Groundwater quality analysis using multivariate statistical techniques (case study: Fars province, Iran)

Area of Science:

• Hydrogeology
• Environmental Science
• Water Resource Management

Background:

• Groundwater quality is crucial for drinking and agricultural uses, especially in arid and semi-arid regions.
• Long-term monitoring is essential to understand spatial and temporal variations in groundwater chemistry.

Purpose of the Study:

• To investigate the spatial variation of groundwater quality over 10 years in Fars province, Iran.
• To identify the major sources of hydro-chemical components affecting groundwater suitability.

Main Methods:

• Hierarchical cluster analysis was used to classify 298 wells based on groundwater quality.
• Schoeller and USSL diagrams were employed for water quality assessment.
• Principal component (PC) and factor analysis were utilized to determine the sources of hydro-chemical parameters.

Main Results:

• Three distinct groundwater quality groups were identified: Ca-HCO3 (two groups) and Na-Cl.
• Groundwater quality deteriorated from the first to the third group, with the Na-Cl group being unsuitable for drinking and irrigation.
• Salinity was the dominant factor, followed by silicate mineral weathering and anthropogenic contaminants (nitrates/nitrites).

Conclusions:

• Groundwater in Fars province exhibits significant spatial variation in quality.
• Salinity and anthropogenic activities are major drivers of groundwater contamination.
• Effective water resource management strategies are needed to address water quality issues for sustainable use.