Spatiotemporal dynamics of landslide susceptibility under future climate change and land use scenarios

Abstract Mountainous landslides are expected to worsen due to environmental changes, yet few studies have quantified their future risks. To address this gap, we conducted a comprehensive analysis of the eastern Hindukush region of Pakistan. A geospatial database was developed, and logistic regression was employed to evaluate baseline landslide susceptibility for 2020. Using the latest coupled model intercomparison project 6 models under three shared socioeconomic pathways (SSPs) and the cellular automata-Markov model, we projected future rainfall and land use/land cover patterns for 2040, 2070, and 2100, respectively. Our results reveal significant changes in future rainfall and land use patterns, particularly in the long-term future (2070 and 2100). Future landslide susceptibility was then predicted based on these projections. By 2100, high-risk landslide areas are expected to increase substantially under all SSP scenarios, with the largest increases observed under SSP5-8.5 (56.52%), SSP2-4.5 (53.55%), and SSP1-2.6 (22.45%). By 2070, high-risk areas will rise by 43.08% (SSP1-2.6), 40.88% (SSP2-4.5), and 12.60% (SSP5-8.5). However, by 2040, the changes in high-risk areas are minimal compared to the baseline, with increases of 9.45% (SSP1-2.6), 1.69% (SSP2-4.5), and 7.63% (SSP5-8.5). These findings provide crucial insights into the relationship between environmental changes and landslide risks and support the development of climate risk mitigation, land use planning, and disaster management strategies for mountainous regions.