Assessing simplified approaches in modeling rainfall-induced landslides using Richards' equation with Biot poroelasticity

Coupled Hydro-Mechanical (HM) models, which involve the interaction between fluid flow and mechanical processes in porous media, are essential for simulating rainfall-induced landslides (RILS). A common strategy to investigate RILS is through the Biot poroelasticity approach combined with the Local Factor of Safety concept. While the two-phase flow and mechanical equations are well-documented for modeling HM processes in variably saturated conditions, the use of Richards' Eq. (RE) in this context remains underexplored. This paper aims to address this gap by providing a comprehensive formulation for coupling RE with mechanical equations and evaluating the impact of various model simplifications on the reliability of RILS predictions. We present the theoretical development of the original mathematical model that leads to a strong coupling between flow and mechanical equations. We also review the different simplification approaches proposed in the literature to reduce the complexity of the original model. A straightforward implementation of these approaches in COMSOL is provided, with validation against established benchmarks. Through a comparative analysis of different approaches, using both hypothetical benchmark and real case study in Azerbaijan, this study provides new insights into the balance between model complexity and prediction accuracy. While simplified approaches are commonly used in literature, this study advocates for the fully coupled model, which delivers the most reliable results. The employment of advanced numerical techniques enhances the computational performance of the fully coupled model, making it competitive with simplified approaches. • Modeling rainfall induced landslide requires coupling hydro-mechanical processes. • In this context, the use of Richards equation for unsaturated flow is unexplored. • We provide the development of the original model and its various simplifications. • A comparative analysis of different simplification approaches is conducted. • We recommend the fully coupled model for its reliability and performance.