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1. Engineered Water Repellency for Mitigating Frost Action in Iowa Soils

   https://doi.org/10.1061/9780784484012.046  

   Brooks, Ty; Daniels, John L.; Uduebor, Micheal; Cetin, Bora; Wasif Naqvi, Mohammad (March 2022, Geo-Congress 2022: Soil Improvement, Geosynthetics, and Innovative Geomaterials)

   Anne Lemnitzer; Armin W. Stuedlein (Ed.)

   Selected papers from sessions of Geo-Congress 2022, held in Charlotte, North Carolina, March 20–23, 2022. Sponsored by the Society of Exploration Geophysicists and the Geo-Institute of ASCE. This Geotechnical Special Publication contains 66 peer-reviewed papers on geosynthetics, innovative geomaterials, and soil improvement techniques. Topics include: rigid inclusions and stone columns; soil stabilization; bio-grouting and bio-inspired solutions; geosynthetics; and innovative geomaterials and methods. GSP 331 will be valuable to practitioners and researchers working in the area of soil improvement. 

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2. Engineered Water Repellency in Frost Susceptible Soils

   https://doi.org/10.1061/9780784484012.047  

   Uduebor, Micheal; Daniels, John; Naqvi, Mohammad Wasif; Cetin, Bora (March 2022, Geo-Congress 2022: Soil Improvement, Geosynthetics, and Innovative Geomaterials)

   Anne Lemnitzer, Ph.D.; Armin W. Stuedlein (Ed.)

   Selected papers from sessions of Geo-Congress 2022, held in Charlotte, North Carolina, March 20–23, 2022. Sponsored by the Society of Exploration Geophysicists and the Geo-Institute of ASCE. This Geotechnical Special Publication contains 66 peer-reviewed papers on geosynthetics, innovative geomaterials, and soil improvement techniques. Topics include: rigid inclusions and stone columns; soil stabilization; bio-grouting and bio-inspired solutions; geosynthetics; and innovative geomaterials and methods. GSP 331 will be valuable to practitioners and researchers working in the area of soil improvement. 

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3. Engineered Water Repellency for Frost Mitigation: Practical Modeling Considerations

   https://doi.org/10.1061/9780784483701.037  

   Daniels, John L.; Langley, William G.; Uduebor, Michael; Cetin, Bora (November 2021, Geo-Extreme 2021: Infrastructure Resilience, Big Data, and Risk)

   Christopher L. Meehan; Miguel A. Pando, Ph.D.; Ben A. Leshchinsky; Navid H. Jafari (Ed.)

   Proceedings of sessions of Geo-Extreme 2021, held in Savannah, Georgia, November 7–10, 2021. Sponsored by the Geo-Institute of ASCE. GSP 330 contains 37 peer-reviewed papers on infrastructure resilience, big data, and risk. Topics include: geo-materials under extreme loading; cold regions and the Arctic; decision making and planning for extreme events; big data and modeling; and risk management. This GSP will be of interest to geotechnical engineers, climate scientists, emergency managers, insurance professionals, and policy makers working to address a wide variety of extreme events. 

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4. Integrating Multi-Sensing Technology for Preemptive Detection of Highway Slope Instability

   Salunke, R; Biswas, R; Khan, S; La_Cour, I (March 2025, American Society of Civil Engineers)

   Highway slopes are susceptible to various geohazards, including landslides, rockfalls, and soil creep, necessitating early detection to minimize disruptions, prevent collisions, and ensure road safety. Conventional methods, such as visual inspections and periodic surveys, may overlook subtle changes or fail to provide timely alerts. This research aims to enhance slope movement and instability detection by leveraging advanced remote-sensing technologies such as interferometric synthetic aperture radar (InSAR), light detection and ranging (LiDAR), and uncrewed aerial vehicles (UAV). The primary objective is to develop an integrated approach combining multiple data sources to detect and predict highway slope movement effectively. InSAR offers surface deformation measurements over time, capturing nuanced slope movements, while LiDAR and UAVs provide high-resolution elevation information, including slope angles, curvature, and vegetation cover. This study explores methods to integrate these complementary data sets to validate the slope movement detection from InSAR. The research involves establishing a baseline ground motion scenario using historical open-access Sentinel-1 satellite data spanning 10 years (2018􀀐2024) for the central Mississippi region, characterized by expansive clay prone to volume changes, then comparing the ground motions with those observed from near-surface remote sensing. The baseline ground motion scenario is compared with ground truthing from near-surface remote sensing surveys conducted by LiDAR and UAV photogrammetry. The point cloud and imagery obtained from LiDAR and UAVs facilitated cross-verification and validation of the InSAR ground displacements. This study provides a comprehensive and innovative methodology for monitoring highway infrastructure using InSAR and near-surface remote sensing techniques such as LiDAR and UAV. Continuous ground motion analysis provides immediate feedback on slope performance, helping to prevent potential failures. LiDAR change detection allows for detailed evaluation of highway slopes and precise identification of potential failure locations. Integrating remote sensing techniques into geotechnical asset management programs is crucial for proactively assessing risks and enhancing highway safety and resilience. Future studies will use this data set to create finite-element-based numerical models, aiding in developing surrogate models for highway embankments based on observed InSAR ground motion patterns. This study will also serve as a foundation for future machine-learning classification models for detecting vulnerable geo-infrastructure assets. 

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5. A database of in situ water temperatures for large inland lakes across the coterminous United States

   https://doi.org/10.1038/s41597-024-03103-8  

   Sorensen, Troy; Espey, Eamon; Kelley, John_G W; Kessler, James; Gronewold, Andrew D (December 2024, Scientific Data)

   Abstract Water temperature dynamics in large inland lakes are interrelated with internal lake physics, ecosystem function, and adjacent land surface meteorology and climatology. Models for simulating and forecasting lake temperatures often rely on remote sensing andin situdata for validation.In situmonitoring platforms have the benefit of providing relatively precise measurements at multiple lake depths, but are often sparser (temporally and spatially) than remote sensing data. Here, we address the challenge of synthesizingin situlake temperature data by creating a standardized database of near-surface and subsurface measurements from 134 sites across 29 large North American lakes, with the primary goal of supporting an ongoing lake model validation study. We utilize data sources ranging from federal agency repositories to local monitoring group samples, with a collective historical record spanning January 1, 2000 through December 31, 2022. Our database has direct utility for validating simulations and forecasts from operational numerical weather prediction systems in large lakes whose extensive surface area may significantly influence nearby weather and climate patterns. 

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