%0 Journal Article
%T Evaluation of Groundwater Nitrate Pollution Based on Main Components and Factor Analysis (Case Study: Karaj Plain Aquifer)
%J Iranian journal of Ecohydrology
%I Faculty of New Sciences and Technologies, University of Tehran
%Z 2423-6098
%A Chitsazan, Manuchehr
%A Eilbeigy, Mehdi
%A Mohammad Rezapour Tabari, Mahmood
%D 2018
%\ 12/22/2018
%V 5
%N 4
%P 1119-1133
%! Evaluation of Groundwater Nitrate Pollution Based on Main Components and Factor Analysis (Case Study: Karaj Plain Aquifer)
%K Groundwater
%K Nitrate
%K factor analysis
%K Clustering
%R 10.22059/ije.2018.256758.870
%X Nitrate is one of the most significant pollutants that most aquifers, including the Karaj aquifer, have suffered from it. Because the conventional method to investigate the hydrogeochemical processes in the aquifer is graphical ones, in order to evaluate the pollution of nitrate in the qualitative data of 86 wells in Karaj aquifer in 2013, the multivariate statistical methods has been carried out as a complementary method for understanding the factors affecting groundwater quality, pollution identification and classification of similar samples. In this regard, XLSTAT software is used to study the pollution of nitrate and its relationship to other chemical parameters of water, and the factors influencing it. The statistical analysis indicates that hierarchal clustering has led to the extraction of three clusters. The second and the third cluster samples have a higher concentration of nitrate than the first one. The results, based on the principal components analysis (PCA), also show that the nitrate parameter has the highest correlation with chlorine and the least adaptation with sodium and sulfate. On the other hand, based on the varimax rotation, the main components were summed up to two components. The first one is a geogenic factor, which is due to the effect of the material that forms aquifer and second is an anthropogenic factor that is due to human actions, especially sewage.
%U https://ije.ut.ac.ir/article_68436_ca543837bc4c9650ee8d027a93dad231.pdf