Contributions of climate and population change to global flood–landslide multi-hazard population exposure under future climate scenarios

Flood and landslide hazards frequently overlap spatially, thereby increasing population exposure worldwide. However, global assessments quantifying flood–landslide multi-hazard population exposure and disentangling the relative roles of climate and population change remain limited. Here, we develop a global framework integrating multi-source remote sensing datasets, machine learning-based susceptibility models validated with both non-spatial and spatial cross-validation, and a multi-hazard risk matrix to delineate high-risk areas under historical and future climate scenarios (SSP1–2.6, SSP2–4.5, SSP5–8.5). Population exposure is quantified within these areas at 10 km resolution, revealing pronounced national-scale concentration, with China and India together accounting for more than 40 % of the population residing within high and extremely high risk areas. Baseline exposure, representing inherited population distributions and historical hazard configurations, constitutes the largest share of total future population exposure, illustrating the enduring structural determinants of risk. Relative contribution analysis further reveals pronounced scenario-dependent variability in the drivers of future exposure growth. Population change dominates exposure increases under the intermediate-emission pathway, whereas climatic and demographic contributions become comparatively more balanced under both low- and high-emission scenarios. Joint effects remain limited overall, but become increasingly evident within stricter high-risk areas. These results highlight the scenario-dependent interplay between climatic and demographic drivers and demonstrate the importance of baseline population structures in shaping future exposure. Collectively, this framework provides a systematic basis for evaluating the drivers and uncertainties of global flood–landslide exposure, informing targeted adaptation strategies and multi-hazard risk management under global change.