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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Research Project #432342

Research Project: Improving the Sustainability of Irrigated Farming Systems in Semi-Arid Regions

Location: Water Management and Systems Research

2021 Annual Report

1. Improve water use efficiency (WUE) by identifying plant traits, mechanisms, and agronomic practices that increase productivity per unit of water used by the crop. 2. Develop simple and accurate methods to quantify evapotranspiration (ET) in agricultural systems under limited water availability to improve the efficiency of irrigation scheduling. 3. Create Water Production Functions (WPF, yield per ET) for alternative crops under limited water availability.

Increased productivity of cropping systems as well as yield stability is vital to meet the challenge of expanding human populations and increased needs for food and fiber. Effective management of cropping systems and irrigation water will depend on our ability to maximize crop water productivity (yield per unit water used by the crop). This, in turn, requires a better understanding and evaluation of complex plant traits, better management of interacting agricultural inputs, and better tools to more efficiently manage agricultural water supplies, especially in the face of greater competition and less water availability. Finally, there is increased efficiency at the farm scale that can be realized with better farm-scale decision making. The overarching goal of this research is to improve the sustainability of irrigated farming systems for agronomic producers in semi-arid and arid regions. These producers vary both in control over the timing and amount of irrigation, and in methods of irrigation; thus multi-faceted solutions are required. Solutions are in three parts: 1) increasing the knowledge base of plant traits, mechanisms and agronomic practices related to crop productivity under limited water; 2) developing tools to assist with real-time decision making for irrigation management; and 3) developing information and tools for farm-scale decision-making regarding crop selection, land area partitioning among crops, and within-farm irrigation distribution. This research will lead to better understanding of crop physiology needed to improve germplasm, increased productivity of cropping systems, and improved irrigation management.

Progress Report
Objective 1a. This objective seeks to identify plant traits and physiological mechanisms with potential for increasing maize productivity under water stress. Both sunflower greenhouse experiments were begun in June 2021 and will provide insight into: 1) the physiological trait networks in sunflower conferring improved performance under fully watered and limited water conditions, and 2) the internal plant pressures resulting in the loss of hydraulic conductance in sunflower as well as the timing and conditions required for recovery after loss of conductance. Measurements in the first experiment will begin on July 12 and measurements on the second experiment will begin on July 20. These two greenhouse experiments engage stakeholders from Colorado State University, the University of Colorado at Boulder, and the University of Georgia, and will replace the proposed maize greenhouse experiment (“Syngenta half-sibs”). This decision was made by ARS scientists, in consultation with stakeholders, to leverage a recent genome-wide association study towards identifying plant trait networks in sunflower. Both sorghum field experiments were planted on June 9. This experiment engages a 33-member stakeholder group from the United States, Australia, and France. These two experiments will provide data on the effectiveness of reduced stomatal conductance on growth and yield in sorghum and the physiological trait networks resulting in improved end-of-season growth. This experiment will also provide data on physiological mechanisms underpinning “reduced transpiration” and “stay green” traits. Objective 1b. We quantified the interactions between water and nitrogen in a field experiment with varying levels of nitrogen (applied in split applications) and water to determine soil plant-available nitrogen, effects on crop growth and productivity, and the physiological mechanisms underpinning interactions. Physiological measurements included leaf osmotic potential, cell membrane stability, photosynthesis, stomatal conductance, photosynthetic enzyme functioning, and stomatal closure point. Microbial inoculum with potential to increase maize functioning under limited water was tested in subplots of one treatment. Objective 2. Data collected in fiscal years 2017-2020 have shown promise for new techniques that use canopy temperature not only to indicate water stress but also to quantify reductions in water use while crops are under water stress. Although infrared temperature sensors and cameras are readily available, as are variable rate irrigation (VRI) systems, the decision support systems and related algorithms are a missing link. Our data suggest that, by obtaining canopy temperature and canopy cover paired with nearby micrometeorological stations, an estimate of crop water use (i.e. actual evapotranspiration) can be made, which can inform irrigation management decisions in real-time. By linking these techniques with our UAV systems, this concept is scalable to the field, where spatially variable data can inform VRI systems. In 2021 we have begun testing these techniques with a new VRI sprinkler system on our research farm. Objective 3. A consolidated water production function (WPF) dataset for five crops (corn, sorghum, sunflower, winter wheat, dry beans) spanning data collected across three research projects (2008-2020), was used to enhance the Unified Plant Growth Model (UPGM) module of the Agricultural Ecosystem Services (AgES) model. The enhanced model will be used to explore crop suitability and test management decisions related to cropping systems across limited-water regions of the High Plains. This modeling effort is in initial stages but has already resulted in improved representation of water-stress effects on crop phenology in AgES/UPGM, provided planting-date recommendations for sorghum studies, and offers an additional opportunity to advance the capacity of the AgES/UPGM model as a decision-making tool for cropping systems under limited-water availability.

1. Improved monitoring of spatially variable crop water stress with remote-sensing. Irrigated agriculture accounts for about half the total value of U.S. crops while occupying only 28% of U.S. harvested cropland. However, climate variability can result in management uncertainty, and the current historic drought in the Western U.S. only intensifies the need to effectively manage crops when full water allocations are not available. While many crops are currently managed uniformly within fields (e.g., same plant spacing, nutrient rates, and irrigation amounts), precision agriculture can optimize management across landscapes and on a spatial and temporal basis. However, many challenges to precision management remain such as understanding the meaning and nuance of the spatial and temporal variability and how this should influence management decisions. ARS scientists in Fort Collins, Colorado, in collaboration with Northern Colorado Water Conservancy District, Colorado State University, the University of Nebraska-Lincoln, and other USDA-ARS units in Fort Collins, Colorado, Bushland, Texas, and Maricopa, Arizona, demonstrated: a) how maize canopy temperature, which increases due to water stress, is related not only to crop water status but more closely to the interaction of water availability and soil characteristics; b) how a remotely-sensed soil salinity related vegetation index enhanced crop yield prediction for water stressed maize during reproductive and maturation stages; and c) how the integration of high-resolution thermal and Red-Green-Blue images taken by unmanned aerial systems provides accurate maps of maize canopy temperature spatial variability. This advancement lays the foundation for full integration of spatial data with decision support systems to create streamlined variable rate irrigation systems, which assist farmers in fully optimizing crop productivity with limited water supplies on large spatial scales not before realized.

2. Discovered potential long-term effects of water limitation on soil function. Water limits crop production in arid and semi-arid systems around the world but also impacts soil health through several interacting processes. While conserving water resources is critical, little was known about how deficit irrigation (a management strategy applying less than full irrigation) impacts crop roots and critical soil characteristics. ARS researchers in Fort Collins, Colorado, and Colorado State University assessed the impacts of soil water availability on corn root growth, soil carbon storage, and soil microbial communities across deficit irrigation treatments with different timing of water availability. When water was limited early in the season, root growth increased deeper in the soil profile and resulted in increased soil organic carbon stores deep in the soil profile. Cumulative years of deficit irrigation reduced microbial biomass, but, importantly, shifted microbial communities to more drought tolerant groups. Limited water availability early in the season had lasting effects, regardless of water availability during the rest of the season, indicating potential impacts beyond the relatively short timeframe during the season that treatments were in effect. This research shows that water availability affects crop root growth and distribution, carbon dynamics, and soil biological activity in critical ways that should be considered alongside potential water savings when setting irrigation management goals. This scientific advancement (with more than 790 citations) provides valuable considerations for policy formulation (e.g., Natural Resources Conservation Service Farm Bill programs) and management guidelines (e.g., State Extension programs and soil health non-governmental organizations).

Review Publications
Drobnitch, S.T., Comas, L.H., Flynn, N.E., Ibarra De Caballero, J., Barton, R.W., Wenz, J.A., Person, T., Bushey, J.A., Jahn, C.E., Gleason, S.M. 2021. Drought-induced root pressure in Sorghum bicolor. Frontiers in Plant Science. 12. Article e571072.
Liang, W., Qiao, X., Possignolo, I., Irmak, S., Heeren, D., Rudnick, D., DeJonge, K.C. 2021. Utilizing digital image processing and two-source energy balance model for the estimation of evapotranspiration of dry edible beans in western Nebraska. Irrigation Science. 39:617-631.
Zhang, H., Ma, L., Douglas-Mankin, K.R., Han, M., Trout, T.J. 2021. Modeling maize production under growth-stage based deficit irrigation management with RZQWM2. Agricultural Water Management. 248. Article e106767.
Zhang, J., Zhang, H., Sima, M.W., Trout, T.J., Malone, R.W., Wang, L. 2020. Simulated deficit irrigation and climate change effects on sunflower production in Eastern Colorado with CSM-CROPGRO-Sunflower in RZWQM2. Agricultural Water Management. 246. Article e106672.
Zhang, L., Zhang, H., Han, W., Niu, Y., Chávez, J.L., Ma, W. 2021. The mean value of gaussian distribution of excess green index: A new crop water stress indicator. Agricultural Water Management. 251. Article e106866.
Zhang, D., Wang, D., Zhang, H., Zhang, J., Liang, D., Gu, C. 2021. Fusion of deep convolution and shallow features to recognize the severity of wheat fusarium head blight. Frontiers in Plant Science. 11. Article e599886.
Flores, L., Bailey, R.T., Harmel, R.D. 2021. Using nutrient transport data to characterize and identify the presence of surface inlets in regions with subsurface drainage. Journal of Environmental Quality. 50(2):396-404.
Niu, Y., Zhang, H., Wenting, H., Zhang, L. 2021. A fixed-threshold method for estimating fractional vegetation cover of maize under different levels of water stress. Remote Sensing. 13(5). Article e1009.
Wagner, K.L., Gentry, T.J., Harmel, R.D., Pope, E.C., Redmon, L.A. 2021. Grazing effects on bovine-associated and background fecal indicator bacteria levels in edge-of-field runoff. Water. 13(7). Article e928.
Lambers, H., Wright, I.J., Pereria, C., Bellingham, P., Bentley, L.P., Cernusak, L.A., Foulds, W., Gleason, S.M., Gray, E.F., Hayes, P.E., Kooyman, R., Malhi, Y., Read, J., Richardson, S.J., Shane, M.W., Staudinger, C., Stock, W.D., Swarts, N.D., Turner, B.L., Turner, J., Wasaki, J., Westoby, M. 2020. Leaf manganese concentrations as a tool to assess belowground plant functioning in phosphorus-impoverished environments. Plant and Soil. 461:43-61.
Lo, T.H., Rudnick, D.R., DeJonge, K.C., Bai, G., Nakabuye, H.N., Katimbo, A., Ge, Y., Franz, T.E., Qiao, X., Heeren, D.M. 2020. Maize differences in soil moisture changes and canopy temperature under varying water × nitrogen treatments. Irrigation Science. 38:519-534.
Shao, G., Han, W., Zhang, H., Liu, S., Wang, Y., Zhang, L., Cui, X. 2021. Mapping maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices. Agricultural Water Management. 252. Article e106906.
Zadworny, M., Mucha, J., Jagodzinski, A.M., Koscielniak, P., Lakomy, P., Modrzejewski, M., Ufnalski, K., Zytkowiak, R., Comas, L.H., Rodríguez-Calcerrada, J. 2020. Seedling regeneration techniques affect root systems and the response of Quercus robur seedlings to water shortages. Forest Ecology and Management. 479. Article e118552.
Zhang, L., Han, W., Niu, Y., Chávez, J.L., Li, G., Sho, G., Zhang, H. 2021. Evaluating the sensitivity of water stressed maize chlorophyll and structure based on UAV derived vegetation indices. Computers and Electronics in Agriculture. 185. Article e106174.
Comas, L.H., Gleason, S.M., Drobnitch, S.T. 2020. Measuring root flow rate as a surrogate for root pressure. Acta Horticulturae. 1300:147-152.
Freschet, G.T., Roumet, C., Comas, L.H., Weemstra, M., Bengough, A., Rewald, B., Bardgett, R.D., De Deyn, G.B., Johnson, D., Klimešová, J., Lukac, M., McCormack, L.M., Meier, I.C., Pagès, L., Poorter, H., Prieto, I., Wurzburger, N., Zadworny, M., Bagniewska-Zadworna, A., Blancaflor, E.B., Brunner, I., Gessler, A., Hobbie, S.E., Iversen, C.M., Mommer, L., Picon-Cochard, C., Postma, J.A., Rose, L., Ryser, P., Scherer-Lorenzen, M., Soudzilovskaia, N.A., Sun, T., Valverde-Barrantes, O.J., Weigelt, A., York, L.M., Stokes, A. 2020. Root traits as drivers of plant and ecosystem functioning: Current understanding, pitfalls and future research needs. New Phytologist.
Gleason, S.M., Nalezny, L.A., Hunter, C., Comas, L.H., Bensen, R., Chintamanani, S. 2021. Growth and grain yield of eight maize hybrids are aligned with water transport, stomatal conductance, and photosynthesis in a semi-arid irrigated system. Physiologia Plantarum. 172(4):1941-1949.
Aritsara, A., Razakandrainibe, V.M., Ramananantoandro, T., Gleason, S.M., Cao, K. 2020. Increasing axial parenchyma fraction allowed for the improvement of hydraulic efficiency during the evolution of Malagasy Magnoliids. New Phytologist. 229(3):1467-1480.
Olson, M.E., Anfodillo, T., Gleason, S.M., McCulloh, K.A. 2020. Tip-to-base xylem conduit widening as an adaptation: Causes, consequences, and empirical priorities. New Phytologist. 229(4):1877-1893.
Zieminska, K., Rosa, E., Gleason, S.M., Holbrook, N.M. 2020. Wood day capacitance is related to water content, wood density, and anatomy across 30 temperate tree species. New Phytologist. 43(12):3048-3067.
Liu, H., Gleason, S.M., He, P., Ye, Q. 2020. Weak tradeoff between xylem hydraulic efficiency and safety: Climatic seasonality matters. New Phytologist. 229(3):1440-1452.
Ocheltree, T.W., Gleason, S.M., Jiang, G., Cao, K. 2020. Loss and recovery of leaf hydraulic conductance: Root pressure, embolism, and extra-xylary resistance. Journal of Plant Hydraulics. 7. Article e001.
Volaire, F., Gleason, S.M., Delzon, S. 2020. What do you mean “functional” in ecology? Patterns versus processes. Ecology and Evolution. 10(21):11875-11885.