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Field application at a DNAPL-contaminated site in Nanjing and discussion of a source search algorithm based on stochastic modeling and Kalman filter
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文摘
Delineation of contaminant sources is vital for successful groundwater and soil remediation. With reliable source information, remediation time and cost can be dramatically reduced. An optimal contamination source search strategy incorporating Monte Carlo method, Kalman filtering and fuzzy set theory was applied to a contaminated site in Nanjing to define suspected multiple DNAPL source locations. Using the available nine sample data, the algorithm identified sources #1 and #4 as true sources, and sources #5 and #6 as false ones. The algorithm results for sources #2 and #3 were inconclusive. Three numerical experiments based on specific site conditions were then designed and conducted to determine the influencing factors on the algorithm’s convergence in sources #2 and #3. The numerical experiments tested the effect of multiple sources, the effect of the sources location in relation to the groundwater flow direction and the effect of a low permeability field on the convergence of the algorithm. Based on the numerical experiments and an understanding of the manufacturing site operations, sources #2 and #3 are likely to be true sources. Their moderate weights have been stabilized due to the existence of multiple true sources and the scarcity of informative sampling data, caused by the low permeability field. The moderate weight value of source #3 also includes a contribution from an overlapping plume caused by the sources’ parallel-to-flow layout pattern. It can be concluded that the algorithm works best for high permeability sites where potential source locations are scattered and source location patterns are orthogonal to the groundwater flow.

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