滑坡一体化全维度监测预警技术进展与展望

Progress and prospect of integrated full-dimensional monitoring and early warning technology for landslides

为应对我国复杂多变地质环境下工程活动与自然地质作用的叠加效应,突破单一化监测手段在表征滑坡灾变演化过程中的局限性,以实现滑坡隐患早期识别和灾害精准预警,首先概括性描述当前用于滑坡监测的天基、空基、地基与体基的天-空-地-体一体化全维度监测预警技术的研究现状;然后从隐患早期识别与应急监测、多源多维一体化智能监测、新材料、新工艺交叉监测及基于分布式声学感测(DAS)技术的海底滑坡监测等方面,总结近年来滑坡监测预警领域中理论、技术与应用方面取得的成果;最后基于多种监测技术的局限性,展望滑坡监测面临的挑战与发展趋势。研究表明:通过综述性对比滑坡一体化全维度监测预警技术,得出多种技术的适用条件和优缺点,然而由于这些技术的指标差异,往往会导致数据漏判与误判,未来应将研究重点聚焦于预警判据标准和系统建模方面。

In order to deal with the superposition effect of human engineering activities and natural geological processes under the complex and changeable geological environment in China,the limitations of single monitoring means in characterizing the landslide hazard evolution process was broken to realize the early identification of landslide hazards and accurate early warning of disasters.Firstly,this paper generally describes the current research status of full-dimension monitoring and early warning technology of integrated monitoring for the air,space,ground,and interior.Then from the aspects of early identification and emergency monitoring of potential hazards,multi-source and multi-dimensional integrated intelligent monitoring,cross-monitoring of new materials and new processes,and monitoring of submarine landslide based on DAS(Distributed Acoustic Sensing)technology.The achievements of theory,technology,and application in landslide monitoring and early warning in recent years are summarized.Finally,based on the limitations of various monitoring technologies,the challenges and development trends of current landslide monitoring are prospected.The research shows that various technologies'application conditions,advantages,and disadvantages are obtained through the comprehensive comparison of landslide integrated full dimension monitoring and early warning technologies.However,the difference in various monitoring technical indicators often leads to missing and miscalculating monitoring data.In the future,the research should focus on early warning criteria and system modeling.