<p>Estimates of suspended sediment concentration (SSC) at high spatial resolution can be used to identify sediment sources, track the natural erosion gradients over entire mountain ranges, and quantify anthropogenic effects on catchment-scale sediment production, e.g. by dam construction or erosion control. Measurements of SSC at a basin outlet yields a basin-integrated picture of possible hydroclimatically-driven sources of sediment. However, a statistical analysis of one-dimensional input-output relations does not give us a full spatial perspective on sediment pathways of production and, potentially transient, storage within the catchment. These sediment pathways within catchments are difficult to identify and quantify due to the lack of affordable monitoring options that can create both spatially and temporally highly resolved datasets. Here, we propose a methodology to quantify these pathways using Sentinel-2 Level-1C imagery and in-situ measurements from a small network of sensors. The study is carried out on the Vjosa river, which represents one of the last intact large river systems in Europe. Geological diversity in the catchment and its widely unobstructed fluvial morphology over the entire river length makes it extremely interesting to monitor natural sediment dynamics. The remote sensing signal from the river’s water column, extracted from satellite imagery, contains an optical measure of turbidity. Furthermore, in-situ turbidity measurements between May 2019 and July 2020 from seven turbidity sensors located across the Vjosa provide ground-truthing. A significant multiple linear regression model between turbidity and reflectance was fitted to these data. The regression model has a low adjusted R<sup>2</sup> value of 0.30 but a highly significant p-value (< 2.2e-16). The satellite data together with the regression model were used to generate longitudinal profiles of predicted turbidity over the catchment from August 2020 to August 2021. Validation of these predictions for two different Sentinel-2 acquisition dates was done with in-situ turbidity measurements taken from a kayak during descents of the entire river. This validation showed accurate prediction of trends on a catchment scale but poor accuracy in the prediction of pointwise turbidity quantification. The model also showed accurate estimation of trends during different climatic seasons, suggesting that our approach captures the temporal variability in suspended sediment concentrations driven by long-term hydrological processes. Gridded rainfall from E-OBS was used to identify short-term hydrological forcing such as storm-driven activation of sediment sources. In order to monitor the many physical connections between hydrology, river processes, and sediment fluxes, future work will include extension of the in-situ turbidity sensor network with new sensors developed by our group. We plan to place these low-cost sensors at the outlet of every major tributary, on the main stem both above and below a confluence with a tributary, and within morphodynamically unique reaches.</p>

Abstract. Measurement of SSC at a basin outlet yields a basin-integrated picture of sediment fluxes, however it does not give a full spatial perspective on possible sediment sources, sinks, and pathways within the catchment. More effortsome spatially resolved estimates of suspended sediment concentrations (SSC) can be used to identify sediment sources, track erosion gradients in river basins, and quantify anthropogenic effects on catchment-scale sediment production, e.g. by dam construction or erosion control. Here we explore the use of high-resolution Sentinel-2 satellite images for this purpose in narrow and morphologically complex mountain rivers, combined with ground station turbidity sensing for calibration, and supported by a lagrangian kayak-derived river profile measurement. The study is carried out on the Vjosa River in Albania, which is one of the last intact large river systems in Europe. We developed a workflow to estimate river turbidity profiles from Sentinel-2 images including atmospheric, cloud cover, and deep water corrections, for the period May 2019 to July 2021 (106 images). In-situ turbidity measurements from four turbidity sensors located along the Vjosa River provided ground truthing. A multivariate linear regression model between turbidity and reflectance was fitted to this data. The extracted longitudinal river turbidity profiles were qualitatively validated with two descents of the river with a turbidity sensor attached to a kayak. The satellite-derived river profiles revealed variability in turbidity along the main stem with a strong seasonal signal, with the highest mean turbidity in winter along the entire length of the river. Most importantly, sediment sources and sinks could be identified and quantified from the river turbidity profiles, both for tributaries and within the reaches of the Vjosa. The river basin and network acted as a sediment source most of the time and significant sediment sinks were rare. Sediment sources were mostly tributaries following basin-wide rainfall, but also within-reach sources in river beds and banks were possible. Finally, we used the data to estimate the mean annual fine sediment yield at Dorez at ~2.5 ± 0.63 Mt/y in line with previous studies, which reveals the importance of the Vjosa River as an important sediment source into the Adriatic Sea. This work presents a proof of concept that open-access high-resolution satellite data has the potential for suspended sediment quantification not only in large water bodies but also in smaller rivers. The potential applications are many, from identifying sediment sources, activation processes, local point sources, and glacial sediment inputs, to sediment fluxes in river deltas, with a necessary future focus on improving accuracy and reducing uncertainty in such analyses.