Dataset for "Frictional timescales of landslides in Mizoram under climate extremes]{Frictional timescales and the impact of climate change-driven extreme weather on rainfall-triggered landslides in Mizoram, NE India"

This repository provides the research data and derived model outputs associated with the paper “Frictional timescales and the impact of climate change-driven extreme weather on rainfall-triggered landslides in Mizoram, NE India.” The dataset supports a rate-and-state friction (RSF) analysis of rainfall-triggered landslide failure timing in and around Aizawl, Mizoram, northeast India. It includes the compiled landslide inventory for 19 events spanning 2016–2025, associated site and trigger information, rainfall-derived pore-pressure forcing estimates, inverted RSF model parameters, and derived quantities used to classify landslides into synchronous and delayed failure regimes. The landslide inventory combines information from published literature, the Geological Survey of India Bhukosh/Bhusanket landslide incidence database, government situation reports, and contemporaneous media reports. Events include monsoon-triggered landslides and the May 28, 2024 Cyclone Remal cluster, which produced multiple near-simultaneous failures in the Aizawl region. For each event, half-hourly NASA GPM IMERG precipitation data were used to reconstruct 15-day antecedent rainfall histories. Rainfall forcing was propagated to an assumed failure depth of 2 m using a one-dimensional infiltration/diffusion model under three hydraulic conductivity scenarios. These pore-pressure time histories were then used to drive RSF block-slider simulations, and the RSF parameters were inverted to reproduce observed failure dates. The resulting outputs include normalized pore-pressure, velocity-weakening ratio, characteristic slip distance, delay from peak pore pressure to failure, and failure-regime classification. The data are intended to enable reproducibility of the analyses presented in the paper and to support further research on rainfall-triggered landslide timing, pore-pressure-driven slope failure, climate-change effects on landslide warning windows, and physics-based early warning approaches for Mizoram and similar monsoon-affected mountain regions. Raw GPM IMERG precipitation data are publicly available from NASA GES DISC. The files deposited here contain the compiled landslide inventory and derived analysis products used in the accompanying study.