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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

2021 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
Significant progress was made towards project’s milestones despite challenges from the dry weather during the fall of 2020 and winter of 2020-2021. Rains in May 2021 enabled the establishment of summer crops on both irrigated and dryland experiments. Progress towards the milestones and products associated with the Objective 1 depend on a crop being grown on the large weighing lysimeter fields. Cotton was planted onto those four fields and additional instruments deployed. Measurements regarding soil evaporation and evapotranspiration (ET) were collected. Data analysis continued regarding estimates of ET from eddy covariance for comparisons to those measured by the large weighing lysimeters. Images from unnamed aerial systems (UAS) equipped with a variety of sensors were captured at various times during the growing season at several heights above the field as to compare several post image analyses processes for estimating ET at various scales from a few square meters to 20 ha fields. Image processing of images collected by the UAS from previous growing seasons were analyzed also. Several experiments contributed towards progress of Sub-objective 2.1. Data comparing crop water use efficiency were collected from the large weighing lysimeter fields where fields are irrigated by either sprinklers or sub-surface drip irrigation. Crop responses to sprinkler irrigation were also compared to low energy precision application (LEPA) and mobile drip irrigation (MDI). Comparison between LEPA and MDI were expanded to include the precision irrigation of vegetable crops because of funding of a grant from the Irrigation Innovation Consortium at Colorado State University. Tomatoes had to be re-planted due to herbicide drift from adjacent fields. Improvements to the irrigation scheduling system (ISSCADA) were tested using cotton again. This year’s test confirmed that data from both canopy leaf thermal and soil moisture data improved the ability of the ISSCADA to schedule irrigation applications. A set of experiments extending the ISSCADA system to irrigation scheduling of potatoes was conducted this year. The potato experiments were conducted in collaboration with Texas A&M AgriLife Research and were supported by funds from Ogallala Aquifer Program, Texas Department of Agriculture and Binational Agricultural Research and Development (BARD) Fund. Persistent dry weather from October 2020 to May 2021 will add to the location’s database of weather conditions that affect grain yields of winter wheat. These results are important aspect of research related to Sub-objective 3.2. An experiment allocating limited irrigation water resources between cotton and corn was started during the summer of 2021. Experiments conducted under the auspices of the Ogallala Aquifer Program on irrigation management of cotton were started in Texas and Kansas. This effort has a field investigation and modeling effort. The model team have met to discuss strategies to use newly acquired field data for crop growth model calibration. Current models tend to significantly underestimate cotton lint yields in area where the accumulation of growing degree days is considered minimal for lint production.

1. ARS patented control system delivers precise irrigation applications. Irrigated crop production in the Texas High Plains is of major importance because irrigated crops produce grain yields that are typically two or three times greater than rainfed production. However, water resources are limited in this region. Site-specific variable rate irrigation (VRI) systems are moving sprinklers that use plant and soil water sensing feedback for irrigation management to improve crop yield per unit of water applied. ARS scientists at Bushland, Texas, have patented an Irrigation Supervisory Control and Data Acquisition (ISSCADA) System that uses a software application, ARSPivot, that builds watering maps based on sensor information and controls the VRI sprinkler hardware. Results from a two-year study showed that corn yields and water use efficiency from plots managed with the ISSCADA system were similar to those resulting from irrigation scheduling using a gold standard for determining crop water needs. The irrigation control system was adapted to irrigate potatoes with similar outcomes as with corn. Finally, trials in four states which demonstrated improved yield and crop water productivity compared favorably with farmer average outcomes. The success of this irrigation scheduling technology in more humid areas is more likely when crop water stress is followed by the Crop Water Stress Index rather than the Time Temperature Threshold method. Using the ARSPivot software and ISSCADA system with any type of center pivot sprinkler can help producers all across the United States to save time and improve yields per unit of water applied.

2. More water right now may be better when it comes to the volume of an irrigation application. Corn production in much of the southern Great Plains relies on irrigation from the Ogallala Aquifer to supplement inadequate precipitation. Decades of pumping with minimal recharge has resulted in declining water tables and reduced well capacities in much of the region. Prudent irrigation scheduling remains an effective tool for maximizing crop water productivity, particularly under deficit irrigation. Although many studies have addressed the effects of irrigation timing and duration of water deficit on corn growth and yield, few have studied the effects of irrigation depth and frequency. Recent results from a crop modeling study by researchers from USDA ARS in Bushland, Texas, and Texas A&M AgriLife indicated in general that increased irrigation application depth reduced seasonal irrigation requirements for all crops. Therefore, researchers from the same two organizations compared yield and crop water productivity between high frequency, low irrigation volume and low frequency, high irrigation volume management in the field. Results indicated there was no obvious reduction in evaporative losses associated with the less frequent, greater application under field conditions. Full crop canopy limited excessive evaporation when frequent low volume applications were made. These results suggest when possible that irrigators should make irrigation applications to greater soil depths.

3. Scheduling subsurface drip irrigation using evapotranspiration data and crop coefficients saves water and energy. Fresh water supply for irrigation is decreasing. One solution to decreasing supply is to increase the productivity of irrigation water use through newer irrigation delivery systems, including subsurface drip irrigation (SDI). There are more than 430,000 acres of SDI on the Texas High Plains. However, best management practices for SDI are still under development. USDA ARS scientists at Bushland, Texas, have developed methods of accurately scheduling sprinkler irrigation of corn, cotton and other crops using crop coefficients and estimates of potential evapotranspiration. However, these methods have not been applied for scheduling SDI. Accurate crop coefficients for SDI were thus needed for efficient irrigation scheduling. The Bushland researchers measured corn water use for two years, comparing it between SDI and sprinkler irrigation. Results showed that crop coefficients for SDI were 10% smaller than those previously developed for sprinkler irrigation. The use of new crop coefficients for SDI will decrease irrigation applications’ using SDI, thus saving water and reducing associated energy costs.

4. Additional support that no-till and contour farming promote dryland crop production. Precipitation is the only water source for increasingly important dryland crops in the Texas High Plains, and runoff decreases both stored soil water and crop yields. ARS scientists from Bushland, Texas, quantified storm water runoff and precipitation storage as soil water under field conditions using conservation practices of either no-tillage (NT) or contour farming. Increased yields of wheat and sorghum grown in a three-year wheat-sorghum-fallow (WSF) rotation were achieved with NT as compared to stubble-mulch (SM) tillage over a 26-year period. By reducing evaporation during fallow, NT had greater soil water and grain sorghum yield than SM. Greater landscape slope increased fallow runoff, but soil water and dryland crop yields were not significantly affected with contour farming. These results will help farmers and crop consultants improve semiarid dryland cropping practices by decreasing evaporation and soil erosion with NT residues.

5. Wetting front detectors save irrigation water when used with furrow irrigation. Furrow irrigation is still used on the Southern Great Plains and typically has an irrigation efficiency of less than 60% (only 60% of water applied can be used by the crop) compared with greater than 90% efficiency of other application methods. However, there are some fields and situations in which furrow irrigation is the only practical method. Efforts to improve furrow irrigation efficiency have met with limited success. Scientists in Uzbekistan and USDA ARS in Bushland, Texas, studied devices called wetting front detectors (WFDs) to see if they could reduce runoff and deep percolation while increasing the crop productivity per unit of water applied. In all three years of a study with cotton, runoff, deep percolation, and volume of irrigation water applied were less when WFDs were used. Both total seed-lint cotton yield and the yield per unit of water applied were increased with the use of WFD. Adoption of this technology should greatly improve irrigation efficiency where furrow irrigation is being used.

6. Better tools for using time domain resonance (TDR) type soil moisture sensors for irrigation scheduling. Irrigation management for efficient use of scarce water resources can be greatly aided by use of accurate soil water sensors. USDA ARS scientists at Bushland, Texas, developed accurate, low-cost TDR soil moisture sensors, in cooperation with a commercial partner who now provides them to agricultural producers, equipment suppliers, and irrigation equipment manufacturers. The scientists have written a guide to the best methods of using these sensors and similar TDR sensors for use in agricultural and environmental management, easing the way towards more widespread use of sensors to save water.

7. Modern drought tolerant corn varieties use less water because they grow faster. Producers in the semiarid Texas High Plains rely on groundwater from the declining Ogallala Aquifer for irrigation to supplement inadequate precipitation for corn production. The use of daily reference evapotranspiration and crop coefficient (Kc) values are commonly used in irrigation scheduling to maximize crop water productivity. However, questions about the applicability of Kcs derived from legacy corn hybrids to modern drought tolerant (DT) hybrids have been raised. Researchers from USDA ARS in Bushland, Texas, and Texas A&M University compared lysimeter-derived Kcs from legacy and modern DT corn hybrids. Although maximum daily Kc values were similar for all hybrids, the average season length of the DT hybrid was 25 days shorter than that of the legacy hybrids. Farmers and crop consultants that use evapotranspiration data to schedule irrigation need to be aware of changes in growth characteristics of modern DT corn hybrids so that they can better match applications with crop needs and reduce pumping costs and water use.

Review Publications
Marek, G.W., Marek, T.H., Evett, S.R., Chen, Y., Heflin, K., Moorhead, J.E., Brauer, D.K. 2021. Irrigation management effects on crop water productivity for maize production in the Texas High Plains. Water Conservation Science and Engineering. 6:37-43.
Marek, G.W., Marek, T.H., Evett, S.R., Bell, J.M., Colaizzi, P.D., Brauer, D.K., Howell, T.A. 2020. Comparison of lysimeter-derived crop coefficients for legacy and modern drought-tolerant maize hybrids in the Texas High Plains. Transactions of the ASABE. 63(5):1243-1257.
Andrade, M.A., O'Shaughnessy, S.A., Evett, S.R. 2020. ARSPivot, a sensor-based decision support software for variable-rate irrigation center pivot systems: Part A. Development. Transactions of the ASABE. 63(5):1521-1533.
Baumhardt, R.L., Haag, L., Gowda, P.H., Schwartz, R.C., Marek, G.W., Lamm, F.R. 2021. Modeling cotton growth and yield response to irrigation practices for thermally limited growing seasons in Kansas. Transactions of the ASABE. 64(1):1-12.
Evett, S.R., O'Shaughnessy, S.A., Andrade, M.A., Colaizzi, P.D., Schwartz, R.C., Schomberg, H.H., Stone, K.C., Vories, E.D., Sui, R. 2020. Theory and development of a VRI decision support system: The USDA-ARS ISSCADA approach. Transactions of the ASABE. 63(5):1507-1519.
Andrade, M.A., O'Shaughnessy, S.A., Evett, S.R. 2020. ARSPivot, a sensor-based decision support software for variable-rate irrigation center pivot systems: Part B. Application. Transactions of the ASABE. 63(5):1535-1547.
Hashem, A.A., Engel, B.A., Marek, G.W., Moorhead, J.E., Flanagan, D.C., Rashad, M., Radwan, S., Bralts, V.F., Gowda, P.H. 2020. Evaluation of SWAT soil water estimation accuracy using data from Indiana, Colorado, and Texas. Transactions of the ASABE. 63(6):1827-1843.
Evett, S.R., Marek, G.W., Colaizzi, P.D., Brauer, D.K., Howell, Sr., T.A. 2020. Are crop coefficients for SDI different from those for sprinkler irrigation application? Transactions of the ASABE. 63(5):1233-1242.
O'Shaughnessy, S.A., Andrade, M.A., Colaizzi, P.D., Workneh, F., Rush, C., Evett, S.R., Kim, M. 2020. Irrigation management of potatoes using sensor feedback: Texas High Plains. Transactions of the ASABE. 63(5):1259-1276.
Strohmeier, S.M., Fukai, S., Haddad, M., Ainsour, M., Mudabber, M., Akimoto, K., Yamamoto, S., Evett, S.R., Oweis, T. 2020. Rehabilitation of degraded rangelands in Jordan: The effects of mechanized micro water harvesting on hill-slope scale soil water and vegetation dynamics. Journal of Arid Environments. 185. Article 104338.
Evett, S.R., Or, D., Schwartz, R.C. 2020. 4.3.2 Time Domain Reflectometry (TDR). In: Montzka, C., Cosh, M., Nickeson, J., Camacho, F., editors. Good Practices for Satellite Derived Land Product Validation, Land Product Validation Subgroup (WGCV/CEOS), National Aeronautics and Space Administration, Goddard Space Flight Center. Greenbelt, MD: NASA. p. 68-73.
Taghvaeian, S., Andales, A.A., Allen, N.L., Kisekka, I., O'Shaughnessy, S.A., Porter, D.O., Sui, R., Irmak, S., Fulton, A., Aguilar, J. 2020. Irrigation scheduling for agriculture in the United States: The progress made and the path forward. Transactions of the ASABE. 63(5):1603-1618.
Baumhardt, R.L., Johnson, G.L., Dockal, J.R., Brauer, D.K., Schwartz, R.C., Jones, O.R. 2020. Precipitation, runoff, and yields from terraced drylands with stubble-mulch or no tillage. Agronomy Journal. 112(5):3295-3305.
Ibragimov, N., Avliyakulov, M., Durdiev, N., Evett, S.R., Gopporov, F., Yakhyoeva, N. 2020. Cotton irrigation scheduling improvements using wetting front detectors in Uzbekistan. Agricultural Water Management. 244. Article 106538.
Baumhardt, R.L., Dockal, J.R., Johnson, G.L., Brauer, D.K., Schwartz, R.C. 2020. Controlling stormwater runoff that limits water availability and dryland crop productivity. Frontiers in Sustainable Food Systems. 4. Article 533687.
Kutikoff, S., Lin, X., Evett, S.R., Gowda, P.H., Brauer, D.K., Moorhead, J., Marek, G.W., Colaizzi, P.D., Aiken, R., Xu, L., Owensby, C. 2021. Water vapor density and turbulent fluxes from three generations of infrared gas analyzers. Atmospheric Measurement Techniques. 14:1253-1266.
Hashem, A.A., Engel, B.A., Bralts, V.F., Marek, G.W., Moorhead, J.E., Radwan, S., Gowda, P.H. 2020. Assessment of Landsat-based evapotranspiration using weighing lysimeters in the Texas High Plains. Agronomy. 10(11). Article 1688.
Chen, Y., Marek, G.W., Marek, T.H., Porter, D., Brauer, D.K., Srinivasan, R. 2020. Simulating the effects of agricultural production practices on water conservation and crop yields using an improved SWAT model in the Texas High Plains, USA. Agricultural Water Management. 244. Article 106574.
Dhungel, R., Aiken, R., Evett, S.R., Colaizzi, P.D., Marek, G., Moorhead, J.E., Baumhardt, R.L., Brauer, D.K., Kutikoff, S., Lin, X. 2020. Energy imbalance and evapotranspiration hysteresis under an advective environment: Evidence from lysimeter, eddy covariance, and energy balance modeling. Geophysical Research Letters. 48(1). Article e2020GL091203.
Marek, G.W., Evett, S.R., Colaizzi, P.D., Brauer, D.K. 2021. Preliminary crop coefficients for late planted short-season soybean: Texas High Plains. Agrosystems, Geosciences & Environment. 4(2). Article e20177.
Marek, T.H., Porter, D.O., Howell, T.A., Marek, G.W., Brauer, D.K. 2020. The impact and value of accurate evapotranspiration networks in Texas High Plains production agriculture. Applied Engineering in Agriculture. 36(4):451-455.
Chen, Y., Marek, G.W., Marek, T.H., Porter, D.O., Moorhead, J.E., Heflin, K., Brauer, D.K., Srinivasan, R. 2020. Watershed scale evaluation of an improved SWAT auto-irrigation function. Journal of Environmental Modeling and Software. 131. Article 104789.
Rho, H., Colaizzi, P.D., Gray, J., Paetzold, L., Xue, Q., Patil, B., Rush, C.M. 2020. Yields, fruit quality, and water use in a Jalapeno pepper and tomatoes under open field and high-tunnel production systems in the Texas High Plains. HortScience. 55(10):1632-1641.
Lena, B.P., Ortiz, B.V., Jimenez-Lopez, A.F., Sanz-Saez, A.K., O'Shaughnessy, S.A., Durstock, M.K., Pate, G. 2020. Evaluation of infrared canopy temperature data in relation to soil water-based irrigation scheduling in a humid subtropical climate. Transactions of the ASABE. 63(5):1217-1231.