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青海省高家湾滑坡的形成条件分析及稳定性评价
王占巍, 赵发睿, 谢文苹, 路睿
青海省地质调查局, 青海 西宁 810000
摘要:
[目的] 评价青海省高家湾滑坡稳定性,为其灾害防治提供一定指导。[方法] 在对高家湾滑坡基本特征分析基础上,先开展其形成条件研究;其次,利用传递系数法和瑞典圆弧法实现其稳定性现状评价,并进一步采用长短时记忆神经网络构建其变形预测模型,实现其稳定性预测评价。结合稳定现状评价结果,实现其稳定性的综合研究。[结果] 高家湾滑坡具有滑坡形成的基本条件,且具有复合多期巨型规模特征,对其防治应具有综合性;同时,滑坡现状处于稳定状态,但局部次级滑坡存在失稳可能,且在不利工况条件下,稳定性将会进一步减弱;另外,据变形预测研究结果,得出其平均相对误差均小于2%,进而验证了本文优化LSTM模型的有效性,且通过外推预测,得出高家湾滑坡变形仍将继续增加,且无收敛迹象。[结论] 高家湾滑坡稳定性还会进一步减弱,趋于不利方向发展,应尽快采取必要措施切实保证滑坡稳定。
关键词:  高家湾滑坡  形成条件  稳定性评价  长短时记忆神经网络  变形预测
DOI:10.13961/j.cnki.stbctb.2020.03.012
分类号:P642.22
基金项目:国家自然科学基金项目“复杂环境条件下链生滑坡灾害研究”(51718054)
Formation Condition Analysis and Stability Evaluation of Gaojiawan Landslide in Qinghai Province
Wang Zhanwei, Zhao Farui, Xie Wenping, Lu Rui
Qinghai Geological Survey, Xi'ning, Qinghai 810000, China
Abstract:
[Objective] The stability of the Gaojiawan landslide in Qinghai Province was evaluated to provide insights for disaster prevention and control.[Methods] Based on the analysis of the basic characteristics of the landslide, the formation conditions were studied initially. Afterwards, the stability status quo was evaluated by using the transfer coefficient method and the Swedish arc method, and the deformation prediction model was constructed using the long-term and short-term memory neural network to obtain the stability prediction evaluation. Subsequently, comprehensive research on the stability was performed by combining the stability status quo evaluation results.[Results] The Gaojiawan landslide had the basic conditions for the formation of landslides, and it had the characteristics of a multistage giant scale, and hence prevention and control should be comprehensive. Simultaneously, the present scenario of the landslide was stable, but a local secondary landslide might cause loosing stability, and that stability could be further weakened under adverse conditions. In addition, according to the deformation prediction research results, the average relative error was less than 2%. The results showed that the deformation of the Gaojiawan landslide would continue to increase, and there was no sign of convergence.[Conclusion] The stability of the Gaojiawan landslide could further weaken and tend to develop in a disadvantageous direction. Necessary measures should be taken as soon as possible to ensure stability.
Key words:  Gaojiawan landslide  formation condition  stability evaluation  long-term and short-term memory neural network  deformation prediction