Joint identification of contaminant source and dispersion coefficients based on multi-observed reconstruction and ensemble Kalman filtering-Reference-Cited by-同舟云学术

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Joint identification of contaminant source and dispersion coefficients based on multi-observed reconstruction and ensemble Kalman filtering

Published:2024-07-09 Issue:9 Volume:38 Page:3565-3585
ISSN:1436-3240
Container-title:Stochastic Environmental Research and Risk Assessment
language:en
Short-container-title:Stoch Environ Res Risk Assess

Author:

Jing Li,Kong Jun,Pan Mingjie,Zhou Tong,Xu Teng

Funder

Fundamental Research Funds for the Central Universities

Postgraduate Research & Practice Innovation Program of Jiangsu Province

National Key Research and Development Program of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00477-024-02767-3.pdf

Reference52 articles.

1. Alapati S, Kabala ZJ (2000) Recovering the release history of a groundwater contaminant using a nonlinear least-squares method. Hydrol Process 14:1003–1016

2. Andre L, Pauss A, Ribeiro T (2017) A modified method for COD determination of solid waste, using a commercial COD kit and an adapted disposable weighing support. Bioprocess Biosyst Eng 40:473–478

3. Barati Moghaddam M, Mazaheri M, Samani MVJ (2021) Inverse modelling of contaminant transport for pollution source identification in surface and groundwaters: a review. Groundw Sustain Dev 15:100651

4. Bauser HH, Berg D, Klein O, Roth K (2018) Inflation method for ensemble Kalman filter in soil hydrology. Hydrol Earth Syst Sci 22(9):4921–4934

5. Chen YP, Wang HM (2013) Fluid dynamics, 2nd edn. Tsinghua University Press, Beijing. ISBN 978-7-302-30734-1

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