Assessment of Water Quality around Surface Coal Mines using Principal Component Analysis and Fuzzy Reasoning Techniques

Water samples collected from surface coal mine sites, adjacent rivers, and nearby tube wells were analyzed for pH, selected contaminant concentrations, electrical conductivity, total dissolved solids, total suspended solids, and total hardness. Statistical analysis of the data showed that most of the parameters (variables) were correlated with each other, having a correlation coefficient between 0.29 and 0.99. Hence, variability of output parameter, in this case, water quality around mine sites, cannot be explained explicitly by any single input parameter. Principal component analysis was used to evaluate the orthogonal and independent components of the original data sets. The first principal component and pH were used to compare water quality around the mine sites using fuzzy reasoning techniques based on Mamdani's principle. Finally, a prediction map of water quality was prepared for the entire study area. Although the contaminants of concern will vary from site to site, this basic approach should be useful in assessing water quality at other locations where funds or site access limit ones ability to sample more intensely.