Organic fertilizers are widely used around the world, because they support the circular economy, sustainable agriculture, and improved soil quality, as well as carbon sequestration. State-of-the-art, process-based models can simulate the environmental impacts of organic fertilizer use and can address issues like the effect of fertilizer amount and type on crop production, soil fertility, soil organic matter accumulation, nitrate leaching, and greenhouse gas emission. However, the lack of information on the proper attribute settings for fertilizer inputs in the models hampers their application. In this study, the main goal was to support the setting of organic fertilizer attributes for process-based model applications. A comprehensive data collection was performed to gather organic fertilizer attributes that are relevant for the carbon and nitrogen cycle-related simulations. Based on the literature search, representative values are presented that can be instantly used in the models as generalized settings for several farmyard manure and slurry types. We also addressed the question of how fertilizer attribute-setting-related uncertainties propagate to the simulation outputs. We used the Biome-BGCMuSo biogeochemical model for that purpose with a maize monoculture simulation. The results indicate that manure type specific attribute setting is crucial for the nitrogen balance related model variables. For soil nitrous oxide efflux, improper composition settings can severely distort the simulation results. Sensitivity analysis suggested that dry matter content and organic nitrogen content are the two most important manure attributes that modellers must properly adjust. For slurry, the dry matter and ammonium content must be constrained for proper simulation results. The study supports crop and biogeochemical model setup with ready-to-use pragmatic information.

Reliable micrometeorological forcing data are essential for process-based climate impact models. Open-source flux-tower products such as ICOS and FLUXNET provide highly valuable standardized datasets for ecosystem research, but their continuous reprocessing, version updates, and multi-step gap-filling may introduce forcing-data sensitivities that are rarely quantified from a modelling perspective. In this study, we applied the subdaily version of the physically based one-dimensional soil-plant-atmosphere model BROOK90 at the spruce forest ecosystem monitoring site DE-Tha in Tharandt, Germany, to assess how dataset versioning, short-term forcing discontinuities, and different gap-filling strategies affect simulated water and energy fluxes. Successive dataset versions led to substantial version-dependent differences in historical time series of air temperature, solar radiation, precipitation, wind speed, and vapor pressure deficit, which altered simulated energy fluxes and the partitioning of evaporation components. Short-term discontinuities associated with sensor gaps and transitions between measured, MDS-filled, and reanalysis-filled values propagated into physically unlikely flux components, including negative interception and soil evaporation as well as reduced transpiration in selected periods. Controlled forcing-substitution experiments showed that model uncertainty increased with both the proportion and duration of substituted data sequences. Latent heat flux was comparatively less sensitive to ERA data substitution, whereas sensible heat flux showed substantial and systematic underestimation. Multivariate forcing substitution amplified these effects, and the partitioning of latent heat flux revealed a consistent overestimation of interception and soil evaporation associated with an underestimation of transpiration. Although BROOK90 remained numerically stable, forcing-data inconsistencies affected the simulated representation of evapotranspiration processes. These findings underline the value of explicit dataset version tracking, diagnostic checks of gap-filled forcing periods, and continued development of user guidance for reproducible and physically interpretable impact modelling.

Robust climate-impact and (eco)hydrological modelling as well as reproducible research practices rely on (micro)meteorological forcing data that are both physically consistent and stable across dataset versions — conditions that are often difficult to meet within long-term micrometeorological networks. Continuous reprocessing of raw measurements, as implemented in ICOS and FLUXNET, can unintentionally reshape subdaily time series and thereby alter simulations of water and energy balance components. In our research, we identified two major post-processing error sources: dataset versioning and gap-filling. To evaluate how these transformations propagate into process-based modelling, we used the ICOS DE-Tha old-spruce forest site in Saxony (Germany) as a representative case study and applied the subdaily, physically based 1D ecohydrological model BROOK90 to perturbed forcing datasets.Successive ICOS dataset versions introduced substantial corrections to air temperature, solar radiation, precipitation, wind speed, and vapor pressure, which in turn noticeably altered simulated interception, transpiration, and soil evaporation. Standard ICOS gap-filling procedures (MDS and ERA-I) were also found to generate implausible values, particularly where outputs from different algorithms occurred in close succession, producing artificial spikes such as 10 °C temperature jumps within a 30-minute interval. Artificial gap-filling experiments using ERA-I demonstrated that uncertainties in modeled water and energy balance components increase systematically with both the proportion (1-50%) and the block-length (30 min - 30 days) of substituted subdaily meteorological data. Precipitation and solar radiation replacements induced the strongest single-variate deviations, and multivariate gap-filling resulted in substantially larger uncertainties than single-variable substitutions—approaching 25% overestimation for latent heat (LE) and more than 40% underestimation for sensible heat (H) at 50% substitution using 30-minute blocks. Evapotranspiration partitioning revealed consistent bias patterns under multivariate substitutions, including reduced transpiration and strong overestimation of interception and soil evaporation. Although BROOK90 remained numerically stable across all tested perturbation scenarios, inconsistencies in subdaily forcing propagated into physically implausible process representations.Importantly, similar inconsistencies and artifacts have been found across many ICOS and FLUXNET sites worldwide, indicating that these issues are systemic rather than site-specific. Our findings highlight that reproducibility and reliability in long-term flux-network modelling depends critically on transparent dataset versioning, rigorous anomaly detection, and harmonized multivariate gap-filling practices. Strengthening these components will enhance the scientific value of flux networks by ensuring that impact-based ecosystem modelling is grounded in trustworthy subdaily forcing data.

Accurate estimation of Gross Primary Productivity (GPP) for European winter wheat is critical for assessing regional food security and understanding land-atmosphere carbon exchange. Light Use Efficiency (LUE) models are widely applied in natural ecosystems, but their performance in dynamic agricultural landscapes, particularly for key crops like winter wheat, remains underexplored. To bridge this gap, we developed IB-WSE-LUE (INRAE-BORDEAUX-water stress enhanced-light use efficiency), a novel GPP model specifically tailored for winter wheat. This model leverages high-resolution Sentinel-2 satellite data and comprehensively integrates key environmental stress factors, enabling GPP simulation at an unprecedented 10-meter spatial resolution. We compared IB-WSE-LUE against thirteen established GPP models, using both tower-based meteorological data and the ERA5 reanalysis dataset (the latter ensuring broader applicability across large scales without reliance on extensive in-situ measurements). Validation demonstrated IB-WSE-LUE's superior performance, achieving average R2 improvements of 11.9% (with tower data) and 8.8% (with ERA5 dataset) in daily GPP simulations for European winter wheat. Furthermore, IB-WSE-LUE more accurately captured spatial, seasonal, and interannual GPP variations and significantly reduced the common underestimation at high GPP levels observed in other models. Its robust performance extended to drought and high-temperature conditions, demonstrating that water stress exerts a stronger influence on winter wheat GPP than temperature stress, a feature accurately captured by our model. This study provides a robust, high-resolution, and spatially transferable framework for accurately monitoring and predicting winter wheat GPP across large agricultural regions, offering key insights for food security assessments and improved agricultural land management in a changing climate.

The storage flux, corresponding to disequilibrium between observed flux and net surface emissions, poses a significant source of uncertainty in tower-based eddy covariance (EC) measurements over urban and forest ecosystems. In this study, we investigated the coupling between the urban inertial sub-layer (ISL) and roughness sub-layer (RSL) and its influence on nighttime storage flux, leveraging tower-EC together with collocated wind profile measurements. Our findings demonstrate that substantial storage flux occurs when the gradient of turbulent kinetic energy (TKE) enlarges, indicating decoupling between ISL and RSL. With increasing wind speed, turbulent eddies generated by bulk wind shear directly interact with the surface, conducive to the recoupling between ISL and RSL and resulting in decreased storage flux. Conversely, when the gradient of TKE between ISL and RSL is small, the storage flux remains low and relatively insensitive to wind speed. The derived diagnostic relation further confirms the predominant influence of stability and turbulent intensity gradient on regulating the storage flux. These results provide valuable insights as a complement to prior storage flux studies in the context of canopy flow.

Abstract. Compared to drought and heat waves, the impact of winter warming on forest CO2 fluxes has been less studied, despite its significant relevance in colder regions with higher soil carbon content. Our objective was to test the effect of the exceptionally warm winter of 2020 on the winter CO2 budget of cold-adapted evergreen needleleaf forests across Europe and identify the contribution of climate factors to changes in winter CO2 fluxes. Our hypothesis was that warming in winter leads to higher emissions across colder sites due to increased ecosystem respiration. To test this hypothesis, we used 98 site-year eddy covariance measurements across 14 evergreen needleleaf forests (ENFs) distributed from the north to the south of Europe (from Sweden to Italy). We used a data-driven approach to quantify the effect of radiation, air temperature, and soil temperature on changes in CO2 fluxes during the warm winter of 2020. Our results showed that warming in winter decreased forest net ecosystem productivity (NEP) significantly across most sites. The contribution of climate variables to CO2 fluxes varied across the sites: in southern regions with warmer mean temperatures, radiation had a greater influence on NEP. Conversely, at colder sites, air temperature played a more critical role in affecting NEP. During the warm winter of 2020, colder regions experienced larger air temperature anomalies compared to the other sites; however we did not observe a significantly larger increase at colder sites due to winter warming. The varying responses of NEP across different sites highlight the complex interactions between climate variables such as air temperature, soil temperature, and radiation. These findings underscore the importance of integrating winter warming effects to more accurately predict the impacts of climate change on forest carbon dynamics.

Terrestrial ecosystems play a crucial role in carbon sequestration and provide vital ecosystem services such as food, energy, and raw materials. Climate change, through rising temperatures, altered precipitation patterns, and extreme events, threatens the carbon sink potential of these ecosystems, with forests and grasslands particularly at risk. Long-term data from flux tower networks offer valuable insights into how different ecosystems respond to climate change and management interventions, helping to develop strategies to mitigate greenhouse gas emissions and maintain ecosystem resilience. In this study, we present such data from a <10 km cluster of long-term FLUXNET/ICOS sites in Central Europe, comprising an old spruce forest (DE-Tha), a young oak plantation after a cleared windthrow (DE-Hzd), a permanent grassland site (DE-Gri), and an agricultural site with a crop rotation typical for this region (DE-Kli). By analysing decades of data from these eddy covariance measurement sites, the research highlights the influence of drought, management, and land cover changes on CO2 and H2O fluxes. The interannual variability of evapotranspiration depends less on land use than the CO2 exchange. Our findings show that intact forests can act as larger carbon sinks than previously estimated. DE-Tha is a consistent carbon sink, with thinning helping to maintain the CO2 sequestration at a stable level of 350 gC m- 2 a- 1. In contrast, disturbances like clear cutting or windthrow can cause ecosystems to become carbon sources for several years, with recovery delayed due to soil carbon losses from increased respiration (DE-Hzd). While DE-Hzd was resilient to drought, the carbon uptake of DE-Tha was significantly reduced by around 50 % during dry years compared to wet years. Furthermore, sustainable management maintains carbon sequestration and land-use practices, such as crop selection, significantly impact net ecosystem productivity. These insights are valuable for optimizing land management strategies to enhance carbon sinks in similar regions.

Oberflächennahe Geothermie ist eine der möglichen Technologien für eine erfolgreiche Wärmewende. Die Auslegung dieser Anlagen erfolgt anhand von Entzugsleistungen, die so bemessen sind, dass sich der Boden in den Sommermonaten regenerieren kann. Der vorliegende Beitrag beleuchtet die Zusammenhänge zwischen Solarstrahlung, Außenluft, Geländeoberkante und Erdreich. Diese Schnittstelle wird bisher in verschiedenen Fachdisziplinen kaum beachtet. Anhand der diskutierten Messwerte der ICOS-Station Grillenburg zeigt sich, dass die im ungestörten Erdreich aufgenommene Jahresenergiemenge deutlich weniger als ein Prozent der jährlichen Nettostrahlung beträgt.

Management practices that increase the surface albedo of cultivated land could mitigate climate change, with similar effectiveness to practices that reduce greenhouse gas emissions or favor natural CO 2 sequestration. Yet, the efficiency of such practices is barely quantified. In this study, we quantified the impacts of seven different management practices on the surface albedo of winter wheat fields (nitrogen fertilizer, herbicide, fungicide, sowing, harvest, tillage, and crop residues) by analyzing observed daily albedo dynamics from eight European flux-tower sites with interpretable machine learning. We found that management practices have significant influences on surface albedo dynamics compared with climate and soil conditions. The nitrogen fertilizer application has the largest effect among the seven practices as it increases surface albedo by 0.015 ± 0.004 during the first two months after application, corresponding to a radiative forcing of −4.39 ± 1.22 W m −2 . Herbicide induces a modest albedo decrease of 0.005 ± 0.002 over 150 d after application by killing weeds in the fallow period only, resulting in a magnitude of radiative forcing of 1.33 ± 1.06 W m −2 which is higher than radiative forcing of other practices in the same period. The substantial temporal evolution of the albedo impacts of management practices increases uncertainties in the estimated albedo-mediated climate impacts of management practices. Although these albedo effects are smaller than published estimates of the greenhouse gas-mediated biogeochemical practices, they are nevertheless significant and should thus be accounted for in climate impact assessments.

In Europe, the heterogeneous features of crop systems with majority of small to medium sized agricultural holdings, and diversity of crop rotations, require high-resolution information to estimate cropland Net Ecosystem Exchange (NEE) and its two main components of Gross Ecosystem Exchange (GEE) and the Ecosystem Respiration (RECO). In this context, this paper presents an assimilation of high-resolution Sentinel-2 indices with eddy covariance measurements at selected European cropland flux sites in a new modified version of Vegetation Photosynthesis Respiration Model (VPRM). VRPM is a data-driven model simulating CO2 fluxes previously applied using satellite-derived vegetation indices from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study proposes a modification of the VPRM by including an explicit soil moisture stress function to the GEE and changing the equation of RECO. It also compares the model results driven by S2 indices instead of MODIS. The parameters of the VPRM model are calibrated using eddy-covariance data. All possible parameters optimization scenarios include the use of the initial version vs. the proposed modified VPRM, S2, or MODIS vegetation indices, and finally the choice of calibrating a single set of parameters against observations from all crop types, a set of parameters per crop type, or one set of parameters per site. Then, we focus the analysis on the improvement of the model with distinct parameters for different crop types vs. parameters optimized without distinction of crop types. Our main findings are: (1) the superiority of S2 vegetation indices over MODIS for cropland CO2 fluxes simulations, leading to a root mean squared error (RMSE) for NEE of less than 3.5 μmolm-2s-1 with S2 compared to 5 μmolm-2s-1 with MODIS (2) better performances of the modified VPRM version leading to a significant improvement of RECO, and (3) better performances when the parameters are optimized per crop-type instead of for all crop types lumped together, with lower RMSE and Akaike information criterion (AIC), despite a larger number of parameters. Associated with the availability of crop-type land cover maps, the use of S2 data and crop-type modified VPRM parameterization presented in this study, provide a step forward for upscaling cropland carbon fluxes at European scale.

The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models.

Abstract. Relative to drought and heat waves, the effect of winter warming on forest CO2 fluxes during the dormant season has less been investigated, despite its relevance for net CO2 uptake in colder regions with higher carbon content in soils. Our objective was to test the effect of the exceptionally warm winter in 2020 on the winter CO2 budget of cold-adapted evergreen needle-leaf forests across Europe, and identify the contribution of soil and air temperature to changes in winter CO2 fluxes in response to warming. Our hypothesis was that warming in winter leads to higher emissions across colder sites due to increased ecosystem respiration. To test this hypothesis, we used 98 site-year eddy covariance measurements across 14 evergreen needle-leaf forests (ENFs) distributed from north to south of Europe (from Sweden to Italy). We used a data-driven approach to quantify the effect of air and soil temperature on changes in net ecosystem productivity (NEP) during the warm winter of 2020. Our results showed that the impact of warming was different across sites, as in the lower altitude and lower latitude sites positive soil temperature anomalies were larger, while positive air temperature anomalies were larger in the northern latitude and high-altitude sites. Warming in winter led to a divergent response across the sites. Out of 14 sites only in 3 sites net ecosystem productivity declined in winter significantly in response to warming. In addition, we observed that in the colder sites daytime NEP (that is dominated by photosynthesis) declined with warming of the air in winter, whereas in the warmer sites daytime NEP increased with warming of the soil. This shows that warming of the air – if not translated into a direct warming of the soil– might not trigger productivity in winter if the soil within the rooting zone remains frozen. Forests within the same plant functional type category can exhibit differing reactions to winter warming and to predict their responses accurately it is crucial to account for variations in local climate, physiology, and structure simultaneously.

Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.

Climate changes are expected to trigger changes in all water budget components at any scale. For Central Europe, higher evapotranspiration (ET) rates are already observed, other factors like land use or land cover characteristics change in parallel, but experimental evidence of the interdcations is limited, as it requires challenging long-term measurements. We take advantage of the well-documented hydro-meteorological dataset from the forested research catchment Wernersbach in Saxony, Germany, covering 52 years between 1968 and 2019 (Pluntke & Bernhofer et al., 2023).We analyzed hydro-climatological time-series for linear trends and for breakpoints. Significant positive trends were found for global radiation, mean air temperature and grass-reference evaporation, as well as for the difference between catchment precipitation and runoff (P-R; hydrological estimate of ET). Precipitation increased and runoff decreased over the 52 years, but not significantly.Air temperature and global radiation show significant breakpoints around 1988 and 1996, respectively, with below average conditions before and above average conditions after the breakpoints. Temperature change is associated with global warming, and possibly with the independent regional effect of air pollution. Since the 1960s, large sulphur dioxide emissions from fossil fuel burning led to a high aerosol density in the troposphere reducing solar radiation over most of Europe and North America. While this effect was reduced by filtering the emissions elsewhere in the early 1980s, it continued in neighboring parts of today’s Germany, Poland, and Czech Republic until the early 1990s. Breakpoint of grass reference evaporation coincides with air temperature (1988), and the breakpoint of P-R is a few years later.We attributed changes in ET to changes in land use and climate by applying an adapted Budyko framework and enabled insights into their interactions. The sulphur dioxide emissions triggered widespread forest dieback in regions over 600 m in Saxony. Consequences were decreasing ET in the 1970s/1980s. The Wernersbach catchment (390 m) shows a similar tendency (not significant). Since the 1990s, both climate (increasing atmospheric demand) and land use (healthier forest stands and improved management practices) led to an increase of ET. In 2010s, climate induced damages of forest stands (due to droughts, storms, snow load, and bark beetle infestations) led to a drastic decrease of ET in Wernersbach despite favorable climatic conditions for ET. Since the intensity and frequency of such extreme events are likely part of climate change, they may cause greater regional changes in the water balance than direct effects of climate change, and may cause lasting damage to Ecosystem Services of forests, like flood mitigation, or carbon sequestration.Our results show the need for climate adaptation measures in forests, such as the establishment of a more site-specific mixed forest, and a sustainable forest management. ReferencesPluntke T. & Bernhofer C., Grünwald T., Renner M., Prasse H.: Long-term climatological and ecohydrological analysis of a paired catchment – flux tower observatory near Dresden (Germany). Is there evidence of climate change in local evapotranspiration? J Hydrol 617 (2023), https://doi.org/10.1016/j.jhydrol.2022.128873

Today, peatlands only cover slightly more than 3.5 % of Germanys territory. However, they play an important role concerning greenhouse gas emissions (CO2, CH4). We can avoid most of these emissions by proper management of the water table. This leads to a large potential net benefit for climate mitigation when re-establishing valuable long-term carbon sinks at the same time. Measurements in peatlands are challenging because they are often situated in remote locations, and it is difficult to install measurement towers on these statically unstable soils. Two wetlands in Germany (grey willow in NE Germany; black alder in Eastern Brandenburg) are compared to the TU Dresden cluster of sites close to Dresden. The wetlands receive comparatively little precipitation, e.g. the grey willow site receives on average 580 mm/year (average from 1991 – 2020) but the water table is dominated by the nearby river Peene (fluctuating in dependence of the hydrological conditions in its estuary area). Similar complexity exists for the black alder site with regard to the managed water table of the river Spree. Measurements are available from eddy-covariance since 2010 for the grey willow, and from 2010 to 2015 for the black alder. Yearly, seasonal and daily data of CO2 (gross primary production, ecosystem respiration) and H2O are analysed relative to the water table and the climate forcing (radiation, vapour pressure deficit and wind). Special attention will be paid to the flux patterns at each site (fingerprints of ET, FC and of WUE). A comparison to the long-term cluster sites (forests, grassland and crop rotation) allows a first assessment of the potential benefit of various land management systems for climate mitigation. However, uncertainty might be large due to the differences in soil and climate, as well as by the typical non-linearity of complex systems like the wetlands and their dependence to the water table.

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.

Data and Code for 'Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects' by Graf et al. (Communications Earth and Environment)

&lt;p&gt;We combine long-term hydro-meteorological data from the small research catchment Wernersbach (WB, 4.6 km&amp;#178;, dominated by Norway spruce) in operation since 1967 and from two eddy-covariance (EC) flux towers, all located in the Tharandt Forest, Germany. This combination forms an observatory, addressing actual evapotranspiration ET from a water budget perspective (catchment) and from an energy perspective (EC flux towers). However, obvious differences exist in time resolution. The spruce dominated tower DE-Tha is located a few kilometres east of the catchment. After a windbreak of another spruce stand (situated inside the catchment) and planting of deciduous oaks, the tower DE-Hzd was set up in 2009. We recently reported systematically about the observatory and the long-term water budgets in Pluntke &amp; Bernhofer et al. (https://doi.org/10.1016/j.jhydrol.2022.128873).&lt;/p&gt;&lt;p&gt;The catchment and both towers did not show any systematic differences in meteorological data (especially wind-loss corrected precipitation totals are almost identical), allowing us to address observed differences in ET as (i) due to different soil and hydrogeological characteristics as well as (ii) due to methodological aspects. The catchment term ET plus storage, derived from precipitation P minus runoff R, showed the expected high variability with a significant increase over the more than 50 years of operation. The older, spruce-dominated flux-tower DE-Tha showed much lower inter-annual variability in ET with an average annual total of 486 mm (1997 to 2019), but no significant trend. For the same period, average catchment ET was 734 mm/year. The younger flux-tower DE-Hzd showed ET values closer to catchment ET at the very dry end of the ten-year record (2010 to 2019).&lt;/p&gt;&lt;p&gt;For the 23 years of parallel measurements, annual ET from EC was about 250 mm lower than catchment ET, despite the careful correction of tower ET for energy balance closure. Catchment ET = P &amp;#8211; R might have a small bias towards larger ET, as the subsurface catchment size of WB could be up to 0.4 km&amp;#178; smaller. In addition, precipitation and runoff may contribute to higher catchment ET. However, the difference is too large to be explained by measurement bias alone. Flux tower ET is compared to (i) independent measurements of ET components, and (ii) model output of BR90. There is evidence from interception and transpiration measurements at the flux tower that more than 100 mm of intercepted water could be missing in the annual ET from EC. Model results show a large additional contribution of interception due to negative sensible fluxes in fall and winter. The difference in ET between tower and catchment of 250 mm is probably due to a variety of reasons: overestimation of catchment ET (up to 50 mm), soil characteristics (50-100 mm), and underestimation of tower ET (100-150 mm).&lt;/p&gt;&lt;p&gt;We conclude that the EC closure correction during interception events needs to be revisited. Generally, results of ET monitoring of similar evergreen forests in a humid climate should be checked for missing contribution of interception, as EC records might be generally too low. This illustrates the necessity of redundant and complementary measurements when dealing with large system complexity.&lt;/p&gt;

(1) Laboratoire des Sciences du Climat et de l’Environnement, IPSL/LSCE, CEA/CNRS/UVSQ, Gif-sur-Yvette, France, (2) Centre International de Recherche sur l’Environnement et le Developpement-CNRS/EHESS, Nogent sur Marne, France, (3) CESBIO Unite mixte CNES-CNRS-UPS-IRDUMR 5126, Toulouse, France, (4) INRA Unite Mixte de Recherche INRA / AgroParisTech Environnement et Grandes Cultures, Thiverval – Grignon, France, (5) ETH Zurich, Institute of Plant Sciences, Zurich, Switzerland, (6) Institute of Hydrology and Meteorology, Technische Universitat Dresden, Tharandt, Germany, (7) Earth System Science and Climate Change Group, Alterra Wageningen UR, Wageningen, The Netherlands