Prediction and Rehabilitation of Highway Embankment Slope Failures in a Changing Climate

University Transportation Centers Program2018PDFTech ReportJafari, Navid HPuppala, Anand J.Transportation Consortium of South-Central States (Tran-SET) University Transportation Center for Region 6Louisiana State University (Baton Rouge, La.)University of Texas at ArlingtonUnited States. Department of Transportation. Office of the Assistant Secretary for Research and TechnologyUnited States. Department of Transportation. University Transportation Centers (UTC) ProgramTransportation Consortium of South-Central StatesLouisianaTexasUnited StatesClay soilsClimate changeCrackingEmbankmentsGuidelinesHighwaysLessons learnedMoisture contentRehabilitation (Maintenance)Shear strengthSlope failure17GTLSU0469A3551747106Final Research Report May 2017 \u2013 May 2018Highway slopes constructed with clayey soil are prone to desiccation cracks due to wetting and drying weather cycle, which allows greater moisture infiltration into the embankment from precipitation. Fissures formed due to extended wetting and drying cycles allow water to seep deeper into the soil than surficial wetting and increase the water content. This increases the moisture content in the soil and results in reduction in shear strength to the fully softened strength. On the other hand, development of desiccation cracks and reduction of the soil matric suction ultimately result in higher hydraulic conductivity value which causes development of higher pore water pressure. As the moisture content of the clayey soil increases, the strength reduces to a fully softened shear strength that causes frequent shallow and medium slope failures that are oriented approximately parallel to the surface of the embankment. Hence, the fully softened strength of Louisiana and Texas soils need to be quantified to develop a predictive tool for identifying high-risk zones of highway embankments. Given the documented failures in Texas and Louisiana, this research project is focused on investigating past failures to develop lessons learned and guidelines that can be implemented in the predictive framework.137