Simultaneous identification of groundwater contaminant sources and simulation of model parameters based on an improved single-component adaptive Metropolis algorithm-Reference-Cited by-同舟云学术

Simultaneous identification of groundwater contaminant sources and simulation of model parameters based on an improved single-component adaptive Metropolis algorithm

Published:2020-11-11 Issue:2 Volume:29 Page:859-873
ISSN:1431-2174
Container-title:Hydrogeology Journal
language:en
Short-container-title:Hydrogeol J

Author:

Chang Zhenbo,Lu Wenxi,Wang Han,Li Jiuhui,Luo Jiannan

Funder

the National Key Research and Development Program of China

The National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Water Science and Technology

Link

http://link.springer.com/content/pdf/10.1007/s10040-020-02257-0.pdf

Reference45 articles.

1. Asher MJ, Croke BFW, Jakeman AJ, Peeters LJ (2015) A review of surrogate models and their application to groundwater modeling. Water Resour Res 51(8):5957–5973. https://doi.org/10.1002/2015WR016967

2. Atmadja J, Bagtzoglou AC (2001) State of the art report on mathematical methods for groundwater pollution source identification. Environ Forensic 2(3):205–214. https://doi.org/10.1006/enfo.2001.0055

3. Ayvaz MT (2010) A linked simulation–optimization model for solving the unknown groundwater pollution source identification problems. J Contam Hydrol 117(1–4):46–59. https://doi.org/10.1016/j.jconhyd.2010.06.004

4. Ayvaz MT, Karahan H (2008) A simulation optimization model for the identification of unknown groundwater well locations and pumping rates. J Hydrol 357(1–2):76–92. https://doi.org/10.1016/j.jhydrol.2008.05.003

5. Bagtzoglou AC, Atmadja J (2005) Mathematical methods for hydrologic inversion: the case of pollution source identification. In: Kassim TA (ed) Environmental impact assessment of recycled wastes on surface and ground waters, vol 3. The handbook of environmental chemistry, water pollution series, vol 5, part F. Springer, Heidelberg, Germany, pp 65–96. https://doi.org/10.1007/b11442

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Application of observed data denoising based on variational mode decomposition in groundwater pollution source recognition;Science of The Total Environment;2024-10

2. Simultaneous identification of groundwater contamination source information, model parameters, and boundary conditions under an unknown boundary mode;Stochastic Environmental Research and Risk Assessment;2024-08-30

3. Groundwater LNAPL Contamination Source Identification Based on Stacking Ensemble Surrogate Model;Water;2024-08-12

4. Groundwater Contamination Source Recognition Based on a Two-Stage Inversion Framework with a Deep Learning Surrogate;Water;2024-07-03

5. Identification of hydraulic conductivity and groundwater contamination sources with an Unscented Kalman Smoother;Stochastic Environmental Research and Risk Assessment;2024-06-27