Sandy Creek at Mill Creek Road. (Amanda Tague, TWRI.)
Peer-reviewed publications by Texas A&M AgriLife and Texas A&M University System scientists
Using electromagnetic induction to inform precision turfgrass management strategies in sand-capped golf course fairways: Dallas Williams, former TWRI Mills Scholarship recipient, and coauthors from Texas A&M’s Department of Soil and Crop Sciences found electrical conductivity (EC) to be a suitable proxy for near-surface soil and turfgrass characteristics, such as soil volumetric water content, for golf course turfgrass management. They suggest that future research study using mobile EC sensors to establish site-specific management units for use in precision turfgrass management.
Probing the Photochemical Formation of Hydroxyl Radical from Dissolved Organic Matter: Insights into the H2O2-Dependent Pathway: Authored by researchers in Texas A&M’s Zachry Department of Civil and Environmental Engineering, this study quantifies the contribution of the hydrogen peroxide (H2O2)-dependent pathway to hydroxyl radical production from the photolysis of dissolved organic matter. Through the analysis there are significant implications for the photochemical production of hydroxyl radical via a H2O2-dependent pathway in natural aquatic systems.
Enhancing streamflow predictions in coastal watersheds with a multisite calibration approach in the Matagorda Bay watershed, Texas: Prairie View A&M University researchers studied streamflow predictions by using a multisite calibration algorithm to effectively capture the historical and future water availability in the Matagorda Bay watershed, Texas. Using the SWAT model for calibration, they can more effectively represent the hydrological process in complex coastal watersheds.
A High-Resolution Global SWAT+ Hydrological Model for Impact Studies: This research team, including Texas A&M AgriLife scientists, worked to develop a high-resolution global SWAT+ model and establish a reproducible framework for large-scale SWAT+ applications that can understand water resources and assess climate change impacts at planetary scales, supporting water management, flood risk assessment, and sustainable development initiatives worldwide.
Enhancing prediction and inference of daily in-stream nutrient and sediment concentrations using an extreme gradient boosting based water quality estimation tool - XGBest: Researchers at Texas A&M AgriLife Research assess more effective methods to estimate concentrations of sediment in surface waterbodies. By implementing the ML-based XGBest tool, water-quality predictions are determined to be more precise.
Toward sustainable desalination: a patent analysis of technology-development trajectories: Co-authored by a Texas A&M researcher, this study analyzed desalinization patent data and found misalignments between desalination research and development pathways, and broader sustainability concerns, with implications for the long-term sustainability of desalination and regional water-security policies.
Enhancing hydrological modeling of ungauged watersheds through machine learning and physical similarity-based regionalization of calibration parameters: Texas A&M AgriLife researchers studied the potential of physical similarity-based clustering and machine learning techniques for improving hydrological modeling in ungauged watersheds. This study’s proposed approach successfully captured physical similarities and flow patterns.
Recent research from other Texas universities
Assessing Short- and Long-Term Anthropogenic Threats to a Reintroduced Fish in a Restored Urban Riverscape: Scientists from the University of Texas at San Antonio examined the effects of human-influenced environmental stressors upon a restored habitat, followed by a reintroduction of native species in the riverscape. They found that by assessing both short-term population dynamics and long-term stressors on the environment, reintroduced species can be maintained through correct monitoring processes.
Efficacy of mitigation strategies for aquifer sustainability under climate change: Specialists at the University of Texas at San Antonio developed a data-driven evaluation of the efficacy of mitigation measures in the karstic Edwards Aquifer system. They analyzed the long-term effectiveness of these strategies under future climate scenarios.
