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.
We made significant progress compiling data related to management strategies for semiarid regions of lower rainfall and of diminishing irrigation-water leading to water conservation and sustaining crop yields. Within Ojective 1, to quantify the environmental factors that affect the degree of crop drought stress, we completed two growing seasons (field-based growth chambers) studying the effects of elevated atmospheric carbon dioxide (CO2) concentration on peanut and on cotton. This is the first available data reporting that during water-stress episodes, long-term elevated CO2 atmospheric concentrations [650 µmol CO2 m2/s] increased leaf-level light-saturated CO2 assimilation (53%), increased vegetative biomass (58%), and increased pod yield (39%) relative to ambient CO2. These results will inform how elevated CO2 atmospheric concentrations may reduce the negative impacts of repeated water stress events on rain-fed peanut in semi-arid regions at critical developmental stages. For Objective 2, related to the development of crop management strategies that enhance water use efficiency, we continued the work with the wind-tunnel and to obtain soil monoliths proposed for Sub-objective 2A. For Sub-objective 2B, data obtained from an earlier soil sampling in different fields allowed us to establish a relationship between irrigation-water and soil microbes. For example, we developed and tested a predictive model that related soil physical and chemical properties, abiotic factors, to biological responses. As an example, by comparing a DNA marker for fungi as a function of fungal fatty acid markers, the model predicted increases of 1.18, and 1.44 times per unit increase in pH and soil organic carbon (SOC), respectively, but decreases of 0.78 units relative to gravimetric water content. Although the model identified irrigation-water as an important variable affecting microbes, additional research is needed on how these indicators are predictors of changes in soil water storage. We plan to use more cost-effective ester-linked fatty acid methyl ester analyses within our indicators as both fungal and bacterial markers can be evaluated using the same soil sample. Producers can then use this information to select agronomic management options that improve the soil microbial community leading to improved soil health. Studies within Objective 3 relate to the development of a framework of methods and models for quantifying the risks associated with dryland agriculture in semi-arid regions. Our goal is to use the approach we developed to assess the economic sustainability of dryland agriculture on the Southern High Plains (SHP). In October 2021, a weather station was installed at the Texas Tech University New Deal stockyard facility to support research conducted by ARS researchers. During fiscal year 21, research was conducted using pedotransfer functions and the Decision Support System for Agrotechnology Transfer (DSSAT) crop growth (CROPGRO)-Cotton crop model to simulate the effects of increasing SOC on the water retention properties and lint yield production of two representative SHP soils. Preliminary research evaluated weather generator configurations as well as collected weather data records for future crop simulation research for stakeholders in Martin County, Texas. Within Objective 4 to evaluate management practices that prevent soil degradation by soil erosion, we continue making progress on studies to investigate soil redistribution and dust emissions from different sources including rangelands and native plant communities. Some data were received from cooperators in Arizona for microbial assessment by collaborators at George Mason University. Plans are being made to re-install equipment at one of the rangeland sites at the Sevilleta National Wildlife refuge that was removed for a controlled burn. Our research activities also included a comparison of dust data obtained with remote sensing vs ground-based network data. We made significant progress evaluating management systems in terms of multi-decadal erosion rates estimated from radioisotope inventories part of Sub-objective 4B. For example, soil cores from the Big Spring Field Station were obtained and processed for plutonium extraction. These samples, along with other core samples from locations sampled in 1947 will allow us to determine how much of the changes in soil properties may be due to soil erosion. A non-funded cooperative agreement with Northern Arizona University was extended so that we can continue to have access to their radio-laboratory. Data from all these studies will continue to improve dust source identification and implementation of management practices that reduce wind erosion. Objective 5 consists of different studies that relate to the use of a model to explore strategies to maximize the use of water from irrigation and from rain. We have done extensive simulation work 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. Sub-objective 5C focuses on changes in groundwater quantity and quality that may affect cropland production in semiarid and arid regions. We collected samples of water from various sources in the SHP region over the past 3 years. Results from our groundwater investigations show that most wells become more saline while wells are actively pumping. Salinity profile measurements have revealed that groundwater tends to be more saline at the bottom of a well. As a result, when a well becomes active the more saline water is mixed from below into the upper portion of the profile and the entire water column becomes more uniform and generally more saline. Measurements of the discharge from a natural spring was found to follow a seasonal pattern of diminished discharge during the summer growing season while irrigation wells are active. This result suggests that irrigation of cropland on the SHP can influence spring-fed streams in the ranchlands to the east of the SHP. With regard to our rainfall study, results suggest that there is a surprisingly weak correlation between rainfall chemistry and atmospheric conditions, such as wind speed or direction. Further analyses of rainfall samples did, however, show a significant inverse relationship between salinity and the amount of rainfall collected in the rain gauge. We made significant progress analyzing data from studies related to Objective 6 focused on the development of management practices that contribute to maintaining diversity to improve soil health, crop productivity, and ecosystem functions under a changing climate. Previous soil samplings from research plots in the SHP showed different microbial communities depending on the cover crop evaluated. These changes were also correlated to differences in the soil organic matter dynamics. For example, SOC content was 9–22% greater with oats than pea, canola, and their mixes, which was also related to higher wet aggregate stability (36–49%), and higher microbial community size (up to 41%) in oats than fallow. Our studies suggest the use of oat as a cover crop to improve soil health and resilience of cropping systems through increases in SOC accumulation in this region. 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 (CO2, ambient temperature, and rainfall) on agro-ecosystems by measuring root biomass, soil microbial diversity, and soil organic matter pools. Results indicate that an increase in CO2 could cause an increase of 82% in soil respiration, and a shift in the microbial community toward higher fungi including an increase in 46% of arbuscular mycorrhizal fungi (AMF). These results may only translate to semiarid regions where soils are sandy and/or have low soil organic matter, and the overall changes in the soil microbiome, soil health, and peanut’s agroecosystem functioning still need to be addressed. However, we detected decreases in AMF with natural droughts in 2011 and 2016 with subsequent recovery, which shows there are different factors with climate change that need to be considered to determine their effects in soil biological health.
1. Identification of Lordsburg Playa dust source locations impairing visibility. Lordsburg Playa in southwest New Mexico is crossed by Interstate Highway 10. Since the highway was built and records kept, dozens of people have died due to crashes caused by reduced visibility from dust. The source of dust has not been identified. Therefore, a team of ARS and university scientists (University of Texas at El Paso, Hebei Normal University, and University of Tulsa) used the Portable In-situ Wind ERosion Laboratory (PI-SWERL) to test possible dust emission sources and suggest priorities for reclamation. Specific areas were found with highest dust emission potentials, which have become priority for remediation. It is expected that remediation of the sources of the fugitive dust accomplished as a result of this ARS study will save lives and improve air quality.
2. Improvement of spatially dust collection data to better detect sources of wind erosion. Dust continues to be a problem because of decreased air quality and erosion of soil from agroecosystems. Remote sensing of atmospheric dust concentrations has allowed estimates to be made between ground-based stations but uncertainties remain. An ARS scientist in Lubbock, Texas, in conjunction with university scientists (George Mason University, Fairfax, Virginia; University of Texas at El Paso) compared the atmospheric dust concentrations obtained from orbiting satellites and from a ground-based dust detection network. Results indicated that satellite dust estimates are more robust at higher latitudes and that the older of the two satellite sensors is the less accurate of the two. These data may be used to adjust algorithms used to estimate dust from satellite data resulting in more accurate spatially distributed dust data with national improvements in air quality and soil health.
3. Seasonal reductions of spring discharge linked to cropland irrigation on the Southern High Plains (SHP). The Ogallala aquifer supplies groundwater for crops in the SHP and to spring-fed streams that flow through cattle ranches in the Rolling Plains to the east of the region. ARS scientists in Lubbock, Texas, conducted a study to detect seasonal changes of spring discharge at the eastern edge of the SHP. Spring discharge was found to follow a seasonal pattern of declining flow during the summer growing season followed by a recovery starting in late fall and reaching maximum discharge during winter and early spring. This result suggests that irrigation of cropland in the SHP can reduce the flow of spring-fed streams in the ranchlands to the east of this region, which can reduce the amount of water available to cattle ranches located downstream of the SHP. This study will encourage more efficient use of available groundwater in this region since water is a shared resource that can influence the production of beef cattle, which is the number one agricultural product in Texas.
4. Rainfall on the Southern High Plains (SHP) varies in salt content. As the Ogallala Aquifer is gradually depleted, many farms on the SHP will be forced to shift from irrigated to rainfed (dryland) agriculture. As the region’s agriculture becomes increasingly dependent on rainfall, knowledge of various aspects of precipitation becomes increasingly important for agricultural producers. For example, they need to know more about the quantity of rain, the timing and distribution across rain events, and possible variations of rainfall chemistry. Therefore, an ARS scientist from Lubbock, Texas, has collected rainfall samples at two locations in the SHP for the past five years. The study showed that rainfall samples exhibit a high degree of variability with respect to the concentration of dissolved salts, which can negatively affect agroecosystems. Measurements show a distinct increase in the concentration of dissolved salts with decreasing precipitation amount. A theory was derived that describes the concentration of dissolved salts in rainfall, which will help producers that are transitioning to dryland agriculture, understand natural and anthropogenic variations of rainfall chemistry that can influence crop production.
5. Linking soil microbes to water management in agroecosystems. Soil health initiatives require soil biological indicators that can be linked to essential soil functions to help producers make management decisions that will result in greater sustainability and productivity of the agroecosystem. Producers need cost effective indicators of increases in fungi relative to bacteria as this measurement can represent higher soil C sequestration, soil aggregation, and soil organic matter accumulation, which should lead to higher soil water holding capacity. Scientists from ARS in Lubbock, Texas, and colleagues from Agriculture and Agri-Food Canada and the University of Florida tested a predictive model for soil physical and chemical properties, abiotic factors, and biological responses in soil samples taken from the Southern High Plains. When comparing two biological methods, the model that best predicted presence of microbial genes with DNA work as a function of microbial markers from fatty acid analyses included silt + clay, season, and irrigation as important variables affecting soil biology. More research is needed on how these indicators are predictors of soil water storage. We will now use the fatty acid analyses as it is a more cost-effective assessment compared to gene work to evaluate fungal and bacterial groups within the same soil sample. This will provide information to producers so they can select management practices linked to increases in soil water storage, using changes in a sensitive indicator, i.e., soil microbial community.
6. Increased soil organic carbon (SOC) effects on soil water retention and crop production. Increasing SOC is widely believed to increase a soil’s capacity to hold water, and, potentially, to increase agricultural yields in drier growing regions like the U.S. Southern High Plains (SHP). ARS scientists from Lubbock, Texas, and Texas A&M AgriLife used crop simulation models to estimate how increasing SOC impacts soil water retention and cotton lint yield production of a clay loam soil and a fine sandy loam soil. Higher SOC increased both soil’s ability to hold water, but those effect’s magnitudes were considerably less than previously expected. As surface SOC levels in both soils increased, the sandier soil’s average simulated cotton lint yields were basically unchanged, while yields simulated with the clay loam actually decreased. This work showed that increased SOC had a minor effect of soil water retention in the two soils, and a neutral or negative effect on cotton lint yield. As a result, soil conservation management practices intended to increase SOC may not have the desired effect of increasing cotton lint yields and profits.
7. Modeling demonstrated how soil conservation practices can enhance soil water content for two predominant soil series in the Texas High Plains (THP). Due to a decline of irrigation-water from the Ogallala aquifer, producers in this region are transitioning from deficit-irrigation to dryland production and need management practices to store water in the soil from precipitation. Scientists from ARS in Lubbock, Texas, evaluated the daily and annual water balance for three scenarios of rain (dry, average, and wet) and two major soil series (Pullman and Amarillo) in the THP. The evaluation was done with the mechanistic simulation model Energy and Water Balance (ENWATBAL). Results showed that in years with average and high precipitation, storage of rainfall in the profile occurred in the Pullman but not in the Amarillo series. The next step is to use the ENWATBAL model to quantify the effect of furrow dikes on soil water storage as a function of rainfall frequency and amount. However, producers will benefit from results that the use of furrow dikes, minimum tillage, and crop covers enhances the storage of rainfall in the soil for subsequent use by the crop for both major soil series of the THP.
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