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Comprehensive Analysis of the Bottom Tracking Features Measured by Adcps in Riverine Environments

Author(s): Slaven Conevski; Massimo Guerrero; Axel Winterscheid; Nils Ruther

Linked Author(s): Slaven Conevski, Massimo Guerrero, Nils Rüther

Keywords: DCP; Bedload transport; Backscattering strength; Apparent bedload velocity

Abstract: The apparent bedload velocity and the backscattering strength are variables derived from the bottom tracking features measured by any acoustic Doppler current profiler. Some previous laboratory and field investigations reported good correlations between these two variables and different bedload transport characteristics. After careful preprocessing and filtering, the ADCP data can be still noisy and would not match perfectly the conventionally measured transport rates. In addition to the typical usage of the mean values, this study examined the time series of the backscattering strength and apparent velocity obtained from ADCP measurements. The measurements were conducted in stationary position in three large rivers with bedload material spanning from fine sand to coarse gravel. Two ADCPs, the Sontek M9 and the RDI Rio Grande, measured almost synchronously. The results demonstrated that the mean values of the corrected backscattering strength measured by slant beams of the M9 are the most sensitive to the different bedload transport conditions, whereas the RDI data showed very low almost negligible sensitivity, smaller even than the vertical beam of the M9. The time series we analyzed used three different temporal features. These results showed that the ADCPs can catch short variations and pulsations of the bedload transport. They also pointed out that averaging of long time series can hinder most of the bedload characteristics by missing its dynamics and variation. Further analysis of different variables in the frequency or time domain, in addition to application of new innovative machine learning methods should be performed to better describe the bedload transport utilizing the ADCP outputs.

DOI: https://doi.org/10.3850/IAHR-39WC2521711920221921

Year: 2022

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