Research progress on landslide deformation monitoring and early warning technology
DENG Lizheng1,2,4, YUAN Hongyong1, ZHANG Mingzhi1,3,4, CHEN Jianguo1
1. Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing 100084, China; 2. Hefei Institute for Public Safety Research, Tsinghua University, Hefei 230601, China; 3. China Institute of Geo-Environment Monitoring(Geological Disaster Technical Guidance Center of Ministry of Natural Resources), Beijing 100081, China; 4. Technology Innovation Centerfor Geohazard Monitoring and Risk Early Warning, Ministry of Natural Resources of the People's Republic of China, Beijing 100081, China
Abstract：[Significance] Landslide hazards are widely distributed in China and are severely harmful. The registered landslide hazards have achieved remarkable benefits in disaster reduction through a comprehensive prevention and control system. However, approximately 80% of all geo-disasters in China still occur outside the scope of identified hazards yearly. Therefore, monitoring and early warning are important means to actively prevent landslide disasters and achieve great success in disaster mitigation owing to promptness, effectiveness, and relatively low-cost advantages. Deformation is the most significant monitoring parameter for landslides and has become a focus and general trend. Landslide deformation monitoring engineering has strict requirements for controlled cost and high reliability to achieve widespread application and accurate early warning. Therefore, the commonly used monitoring instruments focus on surface deformation and rainfall to meet the requirements for easy equipment installation and low implementation cost. However, surface deformation and rainfall are not sufficient conditions to determine the occurrence of landslides. Various challenges exist in the existing monitoring technologies and early warning methods regarding engineering feasibility and performance improvement. Thus, it is important and urgent to summarize the existing research to rationally guide future development.[Progress] The deformation monitoring methods are divided into surface and subsurface monitoring. Most surface deformation monitoring technologies are vulnerable to the interference of terrain, environment, and other factors; therefore, their timeliness and reliability are not easily guaranteed. Additionally, slope subsurface deformation monitoring technologies can directly obtain the development and damage information of the sliding surface; thus, they can recognize the disaster precursor. Subsurface monitoring has advanced early warning ability; however, the existing instruments have problems, such as high cost, small measuring range, or difficult operation. Acoustic emission technology has the advantages of low cost, high sensitivity, and continuous real-time monitoring of large deformation, and has gradually developed into an optional method for landslide subsurface deformation monitoring. Thus, efficient landslide monitoring should comprehensively use multiple technologies to overcome the limitations of a single technology, and an integrated monitoring system becomes the state-of-the-art trend. The purpose of landslide monitoring is to provide a basis for decision-making of disaster early warning, thus, avoiding casualties and property losses through effective early warning efforts. In the field of early warning, regional meteorological and individual landslide early warning methods are gradually developed and improved. Deformation monitoring data are the main basis for landslide early warning, and experts analyze the deformation trend and sudden change characteristics. Different early warning levels could be triggered by the threshold values of velocity, acceleration, or other criteria. However, a landslide has complex dynamic mechanisms and individual differences; thus, the generic early warning model needs further exploration. The intelligent early warning model integrates machine learning technology with geological engineering analysis to improve the accuracy and automation level of landslide early warning.[Conclusions and Prospects] Deformation monitoring is essential in landslide prevention, and deformation data are the main basis for landslide early warning. Moreover, surface monitoring technologies have been widely used in the perception and decision-making process of landslides. Subsurface monitoring technologies can detect early precursors of landslide evolution to continuously improve early warning accuracy. Analyses show that early warning methods can be improved in the future by integrating machine learning models and geotechnical engineering.
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2023, Vol. 63 
