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Risk Mapping of Groundwater‐Drawdown‐Induced Land Subsidence in Heterogeneous Soils on Large Areas

机译:大面积非均质土壤中地下水压降引起的地面沉降风险图

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摘要

Groundwater leakage into subsurface constructions can cause reduction of pore pressure and subsidence in clay deposits, even at large distances from the location of the construction. The potential cost of damage is substantial, particularly in urban areas. The large‐scale process also implies heterogeneous soil conditions that cannot be described in complete detail, which causes a need for estimating uncertainty of subsidence with probabilistic methods. In this study, the risk for subsidence is estimated by coupling two probabilistic models, a geostatistics‐based soil stratification model with a subsidence model. Statistical analyses of stratification and soil properties are inputs into the models. The results include spatially explicit probabilistic estimates of subsidence magnitude and sensitivities of included model parameters. From these, areas with significant risk for subsidence are distinguished from low‐risk areas. The efficiency and usefulness of this modeling approach as a tool for communication to stakeholders, decision support for prioritization of risk‐reducing measures, and identification of the need for further investigations and monitoring are demonstrated with a case study of a planned tunnel in Stockholm.
机译:地下水泄漏到地下结构中会导致孔隙压力的降​​低和粘土沉积的沉降,即使距结构位置很远也是如此。潜在的破坏成本是巨大的,尤其是在城市地区。大规模过程还意味着无法完全描述的非均质土壤条件,这导致需要用概率方法估计沉降的不确定性。在本研究中,通过将两个概率模型(基于地统计学的土壤分层模型与沉降模型)耦合来估计沉降风险。分层和土壤性质的统计分析被输入到模型中。结果包括沉陷幅度和所含模型参数敏感性的空间显式概率估计。从这些区域中,将具有重大沉降风险的区域与低风险区域区分开。通过斯德哥尔摩规划隧道的案例研究,证明了这种建模方法作为与利益相关者进行沟通的工具的有效性和实用性,为降低风险措施的优先次序提供了决策支持,并确定了进一步调查和监测的必要性。

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