GEOCHEMICAL ASSESSMENT OF GROUNDWATER QUALITY INTEGRATING MULTIVARIATE STATISTICAL ANALYSIS WITH GIS IN SHIWALIKS OF PUNJAB, INDIA

摘要

The dependency of people has increased on groundwater due to tremendous increase in crop production, population, industrialization and erratic rainfall due to climate change, in past few decades. The groundwater is the main source of irrigation in Shiwaliks of Punjab. In the present study the samples were collected from predetermined location as was located on satellite image on basis of spectral reflectance using GPS. The analysis of samples formed the attribute database for spatial distribution of water quality parameters using spatial analyst extension of ArcGIS 9.1. Principal components analysis (PCA) together with other factor analysis procedures, consolidate a large number of observed variables into a smaller number of factors that can be more readily interpreted. In the case of groundwater, concentrations of different constituents may be correlated based on underlying physical and chemical processes such as dissociation, ion-exchange, weathering or carbonate equilibrium reactions. The number of factors for a particular dataset is based on the amount of non-random variation that explains the underlying processes. The more factors extracted, the greater is the cumulative amount of variation in the original data. The PCA produced six significant components that explained 78% of the cumulative variance.