- M.M.P.D. Heijmans (1)
- G. Kiely (1)
- A. Klosterhalfen (1)
- V. Magliulo (1)
- A.F. Moene (1)
- M.K. Molen van der (1)
- W. Peters (1)
- J.W.M. Pullens (1)
- T.M. Scanlon (1)
- M. Schmidt (1)
- R. Silveyra González (1)
- M. Sottocornola (1)
- H. Vereecken (1)
- J. Vilà-Guerau de arellano (1)
- A.J.W. Wit de (1)
Sensitivity analysis of a source partitioning method for H2O and CO2 fluxes based on high frequency eddy covariance data : Findings from field data and large eddy simulations
Klosterhalfen, A. ; Moene, A.F. ; Schmidt, M. ; Scanlon, T.M. ; Vereecken, H. ; Graf, A. - \ 2019
Agricultural and Forest Meteorology 265 (2019). - ISSN 0168-1923 - p. 152 - 170.
Flux partitioning - Latent heat flux - LES - Net ecosystem exchange - Sensitivity analysis - Water use efficiency
Scanlon and Sahu (2008) and Scanlon and Kustas (2010) proposed a source partitioning method (SK10 in the following) to estimate contributions of transpiration, evaporation, photosynthesis, and respiration to H2O and CO2 fluxes obtained by the eddy covariance method. High frequency eddy covariance raw data time series are needed, and the source partitioning is estimated based on separate application of the flux-variance similarity theory to stomatal and non-stomatal components of the regarded fluxes, as well as on additional assumptions on leaf-level water use efficiency (WUE). We applied SK10 to data from two test sites (forest and cropland) and analyzed partitioning results depending on various ways to estimate WUE from available data. Also, we conducted large eddy simulations (LES), simulating the turbulent transport of H2O and CO2 for contrasting vertical distributions of the canopy sinks/sources, as well as for varying relative magnitudes of soil sources and canopy sinks/sources. SK10 was applied to the synthetic high frequency data generated by LES and the effects of canopy type, measurement height, given sink-source-distributions, and input of varying WUEs were tested regarding the partitioning performance. SK10 requires that the correlation coefficient between stomatal and non-stomatal scalar fluctuations is determined by the ratio of the transfer efficiencies of these scalar components, an assumption (transfer assumption in the following) that could be tested with the generated LES data. The partitioning results of the field sites yielded satisfactory flux fractions, when fair-weather conditions (no precipitation) and a high productive state of the vegetation were present. Further, partitioning performance with regard to soil fluxes increased with crop maturity. Results also showed relatively large dependencies on WUE, where the partitioning factors (median) changed by around -57% and +36%. Measurements of outgoing longwave radiation used for the estimation of foliage temperature and WUE could slightly increase the plausibility of the partitioning results in comparison to soil respiration measurements by decreasing the partitioning factor by up to 42%. The LES-based analysis revealed that for a satisfying performance of SK10, a certain degree of decorrelation of the H2O and CO2 fluctuations (here, |ρq'c’| < 0.975) was needed. This decorrelation is enhanced by a clear separation between soil sources and canopy sinks/sources, and for observations within the roughness sublayer. The expected dependence of the partitioning results on the WUE input could be observed. However, due to violation of the abovementioned transfer assumption, the known true input WUE did not yield the known true input partitioning. This could only be achieved after introducing correction factors for the transfer assumption, which were known however only in the special case of the LES experiments.
Grain Yield Observations Constrain Cropland CO2 Fluxes Over Europe
Combe, M. ; Wit, A.J.W. de; Vilà-Guerau de arellano, J. ; Molen, M.K. van der; Magliulo, V. ; Peters, W. - \ 2017
Journal of Geophysical Research: Biogeosciences 122 (2017)12. - ISSN 2169-8953 - p. 3238 - 3259.
Carbon cycle - CO - Cropland - Inverse modeling - Net ecosystem exchange - Optimization
Carbon exchange over croplands plays an important role in the European carbon cycle over daily to seasonal time scales. A better description of this exchange in terrestrial biosphere models-most of which currently treat crops as unmanaged grasslands-is needed to improve atmospheric CO2 simulations. In the framework we present here, we model gross European cropland CO2 fluxes with a crop growth model constrained by grain yield observations. Our approach follows a two-step procedure. In the first step, we calculate day-to-day crop carbon fluxes and pools with the WOrld FOod STudies (WOFOST) model. A scaling factor of crop growth is optimized regionally by minimizing the final grain carbon pool difference to crop yield observations from the Statistical Office of the European Union. In a second step, we re-run our WOFOST model for the full European 25 × 25 km gridded domain using the optimized scaling factors. We combine our optimized crop CO2 fluxes with a simple soil respiration model to obtain the net cropland CO2 exchange. We assess our model's ability to represent cropland CO2 exchange using 40 years of observations at seven European FluxNet sites and compare it with carbon fluxes produced by a typical terrestrial biosphere model. We conclude that our new model framework provides a more realistic and strongly observation-driven estimate of carbon exchange over European croplands. Its products will be made available to the scientific community through the ICOS Carbon Portal and serve as a new cropland component in the CarbonTracker Europe inverse model.
The NUCOMBog R package for simulating vegetation, water, carbon and nitrogen dynamics in peatlands
Pullens, J.W.M. ; Bagnara, M. ; Silveyra González, R. ; Gianelle, D. ; Sottocornola, M. ; Heijmans, M.M.P.D. ; Kiely, G. ; Hartig, F. - \ 2017
Ecological Informatics 40 (2017). - ISSN 1574-9541 - p. 35 - 39.
Competition - Net ecosystem exchange - NUCOMBOG - Peatland - R package - Vegetation
Since peatlands store up to 30% of the global soil organic carbon, it is important to understand how these ecosystems will react to a change in climate and management. Process-based ecosystem models have emerged as important tools for predicting long-term peatland dynamics, but their application is often challenging because they require programming skills. In this paper, we present NUCOMBog, an R package of the NUCOM-Bog model (Heijmans et al. 2008), which simulates the vegetation, carbon, nitrogen and water dynamics of peatlands in monthly time steps. The package complements the model with appropriate functions, such as the calculation of net ecosystem exchange, as well as parallel functionality. As a result, the NUCOMBog R package provides a user-friendly tool for simulating vegetation and biogeochemical cycles/fluxes in peatlands over years/decades, under different management strategies and climate change scenarios, with the option to use all the in-built model analysis capabilities of R, such as plotting, sensitivity analysis or optimization.