Boyi Li , Guilin Wang , LiChuan Chen , Fan Sun , Runqiu Wang , MingYong Liao , Hong Xu , Siyu Li , Yanfei Kang
{"title":"降雨和水库水位效应下的滑坡变形机制和耦合效应分析","authors":"Boyi Li , Guilin Wang , LiChuan Chen , Fan Sun , Runqiu Wang , MingYong Liao , Hong Xu , Siyu Li , Yanfei Kang","doi":"10.1016/j.enggeo.2024.107803","DOIUrl":null,"url":null,"abstract":"<div><div>Changes in rainfall, groundwater levels, and reservoir water levels exacerbate the deformation of water-involved landslides, accelerating the transition from landslide evolution to extinction. Extracting the destruction patterns of landslides from extensive monitoring data, and understanding their overall deformation mechanisms are crucial for geological hazard prevention and control. Herein, we took the Jiuxianping landslide in the Three Gorges Reservoir area as an example and proposed a deformation mechanism analysis model for water-related landslides based on monitoring data mining techniques. Using Granger causality testing, the study analyzes the spatiotemporal characteristics of GPS displacement data from three different profiles, which confirms that Jiuxianping exhibits a traction destruction mode. By comparing GPS displacement data and their Granger causality relationships across different profiles, we reveal that segmented sliding features of the landslide's front, middle, and trailing during its evolution. Furthermore, the impact intensity of triggering factors (rainfall and reservoir water level changes) on landslide displacement was identified. Based on GPS displacement data from profiles II–II′, an empirical mode decomposition–long short-term memory-regression model (EMD-LSTM-regression) is developed for multisource prediction of landslide displacements. The Shapley additive explanations algorithm is used to analyze the influence of rainfall and reservoir water level changes on periodic displacements at different positions of the landslide. Owing to the large area of the Jiuxianping landslide, the response to triggering factors varies across different locations. In the context of global warming and frequent extreme weather events, these findings offer important insights for preventing and mitigating water-related landslides in the Three Gorges Reservoir area, while also providing new perspectives for the analysis of global water-involved landslide deformation.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"343 ","pages":"Article 107803"},"PeriodicalIF":6.9000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of landslide deformation mechanisms and coupling effects under rainfall and reservoir water level effects\",\"authors\":\"Boyi Li , Guilin Wang , LiChuan Chen , Fan Sun , Runqiu Wang , MingYong Liao , Hong Xu , Siyu Li , Yanfei Kang\",\"doi\":\"10.1016/j.enggeo.2024.107803\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Changes in rainfall, groundwater levels, and reservoir water levels exacerbate the deformation of water-involved landslides, accelerating the transition from landslide evolution to extinction. Extracting the destruction patterns of landslides from extensive monitoring data, and understanding their overall deformation mechanisms are crucial for geological hazard prevention and control. Herein, we took the Jiuxianping landslide in the Three Gorges Reservoir area as an example and proposed a deformation mechanism analysis model for water-related landslides based on monitoring data mining techniques. Using Granger causality testing, the study analyzes the spatiotemporal characteristics of GPS displacement data from three different profiles, which confirms that Jiuxianping exhibits a traction destruction mode. By comparing GPS displacement data and their Granger causality relationships across different profiles, we reveal that segmented sliding features of the landslide's front, middle, and trailing during its evolution. Furthermore, the impact intensity of triggering factors (rainfall and reservoir water level changes) on landslide displacement was identified. Based on GPS displacement data from profiles II–II′, an empirical mode decomposition–long short-term memory-regression model (EMD-LSTM-regression) is developed for multisource prediction of landslide displacements. The Shapley additive explanations algorithm is used to analyze the influence of rainfall and reservoir water level changes on periodic displacements at different positions of the landslide. Owing to the large area of the Jiuxianping landslide, the response to triggering factors varies across different locations. In the context of global warming and frequent extreme weather events, these findings offer important insights for preventing and mitigating water-related landslides in the Three Gorges Reservoir area, while also providing new perspectives for the analysis of global water-involved landslide deformation.</div></div>\",\"PeriodicalId\":11567,\"journal\":{\"name\":\"Engineering Geology\",\"volume\":\"343 \",\"pages\":\"Article 107803\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering Geology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0013795224004034\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, GEOLOGICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Geology","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0013795224004034","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, GEOLOGICAL","Score":null,"Total":0}
Analysis of landslide deformation mechanisms and coupling effects under rainfall and reservoir water level effects
Changes in rainfall, groundwater levels, and reservoir water levels exacerbate the deformation of water-involved landslides, accelerating the transition from landslide evolution to extinction. Extracting the destruction patterns of landslides from extensive monitoring data, and understanding their overall deformation mechanisms are crucial for geological hazard prevention and control. Herein, we took the Jiuxianping landslide in the Three Gorges Reservoir area as an example and proposed a deformation mechanism analysis model for water-related landslides based on monitoring data mining techniques. Using Granger causality testing, the study analyzes the spatiotemporal characteristics of GPS displacement data from three different profiles, which confirms that Jiuxianping exhibits a traction destruction mode. By comparing GPS displacement data and their Granger causality relationships across different profiles, we reveal that segmented sliding features of the landslide's front, middle, and trailing during its evolution. Furthermore, the impact intensity of triggering factors (rainfall and reservoir water level changes) on landslide displacement was identified. Based on GPS displacement data from profiles II–II′, an empirical mode decomposition–long short-term memory-regression model (EMD-LSTM-regression) is developed for multisource prediction of landslide displacements. The Shapley additive explanations algorithm is used to analyze the influence of rainfall and reservoir water level changes on periodic displacements at different positions of the landslide. Owing to the large area of the Jiuxianping landslide, the response to triggering factors varies across different locations. In the context of global warming and frequent extreme weather events, these findings offer important insights for preventing and mitigating water-related landslides in the Three Gorges Reservoir area, while also providing new perspectives for the analysis of global water-involved landslide deformation.
期刊介绍:
Engineering Geology, an international interdisciplinary journal, serves as a bridge between earth sciences and engineering, focusing on geological and geotechnical engineering. It welcomes studies with relevance to engineering, environmental concerns, and safety, catering to engineering geologists with backgrounds in geology or civil/mining engineering. Topics include applied geomorphology, structural geology, geophysics, geochemistry, environmental geology, hydrogeology, land use planning, natural hazards, remote sensing, soil and rock mechanics, and applied geotechnical engineering. The journal provides a platform for research at the intersection of geology and engineering disciplines.