Research > Agrohydrology

Impacts of Regenerative Agriculture on Soil Health and Ecosystem Services

Poor soil management practices on crop and grazing lands in the Southern Great Plains led to excessive soil and nutrient losses, adversely affecting soil health, ecosystem function, and water quality. Safeguarding natural resources is essential for both preserving agricultural productivity and adapting crops to a changing climate. Regenerative agriculture offers a viable solution by minimizing soil disturbance, maximizing crop diversity, keeping soil covered, maintaining living root year-round and integrating livestock.

Our team investigates the long-term effects of regenerative agricultural practices such as conservation/no-tillage, cover crops, crop rotation, integrated crop-livestock production, and pasture cropping (direct seeding of annual crops into dormant perennial grasses) on soil health and ecosystem services at both the field and watershed scales. Our research has shown that the long-term adoption of cover crops and conservation/no-tillage can increase soil carbon and nitrogen stocks, reduce soil degradation, and lower downstream flood risk, while preserving soil moisture for subsequent cash crops. We have also found that pasture cropping can pay off for producers on lands where environmental conditions are favorable, mainly dormant-season moisture.

Related articles from our team and collaborators:

• Simulated dryland cotton yield response to selected scenario factors associated with soil health
• Assessing the effects of a winter wheat cover crop on soil water use, cotton yield, and soil organic carbon in no-till cotton production systems
• Assessing the effects of no-tillage with rye and mixed cover crops on soil water and nitrogen dynamics and soil carbon sequestration in semi-arid irrigated cotton production systems
• Simulated effects of cover crops with no-tillage on soil and crop productivity in rainfed semi-arid cotton production systems
• Evaluating the potential of no-tillage in enhancing resilience of agricultural watersheds to extreme climatic conditions

Successful establishment of wheat crop (on the left side of the image) in a pasture cropping field experiment at the Nance Ranch near Canyon, TX.

Irrigation Strategies and Decision Support Tools

Agriculture in the semi-arid Texas High Plains and Rolling Plains region faces increasing challenges from rapid declines in groundwater levels, recurring droughts, and projected warmer and drier summers in the future. Increasing water use efficiency while maintaining high crop yields is critical for ensuring the sustainability of crop production in this region.

Our team develops and evaluates efficient irrigation strategies and decision support tools to assist producers in managing water resources effectively under limited availability.  We have suggested efficient, growth-stage-based variable deficit irrigation strategies for cotton, sorghum, and corn to enhance water use efficiency while maintaining optimal crop yields. We have also developed a prototype mobile app (idCROP – Irrigation Decision Support for Conserving Resources and Optimizing Production) that provides real-time irrigation schedules, along with associated yield and economic outcomes, enabling users to select strategies based on well capacity and desired yield and economic goals.

Related articles from our team and collaborators:

• Determining water-use-efficient irrigation strategies for cotton using the DSSAT CSM CROPGRO-cotton model evaluated with in-season data
• Evaluation of crop-growth-stage-based deficit irrigation strategies for cotton production in the Southern High Plains
• Evaluating growth-stage-based variable deficit irrigation strategies for improving yield and irrigation water use efficiency of grain sorghum
• Development and evaluation of a decision support mobile application for cotton irrigation management

Collection of sensor data for the irrigation decision support mobile application

Collection of cotton canopy height data for crop model evaluation

Environmental Impacts of Land Use Change and Grazing Management

Maintenance of healthy soil ecosystems is a key for ensuring water, food and energy security for current and future generations. It is therefore important for producers and ranchers to adopt management practices that maintain or restore soil and ecosystem health and resilience.

Our team assesses the impacts of changes in land use (e.g., row crops to perennial forages) and grazing management practices (continuous grazing versus adaptive multi-paddock grazing) on hydrology, water quality and soil health, and suggests the best management practices. Our research in selected watersheds in Texas and North Dakota highlighted the benefits of adaptive multi-paddock grazing in enhancing water catchment functions, improving ecosystem services of rangelands, and protecting water quality at both the ranch and watershed scales.

Related articles from our team and collaborators:

• Evaluating the ranch and watershed scale impacts of using traditional and adaptive multi-paddock grazing on runoff, sediment and nutrient losses in North Texas, USA
• Evaluating the impacts of alternative grazing management practices on soil carbon sequestration and soil health indicators
• Benefits and challenges of pasture cropping: Perceptions of grazing producers in the United States
• Assessing the hydrologic and water quality impacts of biofuel-induced changes in land use and management
• Grazing management impacts on ecosystem services under contrasting climatic conditions in Texas and North Dakota

Adaptive multi-paddock grazing facilitates good stream bank cover (photo on the right) as compared to continuous grazing (photo on the left)

Future Climate Impacts on Crop Production and Adaptation Strategies

Crop production in the future is increasingly vulnerable to climate variability, rising temperatures and reduced water availability. Hence, there is a need to assess crop yields and water requirements under future environmental changes and suggest adaptation strategies to mitigate potential challenges.

Our team assessed the impacts of projected climate change on crop production and irrigation requirements for major crops in the Texas High Plains, and suggested genotype-based and agronomic adaptation strategies. A similar study is ongoing for cotton production at five sites across the U.S. Cotton Belt.

Related articles from our team and collaborators:

• Evaluating the potential of no-tillage in enhancing resilience of agricultural watersheds to extreme climatic conditions
• Potential genotype-based climate change adaptation strategies for sustaining cotton production in the Texas High Plains: A simulation study
• Potential benefits of genotype-based adaptation strategies for grain sorghum production in the Texas High Plains under climate change
• Potential climate change adaptation strategies for winter wheat production in the Texas High Plains
• Simulating future climate change impacts on seed cotton yield in the Texas High Plains using the CSM-CROPGRO-Cotton model
• Simulating the climate change impacts and evaluating potential adaptation strategies for irrigated corn production in Northern High Plains of Texas

Climate Adaptive Alternate Crops and Forages

Rapidly declining groundwater levels in the Southern Ogallala Aquifer and associated restrictions on groundwater pumping pose a significant threat for the future of irrigated crop production in the Southern Great Plains. Under the projected warmer climate and shifts in precipitation patterns, irrigated crop production may not be viable, and producers may have to transition into rainfed crop production either partially or fully. The projected rise in temperatures may create conditions favorable for growing alternative crops, presenting an opportunity to transition toward less water-intensive options.

Our current efforts focus on identifying alternative field and forage crops suitable for the projected changes in future climate and assess their feasibility and profitability relative to traditional crops. Preliminary results indicate that the areas suitable for cotton production are projected to shift spatially, with increased suitability in the northern Texas Panhandle and Southwest Kansas and Southeast Colorado during the mid- and late-century periods.

Related articles from our team and collaborators:

• Intensifying dryland wheat systems by integrating guar increased production and profitability
• Spatial variability of biofuel production potential and hydrologic fluxes of land use change from cotton to Alamo switchgrass in the Texas High Plains

Mapping of areas suitable for cotton production under projected future climate

Application of Machine Learning and Artificial Intelligence for Land and Water Resource Management in Agroecosystems

Modern agricultural systems generate vast and diverse agronomic, hydrologic, climatic, and remote sensing datasets to manage land water resources. Machine learning and artificial intelligence have the potential to support efficient natural resource management by analyzing large datasets, identifying hidden patterns, and generating predictive insights. Therefore, the Agrohydrology research program uses these modern tools to support more efficient natural resource management and improved decision making in agroecosystems.

Related articles from our team and collaborators:

• A support vector machine and image processing based approach for counting open cotton bolls and estimating lint yield from UAV imagery
• Deriving hydrological inferences from a machine learning model to understand the physical drivers of flow duration curves
• Remote detection of water stress in cotton using a center pivot irrigation system-mounted sensor package
• Estimation of soil water content under different conservation practices using supervised machine learning algorithms on images collected using Unpiloted Aerial System
• Identifying environmental and management drivers of crop yield prediction error using machine learning and Shapley Additive Explanations (SHAP)