Open AccessSource apportionment and quality assessment of surface water using principal component analysis and multiple linear regression statistics
Author(s) -
Md. Ali Hossain,
M. A. Nasly Binti,
Mir Sujaul Islam
Publication year - 2013
Publication title -
environment conservation journal/environment conservation journal
Language(s) - English
Resource type - Journals
eISSN - 2278-5124
pISSN - 0972-3099
DOI - 10.36953/ecj.2013.14302
Subject(s) - principal component analysis , water quality , environmental science , surface runoff , linear regression , pollution , surface water , regression analysis , wastewater , statistics , hydrology (agriculture) , environmental engineering , mathematics , ecology , geotechnical engineering , engineering , biology
Principal component analysis (PCA) and multiple linear regressions (MLR) analysis were applied on the data set of surface water quality for source identification of pollution and their contribution on the variation of water quality. Results revealed that, most of the water quality parameters were found to be toxic compare to the national standard of Malaysia. PCA identified the sources as, ionic groups of salts, soil erosion and agricultural runoff, organic and nutrient pollutions from domestic wastewater, industrial sewage and wastewater treatment plants. MLR investigated the contribution of every variable with R= 0.968 and R2=0.934 and it was highly significant (p<0.01).