Hydrochemical properties of drinking water and their sources apportionment of pollution in Bajaur agency, Pakistan. (June 2019) - Jehan, Shah; Khan, Sardar; Khattak, Seema Anjum; Muhammad, Said; Rashid, Abdur; Muhammad, Nisar
Highlights: Hydrochemical properties of drinking water (groundwater) of Bajaur agency were studied. SO4 −2, K +, NO3 − and HCO3 − concentrations in groundwater generally exceeded the WHO guideline values. Pollution quantification factor were assessed via multivariate statistics viz. PCA and Gibbs plot. PCA shows natural and anthropogenic origin for groundwater contamination. CaHCO3 and NaHCO3 are the major water type of the study area. Abstract: This study investigates the hydrochemical characteristics and quality assessment of drinking water (groundwater) in the Bajaur agency, Federally Administrator Tribal Areas (FATA), Pakistan. For this purpose, water samples (n = 44) were taken and analysed for various physicochemical parameters such as pH, electrical conductivity (EC), total dissolved solids (TDS), total suspend solid (TSS), turbidity, dissolved oxygen (DO), bicarbonates (HCO3 − ), chlorides (Cl − ), nitrates (NO3 − ) sulphates (SO4 −2 ), phosphates (PO4 −3 ), sodium (Na + ), potassium (K + ), calcium (Ca +2 ) and magnesium (Mg +2 ). Results indicated that hydrochemical characteristics and quality assessment parameters were within drinking water guidelines value set by the World Health Organization (WHO) except SO4 −2, K +, NO3 −, and HCO3 − in 9%, 40%, 54%, and 67% of the analysed samples, respectively. According to Hill-piper diagram most of the samples showed Ca-HCO3 − facies which was within the weak-alkaline proportion type, predominantly calcium and bicarbonate facies. Results of the principal component analysis/factor analysis (PCA/FA) and hierarchical cluster analysis (HCA) analyses suggested that most of the variations are explained by geogenic and anthropogenic sources that affect the drinking water quality. This study demonstrates enhanced information about evaluation of drinking water quality by using hydrochemical data and multivariate statistical methods to understand the factors influencing contamination due to natural and anthropogenic impacts.