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

Fengqing LiDepartment of Water, Environment, Construction and Safety, Magdeburg-Stendal University of Applied Sciences, Breitscheidstr. 2, 39114 Magdeburg, GermanyIsakbek TorgoevScientific Engineering Centre “GEOPRIBOR” of the National Academy of Sciences of the Kyrgyz Republic, Mederova Str. 98, Bishkek 720052, KyrgyzstanDamir ZaredinovThe Ministry of Health of the Republic of Uzbekistan, 12 Navoi Street, Tashkent 100011, UzbekistanMarina LiThe Ministry of Health of the Republic of Uzbekistan, 12 Navoi Street, Tashkent 100011, UzbekistanBekhzod TalipovA. P. BelousovaC&E Consulting und Engineering GmbH, Jagdschänkenstr. 52, 09117 Chemnitz, GermanyChristian KunzePetra SchneiderDepartment of Water, Environment, Construction and Safety, Magdeburg-Stendal University of Applied Sciences, Breitscheidstr. 2, 39114 Magdeburg, Germany
Applied Sciencesjournal2021en
ABI

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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.

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