Influence of Earthquakes on Landslide Susceptibility in a Seismic Prone Catchment in Central Asia

• Published in: Applied sciences Vol. 11; no. 9; p. 3768
• Main Authors: Li, Fengqing, Torgoev, Isakbek, Zaredinov, Damir, Li, Marina, Talipov, Bekhzod, Belousova, Anna, Kunze, Christian, Schneider, Petra
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-05-2021
• Subjects: Annual precipitation; Catchments; earthquake impacts; Earthquakes; Environmental impact; Environmental risk; Equilibrium analysis; Fault detection; Fault lines; Geomorphology; Grasslands; Landslides; Landslides & mudslides; limit equilibrium method; Mountains; Pollution dispersion; Precipitation; radioactive contamination; Risk management; River networks; Scoops3D; Seismic activity; Seismic engineering; Seismic stability; Slope stability; Soils; Spatial variations; Stability analysis; Streams; Tien Shan Mountains; Topography; Transboundary pollution; Variables; Vegetation; volume estimation; Central Asia; Tien Shan Mountains
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app11093768

Central Asia is one of the most challenged places, prone to suffering from various natural hazards, where seismically triggered landslides have caused severe secondary losses. Research on this problem is especially important in the cross-border Mailuu-Suu catchment in Kyrgyzstan, since it is burdened by radioactive legacy sites and frequently affected by earthquakes and landslides. To identify the landslide-prone areas and to quantify the volume of landslide (VOL), Scoops3D was selected to evaluate the slope stability throughout a digital landscape in the Mailuu-Suu catchment. By performing the limit equilibrium analysis, both of landslide susceptibility index (LSI) and VOL were estimated under five earthquake scenarios. The results show that the upstream areas were more seismically vulnerable than the downstream areas. The susceptibility level rose significantly with the increase in earthquake strength, whereas the VOL was significantly higher under the extreme earthquake scenario than under the other four scenarios. After splitting the environmental variables into sub-classes, the spatial variations of LSI and VOL became more clear: the LSI reduced with the increase in elevation, slope, annual precipitation, and distances to faults, roads, and streams, whereas the highest VOL was observed in the areas with moderate elevations, high precipitation, grasslands, and mosaic vegetation. The relative importance analysis indicated that the explanatory power reduced with the increase in earthquake level and it was significant higher for LSI than for VOL. Among nine environmental variables, the distance to faults, annual precipitation, slope, and elevation were identified as important triggers of landslides. By a simultaneous assessment of both LSI and VOL and the identification of important triggers, the proposed modelling approaches can support local decision-makers and householders to identify landslide-prone areas, further design proper landslide hazard and risk management plans and, consequently, contribute to the resolution of transboundary pollution conflicts.