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Measured sediment concentration records are important information to support water management activities. However, for various reasons, these time series could be incomplete. This paper contains options for modelling the concentrations of suspended sediments when unmeasured periods occurs. Using of various modelling strategies for is discussed and some statistical and machine learning methods are selected for this task. The results show a significant increase in the accuracy of modelling the concentration of suspe...