Abstract
Over the last two decades, climate change events have significantly affected the stability of geotechnical infrastructure, caused damage and resulting in injuries and loss of life. Climate-change events such as heavy rainfall, high temperatures, and permafrost thaw can affect the stability of slopes and embankments, causing problems with tunnel linings and foundation failures. The effects of climate change-induced extreme weather events on geotechnical infrastructure and people's lives can be minimized by using advanced data analysis techniques for monitoring and design. Recently, Large Language Models (LLMs) have become popular for efficient and accurate infrastructure design and monitoring because they are trained on large volumes of data. This review summarizes the contributions of different researchers on the effects of climate change-induced extreme weather events on geotechnical infrastructure, including slopes, tunnels, embankments, and foundations. Moreover, this research proposes avenues for using LLMs for efficient monitoring and design of geotechnical infrastructure. By summarizing the findings, this paper highlights the impact of extreme weather events on geotechnical infrastructure and helps engineers adopt LLMs for the design and monitoring of geotechnical infrastructure. Overall, integrating LLMs into the design and monitoring of geotechnical infrastructure can improve safety by enhancing early-warning systems for slopes, embankments, and tunnels and by enabling designs that account for the variability of environmental forces during extreme weather events.