Assessment of Groundwater Quality Patterns in the Southern Ramhormoz Aquifer Using K-Means Clustering and GIS

Firoozi, Saeideh; Mousavi, Majid

doi:10.22048/wss.2026.582946.1028

Assessment of Groundwater Quality Patterns in the Southern Ramhormoz Aquifer Using K-Means Clustering and GIS

Articles in Press

Document Type : Research Article

Authors

Saeideh Firoozi

Majid Mousavi

Khuzestan Water and Power Authority, Khuzestan, Iran.

10.22048/wss.2026.582946.1028

Abstract

Monitoring the quality of groundwater resources is essential for the sustainable use of these resources. K-Means is one of the most important and widely used algorithms in clustering. In the present study, qualitative classification of wells in the southern part of Ramhormoz plain aquifer was performed using the K-Means method. Accordingly, water samples were collected from 12 well sampling locations in spring 2022 and, after chemical analysis, were clustered in the Python environment. Qualitative analysis of the data from the sampled wells indicated 3 dominant clusters in this plain. Based on this, the zoning map of Ramhormoz plain was drawn, which showed 3 zones with relatively good, moderate, and undesirable quality. The existence of significant differences in nitrate and salinity levels among clusters also indicates that the factors affecting water quality in the study area have been a combination of natural geological elements and human pressures on groundwater resources. Also, drawing contour maps of total dissolved solids (TDS), electrical conductivity (EC), and nitrate demonstrates the influence of these parameters on K-Means clustering.

Keywords

GIS

Groundwater

K-Means clustering

Nitrate

Qualitative classification

Salinity

Subjects