Review of existing heavy metal contamination indices and development of an entropy-based improved indexing approach
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Review of existing heavy metal contamination indices and development of an entropy‑based improved indexing approach Kunwar Raghvendra Singh1 · Rahul Dutta2 · Ajay S. Kalamdhad2 · Bimlesh Kumar2 Received: 16 May 2019 / Accepted: 5 December 2019 © Springer Nature B.V. 2019
Abstract The present study aims at providing a novel technique for assessment of heavy metal contamination in a water body employing information entropy. For this purpose, 8 different locations, each from four tributaries of Brahmaputra river, Beki, Manas, Baralia and Pagladia, were chosen. Water samples from these tributaries were collected and analyzed for iron (Fe), manganese (Mn), lead (Pb), chromium (Cr), zinc (Zn) and copper (Cu) using atomic absorption spectroscopy (AAS). Information (Shannon) entropy was employed to assign weights to each heavy metal which was then coupled with the sub-indices to evaluate the entropy weighted heavy metal contamination index (EHCI). Spatial trend of EHCI values indicated that the water quality of Beki and Baralia river was either “excellent” (EHCI
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