Groundwater Quality Characterization of North Brahmaputra Basin using Positive Matrix Factorization

This study applies positive matrix factorization (PMF) to 140 groundwater samples collected from four different Public Health Centers in North Brahmaputra basin, Assam, India. The aim of this technique is to identify and quantify the pollution sources (natural and anthropogenic) that affect the water quality. Multivariate statistical analysis, especially factor analysis, is successful in interpreting the water quality data, but it has some limitations: It does not consider analytical uncertainty and factor loadings may be negative which do not give a clear representation of the data. Therefore, we applied PMF to groundwater data and compared the results with those obtained from factor analysis. The major findings from the study are as follows: The first and the second factors show that the natural means are the main source of pollution where Cl, SO4, Ca, Mg, TA and TH were the main contributors from erosion and weathering of rocks. The Pb and NO3 from the third and the fourth factor, respectively, are the major sources of contamination from anthropogenic activities such as the use of fertilizers. The fifth factor results in Fe, As, Mn and Cr, suggesting that both natural and anthropogenic processes are the main pollution contributors. PMF exhibits a more realistic representation of data and helps us to better understand the major sources of contamination and the variation in groundwater quality data. Hence, it can be successfully used for the characterization of groundwater chemistry.