Research Status of Early Warning of Loess Landslides Based on Water-Suction Stress-Local Stability Factor

Journal: Architecture Engineering and Science DOI: 10.32629/aes.v3i1.667

Hai Shao1, Zhiqiang Yin2

1. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Chengdu University of Technology), Chengdu 610059, Sichuan, China China Institute of Geological Environment Monitoring, Beijing 100081, China
2. China Institute of Geological Environment Monitoring, Beijing 100081, China

Abstract

Loess is a special soil with strong water sensitivity. In recent years, the frequency of water-induced loess landslides has been increasing. It has caused great losses to people's lives and property. However, there is no mature early warning and prediction model of loess landslides based on water- suction stress-local stability factor now. Based on the research status of early warning of loess landslide based on water-suction stress-local stability factor at home and abroad, the authors analyzed the basic characteristics and instability mechanism of loess landslides induced by different factors. And the authors initially put forward the establishment of early warning model of loess landslide under different inducement conditions. During it, the authors analyzed the water content of loess, matric suction, suction stress, progressive failure process and local stability factor, and the research status of early warning and physical early warning models of loess landslide based on water-suction stress-local stability factor are discussed. Finally, the authors advanced a refined early warning model of loess landslide based on progressive failure principle and finite element method coupled with water-suction stress-local stability factor is proposed, which takes water as the main line, as well as the research contents and research schemes for realizing the model.

Keywords

water, suction-stress, local stability factor, loess landslide, early warning

Funding

The National Key Research and Development Program Project (No. 2018YFC1504704) and the China Geological Survey Grade II Project (DD20190310)

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