Assessment of Spatio-Temporal Variations in Water Quality of Shailmari River, Khulna (Bangladesh) Using Multivariate Statistical Techniques

作     者：Md. Muhyminul Islam Olaf K. Lenz Abul Kalam Azad Mosummath Hosna Ara Masudur Rahman Nazia Hassan 

作者机构：Tropical Hydrogeology and Environmental Engineering TU Darmstadt Schnittspahnstrasse Germany Institut für Angewandte Geowissenschaften Angewandte Sedimentgeologie TU Darmstadt Schnittspahnstrasse Germany Environmental Science Discipline Khulna University Khulna Bangladesh Chemistry Discipline Khulna University Khulna Bangladesh 

出 版 物：《Journal of Geoscience and Environment Protection》 (地球科学和环境保护期刊（英文）)

年 卷 期：2017年第5卷第1期

页      面：1-26页

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

主　　题：Water Quality Variation Wastewater Multivariate Statistical Analysis Monsoon Bangladesh 

摘      要：Surface water has become one of the most vulnerable resources on the earth due to deterioration of its quality from diverse sources of pollution. Understanding of the spatiotemporal distribution of pollutants and identification of the sources in the river systems is a prerequisite for the protection and sustainable utilization of the water resources. Multivariate statistical techniques such as Principal Component Analysis (PCA) and Factor Analysis (FA) were applied in this study to investigate the temporal and spatial variations of water quality and appoint the major factors of pollution in the Shailmari River system. Water quality data for 14 physicochemical parameters from 11 monitoring sites over the year of 2014 in three sampling seasons were collected and analyzed for this study. Kruskal-Wallis test showed significant (p 0.01) temporal and spatial variations in all of the water quality parameters of the river water. Principal component analysis (PCA) allowed extracting the contributing parameters affecting the seasonal water quality in the river system. Scatter plots of the PCs showed the tidal and spatial variation within river system and identified parameters controlling the behavior in each case. Factor analysis (FA) further reduced the data and extracted factors which are significantly responsible for water quality variation in the river. The results indicate that the parameters controlling the water quality in different seasons are related with salinity, anthropogenic pollution (sewage disposal, effluents) and agricultural runoff in pre-monsoon;precipitation induced surface runoff in monsoon;and erosion, oxidation or organic pollution (point and non-point sources) in post-monsoon. Therefore, the study reveals the applicability and usefulness of the multivariate statistical methods in assessing water quality of river by identifying the potential environmental factors controlling the water quality in different seasons which might help to better understand,