Evidence map›Paper›PMID 37810075›Full record

ArticleHeliyon2023

Integrated clustering analysis for delineating seawater intrusion and heavy metals in Arabian Gulf Coastal groundwater of Saudi Arabia.

Mohammed Benaafi, S I Abba, Bassam Tawabini, Ismail Abdulazeez, Billel Salhi, Jamilu Usman, Isam H Aljundi

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.8field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 13 citations in OpenAlex.

  1. Ensemble machine learning method for δScientific reports · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Mohammed BenaafiInterdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
S I AbbaInterdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Bassam TawabiniCollege of Petroleum Engineering and Geosciences, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Ismail AbdulazeezInterdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Billel SalhiInterdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Jamilu UsmanInterdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Isam H AljundiInterdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
King Fahd University of Petroleum and Minerals · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The intrusion of seawater (SWI) into coastal aquifers is a major concern worldwide, affecting the quantity and quality of groundwater resources. The region of Saudi Arabia that lies along the eastern coast has been affected by SWI, making it crucial to accurately identify and monitor the affected areas. This investigation aimed to map the degree of seawater intrusion in a complex aquifer system in the study area using an integrated clustering analysis approach. The study collected 41 groundwater samples from wells penetrating multi-layered aquifers, and the samples were analyzed for physicochemical properties and major ions. Clustering analysis methods, including Hierarchical Clustering Analysis (double-clustering) (HCA-DC), K-mean (KMC), and fuzzy k-mean clustering (FKM), were employed to evaluate the spatial distribution and association of the groundwater properties. The results revealed that the analyzed GW samples were divided into four clusters with varying degrees of SWI. Clusters A, B, C, and D contained GW samples with very low (

Indexed as

Arabian gulfClustering analysisGroundwaterSeawater intrusionSustainable groundwater management

Identifiers

PMID37810075
PMCPMC10559117
OpenAlexW4386365539

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.