ИСТИНА

The most widely used methods for greenhouse gases (GHG) flux measurements such as eddy covariance and chamber methods have many methodological limitations for flux measurements, especially over non-uniform areas. The main objective of this study is to explore the possibility of estimating GHG fluxes over complex areas using an Unmanned Aircraft Vehicle (UAV) for gas concentrations measurements combined with a three-dimensional hydrodynamic model that was initially designed to compute the distribution of stationary GHG concentrations over a non-uniform surface, when the GHG fluxes at the lower boundary are known. The inverse problem of determining unknown GHG fluxes involves minimizing the difference between measured and modeled GHG concentrations at several levels. A forested area in the foothills of the Greater Caucasus Mountains in Russia was selected as the experimental area for the modeling study. This area is the subject of intensive studies of GHG fluxes using ground-based methods. Hence, we can use the information about surface CO2 and CH4 fluxes for testing our inverse approach. Numerical experiments performed with surrogate concentration data of different measurement errors and density of measurement points shoved the estimated fluxes remain close to the target values even with a coarse measurement grid. The performed statistical analysis revealed that the maximum error values can be considered as outliers of the method and refining the grid near surface heterogeneities improves the results. The study was supported by the state assignment of the Grozny State Oil Technical University (Project Reg. No. FZNU-2024-0002).