Multi-scale geotechnical features of dredger fills and subsidence risk evaluation in reclaimed land using BN

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 km 2 ), site-scale (1 m 2 -1 km 2 ), mesoscale (1 cm 2 -1 m 2 ), and micr...

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Bibliographic Details
Published in:Marine georesources & geotechnology 2020-09, Vol.38 (8), p.947-969
Main Authors: Wu, Linbo, Wang, Jianxiu, Zhou, Jie, Yang, Tianliang, Yan, Xuexin, Zhao, Yu, Ye, Zhenhua, Xu, Na
Format: Article
Language:English
Subjects:
Bayesian analysis
Bayesian network
Boreholes
Coastal zone
Data points
Dredgers
Geotechnical engineering
Independent variables
Inspection
Land reclamation
Land subsidence
Multiscale analysis
Probability theory
Reclaimed land
Regions
Risk assessment
Risk levels
soil heterogeneity
Soil investigations
Soil properties
Soil structure
Soils
Strata
Subsidence
Thickness
Velocity
Void ratio
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Summary: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 km 2 ), site-scale (1 m 2 -1 km 2 ), mesoscale (1 cm 2 -1 m 2 ), and microscale (1 µm 2 -1 cm 2 ) 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.
ISSN:1064-119X
1521-0618
DOI:10.1080/1064119X.2019.1644406