DEVELOPMENT OF WATER QUALITY MATRIX THROUGH SURROGATE MODELING

• Main Author: Laura Kusari
• Format: Article
• Language: English
• Published: University of Bologna 2018-03-01
• Series: EQA
• Subjects: Water quality, monitoring matrix, river pollution, linear regression, surrogate relationships.
• Online Access: https://eqa.unibo.it/article/view/7735

This paper presents the outcome of a research project that was focused on the monitoring of surface water quality through the development of a correlation matrix. The matrix was developed for six main water quality parameters by the use surrogate relations. The grab sampling was performed at selected sites and the same samples were used in the laboratory for the preparation of subsamples. Those subsamples were tested for Turbidity, Total Suspended Solids (TSS), Chemical Oxygen Demand (COD), Biological Oxygen Demand (BOD), Total Organic Carbon (TOC) and Nitrates. Data were analyzed by statistical analyses, using linear regression and the outcome was used for the development of a correlation matrix of main water quality parameters.The analyses revealed that in this study site, TSS has high positive correlation with BOD, COD and NO3 as well as with turbidity. The highest positive correlation was noticed between turbidity and BOD, NO3, TSS andCOD. On the other hand, only Total Organic Carbon (TOC) was negatively (inversely) correlated with the studied parameters. The correlation matrix developed will help in determining the water quality status by using few parameters.