Estimation of Suspended Sediment Concentration Using Regression Analysis: A Case Study from the Patapsco River Basin, USA
2nd International Conference on Engineering, Natural Sciences, and Technological Developments, Bayburt, Turkey, 20 - 23 June 2025, pp.405-411, (Full Text)
- Publication Type: Conference Paper / Full Text
- City: Bayburt
- Country: Turkey
- Page Numbers: pp.405-411
- Karadeniz Technical University Affiliated: Yes
Abstract
Suspended sediment concentration (SSC) is a crucial factor for reservoirs, dams, river ecosystems, structural changes in water resources, operational activities, environmental safety, and water management. In this study, the conventional regression analysis (CRA) method, which is included linear, power, exponential, and quadratic functions, was used to estimate the average daily SSC data for two monitoring stations, which are Catonsville and Elkridge, in the Patapsco River, the United States. Daily mean discharge (Q) and turbidity (T) data for the period October 2016- September 2021 were used to estimate SSC concentrations. Three models were established using different combinations of Q and T as input parameters. For each station, the data were divided into two data sets: training (65.74%) and testing (34.26%). The performance of the models was evaluated using the root means square error the mean absolute error, and the Nash-Sutcliffe efficiency coefficient statistics. The best performance statistics were obtained the model including Q and T parameters for both stations. As for the function performances, the linear function performed better on the training data set, while the quadratic function performed better on the testing data set. It was concluded that the two-input models using the quadratic and linear function showed superior performance.