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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Research Project #432324

Research Project: Precipitation and Irrigation Management to Optimize Profits from Crop Production

Location: Soil and Water Management Research

2019 Annual Report

Objective 1: Develop improved methods and sensor systems for determining crop water use and stress, and integrate these into systems for water management. Sub-objective 1.1: Improve understanding of soil water status and sensing. Sub-objective 1.2: Improve determinations of evapotranspiration (ET). Sub-objective 1.3: Improve water management decisions at multiple scales by incorporating a better understanding of ET into hydrological models. Objective 2: Develop irrigation and sensor technologies, and best management practices for different irrigation application systems and technologies. Sub-objective 2.1: Compare crop water use efficiency (WUE) and partitioning of water use between evaporation (E) and transpiration (T) between subsurface drip (SDI) and sprinkler irrigation systems. Sub-objective 2.2: Develop sensors and algorithms to improve decision support for an irrigation scheduling supervisory control and data acquisition (ISSCADA) system to spatially optimize crop yields and WUE. Sub-objective 2.3: Develop irrigation application strategies that vary water application temporally for improved cotton lint yields. Objective 3: Develop and determine best management practices to maximize WUE, and long-term profitability using multi-year rotations of different crops and cropping practices, including both dryland and intermittent irrigation practices. Sub-objective 3.1: Determine if long-term weather predictions can be used to optimize irrigation strategies for increased WUE and yield. Sub-objective 3.2. Determine the effects of different conservation tillage practices on precipitation capture and harvest in relation to crop rotation phase. Sub-objective 3.3: Evaluate crop yield response to varying levels of deficit irrigation and water stress under differing management (Genetics x Environment x Management, G x E x M).

The Ogallala Aquifer region of the U.S. is one of the primary crop production areas in the country, in part because it overlays one of the country’s largest fresh water aquifers. But water availability from the aquifer has decreased significantly since the beginning of wide-spread irrigation in the 1950s, with the greatest impact on the Southern and Central High Plains of western Kansas and Texas. Responding to this will require both more efficient water use by irrigation and increased productivity with lower risk from dryland farming. Cropping practices such as rotation with fallow period for soil water recharge and irrigation practices that avoid evaporation address many of the unique needs of the Central and Southern Great Plains. However the need remains for more efficient water use in these semi-arid regions. Therefore this project will research three areas. First, a better understanding of soil water movement and evaporation, and evapotranspiration. Second, sensors that monitor soil water and crop water stress will be developed to effectively and efficiently use the remaining groundwater for irrigated crop production. Finally, the project will develop best management practices for using water more efficiently under dryland and marginal irrigation regimes. These results will enable the region to remain a competitive area for crop production, sustain farm based communities, and maintain the strength of American agriculture in world markets. Research will be conducted in laboratory and field situations from scales of small plots to regions where crop related data is extracted from remotely sensed images. New plant and soil water stresses will be developed in the laboratory, and once refined, field tested. Data will be integrated into prescriptions for dynamic site specific irrigation scheduling that account for well capacities. These will be tested under field conditions. Understanding of methods to measure evapotranspiration, like eddy covariance, COSMOS, etc., will be enhanced by comparing values from large weighing lysimeters and accurate water balance derived from neutron probe measurements for the soil profile. Measurements from microlysimeters and soil heat flux plates will be used in the field to provide better separation of measures of evaporation and transpiration components of evapotranspiration. A better understanding of evapotranspiration will be used to guide the development of best management practices for crop production and those practices will be tested under field conditions. Data will be used to refine existing hydrologic models, including AcrSWAT, Aquacrop, etc. Data bases of crop water use will be developed and made available to other scientists. This research project also leads the Ogallala Aquifer Program, a research-education consortium addressing solutions arising from decreasing water availability from the Ogallala Aquifer in western Kansa and the Texas High Plains. The consortium includes the ARS NP211 projects at Bushland and Lubbock, Texas, Kansas State University, Texas A&M AgriLife Research and Extension Service, Texas Tech University and West Texas A&M University.

Progress Report
Research on the project continues to progress as per the approved project plan. Significant progress was made towards every objective and sub-objective as exemplified by attainment of 15 of 16 milestones in the project's research plan. The four large weighing lysimeters continued to be one of the most utilized resource of the research unit. Alfalfa had been proposed in the approved project plan as the subject of investigation for the large weighing lysimeters in FY2018 and FY2019. However, alfalfa was replaced with soybeans in FY2019 because weather conditions prevented planting of alfalfa. Row crops, including corn and soybeans, allow for better estimates of soil evaporation; especially early in the growing season when the crop is smaller, and its management is of more interest to stakeholders. Instrumentation and data collection related to Objectives 1 and 2 involved the large weighing lysimeters facility in FY2019. Irrigation scheduling by Time Domain Reflectometry (TDR) soil moisture was one avenue of investigation for the large weighing lysimeter fields in FY2019 (Sub-objective 2.2). Data collection regarding water sensing by the Cosmic-ray Soil Moisture Observing System (COSMOS) continued in FY2019 and data from COSMOS were compared to soil moisture measurements by the large weighing lysimeters, and neutron and TDR probes (Sub-objective 1.2). Large weighing lysimeters are expensive to install and maintain. Other accurate means for measuring crop evapotranspiration (ET) are needed. ET measurements by laser scintillometers and eddy covariance systems are being compared to data from the large weighing lysimeters (Sub-objective 1.2). These methods still lack the accuracy that large weighing lysimeters provide. A relatively new series of investigations to use imagery from unmanned aerial systems (UAV) to estimate ET continued in FY2019 (Sub-objectives 1.2 and 1.3). Data from the large weighing lysimeters are invaluable for validating and calibrating other measurements of ET including remotely sensed images. Irrigation scheduling based on crop canopy temperatures by stationary infrared thermometers (IRT) and soil moisture values by either neutron probe or time domain resonance (TDR) sensors continued for a third year using the large weighing lysimeters fields (Sub-objective 2.2). Because two of the four large weighing lysimeter fields were irrigated by subsurface drip and the other two were by sprinkler, the data collected from these fields in FY2019 compared the effects of irrigation method on soil evaporation and other components of ET (Sub-objective 2.1). Research into advanced irrigation scheduling and automation continued using 3- and 6-span center pivot irrigation systems. Under the 3-span irrigation system, ET measurements from two-source energy balance model combined with data on soil moisture values from either neutron or TDR probes were used to guide irrigation applications and compared to irrigations scheduled by manual calculations of changes in soil moisture from neutron probe measurements (Sub-objective 2.2). Under the 6-span center pivot irrigation system growing sorghum, the use of computer visual device and Irrigation Scheduling Supervisory Control and Data Acquisition (ISSCADA) system using feedback from plant and soil measurements were tested and compared to manual scheduling of irrigation application using changes in soil moisture by neutron probe readings (Sub-objective 2.2). Under these center pivots, irrigation scheduling using either plant or plant and soil data were compared to scheduling using soil moisture measurements from neutron probes (Sub-objective 2.2). The unit's unique Soil-Plant-Environment Research facility was used for a new experiment in FY2019 as part of the Ogallala Aquifer Program in a cooperative study with Texas A&M and Kansas State Universities in which the effects of irrigation frequency and soil type were assessed on corn yields (Sub-objectives 3.3). This facility included smaller lysimeters of four soil types common to the Southern Great Plains and a rainout shelter for precise control of soil water content. The data from field experiments, especially those related to ET from the large weighing lysimeters, are an exceptional resource in the development and refinement of hydrological models (Sub-objective 1.3). Cooperative research with commercial partners continued under two different Cooperative Research and Development Agreements in FY2019. Project scientists cooperated with numerous researchers in the United States and other countries. Research results in FY2019 generated 23 published journal articles, of which 17 had Bushland scientists as the senior ARS author. Significant technology transfer activities included: 1) Winter wheat field day in May 2019; 2) Smart suburban water use in April 2019.

1. Subsurface drip irrigation saved six inches of irrigation when watering corn. In the face of declining water supplies, it is important for economic sustainability to maximize the yield per unit of water used in crop production, the so-called crop water productivity or CWP. It is not well understood how irrigation application method affects the CWP. Increasing CWP in the face of limited water supplies is a key objective in irrigation and agronomic research because it directly affects profitability, water sustainability and intensification of agricultural production. The irrigation application method can have an effect on CWP that is as large as or even larger than the effects of irrigation scheduling. ARS scientists at Bushland, Texas, compared the water use and yield of grain corn and sorghum grown using sprinkler and subsurface drip irrigation (SDI) methods. Using the SDI application method, loss of water to evaporation from plant and soil surfaces was reduced by two to more than five inches compared to the loss suffered with sprinkler irrigation. Using SDI reduced overall corn water use by up to six inches while increasing yields by up to 20% compared with sprinkler irrigation. Although the SDI system is more expensive to install than are sprinkler irrigation systems, the benefits of SDI are convincing in the dry climate of the Southern High Plains. Using SDI can result in long-term gains in profitability and sustainability of irrigated grain production.

2. Response of dryland grain sorghum to no-till varied with locations in Texas and Kansas. As water availability for irrigation from the Ogallala Aquifer decreases, producers are growing crops on more dryland acres. The yield and profitability of dryland farming is heavily dependent on the fraction of rainfall that is used by the crop. Tillage can influence rainfall capture by the soil, however no-till has shown mixed results across the U.S. Great Plains in improving sorghum grain yield compared with reduced or conventional tillage. ARS scientists from Bushland, Texas, and researchers from Kansas State University evaluated the amount of rainfall that infiltrated the soil as well as that lost to evaporation and drainage during phases of a winter wheat-sorghum-fallow rotation under no-till and reduced tillage. The study was carried out at Bushland, Texas, and at Tribune, Kansas, two locations with very different soils. Deep drainage comprised only a small proportion of available water lost to the cropping system. Evaporation during summer fallow periods was not reduced under no-till at both locations. At the Bushland location, tillage did not significantly influence infiltration, soil water available to crops, and long-term sorghum yield. At the Tribune location, cumulative rainfall infiltration was 60% greater under no-till compared with reduced tillage and increased water available to sorghum during the growing season, thus explaining the long-term 35% sorghum yield advantage compared with reduced tillage. The study demonstrates that no-till does not perform similarly across all environments in increasing effective rainfall that is available to crops. Both farmers and crop consultants need to use tillage regimes that are tailored to their soils and local conditions rather than using generalizations.

3. Uniformity of irrigation applications affects the profitability of corn. Optimized scheduling of irrigation for crops can reduce water and energy use and increase profit. However, the uniformity of the applied irrigation across the field can reduce the success of improved scheduling. The effect of a marginally acceptable irrigation uniformity on corn yields and profitability was studied by ARS scientists at Bushland, and researchers from Texas, and Centro Regional de Estudios de Agua (CREA) University of Castilla-La Mancha, Albacete, Spain. In a field where the crop received more irrigation than required, grain yields were maximized. When irrigation was scheduled to match crop requirements, grain yields were reduced by 8%. Although optimal scheduling met crop water requirements on an area-averaged basis, parts of the field received less than what the crop required because of marginal uniformity. Farmers and crop consultant need to ensure that irrigation application is uniform to get the most out of irrigation scheduling practices.

4. Commercially available soil moisture sensor can be used to schedule irrigation applications. The amount of freshwater available for irrigation is decreasing worldwide, and, therefore, application of irrigation water needs to be more efficient if crop yields are to be maintained. The use of soil water sensors is commonly thought to aid irrigation management in crop production systems. However, limited studies explore how sensor type, installation technique, sensor orientation, and soil texture affect sensor accuracy. ARS researchers from Bushland, Texas, along with scientists from Texas A&M University compared soil water measurements from four commercially available sensors installed at three depths and orientations with co-located neutron probe moisture meter (NMM) readings. Results from paired comparisons indicated that sight-specific sensor calibrations were required for accurate estimation of soil water content for the clay loam soil. However, soil profile water content values integrated from one sensor compared well with values integrated using NMM readings. These results suggest that some factory calibrated sensors may be useful for irrigation scheduling, if installed properly. Farmers and crop consultants that are trying to optimize irrigation applications may benefit from the data from these soil moisture sensors.

5. Alternatives to corn for water limited areas. Decreased irrigation well capacities due to declining groundwater levels in the Ogallala Aquifer will eventually limit the production of corn in the Northern High Plains of Texas, one of the region’s most profitable crops. Alternatively, less water intensive crops may conserve groundwater while allowing producers to remain profitable. Therefore, scientists from ARS in Bushland, Texas, and Texas A&M AgriLife Research and Extension Service used the hydrologic model Soil and Water Assessment Tool (SWAT), equipped with a newly developed irrigation program to simulate water use associated with alternative crops including soybean, sunflower and grain sorghum. Results indicated irrigation amounts were reduced by 19, 21, and 32% respectively, as compared to corn. These results are of interest to farmers, crop consultants and regional water policy makers to identify crops other than corn that can be used under conditions of limited groundwater availability.

6. Hydrologic model SWAT modified to simulate management allowed depletion of soil water. Water scarcity due to drought and groundwater depletion has led to an increased emphasis on irrigation strategies for extending limited water resources. The Soil and Water Assessment Tool (SWAT), a widely used hydrologic model, is increasingly being used to evaluate the impacts of irrigation strategies. However, deficiencies in default auto-irrigate functions in SWAT resulted in the development and localized testing of an alternative algorithm based on the management allowed depletion (MAD) of soil water. Therefore, ARS scientists from Bushland, Texas, along with researchers from Texas A&M AgriLife further evaluated the MAD algorithm by comparing simulated irrigation, crop water use, plant growth, and yield to measure values for corn grown at multiple research sites across the Southern Great Plains. Results indicated that the alternative MAD function outperformed the default auto-irrigation algorithms in SWAT. SWAT has become widely used as a tool for water planning and water policy makers. Prior to this accomplishment, however, SWAT did not simulate irrigation of crops in a means that mimic real-world situation. Therefore, inclusion of this new code will greatly increase the applicability of the model to areas where irrigation occurs.

7. New model developed to estimate corn water use. Predicting crop water use is important for conserving water and managing irrigation, and maximizing farm profits. Corn is profitable but has a high water requirement. Water use by corn can be predicted by models; however, these models are not always accurate and can be too complex for use by farmers and crop consultants. Therefore, ARS scientists from Bushland, Texas, and Kansas State University researchers tested a new crop water use model that was designed to achieve accuracy across different locations without being overly complex. The model accurately predicted the water use by corn for an entire growing season in Bushland, Texas. The model did not require calibration for the windy conditions of Texas. Therefore, the new model will help farmers conserve water and increase farm profits by ensuring that corn is not over-irrigated.

8. Improvements in the use of remotely sensed images to estimate crop water use. As irrigation water available from the Ogallala Aquifer decreases, farmers need to better match irrigation applications to water needs of the crop. Maps of crop water use across large agricultural regions are useful for drought detection and prediction, and management of water resources. Maps of crop water use can be produced by combining satellite images and weather data. The satellite images usually have large pixels, from 100 m to 1 km. The weather data are obtained continuously from weather stations which are located as discrete spots. The spaces between the weather station points can be filled using models so that weather data can have the same locations as the satellite pixels to produce the crop water use maps. However, filling the spaces between the weather stations causes loss of accuracy. Therefore, ARS scientists at Bushland, Texas, and Kansas State University researchers developed and tested a new method to improve the accuracy of crop water use maps. The improved accuracy will provide earlier detection of crop water stress, and will improve farm profitability by better matching crop water use with irrigation applications.

9. Drought tolerant corn yields better with low irrigation. The Texas High Plains is a major corn producing region, but drought and diminishing availability of irrigation water threaten to reduce production. Drought resistant corn varieties and different seeding rates may be tools that farmers can use to continue to produce corn in the region. Two different experiments confirmed that drought tolerant corn yields better at less than optimal irrigation levels. In one study, ARS scientists from Bushland, Texas, along with researchers from Texas A&M AgriLife Research, the University of Arizona, a commodity group, and a commercial seed company, compared a new drought tolerant variety to a conventional corn variety. In a second set of experiments, ARS scientists at Bushland, Texas, and researchers from Texas A&M AgriLife Research tested two drought tolerant maize varieties under three irrigation rates and three planting densities at Etter, Texas. At low irrigation rates, the drought tolerant variety produced greater grain compared with the conventional variety. Grain yield increased slightly with higher planting densities, but this may not offset the greater cost in seed. These data will provide maize farmers with management guidelines for maximizing farm profits while conserving water.

10. Recent expansion of Texas High Plains dairy simulates regional agricultural economy. The dairy industry in the Texas High Plains has experienced rapid expansion in the past two decades. ARS researchers at Bushland, Texas, assessed the impact of the increased presence of dairies on overall water use, crop composition, and the local economy. The increase in water use related to the dairy industry from 2000 to 2015 was primarily due to an increase in demand for drinking by the cows (direct water) as well as an increased demand for silage (indirect water). However, a comparative analysis (dairy presence vs. no dairy presence) from a single year indicates minimal impacts on total water use due to dairies. During the same time period, the number, size, and employment of related local business establishments have increased economic activity in rural areas. These results demonstrated that the establishment of a high value product relative to water use can stimulate a regional agricultural economy while having little impact on groundwater withdrawals.

11. Winter wheat rotations provide maximum soil water at planting for summer crops. As the availability of irrigation water from the Ogallala Aquifer decreases, it is likely that the area being managed for dryland crop production will increase. Dryland crop rotation systems are sustainable only if there is sufficient water available for profitable crop production. However, crop rotations that promote sustainable production have not been determined. The objective of this study by scientists from Kansas State University in the ARS-led Ogallala Aquifer Program was to identify potential crop rotation systems for the central Great Plains from 2000 through 2017 using four summer crops [corn, grain sorghum, soybean, and sunflower] and winter wheat in 1-, 2-, 3-, and 4-year rotations. Results showed that available soil water at planting of the summer crop was greatest in rotations in which winter wheat was immediately prior, probably due to the longer fallow period to store rainfall. These results are of interest to farmers and crop consultants in establishing rotations appropriate for dryland crop production on the Southern High Plains.

Review Publications
Nascimento, A., Schwartz, R.C., Lima, F., Lopez-Mata, E., Dominguez, A., Izquiel, A., Tarjuelo, J., Martinez-Romero, A. 2018. Effects of irrigation uniformity on yield response and production economics of maize in a semiarid zone. Agricultural Water Management. 211(2019):178-189.
Chen, Y., Marek, G.W., Marek, T.H., Xue, Q., Brauer, D.K., Srinivasan, R. 2018. Assessing SWAT plant stress algorithms using full and deficit irrigation treatments. Agronomy Journal.
Chen, Y., Marek, G.W., Marek, T.H., Gowda, P.H., Xue, Q., Moorhead, J.E., Brauer, D.K., Srinivasan, R., Heflin, K.R. 2019. Multisite evaluation of an improved SWAT irrigation scheduling algorithm for corn (Zea mays L.) production in the U.S. Southern Great Plains. Journal of Environmental Modeling and Software. 118:23-24.
Moorhead, J.E. 2019. Field scale estimation of evapotranspiration. In: Bucur, D., editor. Advanced Evapotranspiration Methods and Applications. London, United Kingdom: IntechOpen Limited. p. 1-19.
Kutikoff, S., Lin, X., Evett, S.R., Gowda, P.H., Moorhead, J.E., Marek, G.W., Colaizzi, P.D., Aiken, R., Brauer, D.K. 2018. Heat storage and its effect on the surface energy balance closure under advective conditions. Agricultural and Forest Meteorology. 265:56-69.
Evett, S.R., Marek, G.W., Copeland, K.S., Colaizzi, P.D. 2018. Quality management for research weather data: USDA-ARS, Bushland, Texas. Agrosystems, Geosciences & Environment. 1:180036.
Schwartz, R.C., Schlegel, A., Bell, J.M., Baumhardt, R.L., Evett, S.R. 2019. Contrasting tillage effects on stored soil water, infiltration and evapotranspiration fluxes in a dryland rotation at two locations. Soil and Tillage Research. 190:157-174.
Moorhead, J.E., Marek, G.W., Gowda, P.H., Lin, X., Colaizzi, P.D., Evett, S.R., Kutikoff, S. 2019. Evaluation of evapotranspiration from eddy covariance using large weighing lysimeters. Agronomy. 9(2):99.
Hao, B., Xue, Q., Marek, T.H., Jessup, K.E., Becker, J., Hou, X., Xu, W., Bynum, E., Bean, B.W., Colaizzi, P.D., Howell, T.A. 2018. Grain yield, evapotranspiration, and water use efficiency of maize hybrids differing in drought tolerance. Irrigation Science.
Zhao, J., Xue, Q., Hao, B., Marek, T.H., Jessup, K.E., Xu, W., Bean, B.W., Colaizzi, P.D. 2019. Yield determination of maize hybrids under limited irrigation. Journal of Crop Improvement. 33(3):410-427.
Chen, Y., Marek, G.W., Marek, T.H., Moorhead, J.E., Heflin, K.R., Brauer, D.K., Gowda, P.H., Srinivasan, R. 2018. Assessment of alternative agricultural land use options for extending the availability of the Ogallala Aquifer in the Northern High Plains of Texas. Hydrology. 5(4):53.
Marek, G.W., Colaizzi, P.D., Evett, S.R., Moorhead, J.E., Brauer, D.K., Ruthardt, B.B. 2019. Design, fabrication, and operation of an in-situ microlysimeter for estimating soil water evaporation. Applied Engineering in Agriculture. 35(3): 301-309.
Chen, Y., Marek, G.W., Marek, T.H., Moorhead, J.E., Heflin, K.R., Brauer, D.K., Gowda, P.H., Srinivasan, R. 2019. Simulating the impact of climate change on hydrology and crop production in the Northern High Plains of Texas using an improved SWAT model. Agricultural Water Management. 221:13-24.
Zhang, H., Malone, R.W., Ma, L., Ahuja, L.R., Anapalli, S.S., Marek, G.W., Gowda, P.H., Evett, S.R., Howell, T.A. 2018. Modeling evapotranspiration and crop growth of irrigated and non-irrigated corn in the Texas high plains using RZWQM. Transactions of the ASABE. 61(5):1653-1666.
Colaizzi, P.D., Oshaughnessy, S.A., Evett, S.R. 2018. Calibration and tests of commercial wireless infrared thermometers. Applied Engineering in Agriculture. 34(4):647-658.
Evett, S.R., Stone, K.C., Schwartz, R.C., O'Shaughnessy, S.A., Colaizzi, P.D., Anderson, S.K., Anderson, D.J. 2019. Resolving discrepancies between laboratory-determined field capacity values and field water content observations: Implications for irrigation management. Irrigation Science. 37:751-759.
Bordovsky, J.P. 2019. Low-energy precision application (LEPA) irrigation: A forty-year review. Transactions of the ASABE.
Zhang, T., Mahmood, R., Lin, X., Pielke Sr., R.A. 2019. Irrigation impacts on minimum and maximum surface moist enthalpy in the Central Great Plains of the USA. Weather and Climate Extremes. 23:100197.
Andales, A.A., Straw, D., Marek, T.H., Simmons, L.H., Bartolo, M.E., Ley, T.W. 2018. Design and construction of a precision weighing lysimeter in Southeast Colorado. Transactions of the ASABE. 61(2):509-521.
Zambreski, Z.T., Lin, X., Aiken, R.M., Kluitenberg, G.J., Pielke, Sr., R.A. 2018. Identification of hydroclimate subregions for seasonal drought monitoring in the U.S. Great Plains. Journal of Hydrology. 567:370-381.
Schlegel, A.J., Assefa, Y., Haag, L.A., Thompson, C.R., Stone, L.R. 2018. Yield and overall productivity under long-term wheat-based crop rotations: 2000 through 2016. Agronomy Journal. 111(1):264-274.
Moorhead, J.E., Marek, G.W., Colaizzi, P.D., Gowda, P.H., Evett, S.R., Marek, T.H., Porter, D.O., Brauer, D.K. 2019. Evaluation of sensible heat flux and evapotranspiration using a surface layer scintillometer and a large weighing lysimeter. In: Lakshmi M., editor. Top 5 Contributions in Sensor and Biosensor Technology. 3rd Edition. Hyderabad, India: Avid Science. p. 1-40.