Doctoral Student Morgan State University, Baltimore, Maryland, United States
Abstract Submission: Landslides present a serious risk to human safety, infrastructure, and the environment. Accurate prediction of landslide susceptibility is critical for effective hazard mitigation and risk reduction efforts. In this study, we aim to employ the Transient Rainfall Infiltration and Grid-based Regional Slope-stability (TRIGRS) model to predict landslide susceptibility in selected sites in the state of Maryland. TRIGRS simulates how rainfall infiltrates the soil, causing changes in moisture levels and pore water pressure that can lead to landslides. A combination of spatial data, including topography, geology, soil properties, and rainfall data, will be utilized to run the TRIGRS model. This study demonstrates the potential of TRIGRS for landslide assessment to ensure safe transportation. The results obtained will be validated by using historical landslide data and field observations in the identified slope failures in the State of Maryland’s inventories near highway infrastructures. These results will be useful for transportation stakeholders to identify areas prone to slope failures and help to inform land-use planning, infrastructure development, and emergency response strategies. Mitigation strategies can then be further developed by incorporating rainfall monitoring and forecasting, soil moisture and slope stability monitoring, landslide susceptibility mapping and emergency response planning. By adopting the TRIGRS model, slope failures can be considerably reduced, human lives and infrastructure can be well protected, and sustainable development can be promoted. Future research directions include refining the model inputs and parameters to improve the accuracy of landslide susceptibility predictions.
