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The bottom tracking (BT) feature of the acoustic Doppler current profilers (ADCP) have emerged as a promising technique in evaluating the bed load. Strong statistical correlations are reported between the ADCP BT velocity and the transport rate obtained by physical sampling or dune tracking; however, these relations are strictly site-specific and a local calibration is necessary. The direct physical sampling is very labor intensive and it is prone to high instrument uncertainty. The aim of this work is to develop a methodology for evaluating the bed load transport using commercial ADCPs without calibration with physical samples. Relatively long stationary measurements were performed in a sand-bed and sand gravel rivers, using three different ADCPs working at 3MHz, 1.2MHz and 0.6MHz. Simultaneously, bed load samples were collected with physical samplers, and the riverbed was closely observed with digital cameras mounted on the samplers. It is demonstrated that the kinematic transport model can yield a relatively good estimate of the transport rate by directly using filtered apparent velocity, the knowledge of the hydraulic conditions and instrument-related calibration coefficients. Additionally, the ADCP data can help in qualitative assessment of the physical sampling. Future investigation of the backscattering echo and further confirmation of the BT apparent velocity should be performed in laboratory-controlled conditions.

<p>Assessment of bedload transport rates is of great importance for river morphology. Over the years, many efforts have been made to get a realistic estimate of the bedload transport rate in a river. Several researchers suggested that a reliable estimate of the bedload transport rate can be computed from migration of dunes based on the so-called dune tracking method. To apply this method, bed elevation profiles have to be measured using echosounding of the river bed to determine dune geometries (length (λ) and height (H)) and dune migration rate (C).<br>The migration rate of dunes (C = ∆X/∆T) is calculated by cross-correlation based on dune migration distance (∆X) and time interval (∆T) between echosounded profiles of two successive measurements. Based on literature, the ∆T between successive echosoundings has to be small enough for the same dunes to be clearly detectable in both measurements. However, the parameter ∆T has not been yet quantified for different river conditions. The objective of the present study is to get an appropriate estimation of the ∆T in order for the cross-correlation to work properly and thus to get a reliable magnitude of bedload transport rate which is at the same time also a specification for the execution of the measurements.<br>To provide an accurate estimate of the ∆T, both the dune migration distance (can be related to the dune geometries) and the dune migration rate need to be known. Since both parameters (∆X and C) are not available at the beginning of measurements in the field, they need to be estimated based on the existing predictors (e.g. Allen (1968), Tsuchiya & Ishizaki (1967), Van Rijn (1984), Wilbers (2004)) in the literature. The predictors’ verification has been carried out by using the dune geometries and the dune migration rate obtained based on the echosounded profiles. The analysis has been conducted by using the echosounding data of the LiLaR campaign (November 2021) from the Rhine River around the German-Dutch border between km 858-859. For the verification, the dune tracking method has been used. The applied dune tracking method is based on a combination of the software RhenoBT (Frings et al. 2012) and Bedforms ATM (Gutierrez et al. 2018), which determine the dune geometries. Besides, the dune migration rate has been calculated by the cross-correlation using an R script.<br>This study shows that the dune migration distance can be related to the dune length (∆X = p.λ). The p parameter depends on echosounding measurement uncertainties and dune geometries changes as they migrate downstream. Furthermore, the migration rate would be probably predicted best with Wilbers (2004) predictor in which dune migration rate is related to dune length. While large dunes migrations show high correlation (> 0.7) for time interval of more than 20 hours, small superimposed dunes only show high correlation for time interval lower than 2 hours. Knowing the required time interval can be a helpful factor during echosounding measurements which results in finding the dunes that are most active in transporting bedload material as they migrate downstream.</p>

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