Skip to main content
ARS Home » Plains Area » Lubbock, Texas » Cropping Systems Research Laboratory » Wind Erosion and Water Conservation Research » Research » Research Project #432915

Research Project: Optimizing Water Use Efficiency for Environmentally Sustainable Agricultural Production Systems in Semi-Arid Regions

Location: Wind Erosion and Water Conservation Research

2022 Annual Report

Obj 1: Quantify the environmental factors that affect the degree of crop drought stress. Sub-obj 1A Assess the effects of rising atmospheric CO2 concentration on crop coefficients used in deficit irrigation scheduling systems. Sub-obj 1B Relate seasonal plant stress and water use efficiency responses of crop plants to irrigation scheduling techniques using stable carbon isotope discrimination. Sub-obj 1C Identify active root areas under sub-surface irrigation to determine optimal cultivar for dryland management. Obj 2: Develop crop management strategies that enhance water use efficiency. Sub-obj 2A Quantify the effects of wind speed, tillage management, and irradiance on surface water evaporation. Sub-obj 2B Identify changes in microbial and chemical characteristics that may impact water availability and productivity in dryland production. Obj 3 Develop a framework of methods and models for quantifying and studying the risks associated with water from rainfall for dryland agriculture over the Southern High Plains and other dryland agricultural regions. Sub-obj 3A Evaluate the ability of current weather generator configurations to reproduce the distributional characteristics of Southern High Plains summer weather variability. Sub-obj 3B Run calibrated and validated cotton and sorghum crop models with both observed and stochastically generated weather inputs to generate simulated dryland yield outcomes. Sub-obj 3C Convert modeled yield outcomes generated with simulated weather data into net profit outcomes to form corresponding profit distributions for dryland cotton and sorghum production. Obj 4: Evaluate management practices that prevent soil degradation by soil erosion in semiarid cropping and rangeland systems. Sub-obj 4A Investigate soil redistribution & dust emissions from agro-ecosystems including rangelands & native plant communities under the stressors resulting from climate change. Sub-obj 4B Evaluate management systems in terms of multi-decadal erosion rates estimated from radioisotope inventories. Obj 5: Evaluate management practices to increase soil water availability and contribute to higher water and nutrient use efficiencies. Sub-obj 5A Partitioning of evapotranspiration to water evaporation from soil & crop surfaces for dryland & irrigated cropping systems across different N fertilizer management strategies. Sub-obj 5B Investigate changes in groundwater quantity & quality that may affect cropland production in semiarid & arid regions. Obj 6: Develop management practices that contribute to maintaining microbial diversity and functions needed to improve soil health, ensure ecosystem sustainability, and maintain crop productivity under a changing climate. Sub-obj 6A Compare the effects of different management practices in semiarid regions on soil health indicators including the microbial community size, diversity & functions. Sub-obj 6B Characterize the effects of climatic events on soil health & the effects of future climate change (CO2, temperature and rainfall) on agro-ecosystems by measuring root biomass, soil microbial diversity & soil organic matter pools.

Sustainable agriculture, with emphasis on conservation of natural resources, is a challenge in the semiarid climate of the Southern High Plains (SHP). Of concern is developing cropping systems that cope with climate change, depletion of aquifers used for irrigation, and growing seasons characterized by frequent droughts and erratic rainfall. Climate change is expected to impose general global challenges but, clearly, solutions to these problems will be site specific. Within a framework to quantify and study the risks associated with dryland agriculture, we need sustainable agricultural systems that optimize productivity, conserve water, control soil erosion and improve soil health for agricultural production in semiarid regions and in a changing climate. We will continue long-term research that identifies management practices that impact water availability in dryland farming vs. lands in the Conservation Reserve Program. Our goal is to provide agricultural producers with tools to manage limited water resources in the semi-arid environment of the SHP. New technologies for exposing crops in the field to elevated levels of atmospheric CO2 concentration will be used to monitor hourly and daily whole canopy water use efficiency by simultaneously measuring the ratio of net CO2 assimilation to evapotranspiration. Optimum irrigation scheduling techniques will be determined from stable carbon isotope discrimination while optimal cultivars for dryland agriculture will be selected by identifying and comparing active rooting areas. This multifaceted research program will provide the knowledge base for optimizing the use of scarce water resources in arid and semi-arid regions where ground water resources are being depleted.

Progress Report
We made significant accomplishments from 2017 to 2022 via data compilation, model development, and establishing indexes that support management strategies for semiarid regions with limited irrigation. Within Objective 1, to quantify a major environmental factor affecting the degree of drought stress on crops, we developed a new method to expose small plants to elevated levels of atmospheric [CO2] concentration, that was adapted from previous work done with open, flow-through chambers. Using this approach, it is now possible for plant scientists to perform short-term [CO2] enrichment studies of 4 to 6 weeks or longer in duration depending on plant species. In Sub-objective 1B, we attempted to relate stable carbon isotope discrimination in extracted cotton seed oil to plant water stress. While a critical vacancy prohibited us from correlating photosynthetic leaf stable carbon isotope discrimination to that of developing fruits, we related the end-of-season stable carbon isotope signal of oil, cotton burrs, and leaves to irrigation levels. We did not mechanistically demonstrate the validity of the hypothetical underpinnings of the concept, but we empirically demonstrated the validity of the approach as a surrogate for season long water stress measurement. In Sub-objective 1C, we developed hardware to measure soil water in a 0.3-m cylinder filled with fritted clay. However, due to the critical vacancy the test to identify active roots was not pursued. Objective 2 focused on crop management strategies to enhance water use efficiency. Within Sub-objective 2A, a 15 m long wind tunnel was modified to fit 4 weighing lysimeters under high intensity lamps to study the effects of wind speed, tillage management, and irradiance on surface soil water evaporation. The lysimeters were custom built to allow a cotton module builder to press the shells into undisturbed soil. The knives on the balances were serviced and we used temperature-stable load cells to measure evaporation within 0.33 mm/day. A vented natural gas heater was used to maintain near-constant temperature and vapor pressure deficit during the winter months scheduled for evaporative testing. We are continuing this study in our next project plan. Within Sub-objective 2B, we conducted several studies that will be continued in the next project plan to establish linkages of soil biology on soil water conservation. The main accomplishment was a statistical model that compared laboratory methods to evaluate markers for bacteria vs. fungal groups, and their relationship to sites under dryland or irrigation sites within the Southern High Plains (SHP). Although the model identified irrigation-water as an important variable affecting microbes, we need more research on how these indicators are predictors of changes in soil water storage. A funded National Institute of Food and Agriculture grant, in collaboration with New Mexico State and Colorado State University will expand the geographical coverage of semiarid regions by evaluating soil health indicators in plots under cover crops and manure applications in New Mexico and Colorado. Our goal is a framework for soil health assessment in semiarid environments and to link different soil health indicators with soil functions, e.g., soil water dynamics. To meet Objective 3 goals, we used crop simulation models to estimate the risks and uncertainties of dryland production in the semiarid SHP. Sub-objective 3A tested artificial weather generators that might be used in regions where weather data to drive crop models is sparse or unavailable. However, these evaluations were time-consuming and did not produce publishable results. Instead, Sub-objective 3B model simulations were driven by the available high-quality daily weather data provided by regional Mesonet weather stations. Simulations were conducted to determine best management practices for dryland cotton and sorghum and to compare those crops profitability over a range of commodity price and production costs. These results showed sorghum to be a viable crop to cotton, or useful in cotton-sorghum crop rotations. The fiscal year (FY) 2022 Sub-objective 3C goal –the completion of a SHP dryland risk analysis web application– was not accomplished because the agency prohibited the operation of web servers in June 2020. Given the importance of soil water storage in semiarid agriculture, additional research was conducted in FY 2020 using crop models to evaluate the effects of increasing soil organic carbon (SOC) on soil water storage. Simulations were also conducted in FY 2021 to estimate irrigation practices that maximize the irrigated water use efficiency of SHP cotton production. Other FY 2018 research statistically evaluated field experiment data to estimate the effects of planting dates on SHP cotton yields and fiber quality. Data from a weather station at the Texas Tech University New Deal facility in FY 2020 was used to support stockyard mortality research. In FY 2019 analysis of SHP weather data was used to support a post-doctoral effort to investigate the effects of climate on soil microbial populations. In FY 2022, crop simulation studies were conducted to estimate the impacts of winter wheat cover crops on soil water content and SHP dryland cotton production. Within Objective 4 to evaluate management practices that prevent soil degradation by soil erosion, we made progress investigating soil redistribution and dust emissions from different sources including rangelands and native plant communities. We have a long-term project at the Sevilleta National Wildlife Refuge in New Mexico. Travel was granted to the site in March 2022 to reinstall the desert grassland following removal for a control burn and a collection trip is planned for the fall. Preliminary results of soil redistribution rates were published. Objective 5 deals with water quantity or quality from the Ogallala aquifer as a shared resource providing groundwater for irrigated agriculture in the SHP. We have conducted different studies for a model to explore strategies to maximize the use of water from irrigation and from rain within Sub-objective 5A and B as our efforts to reduce water withdrawn from the aquifer. We have done extensive simulation using as input data gathered from previous field experiments that measured the storage of rainfall and crop yields within major soil types in the SHP. Also, various aspects of groundwater quantity and quality were studied within Sub-objective 5C, including long-term changes of groundwater supplies, seasonal changes in water salinity, and investigation of some consequences of seasonal pumping of groundwater resources. Groundwater samples were collected from 20 wells in 5 Texas counties for a 3 to 6-year period, to investigate seasonal variations of groundwater salinity associated with active pumping during the growing season. Results showed that when wells are actively pumped, water quality can change in complex and unpredictable ways prompting further investigations of the mechanisms involved in measured seasonal water quality changes. We developed a method to compute the average deviation of the groundwater level from a nonstationary annual-average water level. Perturbation curves are observed to follow a regular pattern of declining water levels during the growing season followed by a recovery after irrigation systems are shut down. In areas with limited groundwater, farmers may temporarily shut off irrigation systems when soil water is adequate. Thus, one can often detect periods during the growing season when irrigation is paused, and the water table is allowed time to partially recover. Seasonal changes in the local volume of stored water in the Ogallala aquifer can alter the flow of natural springs along the eastern escarpment. Reductions of spring flow can reduce the supply of freshwater available for livestock production. This is important because beef is the number one agricultural product in Texas. Measurements of spring discharge over a 7-year period revealed that spring discharge follows a seasonal pattern of reduced flows during the summer and peak flows during the winter. It is likely that the combined effects of groundwater extraction for irrigation and the growth of natural vegetation contribute to the observed seasonal patterns of spring discharge. Objective 6 addressed management practices to maintain diversity to improve soil health and crop productivity under a changing climate. Results showed improved soil microbial communities depending on the cover crop that were linked to soil organic carbon (SOC) accumulation in this region. For example, SOC content was greater with oats than pea, canola, and their mixes, which was also related to higher wet aggregate stability, and higher microbial community size in oats than fallow. Soil organic matter (SOM) is central to soil health assessment due to its critical role on microbial diversity, nutrient cycling, aggregate stability, and water storage and infiltration. Our research will continue in the new project plan to address these interactions of alternative management when droughts are more frequent. Within Sub-objective 6B, we completed our simulated studies to characterize the effects of climatic events on soil health and the effects of future climate change on agroecosystems by measuring root biomass, soil microbial diversity, and SOM pools. Results indicated that an increase in CO2 could increase soil respiration and a shift in the microbial community toward higher fungi including an increase of arbuscular mycorrhizal fungi (AMF). However, other published results demonstrated decreases in AMF with droughts in 2011 and 2016 with subsequent recovery, indicating that different factors along with climate change need to be considered to determine their effects in soil biology and their impact on the overall soil health of an agroecosystem.

1. Maximizing the irrigation productivity of the Ogallala aquifer in the U.S. Southern High Plains. The Ogallala aquifer under the Southern High Plains (SHP) is an important groundwater resource for U.S. cotton production, but because pumping rates exceed the aquifer’s recharge rates its water levels are steadily declining. To ensure that the aquifer’s remaining water is used productively, farmers need to know which irrigation practices use the aquifer’s water most efficiently in cotton production. To define the most efficient irrigation practices for SHP farmers, ARS scientists from Lubbock, Texas, conducted cotton crop model simulations in which the amount and timing of irrigation was independently varied during the growing season. These simulations showed that maximum irrigation water use efficiency, that is, the amount of lint yield produced per inch of applied irrigation, occurred when between 12 to 14 inches of irrigation was applied. Simulations that varied irrigation timing showed that when 12 inches was applied only during the cotton crop’s mid-stage reproductive and late-stage maturation periods, irrigation efficiency was increased even further. The results of this research provide important irrigation management guidelines that will allow SHP cotton producers to maximize the ‘crop per drop’ of the remaining groundwater of the southern Ogallala aquifer.

2. Dryland cotton lint yield as a function of rainfall in the U.S. Southern High Plains. Agriculture in the Southern High Plains (SHP) is shifting from producing crops with a diminishing supply of irrigation-water from the Ogallala aquifer to dryland cropping systems. To establish a relation between cotton lint yield and rainfall scientists at ARS in Lubbock, Texas, used county-level values of cotton lint yield and annual rainfall from 1972 to 2018. The ratio between cotton lint yield and rainfall is called crop water productivity (CWP). In our analysis we selected 16 counties from the SHP, including Martin, Glasscock, and Midland in the south and Cochran, Lubbock,and Hockley in the north. We speculate that results from these counties are precursors of future cotton production patterns that will emerge in the SHP. Our results showed that only 2011 – a record drought with 7 inches of rain – failed to produce a dryland cotton crop. The average cotton lint yield ranged from a high of 360 lb/acre in Lubbock County to a low of 225 lb/acre in Andrews County. However, the counties with the highest CWP of 19 lb/acre per inch of rain were in Glasscock, Midland and Martin County. We conclude that management production methods used by dryland producers in these counties represent the future schemes that need to be adopted to sustain the emerging dryland cropping systems across the SHP.

Review Publications
Li, J., Ravi, S., Wang, G., Van Pelt, R.S., Gill, T.E., Sankey, J.B. 2022. Woody plant encroachment of grassland and the reversibility of shrub dominance: Erosion, fire and feedback processes. Ecosphere. 13(3). Article e3949.
Thapa, V.R., Ghimire, R., Vanleewen, D., Acosta Martinez, V., Shukla, M. 2022. Response of soil organic matter to cover cropping in water-limited environments. Geoderma. 406. Article 115497.
Lascano, R.J., Payton, P.R., Mahan, J.R., Goebel, T.S., Gitz, D.C. 2022. Annual rainfall and dryland cotton lint yield - Southern High Plains of Texas. Agricultural Sciences. 13:177-200.
Bergh, E.L., Calderon, F.J., Clemensen, A.K., Durso, L.M., Eberly, J.O., Halvorson, J.J., Jin, V.L., Margenot, A.J., Stewart, C.E., Van Pelt, R.S., Liebig, M.A. 2022. Time in a bottle: Use of soil archives for understanding long-term soil change. Soil Science Society of America Journal. 86(3):520-527.
Edwards, B.L., Webb, N.P., Van Zee, J.W., Courtright, E.M., Cooper, B.F., Metz, L., Herrick, J.E., Okin, G., Duniway, M.C., Tatarko, J., Tedela, N., Newingham, B.A., Pierson Jr, F.B., Toledo, D.N., Van Pelt, R.S. 2021. Parameterizing an aeolian erosion model for rangelands. Aeolian Research. 54.Article 100769.
Mauget, S.A., Ulloa, M., Mitchell-Mccallister, D. 2022. Simulated irrigation water productivity and related profit effects in U.S. Southern High Plains cotton production. Agricultural Water Management. 266.
Eibedingil, I.G., Gill, T.E., Van Pelt, R.S., Tong, D.Q. 2021. Comparison of aerosol optical depth product from MODIS product collection 6.1 and AERONET in the western United States. Remote Sensing. 13(12):2316.
Eibedingil, I.G., Gill, T.E., Van Pelt, R.S., Tong, D.Q. 2021. Combining optical and radar satellite imagery to investigate the surface properties and evolution of the Lordsburg Playa, New Mexico, USA. Remote Sensing. 13(17):3402.
Baker, J.T., Lascano, R.J., Yates, C.E., Gitz, D.C. 2022. Nighttime CO2 enrichment did not increase leaf area or shoot biomass in cotton seedlings. Agriculture and Forest Meteorology. 320.