Estimating the lateral transfer of organic carbon through the European river network using a land surface model

Abstract

Abstract. Lateral carbon transport from soils to the ocean through rivers has been acknowledged as a key component of the global carbon cycle, but it is still neglected in most global land surface models (LSMs). Fluvial transport of dissolved organic carbon (DOC) and CO2 has been implemented in the ORCHIDEE LSM, while erosion-induced delivery of sediment and particulate organic carbon (POC) from land to river was implemented in another version of the model. Based on these two developments, we take the final step towards the full representation of biospheric carbon transport through the land–river continuum. The newly developed model, called ORCHIDEE-Clateral, simulates the complete lateral transport of water, sediment, POC, DOC, and CO2 from land to sea through the river network, the deposition of sediment and POC in the river channel and floodplains, and the decomposition of POC and DOC in transit. We parameterized and evaluated ORCHIDEE-Clateral using observation data in Europe. The model explains 94 %, 75 %, and 83 % of the spatial variations of observed riverine water discharges, bankfull water flows, and riverine sediment discharges in Europe, respectively. The simulated long-term average total organic carbon concentrations and DOC concentrations in river flows are comparable to the observations in major European rivers, although our model generally overestimates the seasonal variation of riverine organic carbon concentrations. Application of ORCHIDEE-Clateral for Europe reveals that the lateral carbon transfer affects land carbon dynamics in multiple ways, and omission of this process in LSMs may lead to an overestimation of 4.5 % in the simulated annual net terrestrial carbon uptake over Europe. Overall, this study presents a useful tool for simulating large-scale lateral carbon transfer and for predicting the feedbacks between lateral carbon transfer and future climate and land use changes.