Addressing Effects of Environment on Eddy-Covariance Flux Estimates at a Temperate Sedge-Grass Marsh

Abstract

We examined the net-ecosystem-exchange (NEE)-based annual carbon-balance estimates obtained from eddy-covariance (EC) measurements at an unmanaged sedge-grass marsh ecosystem (Třeboň, Czech Republic, 49°1′ N, 14°46′ E), seeking methods to improve the EC measurements in inhomogeneous environment. The data filtering procedure was developed using three thresholds: (a) a stationarity test; (b) a stability $${u}_{*}$$ u ∗ -threshold; and (c) a high relative humidity RH-threshold. This procedure was tested in 2014, a year without significant floods and drought events led to a stable water table, reducing the effect of soil respiration on the EC measurements. Estimates of annual carbon-balance were reduced from 182 to 234 ± 12 gC m−2 year−1 for the initial data to 39–44 ± 8 gC m−2 year−1 after the $$RH$$ RH ≤ 95% filtering and to 24–26 ± 7 gC m−2 year−1 after the further $${u}_{*}$$ u ∗ ≥ 0.1 m s−1 filtering. Applying the precipitation/fog threshold reduced this balance to 10–12 ± 7 gC m−2 year−1, closer to carbon neutrality. Up to 9.5% of this identified shift occurred during apparent nocturnal downslope katabatic drainage flows or plume descent coming from the nearby town of Třeboň. High-RH conditions account for up to 27% of this shift. Moreover, both conditions together account for an additional 67% of the identified carbon-balance change. Removing these non-ecosystem-related processes brings EC measurements closer to values of an unmanaged-ecosystem productivity, providing a better NEE-based estimate for the net ecosystem production. The presented procedure is applicable to EC measurements conducted at different wetlands or terrestrial ecosystems with similar conditions.

Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing

“…2a), as detailed in the flux station information file 16 . For the flux stations from the National Tibetan Plateau Data Center (NTPDC) and European Fluxes Database Cluster (EFDC) [134][135][136][137] (http://www.europe-fluxdata.eu/home), the flux data from one hour before (and after) rainfall were excluded. The data collected at 10-min or 30-min intervals were interpolated using the marginal distribution sampling (MDS) method in REddyProc 138 .…”

An Observational Case Study of a Radiation Fog Event

“…(iii) Several countries in the Carpathian-region participate in the ICOS project. The meteorological stations operating within ICOS are also used to study fog events (Kivalov et al, 2023). (iv) Ovesnik et al (2012), Matus et al (2020) and Miclea et al (2020) published results about the improvement of sensors for detection of fog formation and density.…”