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

Abstract

This research investigated the quality of groundwater of 298 wells during 10 years, in Fars province, southern Iran, to survey spatial variation of groundwater quality and also major sources of hydro-chemical components for drinking and agricultural uses. To classify the sampling stations in each year, hierarchical cluster analysis, using the Euclidean distances and "Ward" method, was used. According to the results of cluster analysis, there were three quality groups in groundwater of the research area: first group of 170 wells with type of Ca-HCO3, second group of 98 wells with type of Ca-HCO3, and third group of 30 wells with type of Na-Cl. Hydro-chemical parameters were increased from the first to the third group, and on the basis of Schoeller and USSL diagrams, the water of wells of the third group was considered unsuitable for irrigation and drinking. Principal component (PC) analysis and factor analysis reduced the complex and voluminous data matrix into three main components, accounting for more than 80 % of the total variance. The first PC contained TDS, EC, TH, Na(+), Cl(-), Mg(2+), SO4 (2-), Ca(2+), and SAR parameters. Therefore, the first dominant factor was salinity. In PC2, HCO3 and pH were the dominant parameters, which may indicate weathering of silicate minerals. The PC3 contained high loadings for NO2 (2-) and NO3 (-). This factor indicates anthropogenic contaminants that may be caused by improper disposal of domestic wastes or the use of chemical fertilizers in agriculture and leaching of them.

Groundwater quality evaluation for potable and irrigation uses in the semi‐arid region of southern Iran

“…The significant positive correlation between CI − and Na + and Ca 2+ reveals the dominance of these soluble salts in the samples. To identify the possible sources of Na + and Cl − in the groundwater samples, the relationship between these ions was investigated by plotting the scatter plot of Na + against Cl − (Noshadi & Ghafourian, 2016; Panno et al, 2006). According to Figure 5, most of the points are above the 1 : 1 line in the dry season, which indicates a high concentration of Cl − compared to Na + , which may show evaporation as an effective process.…”

Assessment of groundwater quality in Vavuniya and Mullaitivu, Sri Lanka using multivariate statistical techniques and a Water Quality Index

“…Modern approaches like multivariate statistical analysis have been widely employed for differentiating natural or anthropogenic groundwater contamination sources, data reduction, and classification (Singh et al 2004;Nosrati & van den Eeckhaut 2012;Machiwal & Jha 2015;Balasooriya et al 2021). To determine the underlying reasons for poor groundwater quality, these methodologies provide information on the links between parameters and sampling sites as well as an idea of similarities and differences between parameters (Nosrati & van den Eeckhaut 2012;Noshadi & Ghafourian 2016;Balasooriya et al 2021).…”

“…Selvakumar et al (2017) investigated hydrogeochemical characteristics and groundwater contamination in Coimbatore, India by employing HCA. Noshadi & Ghafourian (2016) investigated the quality of groundwater in Fars province, southern Iran by employing HCA and found three clusters of Ca-HCO 3 and Na-Cl types. Bencer et al (2016) applied HCA for groundwater sources in Ain Djacer (Eastern Algeria).…”

Avaliação da qualidade da água subterrânea na zona rural do município de Pelotas, RS

“…A prática artesanal e rudimentar de construção desses poços, bem como as atividades desenvolvidas no entorno deles, evidenciam a necessidade de realizar um monitoramento da qualidade da água captada, tendo em vista a preservação da saúde da comunidade local. (HELLER;PÁDUA, 2010;NOSHADI;GHAFOURIAN, 2016).…”