Using Turbidity to Determine Total Suspended Solids in an Urban Stream: A Case Study

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2019 by IJETT Journal
Volume-67 Issue-9
Year of Publication : 2019
Authors : Md. Serajuddin, Md. AI Chowdhury, Md. Mahmudul Haque, Md. Ehteshamul Haque
DOI :  10.14445/22315381/IJETT-V67I9P214


MLA Style: Md. Serajuddin, Md. AI Chowdhury, Md. Mahmudul Haque, Md. Ehteshamul Haque "Using Turbidity to Determine Total Suspended Solids in an Urban Stream: A Case Study" International Journal of Engineering Trends and Technology 67.9 (2019):83-88.

APA Style:Md. Serajuddin, Md. AI Chowdhury, Md. Mahmudul Haque, Md. Ehteshamul Haque. Using Turbidity to Determine Total Suspended Solids in an Urban Stream: A Case Study International Journal of Engineering Trends and Technology, 67(9),83-88.

A high concentration of total solids will make drinking water unpalatable and might have an adverse effect on people who are not used to drinking such water. Levels of total solids that are too high or too low can also reduce the efficiency of water treatment plants, as well as the operation of industrial processes that use raw water. The estimation of Total Suspended Solids (TSS) is very much important in relation to the selection of proper treatment process. The direct measurement of TSS is relatively costlier and time consuming than turbidity measurement. Though universal correlation does not exist, there are many investigations showing that turbidity is in relation with suspended sediments. For example, Model developed for Turbidity & TSS for the Sitnica river, Kosovo, shows the coefficient of determination R2 = 0.8687, for fourteen rivers around Singapore R2 = 0.80 & for urbanizing streams at Washington, USA, R2 = 0.96. The aim of this work is to establish a regression model that would enable the measurement of TSS in the Shitalakhya river at Dhaka through the measurements of turbidity. TSS & Turbidity concentration was measured daily throughout the year 2017 and the regression model was developed to surrogate turbidity for TSS. It is found that for the year 2017 as a whole the R2 = 0.48, for the dry and wet season they were 0.51 & 0.59 respectively, which are not excellent but fairly good correlation. When calculating the regression equation for every month we found that R2 varies from 0.04 to 0.79, and half of the twelve values fall below 0.2. Thus for this particular site, the use of turbidity as a surrogate to TSS for individual monthly measurement is not effective throughout, however, to get an instantaneous idea of pollution during dry and wet season as a whole, the model can be used.


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Correlation, surface water, turbidity, total suspended solids.