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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

2022 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
This project ended on January 26, 2022. A new research project that was subjected to scientific review earlier in fiscal year (FY) 2022 was started on January 26, 2022. The new research project, 3090-13000-016-000D, is entitled “Dryland and Irrigated Crop Management Under Limited Water Availability and Drought". The new project represents an evolution of the research that had been conducted under this research project. Please see the annual report for research project 3090-13000-016-000D for FY 2022 accomplishments. The following accomplishments from the completed research project are those that are most likely to have the greatest impact: Precise irrigation scheduling through the use of infrared thermometers (IRT) and two-source energy balance (EB) model. Crop water (CW) stress can be detected by IRT; thus, these sensors have the potential to precisely schedule irrigation. However, the data from the IRT need to be interpreted/transformed via a soil water (SW) or EB model to create functional prescriptions or maps for irrigation applications. This research utilized a two-source EB model developed during research project 3090-13000-014-00D (2011 to 2016). IRT aboard moving center pivot (CP) were found to be effective tools for detecting CW stress and the two-source EB model was found to accurately calculate evapotranspiration of the crop (ETc). This approach has application to all 22 million ha of irrigated crops in the U.S. These results were instrumental in the development of the next accomplishment. Development and transfer of the irrigation scheduling supervisory control and data acquisition (ISSCADA) system for variable rate irrigation (VRI) technology. Research and development by project scientists and commercial partners led to the development of wireless soil water sensing systems and new soil water sensors, wireless plant sensing system and patenting of the ISSCADA. Two U.S. companies are manufacturing and selling the wireless plant sensing and soil water sensing systems. This accomplishment has been recognized by several national awards from federal agencies and industry trade associations. Successful irrigation scheduling depends on understanding how roots are distributed in the soil prolife. With decreasing well capacities on the Southern High Plains, it is vital that irrigation be scheduled to better match targeted yields with irrigation water supply. Scheduling irrigation based on managed allowed depletion fails in deep soils because it neglects how nonuniform distribution of roots interacts with profile SW. Incorporating a nonuniform root distribution into a CW use model can improve predictions of ETc and SW root extraction deeper in the profile. These studies demonstrate that it is crucial to better understand crop stress response functions to water deficit to optimize CW productivity under limited irrigation. Development of a management allowed depletion (MAD) auto-irrigation algorithm for the Soil and Water Assessment Tool (SWAT) model. 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 were identified and led to the development of an alternative algorithm based on the management allowed depletion (MAD) of SW. Results indicated that the alternative MAD function outperformed the default auto-irrigation algorithms in SWAT. Therefore, inclusion of this new code will greatly increase the applicability of the model to areas where irrigation occurs. No-till (NT) promotes higher sorghum grain yields in a dryland wheat-sorghum-fallow rotation. NT residue management improved sorghum grain yield nearly 20% and soil conservation by one third compared with conventional stubble mulch tillage. Yield increases were largely attributed to reduced evaporation with NT residue management. These results indicate that farmers on the Southern High Plains should adopt NT for their dryland crop production.


Review Publications
Chen, Y., Marek, G.W., Marek, T.H., Porter, D.O., Brauer, D.K., Srinivasan, R. 2021. Modeling climate change impacts on blue, green, and grey water footprints and crop yields in the Texas High Plains, USA. Agricultural and Forest Meteorology. 310. Article 108649.
Bagnall, D.K., Morgan, C.L., Cope, M., Bean, G.M., Cappellazzi, S.B., Greub, K.L., Liptzin, D., Baumhardt, R.L., Dell, C.J., Derner, J.D., Ducey, T.F., Dungan, R.S., Fortuna, A., Kautz, M.A., Kitchen, N.R., Leytem, A.B., Liebig, M.A., Moore Jr, P.A., Osborne, S.L., Sainju, U.M., Sherrod, L.A., Watts, D.B., Ashworth, A.J., Owens, P.R., et al. 2022. Carbon-sensitive pedotransfer functions for plant-available water. Soil Science Society of America Journal. 86(3):612-629.
Fan, Y., Himanshu, S.K., Ale, S., Delaune, P.B., Zhang, T., Park, S.C., Colaizzi, P.D., Evett, S.R., Baumhardt, R.L. 2021. The synergy between water conservation and economic profitability of adopting alternative irrigation systems for cotton production in the Texas High Plains. Agricultural Water Management. 262. Article 107386.
Evett, S.R., Thompson, A.I., Schomberg, H.H., Andrade, M.A., Anderson, J. 2021. Solar node and gateway wireless system functions in record breaking polar vortex outbreak of February 2021. Agrosystems, Geosciences & Environment. 4(4). Article e20193.
O'Shaughnessy, S.A., Rho, H., Colaizzi, P.D., Workneh, F., Rush, C.M. 2022. Impact of zebra chip disease and irrigation levels on potato production. Agricultural Water Management. 269. Article 107647.
Lellis, B.C., Martinez-Romero, A., Schwartz, R.C., Pardo, J.J., Tarjuelo, J.M., Dominguez, A. 2021. Effect of the optimized regulated deficit irrigation methodology on water use in garlic. Agricultural Water Management. 260. Article 107280.
Schwartz, R.C., Bell, J.M., Colaizzi, P.D., Baumhardt, R.L., Hiltbrunner, B.A. 2022. Response of maize hybrids under limited irrigation capacities: Crop water use. Agronomy Journal. 114:1324-1337.
Schwartz, R.C., Bell, J., Baumhardt, R.L., Colaizzi, P.D., Hiltbrunner, B.A., Witt, T.W., Brauer, D.K. 2022. Response of maize hybrids under limited irrigation capacities: yield and yield components. Agronomy Journal. 114:1338-1352.
Dominguez, A., Schwartz, R.C., Pardo, J.J., Guerrero, B., Bell, J.M., Colaizzi, P.D., Baumhardt, R.L. 2021. Center pivot irrigation capacity effects on maize yield and profitability in the Texas High Plains. Agricultural Water Management. 261. Article 107335.
Evett, S.R. 2022. Soil water sensing by neutron scattering. In: Mahendran, N., Bentahar, N., editors. Reference Module in Earth Systems and Environmental Sciences. Encyclopedia of Soils in the Environment. 2nd edition. Online:Elsevier.
O'Shaughnessy, S.A., Kim, M., Lee, S., Kim, Y., Shekailo, J.P. 2021. Towards smart farming solutions in the U.S. and South Korea: A comparison of the current status. Journal of Geography and Sustainability. 2(4):312-327.