Optimal Unknown Pollution Source Characterization in a Contaminated Groundwater Aquifer—Evaluation of a Developed Dedicated Software Tool

ISSN Print: 2327-4336
ISSN Online: 2327-4344
www.scirp.org/journal/gep
E-mail: gep@scirp.org

"Optimal Unknown Pollution Source Characterization in a Contaminated Groundwater Aquifer—Evaluation of a Developed Dedicated Software Tool"
written by Bithin Datta, Om Prakash, Pauline Cassou, Mathieu Valetaud,
published by Journal of Geoscience and Environment Protection, Vol.2 No.5, 2014

has been cited by the following article(s):

[1]	Development of a multi-level factorial data assimilation approach for groundwater contaminant sources identification
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[2]	Groundwater contamination source identification based on Sobol sequences–based sparrow search algorithm with a BiLSTM surrogate model
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[3]	Identification of Clandestine Groundwater Pollution Sources in Aquifer Polluted with BTEX
	Journal of Water Resources Planning …, 2023

[4]	Numerical Simulation of Carbon Tetrachloride Pollution-Traceability in Groundwater System of an Industrial City
	Sustainability, 2022

[5]	An Integrated Bayesian and Machine Learning Approach Application to Identification of Groundwater Contamination Source Parameters
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[6]	Further discussion on the influence radius of a pumping well: A parameter with little scientific and practical significance that can easily be misleading
	Water, 2021

[7]	A Bayesian-based integrated approach for identifying groundwater contamination sources
	2019

[8]	A hybrid simulation–optimization approach for solving the areal groundwater pollution source identification problems
	Journal of Hydrology, 2016

[1]	Groundwater contamination source identification based on Sobol sequences–based sparrow search algorithm with a BiLSTM surrogate model Environmental Science and Pollution Research, 2023 DOI:10.1007/s11356-023-25890-0

[2]	Groundwater contamination source identification based on Sobol sequences–based sparrow search algorithm with a BiLSTM surrogate model Environmental Science and Pollution Research, 2023 DOI:10.1007/s11356-023-25890-0

[3]	An Integrated Bayesian and Machine Learning Approach Application to Identification of Groundwater Contamination Source Parameters Water, 2022 DOI:10.3390/w14152447

[4]	Further Discussion on the Influence Radius of a Pumping Well: A Parameter with Little Scientific and Practical Significance That Can Easily Be Misleading Water, 2021 DOI:10.3390/w13152050