Characterization of groundwater quality using water evaluation indices, multivariate statistics and geostatistics in central Bangladesh. Issue 1 (1st April 2016)

• Record Type: Journal Article
• Authors: Bodrud-Doza, Md.; Islam, A.R.M. Towfiqul; Ahmed, Fahad; Das, Samiran; Saha, Narottam; Rahman, M. Safiur
• Is Part Of: Water science. Volume 30:Issue 1(2016)
• Page Start: 19
• Page End: 40
• Publication Date: 2016-04-01
• Subjects: Geostatistics -- Hydrochemistry -- Groundwater quality -- Water indices -- Central Bangladesh; Water quality management -- Research -- Egypt -- Periodicals; Water resources development -- Research -- Egypt -- Periodicals; Water-supply, Agricultural -- Egypt -- Periodicals; Water-supply -- Research -- Egypt -- Periodicals; Water quality management -- Research; Water resources development -- Research; Water-supply, Agricultural; Water-supply -- Research; Egypt; Periodicals; Electronic journals; 628.1
• DOI: 10.1016/j.wsj.2016.05.001
• Languages: English
• ISSNs: 1110-4929

Abstract

Abstract: This study investigates the groundwater quality in the Faridpur district of central Bangladesh based on preselected 60 sample points. Water evaluation indices and a number of statistical approaches such as multivariate statistics and geostatistics are applied to characterize water quality, which is a major factor for controlling the groundwater quality in term of drinking purposes. The study reveal that EC, TDS, Ca 2+, total As and Fe values of groundwater samples exceeded Bangladesh and international standards. Ground water quality index (GWQI) exhibited that about 47% of the samples were belonging to good quality water for drinking purposes. The heavy metal pollution index (HPI), degree of contamination ( C d ), heavy metal evaluation index (HEI) reveal that most of the samples belong to low level of pollution. However, C d provide better alternative than other indices. Principle component analysis (PCA) suggests that groundwater quality is mainly related to geogenic (rock–water interaction) and anthropogenic source (agrogenic and domestic sewage) in the study area. Subsequently, the findings of cluster analysis (CA) and correlation matrix (CM) are also consistent with the PCA results. The spatial distributions of groundwater quality parameters are determined by geostatistical modeling. The exponential semivariagram model is validated as the best fitted models for most of the indices values. It is expected that outcomes of the study will provide insights for decision makers taking proper measures for groundwater quality management in central Bangladesh.