Assessment of hydrogeochemical processes in a coastal region: Application of multivariate statistical model

作者：Rao N Subba^*; Vidyasagar G; Rao P Surya; Bhanumurthy P

来源：Journal of the Geological Society of India, 2014, 84(4): 494-500.

DOI：10.1007/s12594-014-0155-6

• Aquifer chemistry
• Multivariate statistical model
• Salinity
• Alkalinity
• Coastal region
• Andhra Pradesh

Hydrogeochemical studies have been carried out in a coastal region, using multivariate statistical model, for better understanding the controlling processes that influence the aquifer chemistry. Two principal components (PC1 and PC2) are extracted from the data set of chemical variables (pH, TDS, Ca2+, Mg2+, Na+, K+, HCO (3) (-) , Cl-, SO (4) (2-) , NO (3) (-) and F-), which account for 79% of the total variation in the quality of groundwater. The PC1 (salinity controlled process) includes the concentrations of TDS, Mg2+, Na+, K+, Cl-, SO (4) (2-) and NO (3) (-) , while the PC2 (alkalinity controlled process) comprises the concentrations of pH, HCO (3) (-) and F-. The spatial distribution of PC scores identifies the locations of high salinity and alkalinity processes. The first process corresponds to the influences of geogenic, anthropogenic and marine sources, and the second one to the influence of water-soil-rock interaction. Thus, the present study shows the usefulness of multivariate statistical model as an effective means of interpretation of spatial controlling processes of groundwater chemistry.

• 出版日期2014-10