Investigating the effects of surface water recharge on groundwater quality using hydrochemistry and ANFIS model: A case study Minia Governorate, Egypt.

Autor: Makhlouf A; Environmental Engineering Department, Egypt-Japan University of Science and Technology, Alexandria, 21934, Egypt; Civil Engineering Department, Faculty of Engineering, Minia University, Minia, 61111, Egypt. Electronic address: ahmed.makhlouf@ejust.edu.eg., Sharaan M; Environmental Engineering Department, Egypt-Japan University of Science and Technology, Alexandria, 21934, Egypt; Civil Engineering Department, Faculty of Engineering, Suez Canal University, Ismailia, 41522, Egypt. Electronic address: mahmoud.sharaan@ejust.edu.eg., El-Rawy M; Civil Engineering Department, Faculty of Engineering, Minia University, Minia, 61111, Egypt; Civil Engineering Department, College of Engineering, Shaqra University, Dawadmi, 11911, Saudi Arabia. Electronic address: mustafa.elrawy@mu.edu.eg., Kanae S; Department of Civil and Environmental Engineering, Tokyo Institute of Technology, Tokyo, Japan. Electronic address: kanae@cv.titech.ac.jp., Ibrahim MG; Environmental Engineering Department, Egypt-Japan University of Science and Technology, Alexandria, 21934, Egypt; Environmental Health Department, High Institute of Public Health, Alexandria University, Alexandria, 21544, Egypt. Electronic address: mona.gamal@ejust.edu.eg.
Jazyk: angličtina
Zdroj: Journal of environmental management [J Environ Manage] 2024 Jun; Vol. 362, pp. 121269. Date of Electronic Publication: 2024 May 31.
DOI: 10.1016/j.jenvman.2024.121269
Abstrakt: Monitoring and assessing groundwater quality and quantity lays the basis for sustainable management. Therefore, this research aims to investigate various factors that affect groundwater quality, emphasizing its distance to the primary source of recharge, the Nile River. To this end, two separate study areas have been considered, including the West and West-West of Minia, Egypt, located around 30 and 80 km from the Nile River. The chosen areas rely on the same aquifer as groundwater source (Eocene aquifer). Groundwater quality has been assessed in the two studied regions to investigate the difference in quality parameters due to the river's distance. The power of machine learning to associate different variables and generate beneficial relationships has been utilized to mitigate the cost consumed in chemical analysis and alleviate the calculation complexity. Two adaptive neuro-fuzzy inference system (ANFIS) models were developed to predict the water quality index (WQI) and the irrigation water quality index (IWQI) using EC and the distance to the river. The findings of the assessment of groundwater quality revealed that the groundwater in the west of Minia exhibits suitability for agricultural utilization and partially meets the criteria for potable drinking water. Conversely, the findings strongly recommend the implementation of treatment processes for groundwater sourced from the West-West of Minia before its usage for various purposes. These outcomes underscore the significant influence of surface water recharge on the overall quality of groundwater. Also, the results revealed the uncertainty of using sodium adsorption ratio (SAR), Sodium Percentage (Na%), and Permeability Index (PI) techniques in assessing groundwater for irrigation and recommended using IWQI. The developed ANFIS models depicted perfect accuracy during the training and validation stages, reporting a coefficient of correlation (R) equal to 0.97 and 0.99 in the case of WQI and 0.96 and 0.98 in the case of IWQI. The research findings could incentivize decision-makers to monitor, manage, and sustain groundwater.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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