Generating strategies for land subsidence control and remediation based on risk classification evaluation in Tianjin, China

Yi, Lixin; Yanxiang, Jiang; Zheng, Yuanyi; Dong, Lixin; Kang, Jian; Yuan, Jing; Yang, Yongpeng

doi:10.1007/s11069-022-05410-y

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…Land subsidence is a complex nonlinear phenomenon, and accurate prediction necessitates the inclusion of causative factors with substantial influence on subsidence occurrence in analysis and prediction models. Considering the subsidence mechanisms and influencing factors discussed earlier, geological background (GB), current land subsidence status (LS), and groundwater exploitation (GE) are identified as primary evaluation indicators for hazard assessment 50 . From a geological background perspective, the Cenozoic strata constitute the primary subsidence layer in the study area, with the thickness of these strata directly impacting subsidence occurrence and development.…”

Section: Methodsmentioning

confidence: 99%

Risk assessment of land subsidence based on GIS in the Yongqiao area, Suzhou City, China

Chai,

Wei,

Cai

et al. 2024

Sci Rep

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This study focuses on the Yongqiao District in Suzhou City, Anhui Province, China, aiming to analyze the current situation of ground settlement and its influencing factors in the area. The selected risk indices include settlement rate, cumulative settlement amount, groundwater level drop funnel, thickness of loose sediment layer, thickness of soft soil layer, and the number of groundwater extraction layers. Additionally, vulnerability indices such as population density, building density, road traffic, and functional zoning are considered. An evaluation index system for assessing land Subsidence risk was established. The risk evaluation of land Subsidence was conducted using the Hierarchical analysis-composite index method and ArcGIS spatial analysis, The evaluation results show that the area of higher risk area is about 2.82 km2, accounting for 0.96% of the total area, mainly distributed in the area of Jiuli village, Sanba Street. The middle risk area is distributed around the higher area, with an area of about 9.18 km2, accounting for 3.13% of the total area. The lower risk areas were distributed in most of the study area, covering an area of 222.24 km2, accounting for 75.82% of the total area. The low risk assessment area is mainly distributed in Bianhe Street and part of Zhuxianzhuang Town, with an area of about 58.88 km2, accounting for 20.09% of the total area. The findings of this study are not only crucial for informing local policies and practices related to land use planning, infrastructure development, and emergency response but also enhance our understanding of the complexities of land Subsidence processes and their interactions with human activities, informing future research and practice in environmental risk assessment and management.

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Section: Methodsmentioning

confidence: 99%

Risk assessment of land subsidence based on GIS in the Yongqiao area, Suzhou City, China

Chai,

Wei,

Cai

et al. 2024

Sci Rep

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“…Researchers have explored the application of InSAR in evaluating surface deformation risks related to urban geohazards like ground subsidence and secondary natural geohazards such as landslides. However, these studies underscore the adaptability of the risk evaluation system, meaning that indicators within the system can be added, deleted, or modified based on the actual circumstances and attributes of the study area [23,48,50].…”

Section: Risk Evaluation Methodsmentioning

confidence: 99%

“…However, the absence of research on subsidence risk evaluation poses a challenge in offering reliable assistance for practical management. The comprehensive risk evaluation process for ground subsidence typically involves three key stages: indicator selection, determination of indicator weights, and construction of a mathematical model [23]. Monitoring and analyzing the spatial and temporal characteristics of ground subsidence constitute fundamental research, while uncovering and exploring influencing factors represent a research process.…”

Section: Introductionmentioning

confidence: 99%

Integrated Assessment of Coastal Subsidence in Nansha District, Guangzhou City, China: Insights from SBAS-InSAR Monitoring and Risk Evaluation

Wang,

Sun,

Wei

et al. 2024

Remote Sensing

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Monitoring and assessing coastal subsidence is crucial to mitigating potential disaster risks associated with rising sea levels. Nansha District in Guangzhou City, representing global coastal soft-soil urban areas, faces significant challenges related to ground subsidence. However, the current understanding of the status, causative factors, and risk (includes subsidence susceptibility and vulnerability) assessment of ground subsidence in Nansha District is unclear. To address this gap, we utilized the SBAS-InSAR technique, analyzing 49 Sentinel-1A images from December 2015 to June 2019, for systematic ground subsidence monitoring. Subsequently, we assessed subsidence risk using a comprehensive index method and a risk matrix. Our findings indicate that subsidence velocity primarily ranged from −40 to −5 mm/a, with a spatial pattern of increasing subsidence from inland to coastal areas. The cumulative subsidence process unfolded in four distinct stages. The genesis of land subsidence was linked to an endogenous geological context dominated by soft-soil deposition, influenced by external factors such as surface loading and groundwater extraction. High-risk zones were concentrated in key engineering development areas, transportation pipeline trunk lines, and densely populated regions, demanding special attention. This study provides a foundational resource for disaster prevention and control strategies in Nansha District and similar coastal cities.

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Evaluating the Safety and Control Scheme of Coastal Railway Using Land Subsidence Coupling Model

Yang,

Jia,

Yang

et al. 2023

KSCE J Civ Eng

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Generating strategies for land subsidence control and remediation based on risk classification evaluation in Tianjin, China

Cited by 4 publications

References 24 publications

Risk assessment of land subsidence based on GIS in the Yongqiao area, Suzhou City, China

Risk assessment of land subsidence based on GIS in the Yongqiao area, Suzhou City, China

Integrated Assessment of Coastal Subsidence in Nansha District, Guangzhou City, China: Insights from SBAS-InSAR Monitoring and Risk Evaluation

Evaluating the Safety and Control Scheme of Coastal Railway Using Land Subsidence Coupling Model

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