Quantifying landcover-specific fluxes over a heterogeneous landscape through coupling UAV-measured mixing ratios with a large-eddy simulation model and Eddy-covariance measurements

Abstract. Many natural ecosystems are composed of heterogeneous patches differentiated by wetness levels and vegetation composition, resulting in fine-scale flux patterns across the different landcovers that can be challenging to quantify. Here, we present a case study at Stordalen Mire in subarctic Sweden, where we conducted Uncrewed Aerial Vehicle (UAV) measurements of CO₂ mole fractions and combine them with a large-eddy simulation (LES) model through a site-level inversion method to differentiate the flux rate signatures from different patch types. We use the LES model EULAG (EUlerian LAGrangian) to simulate high-resolution flow patterns and benchmark the spatial variability of modelled concentrations with data from UAV-based grid surveys of CO2 mixing ratio. Coupling the inversion results with eddy-covariance (EC) flux measurements for the time of the UAV flight allows quantifying net CO2 fluxes for the individual landcover types. Model evaluation showed an R2 exceeding 0.60, with model uncertainties mostly related to the transport model uncertainty and the UAV sampling footprint that does not evenly sample landcover types. The inversion fluxes were subsequently compared to patch-level chamber measurements of carbon dioxide from palsa, bog, and fen, and showed a good agreement in flux patterns across those patch types dominating the UAV-sampled footprint. Different landcover classification schemes were considered, and results showed a consistent improvement in the model performance when further representing the ecological and hydrological heterogeneities. Our novel technique shows promising results in estimating landcover-type flux heterogeneity within eddy-covariance tower footprints, thus providing a basis for upscaling of EC fluxes to a larger domain.