Presentation Information
[350102-02-01]Landslide hazard assessment under changing climate conditions
Prof. Shabnam J. Semnani (University of California, San Diego)
Rainfall-triggered landslides are widespread natural hazards which take a heavy toll on lives, properties, and infrastructure each year. Estimating the regional evolution of landslide hazard in a changing climate is essential for adaptation planning and risk mitigation efforts. Various data-driven and machine learning based algorithms have been applied to assess landslide susceptibility. However, data-driven methods fail to account for the physical mechanisms behind landslides and are affected by issues such as extrapolation. On the other hand, physics-based models are typically only applicable to a limited region. In this talk, we present the recent advances in data-driven and physics-informed landslide susceptibility assessment techniques as promising tools to investigate landslide susceptibility and its evolution at the regional and national scales to inform decision making and risk mitigation efforts.