REGRESSION MODEL AS A TOOL TO PREDICT CONCENTRATIONS OF TOTAL SUSPENDED SOLIDS IN RIVERS

Laura Kusari

Abstract


The river polluted by different discharges today is a worldwide growing concern. Due to human interactions and hydrological extreme events, the amount of total suspended solids in rivers is continuously changing. For river quality, the estimation of TSS is a must. The direct measurement of TSS requires frequent sampling, large suspension volume and is a very time consuming laboratory procedure. Therefore, the goal of the study was to develop a regression model that would enable the tracking of changes and predict TSS in rivers, through the measurement of turbidity. For this purpose, the grab samples were collected and then used for the preparation of subsamples in the laboratory. The results provided the necessary data for the establishment of a regression model. The relationship showed that there is a relation between turbidity and TSS, within the observed ranges, since the coefficient of determination is R2 = 0.8687. 


Keywords


Total Suspended Solid; turbidity; regression model; sub samples; rivers; quality

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References


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DOI: 10.6092/issn.2281-4485/6865

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