ArticleScientific reports2026
Exploring rainfall effects on the Xingfu Dayuan Landslide in Yecheng, Xinjiang, China using time-series InSAR technology and numerical simulation.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Rainfall-induced landslides are increasingly frequent in loess-covered regions of Xinjiang, China, posing a serious threat to residents and infrastructure. This study investigates the deformation behavior and stability response of the Xingfu Dayuan landslide in Yecheng County, aiming to clarify how rainfall characteristics control landslide development. Field investigations, time-series InSAR-based deformation monitoring, and numerical simulations were integrated to analyze landslide evolution from 2022 to 2024. Satellite observation results reveal that deformation is unevenly distributed across the slope and is most pronounced in the middle and lower sections, where average deformation rates reach approximately 15–18 mm per year, and cumulative displacement exceeds 50 mm, indicating that the landslide remains active. Deformation intensified from 2023 to 2024 and exhibited clear seasonal variations, with accelerated movement during periods of concentrated rainfall and higher temperatures. Numerical simulation results reveal that rainfall infiltration significantly increases internal water pressure, with infiltration depths extending from about 4 m under low-intensity rainfall to nearly 8 m during extreme rainfall events. As a result, slope stability decreases progressively, with the stability factor approaching or falling below the critical threshold. Notably, the minimum stability does not occur during rainfall but typically 12–24 h after rainfall ceases, revealing a pronounced delayed response of the loess slope to rainfall infiltration. These findings demonstrate that rainfall intensity, duration, and post-rainfall infiltration jointly control loess landslide deformation and stability, highlighting the importance of considering delayed instability in landslide hazard assessment and early warning.
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