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

Location: Water Management and Systems Research

2022 Annual Report

Objectives
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.

Approach
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
This is the final report for this project. Objective 1 sought to improve water use efficiency (WUE) by identifying plant traits, mechanisms, and agronomic practices that increase productivity per unit of water used by the crop. Over the entire five-year period of the project, significant progress was achieved towards this objective. Trait networks were identified that are aligned with higher productivity under water limited and non-limited conditions in maize, sorghum, and winter wheat. Key coordinated traits include higher maximal stomatal conductance, higher xylem-specific conductivity in stems and leaves, coordinated root growth, and nighttime root pressure. We also found that root pressure was actively regulated in sorghum and was greatly increased during short-term drought treatments. Using genotypes from the maize nested association mapping population, key xylem anatomical traits linked with xylem-specific conductivity (vessel diameter and density) were identified, measured, and mapped. A new method using carbon nanoparticles was developed to quantify pit membrane pore diameter (xylem inter-vessel connections), widely thought to be an important determinant of drought tolerance in vascular plants. Large multi-year field-scale experiments in maize lead to meaningful progress towards identifying important effects of deficit irrigation on soil nitrogen, microbial community composition, and the physiological mechanisms aligned with these effects. Specifically, we found that deficit irrigation promoted greater maize root growth, and, although microbial biomass was reduced, shifted microbial communities to more drought tolerant bacteria. This shift in microbial community structure has the potential to impact soil organic carbon and nitrogen mineralization beyond the relatively short time water limitation was applied. Data collected in fiscal year 2019, combined with previous years, were used to build and improve physiologically-based plant growth models – the Terrestrial Regional Ecosystem Exchange Simulator (TREES), and the SurEau model. These models were then used to identify the key coordinated processes (i.e., trait networks) that underpinned desired agronomic outcomes, e.g., higher productivity, higher water use efficiency, higher soil water extraction. This work with process-based plant growth models has forged valuable collaborations between the ARS, France’s National Research Institute for Agriculture Food and Environment (INRAe), the University of Tasmania, the University of Buffalo, Macquarie University, the University of Queensland, and other international institutions. Objective 2 sought to develop simple and accurate methods to quantify evapotranspiration (ET) in agricultural systems under limited water availability to improve the efficiency of irrigation scheduling. Much progress has been achieved towards this objective over the lifetime of the project. We successfully developed multispectral imagery methods to quantify canopy cover and crop water use across eight maize hybrid lines. Key to this method’s success was our ability to collect and analyze imagery within 24 hours of irrigation decisions. We also made significant progress towards the detection of crop stress using thermal imagery (from unmanned aerial vehicles) and stationary infrared thermometers (IRT). This was accomplished through accurate measurement of canopy temperature, i.e., leaf temperature is expected to be higher during the downregulation of stomatal conductance (stress) and reduced plant transpiration. Furthermore, methods for the calculation of crop evaporation (ET) were successfully developed using thermal imagery and vegetation indices derived from multispectral imagery. Taken together, canopy cover, canopy temperature, and remote sensing imaging and data were used to estimate ET and evaluate four irrigation control methods – one using a traditional soil water balance approach, and three using canopy temperature-based crop water stress indices. We were able to successfully evaluate the efficacy of each of these methods for scheduling full and deficit irrigation. We found that methods based on canopy temperature were not only capable of accurately indicating water stress, but also quantified water use (ET) while the crops were experiencing water stress. Combining these two advantages of temperature-based methods (simultaneous measurement of stress and water use) with data from nearby micrometeorological stations, allowed for real-time irrigation management decisions. Importantly, measurement of plant stress and crop water use (actual ET) using remotely sensed data provides both temporal and spatial information, and therefore, represent important progress towards the improvement of variable rate irrigation systems (VRI). Objective 3 sought to create Water Production Functions (WPF, yield per ET) for alternative crops under limited water availability. Over the five-year period of the project, significant progress was achieved towards this objective. A consolidated water production function 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 is being used to explore crop suitability and test management decisions related to cropping systems across limited-water regions of the High Plains. This modeling effort has resulted in improved representation of water-stress effects on crop phenology in AgES/UPGM, provided planting-date recommendations for sorghum studies, and represents an opportunity to advance the capacity of the AgES/UPGM model as a decision-making tool for cropping systems under limited-water availability.

Accomplishments
1. Developed global-level understanding of crop drought response traits. Through the application of field, greenhouse, and laboratory experiments, ARS scientists in Fort Collins, Colorado, identified key drought response mechanisms (physiological and structural “traits”) in maize, sorghum, and sunflower. This research, conducted in close collaboration with scientists in the United States, France, Australia, India, Mexico, and China, has meaningfully improved our scientific understanding of drought physiology (specifically water-carbon exchange processes), plant growth modeling (during drought), and soil-plant interactions. These traits and their connections represent uniquely coordinated networks that confer improved performance either when water is limiting or when it is non-limiting. These identified trait networks are a blueprint for geneticists and breeders on how whole plants (i.e., not single traits in isolation) could be manipulated to improve performance in contrasting environments. These important advances have produced high-impact publications, numerous invitations to high-profile national and international scientific meetings, and invitations to present research findings at prestigious universities and private labs (e.g., Harvard University). These important contributions, as part of a long-term international effort to improve dryland and irrigated crop production, represent potentially revolutionary advances in crop science and plant breeding.

2. Improved mapping of spatially variable crop water stress and water use with remote sensing. Agricultural water supplies in arid and semi-arid regions in the U.S. are experiencing uncertainty and limitations due to climate variability and extreme drought, wildfires, interstate compacts/agreements, declining aquifers, and water delivery restrictions. These water limitations intensify the need to manage irrigation on an optimized spatial and temporal basis, instead of traditional uniform irrigation practices. While both spatial data and variable-rate irrigation systems exist, there is a large knowledge gap preventing farmers from effectively using the data and technology. ARS scientists in Fort Collins, Colorado, successfully used unmanned aerial vehicle (UAV)-based remote sensing technology to map the spatial variability of crop growth and water stress at a farm scale. The UAV-based remote sensing techniques coupled with multiple imagery sources provide accurate maps of crop water use, representing an important integration of remote sensing and variable-rate irrigation technologies to support the irrigation industry. New remote sensing data and technologies were also harnessed to address farmers’ concerns regarding managing irrigation in response to within-field soil variability. ARS scientists in Fort Collins, Colorado, in collaboration with other ARS units, and universities in the U.S. and China, demonstrated that maize canopy temperature is not only related to crop water stress but more closely to the interaction of water availability and soil characteristics. Also, a remotely sensed soil salinity-related vegetation index and canopy temperature-based stress index enhanced crop yield prediction for water-stressed maize during reproductive and maturation stages. This work bridges the gap between data collection and irrigation decisions with limited water at scales not previously realized. Such technology will be valuable to irrigation system manufacturers, agronomists, and farmers with the need to optimize crop production with limited water.

3. Economic impacts of strategic deficit irrigation on maize grain yield. Globally, almost half (40%) of agricultural production comes from irrigated lands with demands on water availability increasing and many farmers facing limited water for irrigation. There is urgent need to find solutions to avoid global food shortages. ARS scientists in Fort Collins, Colorado, reduced crop water use by 15-17% and maintained yield by applying moderate shortfalls during the crop late-vegetative stage (prior to flowering) followed by near full irrigation for the remainder of the growing season. Furthermore, late-vegetative irrigation shortfalls protected crops from dramatic yield losses in response to late-season water shortfalls, compared to crops that were fully irrigated through much of the season but were water limited at season end. In collaboration with agricultural economists at Colorado State University, we also identified the price of water needed for producers to benefit from intentionally applying less irrigation. Water lease prices in the range identified are beginning to be found in regions with high demands on water. This research provides a cost-effective water management strategy for irrigated maize production in water limited regions. It identified the critical need for late season irrigation for optimal regional management of limited irrigation water; and economic thresholds for policies to balance agricultural and municipal water interests for water conservation districts and policy makers.

4. Discovered potential long-term effects of water limitation on soil function. Water limits crop production in arid and semi-arid regions around the world but also degrades soil health through several interacting processes. While conserving water resources is critical, little was known about how shortfalls in irrigation impacted crop roots and critical soil characteristics. ARS researchers in Fort Collins, Colorado, along with collaborators at 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. 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 highly-cited scientific advancement 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
Costa-Filho, E., Chávez, J.L., Zhang, H., Andales, A.A. 2021. An optimized surface aerodynamic temperature approach to estimate maize sensible heat flux and evapotranspiration. Agricultural and Forest Meteorology. 311. Article e108683. https://doi.org/10.1016/j.agrformet.2021.108683.
Zhang, L., Zhang, H., Han, W., Niu, Y., Chávez, J.L., Ma, W. 2022. Effects of image spatial resolution and statistical scale on water stress estimation performance of MGDEXG: A new crop water stress indicator derived from RGB images. Agricultural Water Management. 264. Article e107506. https://doi.org/10.1016/j.agwat.2022.107506.
Strand, E.J., Bihar, E., Gleason, S.M., Han, S., Schreiber, S.W., Renny, M.N., Malliaras, G.G., McLeod, R.R., Whiting, G.L. 2021. Printed organic electrochemical transistors for detecting nutrients in whole plant sap. Science and Technology of Advanced Materials. 8(4). Article e2100853. https://doi.org/10.1002/aelm.202100853.
Veettil, A.V., Mishra, A.K., Green, T.R. 2022. Explaining water security indicators using hydrologic and agricultural systems models. Journal of Hydrology. 607. Article e127463. https://doi.org/10.1016/j.jhydrol.2022.127463.
Flynn, N.E., Stewart, C.E., Comas, L.H., Del Grosso, S.J., Schnarr, C., Schipanski, M., Von Fischer, J.C., Stuchiner, E.R., Fonte, S.J. 2022. Deficit irrigation impacts on greenhouse gas emissions under drip-fertigated maize in the Great Plains of Colorado. Journal of Environmental Quality. 51(5):877-889. https://doi.org/10.1002/jeq2.20353.
Katimbo, A., Rudnick, D.R., DeJonge, K.C., Lo, T.H., Qiao, X., Franz, T., Nakabuye, H.N., Duan, J. 2022. Crop water stress index computation approaches and their sensitivity to soil water dynamics. Agricultural Water Management. 266. Article e107575. https://doi.org/10.1016/j.agwat.2022.107575.
Flynn, N.E., Comas, L.H., Stewart, C.E., Fonte, S.J. 2020. Deficit irrigation drives maize root distribution and soil microbial communities with implications for soil carbon dynamics. Soil Science Society of America Journal. 85(2):412-422. https://doi.org/10.1002/saj2.20201.
Zadworny, M., Comas, L.H., Bagniewska-Zadworna, A. 2021. Root anatomy. New Phytologist. 232(3):1028-1037. https://doi.org/10.1111/nph.17572.
Mommer, L., Comas, L.H., Weigelt, A. 2021. Root spatial distribution. New Phytologist. 232(3):1017-1021. https://doi.org/10.1111/nph.17572.
Flaster, D., Gallagher, R., Wenk, E., Wright, I., Indiarto, D., Lawson, J., Allen, S., Gleason, S.M., Blackman, C.J. 2021. AusTraits, a curated plant trait database for the Australian flora. Scientific Data. 8. Article e254. https://doi.org/10.1038/s41597-021-01006-6.
Trout, T.J., DeJonge, K.C. 2021. Evapotranspiration and water stress coefficient for deficit-irrigated maize. American Society of Civil Engineers Journal of Irrigation and Drainage. 147(10). https://doi.org/10.1061/(ASCE)IR.1943-4774.0001600.
Niu, Y., Han, W., Zhang, H., Zhang, L., Chen, H. 2021. Estimating fractional vegetation cover of maize under water stress from UAV multispectral imagery using machine learning algorithms. Computers and Electronics in Agriculture. 189. Article e106414. https://doi.org/10.1016/j.compag.2021.106414.
Zhang, H., Zhang, L., Niu, Y., Han, M., Yemoto, K.K. 2020. Comparison of water stress coefficient using three alternative canopy temperature-based indices. International Journal of Precision Agricultural Aviation (IJPAA). 3(2):28-34. https://doi.org//10.33440/j.ijpaa.20200302.78.
Hunter, C., Ware, M.A., Gleason, S.M., Pilon-Smits, E., Pilon, M. 2022. Recovery after deficiency: Systemic copper prioritization and partitioning in the leaves and stems of hybrid poplar. Tree Physiology. Article etpac038. https://doi.org/10.1093/treephys/tpac038.
Gleason, S.M., Barnard, D.M., Green, T.R., Mackay, D.S., Wang, D.R., Ainsworth, E.A., Altenhofen, J., Banks, G.T., Brodribb, T.J., Cochard, H., Comas, L.H., Cooper, M., Creek, D., DeJonge, K.C., Delzon, S., Fritschi, F.B., Hammer, G., Hunter, C., Lombardozzi, D., Messina, C.D., Ocheltree, T., Stevens, B.M., Stewart, J.J., Vadez, V., Wenz, J.A., Wright, I.J., Zhang, H. 2022. Physiological trait networks enhance understanding of crop growth and water use in contrasting environments. Plant, Cell & Environment. 45(9):2554-2572. https://doi.org/10.1111/pce.14382.
Delfin, E.F., Drobnitch, S.T., Comas, L.H. 2021. Plant strategies for maximizing growth during water stress and subsequent recovery in Solanum melongena L. (eggplant). PLoS ONE. 16(9). Article e0256342. https://doi.org/10.1371/journal.pone.0256342.