Frictional timescales and the impact of climate change-driven extreme weather on rainfall-triggered landslides in Mizoram, NE India

Abstract

Mizoram records the highest landslide frequency among all Indian states, yet physics-based models that predict the timing of slope failure remain unavailable for the region. Here, we apply the rate-and-state friction (RSF) block-slider framework of Paul et al.(2024) to 19 rainfall-triggered landslides in and around Aizawl (2016--2025) to investigate the hydro-mechanical coupling between pore-pressure transients and the slow-to-fast transition of slopes hosted in Miocene shale-dominated lithology. For each event, satellite-derived (GPM) rainfall is propagated to failure depth using a 1D infiltration model across three hydraulic conductivity scenarios, and RSF parameters are inverted to reproduce the observed failure date. The resulting dimensionless normalized pore-pressure $χ= μ_0 ΔP / (a\,σ'_f)$ cleanly separates the 19 events into two dynamically distinct failure regimes: synchronous failure ($χ\gtrsim 4$, zero delay from peak pore-pressure), exemplified by the eight-event Cyclone Remal cluster of May 2024, and delayed failure ($χ\sim 1$--$3$, delays of hours to 10~days), controlled jointly by $χ$ and the velocity-weakening ratio $a/b$. Using CMIP6 extreme-rainfall scaling factors for northeast India under SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios, we project that the fraction of landslides falling in the zero-warning synchronous regime increases from the current $\sim$56% to $\sim$72% under SSP5-8.5. Our results imply a significant climate-driven escalation of multi-site, clustered landslide failure risk driven by the intensification of extreme precipitation events.