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A least squares method for identification of unknown groundwater pollution source.

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Title: A least squares method for identification of unknown groundwater pollution source.
Authors: Zhukun He1,2, Rui Zuo1,2 zr@bnu.edu.cn, Dan Zhang3, Pengcheng Ni1,2, Kexue Han1,2, Zhenkun Xue1,2, Jinsheng Wang1,2, Donghui Xu1,2
Source: Hydrology Research. Apr2021, Vol. 52 Issue 2, p450-460. 11p.
Subjects: Groundwater pollution, Least squares, Pollution prevention, Pollution remediation, Analytical solutions, Fuel tanks
Abstract: The identification of unknown groundwater pollution sources is one of the most important premises in groundwater pollution prevention and remediation. In this paper, an exploratory application of a least squares method to identify the unknown groundwater pollution source is conducted. Supported by a small amount of observation data and the analytical solutions of the pollutant transport model, the initial concentration, the leakage location and the pollutant mass are identified by using the least squares method under a sand tank experiment and a gas station area. In the sand tank experiment, it is found that the fitting errors of three cross-sections are within 6%. In the gas station area, it is found that the results are nearly consistent with the site investigation information. The results indicate that the least squares method has considerable application values in the identification of groundwater pollution sources. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:The identification of unknown groundwater pollution sources is one of the most important premises in groundwater pollution prevention and remediation. In this paper, an exploratory application of a least squares method to identify the unknown groundwater pollution source is conducted. Supported by a small amount of observation data and the analytical solutions of the pollutant transport model, the initial concentration, the leakage location and the pollutant mass are identified by using the least squares method under a sand tank experiment and a gas station area. In the sand tank experiment, it is found that the fitting errors of three cross-sections are within 6%. In the gas station area, it is found that the results are nearly consistent with the site investigation information. The results indicate that the least squares method has considerable application values in the identification of groundwater pollution sources. [ABSTRACT FROM AUTHOR]
ISSN:19989563
DOI:10.2166/nh.2021.088