content, such as in Gaines, Terry and Yoakum Counties, the SDI production practice has 

experienced limited success. Western Peanut Growers funded a research farm in the mid 1990’s 

for a period of five years that was run by Texas A&M and Texas Tech University researchers. The 

conclusion was the inability to push adequate amounts of water to the root zone in soils with 

high sand contents and that SDI was not workable on peanuts; further only limited success was 

experienced with cotton at the time. As a result, the MESA and LESA systems still comprise most 

of the irrigated acreage in the region with the remainder being LEPA systems. In examining a soil 

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map of the high plains, the areas where SDI has been most successful are those where the soils 

have a lower concentration of sand and a higher concentration of clay. 

Figure 5. Excerpt of Texas High Plains from Texas Agricultural Experiment Station, Texas A&M 

University, General Soil Map of Texas 1973 (Godfrey, et al, 1973) 

One such area is the region surrounding Plainview, Texas stretching down toward Lubbock. One 

of the most extensive scientifically rigorous studies on the performance of SDI relative to some 

of the more advanced center pivot systems has been conducted at the Helms Research Farm, 

located in Halfway, TX. The lead scientist for this study was Dr. Jim Bordovsky, agricultural 

engineer with Texas A&M AgriLife Research. The research objective was to compare yields and 

irrigation quantities from farm scale cotton production irrigated by SDI and LEPA. Helms Research 

Farm has many advantages to perform this type of research in that it provides a controlled 

environment and offers side by side comparisons of the two technologies. Data was collected 

from 2002 to 2012 (Bordovsky, et al, 2009; Bordovsky, et al, 2013). Results are shown in Table 3. 

SDI yields averaged 1,281 pounds per acre, approximately 25% higher than the 1,023 pounds per 

acre produced on the LEPA system. The higher yield performance on SDI is not surprising given 

the farm is comprised of deep clay loam and silty clay loam soils (Bordovsky, et al, 2013). In the 

report Dr. Bordovsky observes that from various experiments, SDI yields ranged from zero to 

2,400 pounds per acre. LEPA yields ranged from 200 to 2,000 pounds per acre. The wide range 

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gridded dataset was utilized (NCDC, 2020). The results of that analysis are presented in Figure 7. 

The clear consistent advantage for SDI over LEPA is demonstrated in the figure from a total water 

applied perspective. 

However, to take the analysis a step further you must consider what moisture is available to the 

crop. It is common with natural precipitation events for there to be considerable runoff when the 

amount exceeds a given threshold. To account for the infiltration rate of precipitation events into 

the soil profile a capping mechanism for the daily precipitation observations was established. 

This enabled an estimate of the precipitation that could be utilized by the crop for each event. 

To conduct the analysis, an infiltration factor of 7.5 mm per hour for clay and 25 mm per hour for 

sand was utilized in conjunction with the clay and sand compositions of the soil in the area. The 

duration of precipitation events and its interaction with the daily infiltration rates was assumed 

to be 1 hour for this evaluation. The result of the analysis is presented in Figure 8. The expected 

relationship between total available moisture to the crop and yield is demonstrated in the figure 

with the advantage of SDI being highlighted as years in which lower levels of precipitation are 

experienced after seed emergence which produces a more consistent yield expectation. This was 

particularly the case for a year like 2011. 

Ultimately, the yield differential between the two systems is contingent on the percentage of 

water delivered by irrigation relative to available rainfall and soil moisture. The improved water 

use efficiency for SDI is optimal when irrigation represents in excess of 50% of total water 

availability after the crop has emerged from the soil. This is most notable in 2011 when irrigation 

made up between 58% to 65% of the total water availability (on a daily capped basis accounting 

for infiltration rates of approximately 76% and 70% respectively) for SDI and LEPA respectively, 

as depicted in Figure 9, and when evapotranspiration (ET) rates were extreme during the growing 

season. 

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Figure 6. Inches of Irrigation Water Applied and Resulting Yields, SDI vs. LEPA 

Figure 7. Total Water Applied (Irrigation & Precipitation of March – October) SDI vs. LEPA Cotton 

Yields 

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Figure 8. Total Water Applied (Irrigation & Precipitation of March – October with Mean Storm 

Duration Assumed of 1 hr. for Infiltration Purposes) SDI vs. LEPA Cotton Yields 

Figure 9. Actual and Predicted Yields – SDI vs. LEPA 2002 - 2012 

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The conclusion of the analysis is the SDI systems do provide advantages over other types of 

irrigation in specific situations including those areas where soil contents have a higher 

concentration of clay and in years where ET rates are high. SDI also has an advantage where well 

capacities are low and if the field is small or has an irregular shape. However, it does not offer a 

distinct advantage in all applications as demonstrated by the TAWC study which considered a 

broader view of soil compositions, variations in management intensity by producers, and other 

factors common to commercial scale operations. This is particularly the case in years where there 

is inadequate moisture to germinate the seeds for establishing the crop and in those areas with 

soils comprised of higher compositions of sand. 

When the broader range of applications are considered (particularly when SDI is compared to 

LEPA) the water application efficiency is not significantly greater (for SDI of 97% versus 95% for 

LEPA) (Amosson, et al., 2011). When SDI is considered relative to other types of commonly used 

irrigation such as MESA and LESA that comprise most of the irrigated acreage in the Texas High 

Plains, SDI does offer a significant advantage in several applications with 78% water application 

efficiency for MESA and 88% for LESA. The water application efficiency between alternative 

center pivot systems is further complicated when you consider that some LEPA machines have 

bubble emitters that can be adjusted to function as sprinkler emitter, thereby operating more as 

a LESA system for getting seed emergence at planting (Brown, 2020). This blurs the lines between 

some systems, leading to the current structure of crop insurance practices in the region that 

classifies all irrigated cotton into one practice irrespective of the system utilized. 

In conclusion, when you consider SDI versus center pivot style systems in a broad range of 

commercial scale applications, which is more reflective of potential insureds than a purely 

research trial would be, the mean advantage across the board for SDI is not evident. It is instead 

driven more by the specific circumstances of soil types and management practices than the 

irrigation method. 

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COTTON YIELD VARIABILITY WITH SDI VS. OTHER COMMON IRRIGATION SYSTEMS 

To address the second question, as to SDI’s impact on cotton yield variability that would translate 

into the premium rate appropriate for characterizing the risk of extending crop insurance 

coverage to the crop, the yield data from the TAWC and Helms farm studies were once again 

considered. The mean yield for the SDI production practice was calculated and the percent 

deviation of each annual yield observation from the mean was determined. The process was 

repeated for the center pivot data series comprised of MESA, LESA, and LEPA systems. The results 

of those calculations are presented as a probability distribution functions (PDF) of cotton yields 

from the TAWC study from 2005 to 2018 in Figure 10 and from the Helms Farm study from 2002 

to 2012 in Figure 11. 

The figures suggest that the distributions of yields are recognizably different between SDI and 

other irrigated production practices. The left tail of the distributions (i.e. 85% and less) is of the 

most interest from rating perspective suggesting that the corresponding premium rates for the 

irrigation practice would diverge from the other common irrigation methods. It is suspected that 

a significant portion of this could be attributed to farmers learning how to effectively manage the 

SDI practice in the TAWC data as it is not a controlled research study but, instead more reflective 

of commercial operations. Despite those limitations the similarity to the pdfs estimated for the 

Helms Farm which was a controlled research study suggests that the relationship is likely valid 

and representative of actual expectations. 

Figure 10. Probability Distribution Function (PDF) of Cotton Yields from the Mean Irrigation System 

Observed Yields TAWC from 2005-2018 for SDI and Center Pivot Systems 

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Figure 11. Probability Distribution Function (PDF) of Cotton Yields from the Mean Irrigation System 

Observed Yields Helms Farm from 2002-2012 for SDI and Center Pivot Systems 

The understanding of the distribution characteristics of SDI versus other irrigation practices is 

different yet there are likely an array of distributional characteristics included in the other 

irrigation practices with furrow, MESA, LESA, and LEPA, which comprise the current population 

of irrigated insurance experience in each county. With this consideration the continuous rating 

methodology can likely be fine-tuned over time to account fluctuations in distributional 

characteristics for SDI along with the other irrigated production practices. 

USDA RMA T-YIELDS VS. COUNTY AVERAGE NASS AND RMA ANNUAL DATA 

There were comments received during our evaluation that irrigated T-Yields in some counties 

were not entirely representative of actual expectations in the locations. Therefore, an evaluation 

of the irrigated T-yields on cotton in the Texas High Plains was conducted. The objective of the 

analysis was to determine if the T-yields were generally representative of irrigated cotton 

producer yields for the practice and if those farmers who were utilizing advanced irrigation 

methods were properly represented. 

T-yields may be necessary to fill in the gaps when a producer is seeking insurance but does not 

yet have the minimum required four years of yield history to establish an initial yield guarantee. 

For example, if a producer is growing irrigated cotton for the first time in a county, he would have 

multiple options6 with the most common being the use of T-yields. T-yields can be used to 

establish an initial yield guarantee for the first four years until he accumulates enough of his own 

6 The T-yields may not apply if the insured is farming the insured acreage on a share basis with another insured who has yield 

history for the production practice in the county or could use the yield history established by the person who farmed the land 

previously if they had participated in the management and physical activities of the operation. 

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experience for the crop and production practice in the county. T-yields are used to complete four 

years of data in the following manner: 

• No actual record available, use 65% of T-yield for all 4 years 

• One year of actual record, use 80% of T-yield for remaining 3 years 

• Two years of records, use 90% of T-yield for remaining 2 years 

• Three years of records, use 100% of T-yield for one missing year 

If the insured qualifies as a new producer, he can use 100% of the T-yields for the years without 

actual yields. 

In the Northern High Plains, most producers have predominately grown corn on their irrigated 

acreage historically but recently have begun to rotate cotton into their operations. This is due to 

the more limited water availability which has incentivized them to consider more drought 

tolerant crops. As a result, better cotton varieties have been developed for the region and 

infrastructure has begun to be established making cotton a feasible alternative for more 

producers. One such example of the infrastructure in development is the Adobe Walls Gin in 

Spearman, Texas. It is now recognized as the largest gin in the country and is expected to process 

approximately 400,000 bales annually (Boyd, 2019). 

An evaluation of the T-yields was conducted on a county and practice-specific basis. The 

aggregate view of that information is presented in Figure 12 and Figure 13 for the Southern and 

Northern High Plains, respectively. The columns represent the annual USDA NASS yield 

observations, while the blue line series represents the mean USDA RMA T-yield for the region 

and year. The 10-year moving average yield, with a lag year to account for the information that 

would be available when the T-yield is published annually, was calculated both for NASS 

(represented by the yellow line series) and the RMA7 annual actual yield observation data sets. 

The result of that analysis suggests that for the overall irrigated production practice the T-yields 

do tend to lag the NASS observations. However, since the NASS observations are the function of 

a voluntary survey and not necessarily verifiable records in all instances, the internal RMA data 

series driven by yield reports aggregated from verifiable insured data is likely a more 

representative measure of actual conditions. The T-yield in the last three years appears to be 

appropriate for the overall production practice in both the Northern and Southern High Plains. 

There was a period from 2010 to 2015 that the RMA T-yields appeared to lag actual expectations, 

yet that appears to have largely been rectified by 2016 in both regions. The appearance of a 

discrepancy during this period is likely attributed to NASS not reporting an irrigated practicespecific yield observation for 2011 due to the severe drought conditions. That shock to the 

system, if included, would temper the yield expectations and lead to RMA holding the T-yields 

constant for the period. 

7 The USDA RMA actual annual yield observations are reported through their Area Plan Historical Yield report annually (RMA2, 

2020). 

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The T-yields in the Northern High Plains are reasonable for the overall production practice for the 

2016 to 2018 period but prior to that the T-yields consistently lagged the mean yield observations 

for the majority of years, as demonstrated by Figure 13. The significant departure of the NASS 

reported and RMA calculated actual average yields (demonstrated as the green and yellow series 

in the figures) from the T-yield is likely attributed to RMA not considering that enough 

information had been accumulated for many of the Northern High Plains’ counties to allow the 

T-yields to be principally established from the county’s own information which was often much 

higher than the T-yield. This is in the consideration of the credibility requirements on the 

counties’ information was limited until adequate insurance experience was accumulated. 

Figure 12. USDA RMA T-yields vs. NASS and RMA 10-Yr Moving Average County Yields, Southern High 

Plains 2001-2018 

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Figure 13. USDA RMA T-yields vs. NASS and RMA 10-Yr Moving Average County Yields, Northern High 

Plains 2001-2018 

T-yields in Hale County, which is located in the southern portion of the Northern High Plains track 

very closely to the RMA 10-year moving average yield as depicted in Figure 14. However, the Tyields in Ochiltree County in the northern portion of the Northern High Plains where cotton 

production was more intermittent, took longer to catch up with the RMA 10-year moving average 

yield as demonstrated in Figure 15. Until 2016, the T-yield was less than 58% of the actual county 

average yield, where RMA had a county yield reported 13 out of the 15 years in which 8 of the 

years the observed yield was almost double the T-yield. This significant delay in the T-yield 

aligning with expectations for the county is likely due to a lack of credible metrics for recognizing 

county-specific yield performance coupled with a conservative approach to T-yield establishment 

for an area largely new to cotton production. Most likely, areas like Ochiltree County is where 

the call for T-yield reviews may have originated. 

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Figure 14. USDA RMA T-yields vs. NASS and RMA 10-Yr Moving Average County Yields, Hale County, 

TX 2001-2018 

Figure 15. USDA RMA T-yields vs. NASS and RMA 10-Yr Moving Average County Yields, Ochiltree 

County, TX 2001-2018 

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To confirm the theory on the lag observed in some areas, current T-yield review parameters were 

sought to be understood. The cotton specialist in the Oklahoma City RMA Regional Office (RO) 

was contacted, to better understand the current procedures used and the status of irrigated 

cotton yields in the High Plains. Based on our discussion, T-yields for irrigated cotton in the Texas 

High Plains were updated for 2018. The RO representative indicated that since cotton has been 

produced for a few years in most all the counties in the High Plains, he was able to find credible 

data by the time they made it to the 2018 T-yield updates. If such data was not available for a 

given county, yields from a neighboring county were used. The representative also reported that 

RMA is on a three-year cycle to update cotton T-yields in the High Plains, and such timely updates 

will keep them in line with improvements in yields due to new varieties and other developments. 

DeDe Jones, an extension specialist with Texas AgriLife Extension in Amarillo also reviewed the 

2018 T-yields for appropriateness in selected counties and consulted with various other county 

agents. The general response she received was that the yields might be on the low side by about 

10 percent, but they were generally in the correct range for the overall irrigated production 

practice. This confirms our assessment as well, since in most areas the yields since 2016 seem to 

be well aligned with typical irrigation production practices. 

Since most of the irrigated acreage on the Texas High Plains is still comprised of MESA and LESA 

systems (e.g. ≈ 60%) whose water application efficiency is significantly less (and in turn the 

corresponding yield performance is also less) than LEPA or other higher efficiency systems such 

as SDI, the all irrigated acreage T-yield for the county as is currently published by RMA will lag 

that of the higher efficiency systems on theoretical basis. However, when the variance in 

performance is realized in commercial scale operations with a broad array of circumstances and 

management intensities, the difference in system performance becomes more varied as 

demonstrated in the TAWC study from 2005 to 2018. Hence, the differences are not as evident, 

and the additional administrative burden must be considered when evaluating the potential of 

segregating irrigated production practices into higher and lower efficiency characterizations. 

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CONCLUSION 

As part of analyzing the possible justification for segregating SDI from other irrigation production 

practices, AgriLogic considered the potential benefits of offering a separate practice while also 

considering the limitation that it may present. The reasons for establishing a separate practice 

for SDI from the standard irrigation production practice are twofold: first is that a T-yield must 

align with the practice’s general yield potential for the county (e.g. expected SDI yield, LESA yield, 

LEPA yield, etc.). If the yield expectations are significantly different, then they should be 

segregated. The second is if the risk of yield variability differs significantly between the 

alternative irrigated production practices. The case for establishing an alternative T-yield for SDI 

is largely to address the coverage for the first four years that an insured uses SDI irrigation in a 

specific location (after four years the insured’s yield guarantee will be established off their own 

history). Given that the continuous rating methodology adjusts the insured’s premium rate by 

comparing the mean yield performance relative to the county, the insured’s insurable unit would 

be dynamically aligned with their performance over the four-year period anyway. 

T-yields allow producers producing cotton for the first time to establish an initial insurance 

guarantee for coverage until their own actual yields are accumulated and this process tends to 

mitigate the impact of T-yields. Other uses of T-yield plugs are situations where yield 

substitutions or yield exclusions are used according to APH procedures. This function is 

implemented to help support the insured’s APH when loss years are experienced. Because the 

concentration of cotton produced on SDI varies significantly across the Texas High Plains, the 

practice if segregated should only be done for a limited number of counties where the practice 

is a valid consideration (e.g. high clay contents in the soil profile). In other words, if the 

segregation of SDI acreage into a specific irrigation practice were implemented, it would only 

have merit in certain areas8 since the practice’s performance lags that of other methods (e.g. 

LEPA) in certain circumstances9 as previously discussed. 

SDI on cotton is a long-standing and accepted practice; its viability is not in question but instead 

it must be considered in the context for which the production practice is being established. This 

is not limited to soil characteristics but also to the insured’s understanding of proper 

management of the system, the insured’s diligence in executing its operation, and the 

consistency of that approach. These questions require that the insured prove their performance 

to earn that recognition to justify a higher yield guarantee. SDI does not consistently produce a 

significantly higher yield in all circumstances as previously discussed compared to a modern wellmaintained LEPA and in some instances LESA systems. This conclusion is based on extensive 

8 Where the SDI practice has been adopted in meaningful volumes and has demonstrated significantly different performance from 

other irrigation methods. Otherwise the additional resources required to collect and maintain the additional level of detail would 

not be justified and a single irrigation practice should be used in the interest of simplicity of program administration. 

9 The SDI practice is actually inferior to MESA, LESA, and LEPA in areas such as Gaines County, TX where soils are comprised 

of high concentrations of sand that do not lead to successful implementations of the SDI method. 

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conversations with producers, cotton organization personnel and irrigation specialists. On 

properly managed operations with soil properties conducive to the practice, SDI does present 

advantages over other irrigation methods, however, the results are not always consistent. 

Therefore, other factors must also be considered prior to recommending the addition of a 

segregated irrigation practice, which include the insured support for the segregation and the 

additional administrative burden required on insureds, the insurance industry (i.e. AIPs), and the 

regulator (i.e. USDA) to administer the more complex program. 

Meetings were conducted with producers in multiple locations throughout the High Plains to 

assess their interest in a separate practice for SDI irrigation. Overall, based on discussions, 

significant support for the segregation of SDI from other irrigated production practices was not 

identified at this time. The primary commodity association representing cotton producers in the 

High Plains, Plains Cotton Growers Inc., was consulted and they do not support a separate SDI 

practice for cotton, if it is to be implemented as a mandatory reporting requirement. The reasons 

for their position are: 

1) An adequate supply of water including adequate well capacity is more important in 

determining yield potential for cotton than the irrigation system utilized; 

2) There is an array of irrigation systems available which offer enhanced efficiency with each 

having advantages and disadvantages; and 

3) It would not be worth the additional effort for most producers to collect and report 

separate yield information for a SDI as a separate irrigation practice. 

The role water availability plays in assessing the production potential of a crop is vast, and there 

are unquestionable advantages to many of the higher efficiency systems. The question gets down 

to the economics of the situation for a specific insurable unit as to whether a high efficiency 

irrigation system makes sense. This has to do with the suitability of the soil properties and the 

management style of the producer which would better suggest what level of improved 

performance may be anticipated. The return of a higher efficiency system from an economic 

perspective must be considered as to the merit of making the investment. 

Plains Cotton Growers’ position that if you have enough water you can make a crop with 

whatever irrigation application method that is used is appreciated, but in the context of the 

insurance program where water availability is limited, the efficiency of that system can have an 

impact on the expected yield and the variability about that expectation (i.e. the risk and the 

associated premium rate appropriate for it). In this context, the water availability and system 

type must be considered simultaneously to fully evaluate potentially different outcomes. This 

would suggest for certain counties whose soils are principally comprised of higher clay contents 

such as Hale and Floyd Counties, a separate production practice for SDI could be established that 

would typically demonstrate a higher yield expectation. In a perfect world where collection of 

detailed practice-specific information did not require a significant effort by the insurance 

program participants, it would be ideal to capture the segregated irrigated practice-specific 

insurance experience for furrow, MESA, LESA, LEPA and SDI to better understand the risk 

associated with insuring each of the alternative methods. However, that is not feasible on a broad 

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scale in considering the burden that would place on the industry particularly in many other 

counties where the difference is not significant. In actuality, other irrigation methods in certain 

circumstances are preferred over SDI due to their superior performance for the application. 

These considerations coupled with a lack of broad producer support for the addition of a new SDI 

practice places more emphasis on the additional administrative burden to introduce the added 

level of detail. The additional administrative burden is not trivial particularly given the number of 

irrigation systems that the typical Texas High Plains irrigated producer must manage and track. 

This is particularly the case when multiple systems currently underly a single insurable unit even 

at the optional unit level. 

When the increased efficiency of the LEPA system is considered relative to the furrow, MESA, or 

LESA systems, it is more like SDI regarding its yield potential than those other irrigation methods 

with which it is currently grouped. As a result, if a new production practice were considered it 

may be more appropriate to consider LEPA with SDI in an advanced irrigation production practice 

as opposed to just singling our SDI. The approach to managing a LEPA system is very similar to 

that for MESA or LESA systems for which farmers are already well acquainted. However, 

successful management of SDI systems require a significantly different understanding10 and 

management approach. This could be a limiting factor for combining SDI with LEPA into a single 

high-efficiency practice; however, in most applications it is believed that SDI and LEPA systems’ 

performance will be comparable for most insureds. In summary, there are already a broad range 

of irrigated production practice systems grouped together under a single classification (irrigated) 

in the insurance program; if SDI were segregated into its own irrigated practice, other high 

efficiency systems such as LEPA should be considered in that classification as well. 

10 In dry years, farmers must begin pre-watering 10 days or more in advance prior to planting to germinate the cotton seeds while 

they may have traditionally planted the crop and then watered the crop up in a matter of days given their ability to apply large 

amounts of water to the seed bed rapidly with center pivots. 

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RECOMMENDATIONS 

In conclusion, given the additional administrative burden required, coupled with the lack of broad 

producer support for segregation of the production practices, a separate production practice is 

not recommended to be established for SDI at this time. While a separate production practice 

is not recommended for SDI, RMA may want to consider offering a pilot written agreement 

program allowing interested producers to establish a separate yield for cotton produced with SDI 

and possibly extending that opportunity for LEPA as well. Both irrigation practices for cotton in 

the Texas High Plains have demonstrated the ability in some circumstances to produce higher 

yields in comparison to other types of irrigation systems. 

This task of this project focuses on the feasibility and evaluation of possible changes related to 

SDI and it did not direct the contractor to develop detailed policy provisions. However, if RMA 

decides to develop a pilot written agreement program for SDI on cotton, AgriLogic suggests the 

following elements be considered for the program: 

• A producer’s SDI actual cotton yield history would be the basis for establishing the 

relationship to the other irrigated yields for any new acreage on SDI. This feature could 

enable those desiring to transition acreage from less efficient irrigation practices to 

transfer their yield experience from the SDI acreage to the newly converted insurable unit 

(e.g. going from a MESA to an SDI system should demonstrate different yield 

expectations). 

• A written agreement would be required because there is not a separate production 

practice for SDI. The function of the written agreement would be to allow the insured to 

translate their SDI irrigated experience to other acreage as it is converted to the new 

system. 

• As determined by the RO the number of SDI records required (e.g. 2 years) of experience 

could be utilized to begin the translation of SDI experience to other acreage. 

• The SDI rate and approved yield would be used for input into the continuous rating 

methodology to determine the applicable premium rate. 

This pilot written agreement program would also enable RMA to capture valuable insurance 

experience for assessing future policy offerings in the area regarding the divergence of SDI 

premium rates from other irrigated production practices. 

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