A new approach for assessing the assembled vulnerability of coastal aquifers based on optimization models

Gharekhani, M; Reza Nikoo, M; Allah Nadiri, A; Al-Rawas, G; Sana, A; Gandomi, AH; Nematollahi, B; Senapathi, V

A new approach for assessing the assembled vulnerability of coastal aquifers based on optimization models

Gharekhani, M Reza Nikoo, M Allah Nadiri, A Al-Rawas, G Sana, A Gandomi, AH Nematollahi, B Senapathi, V

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Journal of Hydrology, 2023, 625
Issue Date:: 2023-10-01

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Field	Value	Language
dc.contributor.author	Gharekhani, M
dc.contributor.author	Reza Nikoo, M
dc.contributor.author	Allah Nadiri, A
dc.contributor.author	Al-Rawas, G
dc.contributor.author	Sana, A
dc.contributor.author	Gandomi, AH
dc.contributor.author	Nematollahi, B
dc.contributor.author	Senapathi, V
dc.date.accessioned	2024-03-17T22:47:53Z
dc.date.available	2024-03-17T22:47:53Z
dc.date.issued	2023-10-01
dc.identifier.citation	Journal of Hydrology, 2023, 625
dc.identifier.issn	0022-1694
dc.identifier.issn	1879-2707
dc.identifier.uri	http://hdl.handle.net/10453/176821
dc.description.abstract	Developing Assembled Vulnerability (AV) maps is essential for preventing environmental issues corresponding to the groundwater conditions in aquifers that are exposed to multiple contaminants from multiple origins. There is a research gap in the application of multiple models to produce the AV map of aquifers with two or more origins of contaminant. This study fills this knowledge gap by considering two objectives using the non-dominated sorting genetic algorithm-II (NSGA-II) multi-objective optimization approach to evaluate the vulnerability of coastal urban aquifers to wastewater and seawater intrusion contamination for the first time in the literature. For this purpose, the DRASTICA-GA and GALDIT-GA groundwater vulnerability models as individual models have been combined using NSGA-II to produce the AV maps as multiple models. In this step, two states are considered to produce the AV map: (1) The NSGA-II multi-objective optimization model aims to maximize the correlation coefficients between nitrate (NO3) and AV as well as total dissolved solids (TDS) and AV, and (2) A qualitative index obtained by data fusion (DF) is used in the NSGA-II model to produce the AV map. Finally, to prove the efficiency and applicability of the proposed framework, it is applied to an important aquifer in Oman, the Al Khoudh aquifer, which shows that the north of the Al Khoudh aquifer is more vulnerable than other parts exposed to wastewater and seawater intrusion contamination. In addition, results indicate that the presented methodology can accurately define the AV indices to identify the vulnerable areas corresponding to the different contamination origins. Moreover, the ROC/AUC criteria for the AV-NSGA-II-DF are more than the AV-NSGA-II, which are 0.962 and 0.956, respectively.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	Journal of Hydrology
dc.relation.isbasedon	10.1016/j.jhydrol.2023.130084
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Environmental Engineering
dc.title	A new approach for assessing the assembled vulnerability of coastal aquifers based on optimization models
dc.type	Journal Article
utslib.citation.volume	625
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
dc.date.updated	2024-03-17T22:47:48Z
pubs.publication-status	Published
pubs.volume	625

Abstract:

Developing Assembled Vulnerability (AV) maps is essential for preventing environmental issues corresponding to the groundwater conditions in aquifers that are exposed to multiple contaminants from multiple origins. There is a research gap in the application of multiple models to produce the AV map of aquifers with two or more origins of contaminant. This study fills this knowledge gap by considering two objectives using the non-dominated sorting genetic algorithm-II (NSGA-II) multi-objective optimization approach to evaluate the vulnerability of coastal urban aquifers to wastewater and seawater intrusion contamination for the first time in the literature. For this purpose, the DRASTICA-GA and GALDIT-GA groundwater vulnerability models as individual models have been combined using NSGA-II to produce the AV maps as multiple models. In this step, two states are considered to produce the AV map: (1) The NSGA-II multi-objective optimization model aims to maximize the correlation coefficients between nitrate (NO3) and AV as well as total dissolved solids (TDS) and AV, and (2) A qualitative index obtained by data fusion (DF) is used in the NSGA-II model to produce the AV map. Finally, to prove the efficiency and applicability of the proposed framework, it is applied to an important aquifer in Oman, the Al Khoudh aquifer, which shows that the north of the Al Khoudh aquifer is more vulnerable than other parts exposed to wastewater and seawater intrusion contamination. In addition, results indicate that the presented methodology can accurately define the AV indices to identify the vulnerable areas corresponding to the different contamination origins. Moreover, the ROC/AUC criteria for the AV-NSGA-II-DF are more than the AV-NSGA-II, which are 0.962 and 0.956, respectively.

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http://hdl.handle.net/10453/176821