| 1. |
- Jansen, Joachim, 1989-, et al.
(författare)
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Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing
- 2023
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Ingår i: Scientific Data. - : Springer Nature. - 2052-4463. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.
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| 2. |
- Gottselig, N., et al.
(författare)
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Elemental Composition of Natural Nanoparticles and Fine Colloids in European Forest Stream Waters and Their Role as Phosphorus Carriers
- 2017
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Ingår i: Global Biogeochemical Cycles. - 0886-6236 .- 1944-9224. ; 31:10, s. 1592-1607
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Tidskriftsartikel (refereegranskat)abstract
- Biogeochemical cycling of elements largely occurs in dissolved state, but many elements may also be bound to natural nanoparticles (NNP, 1-100 nm) and fine colloids (100-450 nm). We examined the hypothesis that the size and composition of stream water NNP and colloids vary systematically across Europe. To test this hypothesis, 96 stream water samples were simultaneously collected in 26 forested headwater catchments along two transects across Europe. Three size fractions (~1-20 nm, >20-60 nm, and >60 nm) of NNP and fine colloids were identified with Field Flow Fractionation coupled to inductively coupled plasma mass spectrometry and an organic carbon detector. The results showed that NNP and fine colloids constituted between 2 ± 5% (Si) and 53 ± 21% (Fe; mean ± SD) of total element concentrations, indicating a substantial contribution of particles to element transport in these European streams, especially for P and Fe. The particulate contents of Fe, Al, and organic C were correlated to their total element concentrations, but those of particulate Si, Mn, P, and Ca were not. The fine colloidal fractions >60 nm were dominated by clay minerals across all sites. The resulting element patterns of NNP <60 nm changed from North to South Europe from Fe- to Ca-dominated particles, along with associated changes in acidity, forest type, and dominant lithology.
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| 3. |
- Zhang, Weijie, et al.
(författare)
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The effect of relative humidity on eddy covariance latent heat flux measurements and its implication for partitioning into transpiration and evaporation
- 2023
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Ingår i: Agricultural and Forest Meteorology. - : Elsevier BV. - 0168-1923. ; 330
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Tidskriftsartikel (refereegranskat)abstract
- While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or 'evapotranspiration’, ET), the measurement is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (>70%), due to low-pass filtering with some EC systems. Yet, this underestimation for different types of EC systems (e.g. open-path or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of latent heat fluxes (LE, or ET) from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that the LE underestimation is most apparent during hours when RH is higher than 70%, predominantly observed at sites using closed-path EC systems, but the extent of the LE underestimation is highly site-specific. We then propose a machine learning based method to correct for this underestimation, and compare it to two energy balance closure based LE correction approaches (Bowen ratio correction, BRC, and attributing all errors to LE). Our correction increases LE by 189% for closed-path sites at high RH (>90%), while BRC increases LE by around 30% for all RH conditions. Additionally, we assess the influence of these corrections on ET-based transpiration (T) estimates using two different ET partitioning methods. Results show opposite responses (increasing vs. slightly decreasing T-to-ET ratios, T/ET) between the two methods when comparing T based on corrected and uncorrected LE. Overall, our results demonstrate the existence of a high RH bias in water fluxes in the FLUXNET2015 dataset and suggest that this bias is a pronounced source of uncertainty in ET measurements to be considered when estimating ecosystem T/ET and WUE.
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