Kernel principal component analysis-based water quality index modelling for coastal aquifers in Saudi Arabia.

Ali Aldrees, Abdulhayat M Jibrin, Salisu Dan'azumi, Mohammad Al-Suwaiyan, Sani I Abba, Zaher Mundher Yaseen

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 citing paper in PubMed.

Regime-based interpretation of groundwater pollution using Gaussian mixture modelling and water pollution index in aquifer systems.Scientific reports · 2026
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Authors and funding

6 authors.

Ali AldreesDepartment of Civil Engineering, College of Engineering in Al-Kharaj, Prince Sattam Bin Abdulaziz University, 11942, Al-Kharj, Saudi Arabia.

Abdulhayat M JibrinCivil and Environmental Engineering Department, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia. g202303890@kfupm.edu.sa.

Salisu Dan'azumiDepartment of Civil Engineering, College of Engineering in Al-Kharaj, Prince Sattam Bin Abdulaziz University, 11942, Al-Kharj, Saudi Arabia.

Mohammad Al-SuwaiyanCivil and Environmental Engineering Department, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia.

Sani I AbbaDepartment of Civil Engineering, Prince Mohammad Bin Fahd University, 31952, Al Khobar, Saudi Arabia.

Zaher Mundher YaseenCivil and Environmental Engineering Department, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia.

Funding

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6 · The paper itself

Abstract

This study developed a novel Water Quality Index (WQI) using Kernel Principal Component Analysis (PCA) to assess groundwater quality (GWQ) in the coastal aquifers of Al-Qatif, Saudi Arabia. A total of 39 groundwater samples were collected from shallow and deep wells and analyzed for key physicochemical parameters. Six kernel types were tested, and the polynomial kernel was found to be most effective in preserving variance and reducing dimensionality. The Kernel PCA-based WQI classified wells into 'Very Bad,' 'Bad,' and 'Medium' categories, with scores such as W3 (WQI = 25.51, "Very Bad"), W31 (WQI = 46.7, "Bad"), and W38 (WQI = 56.75, "Medium"). Salinity and EC presented poor Sub-Index (SI) scores, reflecting the impact of seawater intrusion and over-extraction, while pH consistently showed high SI values (100), indicating natural buffering. By integrating non-linear dimensionality reduction, the proposed framework enhances traditional WQIs and facilitates more targeted and transparent groundwater decision-making. This includes identifying priority wells for remediation and supporting sustainable abstraction policies. The findings offer insight into sustainable water management in arid and semi-arid regions that are confronting groundwater degradation.

Indexed as

Coastal aquifersGroundwater quality assessmentKernelsPrincipal component analysisSeawater intrusionWater quality index

Identifiers

PMID41062553

DOI10.1038/s41598-025-18980-1

PMCPMC12508030

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LicenceCC BY-NC-ND

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