ABSTRACT
The primary objective of this study is to present a statistically significant water quality database of Dhemaji district, Assam (India) with special reference to pH, fluoride, nitrate, arsenic, iron, sodium and potassium. 25 water samples collected from different locations of five development blocks in Dhemaji district have been studied separately. The implications presented are based on statistical analyses of the raw data. Normal distribution statistics and reliability analysis (correlation and covariance matrix) have been employed to find out the distribution pattern, localisation of data, and other related information. Statistical observations show that all the parameters under investigation exhibit non uniform distribution with a long asymmetric tail either on the right or left side of the median. The width of the third quartile was consistently found to be more than the second quartile for each parameter. Differences among mean, mode and median, significant skewness and kurtosis value indicate that the distribution of various water quality parameters in the study area is widely off normal. Thus, the intrinsic water quality is not encouraging due to unsymmetrical distribution of various water quality parameters in the study area.
Subject(s)
Water Supply/analysis , Water Supply/standards , Databases, Factual , Elements , Humans , Hydrogen-Ion Concentration , India , Maximum Allowable Concentration , Water Pollutants, Chemical/analysis , Water Supply/statistics & numerical data , World Health OrganizationABSTRACT
Seasonal variations in the concentrations of groundwater with respect to arsenic, lead, cadmium and aluminium has been studied in Dhemaji district of Assam, India. The water samples were collected from 20 different sites in both dry and wet seasons. The metals were analysed by using atomic absorption spectrometer, Perkin Elmer AAnalyst 200 model. The concentrations of aluminium, lead and cadmium in groundwater were found to be significantly elevated. High concentrations of all the metals were recorded in the dry season than in the wet season. Univariate statistics along with skewness, kurtosis and confidence limit have been calculated for both the seasons to test the distribution normality for each metal. Statistical analyses of the data reveal non-uniform distribution of the metals in the area. The metal contamination of groundwater in the district follows the trend Al>Pb>Cd>As in both the seasons.
