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A combined search method based on a deep learning combined surrogate model for groundwater DNAPL contamination source identification by Zibo Wang; Wenxi Lu; Zhenbo Chang; Jiannan Luo is a Environmental Science article available to read on EtoBox.

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Ensemble Kalman filter (EnKF) and optimization methods are two mainstream methods in groundwater contamination source identification, but most researchers usually only use or improve on one method. However, each method has strengths and weaknesses, and using one method alone may cause inaccuracy of the identification results for complex situations. Therefore, it is necessary to explore the combination of methods. In this paper, for the optimization method, to further enhance the solution precision of the optimization model for groundwater dense non-aqueous phase liquid (DNAPL) contamination source identification (GDCSI), we first constructed an improved butterfly optimization algorithm by introducing the dynamic switching probability mechanism in the previous butterfly optimization algorithm. Next, the EnKF method and optimization method (based on the improved butterfly optimization algorithm) were used respectively for GDCSI, to assess the strengths and weaknesses of the methods. Then, according to the strengths and weaknesses of the EnKF and optimization methods, the two methods were merged to build a more robust and practical combined search method (CSM) for GDCSI, to further en

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Author

Zibo Wang; Wenxi Lu; Zhenbo Chang; Jiannan Luo

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Environmental Science (Physical Sciences)