Coupling finite element modelling and InSAR data for enhanced understanding of landslide behaviour along highway infrastructures

Landslides pose an increasing threat in Italy, significantly impacting highway infrastructure, highlighting the importance of studying their triggering processes and interaction. While InSAR monitoring has been successfully employed to derive the temporal evolution of ground deformations in slow-moving landslides, it lacks the ability to provide physical insights into the phenomenon mechanism under varying loads. Numerical modelling addresses this limitation by simulating full-scale landslide behaviour, estimating mechanical response and stress levels on interacting structures, although it relies on in situ geotechnical parameters that may be unavailable. This paper combines satellite-based InSAR data and numerical modelling to analyse landslides partially interacting with infrastructure. After assessing InSAR data distribution across an extensive highway area prone to slope instabilities, the proposed method was applied to a case study based on a real bridge-landslide interaction scenario. Post-processing of InSAR data derived transverse and vertical actual displacement components, aligning with observed landslide movement. InSAR results facilitated preliminary assessments of landslide progression and reinforced the numerical model's reliability. FEM simulation revealed significant deformations in the downstream section of the slope, affecting bridge foundations within the landslide-affected area due to horizontal forces, thereby enhancing the understanding of landslide evolution. The consistency between InSAR observations and numerical results confirmed the ability of the numerical model in identifying susceptible areas, even in the absence of in situ data. Coupling numerical modelling with InSAR monitoring can provide a predictive tool for evaluating hydrogeological risks, analysing landslide evolution under complex loads, and supporting maintenance strategies for highway infrastructure in landslide-prone areas.