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Multi-scale geotechnical features of dredger fills and subsidence risk evaluation in reclaimed land using BN
Authors:Linbo Wu  Jianxiu Wang  Jie Zhou  Tianliang Yang  Xuexin Yan  Yu Zhao
Affiliation:1. College of Civil Engineering, Tongji University, Shanghai, China;2. 26linbowu@tongji.edu.cn;4. Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education, Tongji University, Shanghai, China;5. Key Lab of Environment Protection &6. Safety in Foundation Engineering of Transportation, China Communication Construction Company Ltd., Guangzhou, China;7. Key Laboratory of Land Subsidence Monitoring, Prevention and Control of Ministry of Land and Resources, Shanghai Institute of Geological Survey, Shanghai, China
Abstract:Abstract

Shanghai has the largest newly reclaimed area in China’s coastal regions, and dredger fills are universally distributed in reclaimed lands there. Multi-scale geotechnical properties of dredger fills in region-scale (>1?km2), site-scale (1?m2–1?km2), mesoscale (1?cm2–1 m2), and microscale (1?µm2–1?cm2) were studied mainly through cone penetration investigation, borehole investigation, and microscopic inspections. Dredger impact craters, soil structures, and soil textures were investigated qualitatively and quantitatively to identify the dredger fills. Ultimate land subsidence since 1 July 2018 and land subsidence velocity characterized by the land subsidence from 1 July 2018 to 1 January 2019 were evaluated in Shanghai’s typical reclaimed regions. Afterwards, Bayesian network including sixteen variables was proposed for land subsidence risk assessment. Surface subsidence, land subsidence velocity, and comprehensive land subsidence were the most sensitive to data point location and average initial void ratio of underlying strata. These three risk variables were also highly correlated to the thickness of the dredger fill layer and the reclamation time. This finding indicates that variances of the four independent variables (i.e., data point location, average initial void of underlying strata, land reclamation time, and thickness of dredger fill layer) significantly decide variances of the three risk levels.
Keywords:Land reclamation  land subsidence  soil heterogeneity  Bayesian network
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