Landslide susceptibility over the Tibetan Plateau in a warming climate

Introduction The Tibetan Plateau (TP) is experiencing increasingly frequent landslides under climate warming. Projecting landslide susceptibility across the TP requires joint representation of antecedent rainfall, soil wetness and temperature under changing climate conditions. Methods Here we use 38 hydroclimatic and slope predictors to project daily susceptibility under SSP1-2.6 and SSP5-8.5 through 2100. CatBoost and XGBoost scores are averaged to provide a common basis for scenario comparisons. Results Maximum antecedent daily precipitation is the leading predictor in both models. Under SSP5-8.5, the annual fraction of grid cells classified as High or Very High increases by 4.37 percentage points per decade and reaches 51.2% in 2100. Increased susceptibility in June and September accompanies the July–August peak. For 2081–2100, the regional mean increases from 0.3103 to 0.3198 across precipitation perturbations of 0–50%, with progressively larger increments between successive levels. Discussion These results identify spatially heterogeneous hydroclimatic responses and a nonlinear regional-mean perturbation response, informing spatial and seasonal priorities for landslide monitoring.