• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.125-134
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• 2023

In order to develop a backtracking technique for turbidity measurement data without discriminatory characteristics, three turbidity backtracking techniques for predicting inflow turbidity of a stream were compared using real-time turbidity data measured at automatic water quality measurement points located upstream and downstream of the stream and the Py_STPS model. Three turbidity backtracking techniques were applied: 1) simple preservation method of turbidity load considering flow time, 2) a method of using the flow rate at the upstream boundary considering the flow time as the flow rate at the downstream boundary, 3) method of introducing internal reaction rate to reflect the behavior characteristics of turbidity-causing substances. As a result of applying the three backtracking models, it was confirmed that the backtracking technique that introduced the internal reaction rate had the best results.