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INDUSTRIAL EXPERIENCE FEEDBACK OF A GEOSTATISTICAL ESTIMATION OF CONTAMINATED SOIL VOLUMES

机译:污染土壤体积的地统计学估计的工业经验反馈

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Geostatistics meets a growing interest for the remediation forecast of potentially contaminated sites, by providing adapted methods to perform both chemical and radiological pollution mapping, to estimate contaminated volumes, potentially integrating auxiliary information, and to set up adaptive sampling strategies. As part of demonstration studies carried out for GeoSiPol (Geostatistics for Polluted Sites), geostatistics has been applied for the detailed diagnosis of a former oil depot in France. The ability within the geostatistical framework to generate pessimistic / probable / optimistic scenarios for the contaminated volumes allows a quantification of the risks associated to the remediation process: e.g. the financial risk to excavate clean soils, the sanitary risk to leave contaminated soils in place. After a first mapping, an iterative approach leads to collect additional samples in areas previously identified as highly uncertain. Estimated volumes are then updated and compared to the volumes actually excavated. This benchmarking therefore provides a practical feedback on the performance of the geostatistical methodology.
机译:通过提供适用于执行化学和放射污染制图,估算污染量,潜在整合辅助信息以及建立自适应采样策略的适应方法,地统计学对潜在污染站点的补救预测越来越引起人们的兴趣。作为对GeoSiPol(污染场地的地统计学)进行的论证研究的一部分,地统计学已用于法国前油库的详细诊断。地统计学框架内针对受污染量生成悲观/可能/乐观方案的能力可以量化与修复过程相关的风险:开挖干净土壤的财务风险,将受污染土壤留在原地的卫生风险。在第一次映射之后,迭代方法导致在先前确定为高度不确定的区域中收集其他样本。然后更新估计的体积,并将其与实际挖掘的体积进行比较。因此,该基准测试提供了有关地统计方法学性能的实用反馈。

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