Spatial distribution of metals in ground/surface waters in the Chandrapur district (Central India) and their plausible sources

• Published in: Environmental Geology 2009-02, Vol.56 (7), p.1323-1352
• Main Authors: Satapathy, D. R, Salve, P. R, Katpatal, Y. B
• Format: Article
• Language: English
• Subjects: Cadmium; Contamination; Earth and Environmental Science; Earth Sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Environmental hazards; Exact sciences and technology; Geology; Global positioning systems; GPS; Groundwater; Hydrogeology; Hydrology; Hydrology. Hydrogeology; Lead; Lithology; Metals; Original Article; Pollution, environment geology; Principal components analysis; Soil contamination; Spatial distribution; Statistical methods; Studies; Surface water; Surface-groundwater relations; Trace elements; Trace metals; Water analysis; Water sampling
• ISSN: 0943-0105; 1866-6280; 1432-0495; 1866-6299
• DOI: 10.1007/s00254-008-1230-3

This study addresses a framework to evaluate and map environmental hazard with reference to spatial distribution of major and trace metal contamination and its relationship with lithology in Chandrapur district of Maharashtra, India using geospatial, statistical and GIS tools. In all, 208 ground water and 35 surface water samples were collected using global positioning system (GPS) synoptically with satellite imagery IRS P6 LISS III and were analyzed in ICP-AES. Analytical results reflect the presence of major and trace metals in ground water in terms of % as Fe (48%), Mn (12%), Zn (9%), Al (8%), Pb (7%), Cu (6%), Ni (4%), Cd (3%) and Cr (3%) of the total average concentration. The contamination is attributed to weathering of rocks and also to mining activities. Similarly, surface water contribution of major and trace metals was found as Al (47.8%), Fe (42.8%), Mn (5.5%), Zn (2.3%), Pb (0.56%), Ni (0.42%), Cu (0.16%), Cr (0.16%) and Cd (0.10%) of the total average concentration. Ordinary kriging interpolation method was adopted to assess the spatial distribution of different major and trace metals in groundwater samples with their best model fit variogram Classical statistical method like principal component analysis (PCA) was carried out in order to establish correlation between spatial pattern of metal contamination and geology of the area in GIS environment. Various surface and subsurface aspects like landuse/land cover, structural features, hydrogeology, topography etc were also considered to ascertain their impact to supplement the inference of the study.