In the past decades the Arctic has experienced stronger temperature increases than any other region globally. Shifts in hydrological regimes and accelerated permafrost thawing have been observed and are likely to mobilize organic matter through rivers into the Arctic Ocean. Consequently, Arctic rivers such as the Lena River in Siberia need to be monitored closely to measure changes and better understand the Arctic carbon cycle. At the Research Station Samoylov Island in the Lena River Delta water samples are taken at a high frequency since 2018. From these samples, biogeophysical parameters, including concentrations of dissolved organic carbon (DOC) and colored dissolved organic matter (CDOM), are retrieved. In this study we collocated these samples with overpasses of the Ocean and Land Colour Instrument (OLCI) for the ice-free periods (May – October). The observations were atmospherically corrected using Polymer and used to derive absorption of CDOM (aCDOM). From aCDOM we deduced the amount of DOC using known relationships. The dataset includes over 2000 scenes for the five ice-free months of each year. First results reveal that simple band ratios provide a good estimate for aCDOM. These leave some residuals for further investigation. The best performing retrieval will then be used to create a DOC algorithm. Preliminary remotely sensed DOC agrees well with the in situ DOC data (r²=0.92, n=120) and captures the seasonal variability of DOC. We are thus able to simultaneously assess and refine the quality of satellite retrievals for the Lena River. We aim to improve existing algorithms for DOC monitoring and develop new algorithms, using a bootstrapping approach. These advances would extend existing in situ monitoring capabilities at the Lena River. Furthermore, they are beneficial for the pan-Arctic monitoring of DOC fluxes and broaden our understanding of the Arctic and global carbon cycle in a changing climate.