Quantifying landcover-specific fluxes over a heterogeneous landscape through coupling UAV-measured mixing ratios with transport models and eddy-covariance measurements

Many natural ecosystems are composed of heterogeneous patches differentiated by e.g. topography, wetness levels, or vegetation composition, leading to strong small-scale variability in surface–atmosphere exchange fluxes. Quantifying this variability remains challenging, as traditional approaches rely either on episodic point-scale measurements (e.g. chambers) or on eddy-covariance (EC) observations that integrate fluxes over large and spatially mixed footprints. Unmanned Aerial Vehicles (UAV) offer a unique observational capability to bridge this scale gap by providing flexible, high-resolution measurements of atmospheric trace gas distributions.

Here, we present a case study based in Stordalen Mire in subarctic Sweden, where we set-up a site-level inversion method to differentiate the flux rate signatures from different patch types. We used 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 and CH₄ mixing ratio. 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 fluxes from palsa, bog, and fen, and showed a good agreement in flux patterns across those patch types dominating the UAV-sampled footprint. To reduce the computational requirements and make the workflow more efficient, bLSmodelR, a backward Lagrangian stochastic (bLS) dispersion model, was added as an alternative transport model to inform the inversion. Results based on bLS transport in a standard setup showed comparable results to the LES model, while the reduced computation time allowed more degrees of freedom for refining the optimization.

Our results demonstrate the potential of UAV-based atmospheric measurements, combined with transport modelling, to resolve surface–atmosphere exchange heterogeneity within complex landscapes. Ongoing efforts aim to derive patch-level fluxes over the mire by integrating UAV-measured mixing ratios with eddy-covariance and chamber measurements collected within nested footprints during the STORDALENX25 campaign in summer 2025.