ИСТИНА

Carbon status in agroecosystems depends on climate, land use and the level of agricultural technology. The Central Russia is still one of the less GHG-investigated areas especially in case of agroecosystem-level carbon dioxide fluxes monitoring by eddy covariance (EC) method. An attractive way to compare the agricultural practices influences on the CO2 fluxes and budget is to divide a crop area into subplots managed in different ways. Unfortunately, to install stationary EC towers on all versions of field experiment is not possible due to financial reasons. The objective of this work was to evaluate the uncertainty of CO2 fluxes monitoring by mobile EC towers on the basis of data obtained for 2 years with two stationary towers located on neighboring fields. Simulation was based on the research carried out on the Precision Farming Experimental Field of the RTSAU (Moscow, Russia) in 2013 and 2014 under the support of RF Government grant № 11.G34.31.0079. The agroecosystem CO2 flux seasonal monitoring was done by two eddy covariance stations located on the 4 ha experimental field at the distance of 108 m. The LI-COR instumental eqipments was the same for the both stations. The stations differ only by current crop version of the crop rotation including potato, winter weat, barley and grasses. The measurement height was 1.4 m. The footprints was considered as 55 m. Calculatings were done using EddyPro softwere. The data gap filling by Reichstein et al. (2005) was used. The difference between micrometeorological conditions on two fields was negligible during the same year. The simulation was performed in the same way for each of the four annual series of net ecosystem exchange (NEE) with the 30 minutes lag. The year was conditionally divided into periods according to the seasons and phases of the crop development. For each period, the distributions of missing and rejected for some reasons data were evaluated for every annual series of NEE. The gaps distributions during daytime and nighttime were different for the vegetation periods and were estimated separately. The actual data from two stationary EC towers within 2 years were provisionally accepted as four general populations. One hundred time series of NEE with gaps were obtained for every general population. Three strategies for mobile towers were considered: they expected to be moved every 5, 10 or 15 days. The gaps filling procedure was applied to the obtained datasets and the carbon fluxes and budget values during the growing seasons and the years were calculated. The results have shown that when using the mobile towers the uncertainty assessment of daily and seasonal dynamic CO2 fluxes exceeded 10%, and in some cases grew up to 30%. The optimal strategy in terms of reducing uncertainty assessment of CO2 fluxes is to move the mobile tower every 5 days during the periods of intensive crop growth and its ripening.