Multivariate statistical evaluation of ground water quality

Salar Khaiiatali; Arezoo Hassan Noori; Reza Masoudiaghdam Mehrabad

doi:10.21859/jces.8147

Salar Khaiiatali Department of Civil Engineering, Azerbaijan Shahid Madani University, Tabriz, Iran.
Arezoo Hassan Noori Department of Chemistry, Kerman branch, Islamic Azad University, Kerman, Iran.
Reza Masoudiaghdam Mehrabad Department of Geosciences, Islamic Azad University, Science and Research Branch, Tehran, Iran.

Keywords: Groundwater quality, WHO, CCME, WQI, GQI

Abstract

In this study, the statistical results for the underground water of Qaem Shahr plain were evaluated. This evaluation is particularly important due to the main concerns of drinking water, irrigation, and sustainable agriculture in the region. Farmers rely on underground water as a supplement to surface water for irrigating their fields. Given the significance of this issue, the primary objective of this research is to study the water quality in the case study.

Multivariate statistical analysis has become increasingly popular for quantifying the relationship between water quality parameters and processes in groundwater aquifers. In this particular study, data were collected from water samples taken from 22 wells in the years 1999 and 2011. By analyzing these samples, we sought to identify the elements that have a significant impact on the quality of the unlimited coastal aquifer of Qaem Shahr plain. Our investigation focused on the wells in use and explored the influential processes that affect water quality in the aquifer.

The water samples were analyzed using multivariate statistical analysis, which involved measuring the concentration of cations and main anions, as well as parameters such as EC, T.D.S, pH, and hardness. For this study, we utilized multivariate statistical methods, including factor analysis (FA), and water quality indicators such as WHO and CCME classifications.