Identifying Stacked Conservation Practices that Optimize Water Use in Agriculture: Phase II

Objective 1 - Identify combinations of six water conservation practices (irrigation system and rate, coupled with crop type, crop genetics, cover crops, and tillage) with the greatest ability to optimize crop production, crop profit, and water use.

The ongoing water optimization or stacking conservation practice trial was conducted at Cedar City, Logan, and Vernal, Utah during the 2022-2024 growing seasons. Due to an extension of the grant, we also conducted the trials in 2025. The treatments at each of the three sites include three replications of:

1. four irrigation systems [the conventional mid-elevation spray application (MESA) system vs. low-elevation spray application (LESA), low energy precision application (LEPA), and low-elevation Nelson advantage (LENA)];
2. four irrigation rates (50, 50, 75, and 100% of evapotranspiration). One of the 50% irrigation rates is a partial irrigation strategy focused on applying more water during critical crop growth stages; and
3. up to five crop management treatments depending on the crop:

• Corn has five treatments (conventional, drought-tolerant genetics, no-tillage, cover crops, and a fifth treatment that combines the latter three conservation practices)
• Alfalfa has two treatments (conventional vs. drought tolerant cultivar)
• Small grain forage has two treatments (tillage vs. no-tillage)
• Alternative crops (teff, sorghum-sudangrass, and forage rye) do not have crop treatments but are tested against other traditional crops

Major activities and findings:

The first major activity was to fully establish and maintain the three long-term irrigation sites near Logan, Vernal, and Cedar City Utah. It included removing MDI at the Vernal, UT site in 2022 and replacing it with LENA (based on cooperating farmer and stakeholder input and difficulty with filtration). Annual research activities included implementing 16-20 treatments at each site with a total of over 1500 individual plots.

A second major activity was to maintain a large soil moisture monitoring network at all three sites and use the data to calculate evapotranspiration (ET) of each treatment with a sensor installed. We used a soil moisture ET model (SMET) developed recently at Utah State University to estimate ET for plots with soil moisture sensors. The model requires daily soil moisture. Some of the soil moisture sensors were damaged by rodents or temporarily malfunctioned but we were able to collect data for several site-years for each crop. The objective of this effort was to compare the water use of various water optimization approaches. Results showed that the evapotranspiration (ETa) varied across crops, irrigation technologies, and years, with alfalfa generally exhibiting the highest ETa.

• In the alfalfa, small grain forage, and grain corn, low-elevation irrigation systems (LEPA, LENA®, LESA) resulted in greater ETa than MESA, likely due to reduced evaporative losses and wind drift. However, MESA performed better in silage corn with a higher ETa with an application of the same amount of irrigaiton.
• Deficit irrigation strategies did not reduce ETa, which might be due to overestimates of the ETc model or the SMET ETa or partial root-zone coverage with the installed sensor depth.
• Drought-tolerant genetics of alfalfa had a marginally greater ETa compared to conventional, while for corn and small grain forage, a reduced crop vigor under NT practice reduced the ETa compared to conventional practices.
• Alfalfa, SGF, and grain corn were the most water-productive crops under a low-elevation sprinkler system, while silage corn was under mid-elevation in terms of water productivity (WP).
• Deficit irrigation had mixed trends for WP but performed better most of the time compared to full irrigation.
• In general, DT genetics improved the WP in alfalfa, while conventional treatment performed better in small grain forage and corn compared to tillage and combined genetics, tillage, and cover crop treatment, respectively.

Figure 1. The effect of irrigation technologies: low-elevation Nelson Advantage^® (LENA), low-elevation precision application (LEPA), low-elevation spray application (LESA), and mid-elevation spray applicators (MESA) on actual evapotranspiration (ET_a) for different crops [alfalfa, corn grain at Cedar City (CC) and silage at Vernal (V), and small grain forage (SGF)]. Note: Volumetric water content data were missing from June 17^th to July 12^th for grain corn in LEPA in 2022 at CC, which led to variation in estimated ET_a.

Figure 2. Effect of irrigation levels (100% or 50% of ET_c) on actual evapotranspiration (ET_a) of alfalfa, corn, and small grain forage (SGF) at Cedar City (CC) and Vernal (V), UT during 2022-23.

Figure 3. Effect of crop genetics [conventional and drought-tolerant (DT)] of alfalfa, no-till (NT) of small grain forage (SGF), and the combined effect of NT, DT genetics, and cover cropping (CCr) of grain corn at Cedar City (CC) and silage corn at Vernal (V) on actual evapotranspiration (ET_a) during 2022-23.

A third major activity was to hire and train graduate students. Dakota Boren completed his Master’s degree in 2022, Tina Sullivan is finished her PhD in 2024, Kamal Deep completed his M.S. degree in 2025, and two additional students (Tejinder Singh – PhD and Shikha Swarma – MS) will complete their degrees in summer of 2026.

A fourth major activity included collecting yield, forage quality, and water use data from each of the >1,500 research plots in 2023-2025 and publishing and presenting the results. In addition, we collected data on existing and new alternative crops. In 2022-2025, we collected data for two existing alternative crops (teff, sorghum-sudangrass) and two new alternative crops (Italian ryegrass and forage rye) that were highly recommended by local producers and crop advisors.

The results of the alternative crops demonstrated that:

• Both irrigation level and irrigation technology can substantially influence the yield and nutritive value of alternative forage crops in semi-arid environments, though responses were highly crop and site-specific.
• For teff and sorghum-sudangrass, full and moderate deficit irrigation (≥75% of estimated ET), respectively, was generally required to maintain maximum biomass yield, particularly during early cuttings. However, 50% and 50% T irrigation level consistently enhanced forage nutritive value by increasing crude protein, fiber digestibility, and energy-related parameters while reducing structural fiber concentrations.
• Water productivity was generally enhanced under deficit irrigation, highlighting a trade-off between forage quantity and quality under water-limited conditions. Forage rye exhibited limited sensitivity to irrigation level, likely due to its cool-season growth habit and reliance on stored soil moisture though WP was maximum at 50% irrigation level.
• Irrigation technology effects were inconsistent across site-years; sprinkler-based systems tended to support greater yields, while MDI often improved forage quality but greatly reduced total biomass. No single irrigation technology consistently optimized both yield and quality across all crops and environments.

Overall, these findings highlight the importance of tailoring irrigation management to specific production goals. When water is a limiting resource, irrigation strategies should be guided by water productivity. Given the variability observed across sites and years, site-specific management and adaptive irrigation strategies will be essential for optimizing forage production under increasing water scarcity.

Figure 4. Effect of interaction between irrigation levels and cutting on dry matter (DM) yield of sorghum-sudangrass (SS) in 2022 and the effect of irrigation level in 2023 at a site near Vernal, UT, USA. The irrigation levels are full (100%), uniform reduction (75%, 50%) and 50% targeted reduction (50% T) of the estimated evapotranspiration. Different letters above bars represent statistically significant differences at α ≤ 0.05 for different irrigation levels within years. Error bars represent standard error (SE).

Figure 5. Effect of different irrigation technologies on total dry matter (DM) yield of teff in 2020 at a site near Vernal, UT, USA and the interaction effect of irrigation technologies and cutting on DM yield of teff in 2021 at a site near Cedar City, UT, USA. The technologies used included low-elevation precision application (LEPA), low-elevation sprinkler application (LESA), low-elevation Nelson Advantage (LENA), mobile drip irrigation (MDI), and mid-elevation sprinkler application (MESA). Different letters above bars represent statistically significant differences (at α ≤ 0.05) for different irrigation technologies within site-years. Error bars represent standard error (SE).

A fifth major activity was to summarize data on how longer-term no-tillage and cover crop use (4-6 years) influence crop production, quality, and soil health. The key takeaways from analysis suggest that:

• Growers in northern Utah can reduce irrigation by up to 50% without decreasing soil health, especially with NT and possibly CC in annual forage crops, such as silage corn and small grain forage.
• Alfalfa in moderate deficit (75%) not only maintains yield and improves forage quality but also consistently supports the strongest soil health indicators and infiltration capacity, making it the most resilient and reliable crop for water-limited systems.
• For silage corn, a uniform 75% irrigation strategy provides a safer balance between water savings, yield, and forage quality. But a 50% deficit showed reduced microbial activity and more variable infiltration responses.
• For growers in the southern part of Utah (Cedar City), water reduction may need to be limited to 25%, unless NT and CC are used to buffer the negative impacts of greater DI rates.

Figure 6. Effect of deficit irrigation on Soil Respiration CO2 C, (ppm C) during 2024 at Vernal (a), Wellsville (b), and Cedar City (c). Bars represent treatment means (±SE), and letters denote significant differences among treatments within each irrigation level, as determined by Tukey.

Figure 7. Effect of deficit irrigation on aggregate stability (%) during 2024 at Vernal, Wellsville, and Cedar City. Bars represent treatment means (±SE), and letters denote significant differences among treatments within each irrigation level, as determined by Tukey.

Figure 8. Effect of no-till, cover crop, and their interaction with drought-tolerant genetics in corn on ace protein (g/kg) during 2024 at Vernal, Wellsville, and Cedar City. Bars represent treatment means (±SE), and letters denote significant differences among treatments within each irrigation level, as determined by Tukey.

A sixth major activity was to evaluate the impacts of all treatments (irrigation technologies, deficit irrigation, cover crops, no-till, drought-tolerant genetics, and alternative crops) influence economic returns. It was a tremendous effort to compile all the economic data from all site-years included in this study from 2020-2025. We are in the process of summarizing this data across 2020-2025. A thesis chapter and manuscript are being developed and will be published in the summer of 2026.

Objective 2 - Demonstrate variable-rate irrigation systems that improve water and energy use efficiencies in long-term trials and on production farms.

Long-term zone VRI trials

 In Phase II of this project, variable irrigation research was conducted at five irrigated field locations in Utah or Idaho, totaling eight site-years and six different crops (Table 1). At two field locations, the study evaluated speed control VRI, at two other locations the study evaluated zone control VRI, and one site was a VRI pilot study that evaluated spatial variation within the field under uniform irrigation. At all field sites, soil water content and water potential sensors were installed in multiple locations within the fields.  

Table 1.  Variable rate irrigation studies conducted during the 2023-2025 growing season

We extended long-term trials to assess the impacts of zone VRI on potato (Tuberosum solanum) production, creating a unique and powerful dataset not previously studied and demonstrating a strong potential application of VRI. In Phase I of this project, we conducted a comparison of uniform irrigation vs. VRI at the field location near Grace, Idaho, to determine how zone VRI impacts crop yield, quality, profit, and water use. This is especially meaningful as a long-term study site because of the long-crop rotation commonly used for potato production. At the Grace, Idaho site, potato is grown every third year, with winter wheat grown the other two years in the crop rotation. With our long-term study, we now have potato data in 2018, 2021, and 2024. In each of these years, the potato study was conducted at field scale in a 22-ha field irrigated with a state of the art, zone-control VRI system. The primary objective was to examine water use and potato response to sensor-based VRI (Figure 9). Five irrigation zones were delineated from historical yield and evapotranspiration (ET) data (Figure 10). Soil sensors were placed at multiple depths within each zone to give real time data of the VWC values within each soil profile. For each irrigation event, irrigation rates were determined by comparing current soil volumetric water content to zone-specific soil field capacity values. Two control strips were created throughout each zone and irrigated based on the grower standard practice (GSP) for statistical comparisons.

Figure 9.  Team members installing soil sensors at the beginning of the 2024 Grace, Idaho potato research trial in Grace, Idaho (left) and collecting potato yield samples at the end of the trial (right).

Figure 10.  Potato yield and evapotranspiration (ET) data from the long-term study (2018) were mapped and used to create five variable rate irrigation (VRI) zones and uniform irrigation control strips for the 2021 and 2024 study years.

Cumulative irrigation rates varied among zones and years (Figure 11). In 2021, when averaged over zones, irrigation was significantly less for VRI compared to the control in 2021 and was similar on average in 2024. In both years, water applied in sensor-based VRI was less than the control strips in lower topographic areas of the field (zones 1 and 2). Historically, these areas have been excessively wet, resulting in diseased potatoes. Sensor-based VRI allowed for much better control of soil water throughout the field and a notable absence of diseased potatoes. In 2024, sensor-based VRI resulted in prescriptions for slightly higher irrigation in high yielding zones (zones 4 and 5). This illustrates the potential for VRI to reallocate water within a field from areas that previously were too wet to areas where the soil and crop can respond to increased water application. As such, even in 2024 when average water use was the same for VRI and control, the water use efficiency was much better. We analyzed total, marketable, and US. No.1 potato yield to evaluate the effects of VRI. The VRI procedure maintained or increased total, marketable and U.S. No. 1 yields (Figure 11). VRI increased tuber count, which resulted in a decreased of tuber size in some zones (data not shown). Overall, the data clearly documents the potential for VRI to benefit growers by improving yields, optimizing water usage, and reducing the negative affects of potato diseases in waterlogged areas of the field.

Figure 11.  Left plot: Growing season cumulative irrigation for variable rate irrigation zones 1-5 compared to control strips with uniform irrigation rates for potato research at the Grace, Idaho location in 2021 and 2024. Right plot: The differences in potato total, marketable, and US No.1 yields between variable rate irrigation and control strips in 2024, by zone 1-5. Yield values for bars marked with * (p<0.10) or ** (P<.05) were significantly different than the yield for the growers standard practice control strips.

On Farm Trials of Speed Control VRI

While zone-control VRI systems offer the highest potential for precision water application, few growers have center-pivot sprinklers with zone control capabilities. Speed control VRI, limited to wedge-shaped zones created by changing the travel speed of center-pivot irrigation system, are less flexible, but have higher adoptability because this approach to VRI can be implemented on nearly all existing center-pivot sprinklers. In Phase 2 of our long-germ research project, we added on-farm studies to evaluate sensor-based, speed control applications.

Enterprise, UT Site.  As an example research layout for one of the field locations, speed-control VRI was evaluated at the Enterprise, UT site (Figure 12).  At this site, the full, 120 ac pivot field was subdivided into four quadrants (SW, 40 ac; NW, 40 ac; NE, 20 ac; SE, 20 ac), with spatial variation of soil texture being the key factor delineating the quadrants on the west and east sides.  The soil textural classes were sandy loams on the west side quadrants (SW, NW) and silty or silty clay loams on the east side quadrants (NE, SE).  The quadrants were assigned an irrigation treatment as either speed control VRI or a growers standard irrigation practice treatment as a control. Irrigation rates and timings for the standard irrigation practices were done as the normal practice by the farm cooperator.  For the speed control VRI treatments, irrigation timing matched the standard irrigation practice, but rates were determined from the soil moisture sensors.  The procedure for determining irrigation rates was first to determine site-specific soil water thresholds (volumetric water content at field capacity) for each VRI zone, then to compare volumetric water content measured with sensors at three depths with the thresholds and to calculate the irrigation rates needed for each VRI zone to bring the soil to the threshold. 

Figure 12.  Experimental layout for speed control variable rate irrigation (VRI) study of alfalfa at the Enterprise, Utah location in 2023. The field was divided into four quadrants by soil texture class and by VRI or standard irrigation practice.

In 2023, the field had an established stand of alfalfa. There were a total of 38 irrigation events during 2023 and there were four alfalfa harvests. Total amounts of irrigation applied for each quadrant varied by harvest interval and between the standard irrigation and speed control VRI treatments (Table 2). On average, the speed-control VRI practice resulted in more than a 10-inch reduction in applied irrigation compared to the standard irrigation practice.  Despite the differences in applied irrigation, there were no differences observed in alfalfa yield (Table 3).

Table 2.  Rates of irrigation applied to alfalfa by irrigation treatment in 2023 at the Enterprise, Utah research location.  Applied irrigation is shown by harvest interval or prior to greenup (Jan 01-Mar 31) or after the final harvest in 2023 (Sept 21-Dec 31).

Table 3.  Alfalfa yield by irrigation treatment and harvest period in 2023 at the Enterprise, Utah research location. 

The same field in Enterprise, UT was planed to corn silage in 2024 and the same study design was used to compare VRI to the growers standard practice.  While the VRI prescriptions for alfalfa in 2023 resulted in significant differences in the amount of applied irrigation, this was not observed for corn silage in 2024.  Two main factors help explain this: 1) much of the irrigation water savings for alfalfa happened early in the growing season (March-June), whereas corn silage isn’t planted until mid to late May and its greatest water use occurs later in the summer, and 2) the growing season precipitation was much less in 2024 than in 2023.  This result illustrates that using sensor-based VRI does not guarantee water savings. It does, however, allow for informed irrigation scheduling and also provides a detailed record of the soil water conditions experienced by a crop, which can be helpful in documenting growing conditions and explaining yield observations.

Elberta, UT Site.   As another example research layout, speed-control VRI was evaluated at the Elberta Research site (Figure 13).  At this site, the full, 120 ac pivot field was subdivided into four quadrants (N, 30 ac; E 30 ac; S, 30 ac; W, 30 ac), with spatial variation of elevation and mapped soil series being the key factor delineating the quadrants.  The soil textural class was loam for all four quadrants. The quadrants were assigned an irrigation treatment as either speed control VRI or a growers standard irrigation practice treatment as a control. Irrigation rates and timings for the standard irrigation practices were done as the normal practice by the farm cooperator.  For the speed control VRI treatments, irrigation timing matched the standard irrigation practice, but rates were determined from the soil moisture sensors.  The procedure for determining irrigation rates was first to determine site-specific soil water thresholds (volumetric water content at field capacity) for each VRI zone, then to compare volumetric water content measured with sensors at three depths with the thresholds and to calculate the irrigation rates needed for each VRI zone to bring the soil to the threshold. 

Figure 13. Experimental layout for speed control variable rate irrigation (VRI) study of winter wheat at the Elberta, Utah location in 2023 and 2005. The field was divided into four quadrants based on mapped soil type and by VRI or standard irrigation practice.

There were a total of 12 irrigation events during 2023 and 17 in 2025. Total amounts of irrigation applied varied between the growers standard irrigation and speed control VRI treatments (Table 4). On average, the speed-control VRI practice resulted in 2.1-inch reduction in applied irrigation compared to the standard irrigation practice. In both years, grain yield was greater for the VRI treatment than for the GSP (Table 3). Achieving consistently greater yield with lower irrigation rates is a very key result showing that using sensors and VRI permits modification of commonly used irrigation practices to both save water and improve productivity. Evaluation of the soil water dynamics during the growing season (Figure 14) shows potential reasons for this. Soil water content for the standard irrigation practice regulary exceeded the soil field capacity, leading to water movement deeper in the soil, which likely also leached nutrients from the soil. Conversely, soil water for the VRI treatment stayed within the plant available water zone and showed very little downward movement of water. 

Table 4. Number of irrigation events, average depth of even irrigation, total irrigation, and grain yield for variable rate irrigation (VRI) and the grower’s standard practice (GSP) treatments. Rates of irrigation applied to winter wheat by irrigation treatment in 2023 and 2025 at the Elberta, Utah research location.

Figure 14. Soil water dynamics over the 2025 winter wheat growing season at the Elberta, UT study location.  The upper figure (east quadrant) shows results of the growers standard irrigation practice, while the lower figure (north quadrant) shows results of the variable rate irrigation treatment (VRI). The yellow bands are the site-specific plant available water zones. Each plot shows soil water dynamics for a shallow sensor (6 inches) and a deep sensor (18 inches).