Search

Despite previous reports on European growing seasons lengthening due to global warming, evidence shows that this trend has been reversing in the past decade due to increased transpiration needs. To asses this, we used an innovative method along with space-based observations to determine the timing of greening and dormancy and then to determine existing trends of them and causes. Early greening still occurs, albeit at slower rates than before. However, a recent (2011–2020) shift in the timing of dormancy has caused the season length to decrease back to 1980s levels. This shortening of season length is attributed primarily to higher atmospheric water demand in summer that suppresses transpiration even for soil moisture levels as of previous years. Transpiration suppression implies that vegetation is unable to meet the high transpiration needs. Our results have implications for future management of European ecosystems (e.g., net carbon balance and water and energy exchange with atmosphere) in a warmer world.

Integrated long-term, in-situ observations are needed to document ongoing environmental change, to “ground-truth” remote sensing and model outputs and to predict future Earth system behaviour. The scientific and societal value of in-situ observations increases with site representativeness, temporal duration, number of parameters measured and comparability within and across sites. Research Infrastructures (RIs) can support harmonised, cross-site data collection, curation and publication. Integrating RI networks through site co-location and standardised observation methods can help answers three questions about the terrestrial carbon sink: (i) What are present and future carbon sequestration rates in northern European forests? (ii) How are these rates controlled? (iii) Why do the observed patterns exist? Here, we present a conceptual model for RI co-location and highlight potential insights into the terrestrial carbon sink achievable when long-term in-situ Earth observation sites participate in multiple RI networks (e.g., ICOS and eLTER). Finally, we offer recommendations to promote RI co-location.

Hydro-pedotransfer functions (PTFs) relate easy-to-measure and readily available soil information to soil hydraulic properties for applications in a wide range of process-based and empirical models, thereby enabling the assessment of soil hydraulic effects on hydrological, biogeochemical, and ecological processes. At least more than four decades of research have been invested to derive such relationships. However, while models, methods, data storage capacity, and computational efficiency have advanced, there are fundamental concerns related to the scope and adequacy of current PTFs, particularly when applied to parameterize models used at the field scale and beyond. Most of the PTF development process has focused on refining and advancing the regression methods, while fundamental aspects have remained largely unconsidered. Most system settings are not captured by existing PTFs, which have been built mostly for agricultural soils in temperate climates. Thus. existing PTFs largely ignorie how parent material, vegetation, land use, and climate affect processes that shape soil hydraulic properties. The PTFs used to parameterise the Richards-Richardson equation are mostly limited to predicting parameters of the van Genuchten-Mualem soil hydraulic functions, despite sufficient evidence demonstrating their shortcomings. Another fundamental issue relates to the diverging scales of derivation and application, whereby PTFs are derived based on laboratory measurements while being often applied at field to regional scales. Scaling, modulation, and constraining strategies exist to alleviate some of these shortcomings in the mismatch between scales. These aspects are addressed here in a joint effort by the members of the International Soil Modelling Consortium (ISMC) Pedotransfer Functions Working Group with the aim to systematise PTF research and provide a roadmap guiding both PTF development and use.

Climate change increases the occurrence and severity of droughts due to increasing temperatures, altered circulation patterns, and reduced snow occurrence. While Europe has suffered from drought events in the last decade unlike ever seen since the beginning of weather recordings, harmonized long-term datasets across the continent are needed to monitor change and support predictions. Here we present soil moisture data from 66 cosmic-ray neutron sensors (CRNSs) in Europe (COSMOS-Europe for short) covering recent drought events. The CRNS sites are distributed across Europe and cover all major land use types and climate zones in Europe. The raw neutron count data from the CRNS stations were provided by 24 research institutions and processed using state-of-the-art methods. The harmonized processing included correction of the raw neutron counts and a harmonized methodology for the conversion into soil moisture based on available in situ information. In addition, the uncertainty estimate is provided with the dataset, information that is particularly useful for remote sensing and modeling applications. This paper presents the current spatiotemporal coverage of CRNS stations in Europe and describes the protocols for data processing from raw measurements to consistent soil moisture products. The data of the presented COSMOS-Europe network open up a manifold of potential applications for environmental research, such as remote sensing data validation, trend analysis, or model assimilation. The dataset could be of particular importance for the analysis of extreme climatic events at the continental scale. Due its timely relevance in the scope of climate change in the recent years, we demonstrate this potential application with a brief analysis on the spatiotemporal soil moisture variability. The dataset, entitled “Dataset of COSMOS-Europe: A European network of Cosmic-Ray Neutron Soil Moisture Sensors”, is shared via Forschungszentrum Jülich: https://doi.org/10.34731/x9s3-kr48 (B

In this chapter, we present the Root and Soil Water Movement and Solute transport model R-SWMS, which can be used to simulate flow and transport in the soil–plant system. The equations describing water flow in soil–root systems are presented and numerical solutions are provided. An application of R-SWMS is then briefly discussed, in which we combine in vivo and in silico experiments in order to decrypt water flow in the soil–root domain. More precisely, light transmission imaging experiments were conducted to generate data that can serve as input for the R-SWMS model. These data include the root system architecture, the soil hydraulic properties and the environmental conditions (initial soil water content and boundary conditions, BC). Root hydraulic properties were not acquired experimentally, but set to theoretical values found in the literature. In order to validate the results obtained by the model, the simulated and experimental water content distributions were compared. The model was then used to estimate variables that were not experimentally accessible, such as the actual root water uptake distribution and xylem water potential.

Root systems of crops play a significant role in agro-ecosystems. The root system is essential for water and nutrient uptake, plant stability, symbiosis with microbes and a good soil structure. Minirhizotrons, consisting of transparent tubes that create windows into the soil, have shown to be effective to non-invasively investigate the root system. Root traits, like root length observed around the tubes of minirhizotron, can therefore be obtained throughout the crop growing season. Analyzing datasets from minirhizotrons using common manual annotation methods, with conventional software tools, are time consuming and labor intensive. Therefore, an objective method for high throughput image analysis that provides data for field root-phenotyping is necessary. In this study we developed a pipeline combining state-of-the-art software tools, using deep neural networks and automated feature extraction. This pipeline consists of two major components and was applied to large root image datasets from minirhizotrons. First, a segmentation by a neural network model, trained with a small image sample is performed. Training and segmentation are done using “Root-Painter”. Then, an automated feature extraction from the segments is carried out by “RhizoVision Explorer”. To validate the results of our automated analysis pipeline, a comparison of root length between manually annotated and automatically processed data was realized with more than 58,000 images. Mainly the results show a high correlation (R=0.81) between manually and automatically determined root lengths. With respect to the processing time, our new pipeline outperforms manual annotation by 98.1 - 99.6 %. Our pipeline,combining state-of-the-art software tools, significantly reduces the processing time for minirhizotron images. Thus, image analysis is no longer the bottle-neck in high throughput phenotyping approaches.

Soil hydrological processes (SHP) support ecosystems, modulate the impact of climate change on terrestrial systems and control feedback mechanisms between water, energy and biogeochemical cycles. However, land-use changes and extreme events are increasingly impacting these processes. In this Review, we describe SHP across scales and examine their links with soil properties, ecosystem processes and climate. Soil structure influences SHP such as infiltration, soil water redistribution and root water uptake on small scales. On local scales, SHP are driven by root water uptake, vegetation and groundwater dynamics. Regionally, SHP are impacted by extreme events such as droughts, floods, heatwaves and land-use change; however, antecedent and current SHP partially determine the broader effects of extreme events. Emerging technologies such as wireless and automated sensing, soil moisture observation through novel synthetic aperture radars satellites, big data analysis and machine learning approaches offer unique opportunities to advance soil hydrology. These advances, in tandem with the inclusion of more key soil types and properties in models, will be pivotal in predicting the role of SHP during global change.

Aims We aimed at assessing the influence of above- and below-ground environmental conditions over the performance of Centaurea jacea L., a drought-resistant grassland forb species. Methods Transpiration rate, CO2 assimilation rate, leaf water potential, instantaneous and intrinsic water use efficiency, temperature, relative humidity, vapor pressure deficit and soil water content in one plant and root length density in four plants, all grown in custom-made columns, were monitored daily for 87 days in the lab. The soil water isotopic composition in eleven depths was recorded daily in a non-destructive manner. The isotopic composition of plant transpiration was inferred from gas chamber measurements. Vertical isotopic gradients in the soil column were created by adding labeled water. Daily root water uptake (RWU) profiles were computed using the multi-source mixing model Stable Isotope Analysis in R (Parnell et al. PLoS ONE 5(3):1–5, 2010). Results RWU occurred mainly in soil layer 0–15 cm, ranging from 79 to 44%, even when water was more easily available in deeper layers. In wet soil, the transpiration rate was driven mainly by vapor pressure deficit and light intensity. Once soil water content was less than 0.12 cm3 cm− 3, the computed canopy conductance declined, which restricted leaf gas exchange. Leaf water potential dropped steeply to around − 3 MPa after soil water content was below 0.10 cm3 cm− 3. Conclusion Our comprehensive data set contributes to a better understanding of the effects of drought on a grassland species and the limits of its acclimation in dry conditions.

Modular Observation Solutions of Earth Systems (MOSES) is a novel observation system that is specifically designed to unravel the impact of distinct, dynamic events on the long-term development of environmental systems. Hydrometeorological extremes such as the recent European droughts or the floods of 2013 caused severe and lasting environmental damage. Modeling studies suggest that abrupt permafrost thaw events accelerate Arctic greenhouse gas emissions. Short-lived ocean eddies seem to comprise a significant share of the marine carbon uptake or release. Although there is increasing evidence that such dynamic events bear the potential for major environmental impacts, our knowledge on the processes they trigger is still very limited. MOSES aims at capturing such events, from their formation to their end, with high spatial and temporal resolution. As such, the observation system extends and complements existing national and international observation networks, which are mostly designed for long-term monitoring. Several German Helmholtz Association centers have developed this research facility as a mobile and modular “system of systems” to record energy, water, greenhouse gas, and nutrient cycles on the land surface, in coastal regions, in the ocean, in polar regions, and in the atmosphere—but especially the interactions between the Earth compartments. During the implementation period (2017–21), the measuring systems were put into operation and test campaigns were performed to establish event-driven campaign routines. With MOSES’s regular operation starting in 2022, the observation system will then be ready for cross-compartment and cross-discipline research on the environmental impacts of dynamic events.

Modular Observation Solutions of Earth Systems (MOSES) is a novel observation system that is specifically designed to unravel the impact of distinct, dynamic events on the long-term development of environmental systems. Hydrometeorological extremes such as the recent European droughts or the floods of 2013 caused severe and lasting environmental damage. Modeling studies suggest that abrupt permafrost thaw events accelerate Arctic greenhouse gas emissions. Short-lived ocean eddies seem to comprise a significant share of the marine carbon uptake or release. Although there is increasing evidence that such dynamic events bear the potential for major environmental impacts, our knowledge on the processes they trigger is still very limited. MOSES aims at capturing such events, from their formation to their end, with high spatial and temporal resolution. As such, the observation system extends and complements existing national and international observation networks, which are mostly designed for long-term monitoring. Several German Helmholtz Association centers have developed this research facility as a mobile and modular system of systems to record energy, water, greenhouse gas, and nutrient cycles on the land surface, in coastal regions, in the ocean, in polar regions, and in the atmosphere-but especially the interactions between the Earth compartments. During the implementation period (2017-21), the measuring systems were put into operation and test campaigns were performed to establish event-driven campaign routines. With MOSES's regular operation starting in 2022, the observation system will then be ready for cross-compartment and cross-discipline research on the environmental impacts of dynamic events.

Modular Observation Solutions of Earth Systems (MOSES) is a novel observation system that is specifically designed to unravel the impact of distinct, dynamic events on the long-term development of environmental systems. Hydrometeorological extremes such as the recent European droughts or the floods of 2013 caused severe and lasting environmental damage. Modeling studies suggest that abrupt permafrost thaw events accelerate Arctic greenhouse gas emissions. Short-lived ocean eddies seem to comprise a significant share of the marine carbon uptake or release. Although there is increasing evidence that such dynamic events bear the potential for major environmental impacts, our knowledge on the processes they trigger is still very limited. MOSES aims at capturing such events, from their formation to their end, with high spatial and temporal resolution. As such, the observation system extends and complements existing national and international observation networks, which are mostly designed for long-term monitoring. Several German Helmholtz Association centers have developed this research facility as a mobile and modular “system of systems” to record energy, water, greenhouse gas, and nutrient cycles on the land surface, in coastal regions, in the ocean, in polar regions, and in the atmosphere—but especially the interactions between the Earth compartments. During the implementation period (2017–21), the measuring systems were put into operation and test campaigns were performed to establish event-driven campaign routines. With MOSES’s regular operation starting in 2022, the observation system will then be ready for cross-compartment and cross-discipline research on the environmental impacts of dynamic events.

Modular Observation Solutions of Earth Systems (MOSES) is a novel observation system that is specifically designed to unravel the impact of distinct, dynamic events on the long-term development of environmental systems. Hydrometeorological extremes such as the recent European droughts or the floods of 2013 caused severe and lasting environmental damage. Modeling studies suggest that abrupt permafrost thaw events accelerate Arctic greenhouse gas emissions. Short-lived ocean eddies seem to comprise a significant share of the marine carbon uptake or release. Although there is increasing evidence that such dynamic events bear the potential for major environmental impacts, our knowledge on the processes they trigger is still very limited. MOSES aims at capturing such events, from their formation to their end, with high spatial and temporal resolution. As such, the observation system extends and complements existing national and international observation networks, which are mostly designed for long-term monitoring. Several German Helmholtz Association centers have developed this research facility as a mobile and modular “system of systems” to record energy, water, greenhouse gas, and nutrient cycles on the land surface, in coastal regions, in the ocean, in polar regions, and in the atmosphere—but especially the interactions between the Earth compartments. During the implementation period (2017–21), the measuring systems were put into operation and test campaigns were performed to establish event-driven campaign routines. With MOSES’s regular operation starting in 2022, the observation system will then be ready for cross-compartment and cross-discipline research on the environmental impacts of dynamic events.

Climate change increases the occurrence and severity of droughts due to increasing temperatures, altered circulation patterns, and reduced snow occurrence. While Europe has suffered from drought events in the last decade unlike ever seen since the beginning of weather recordings, harmonized long-term datasets across the continent are needed to monitor change and support predictions. Here we present soil moisture data from 66 cosmic-ray neutron sensors (CRNSs) in Europe (COSMOS-Europe for short) covering recent drought events. The CRNS sites are distributed across Europe and cover all major land use types and climate zones in Europe. The raw neutron count data from the CRNS stations were provided by 24 research institutions and processed using state-of-the-art methods. The harmonized processing included correction of the raw neutron counts and a harmonized methodology for the conversion into soil moisture based on available in situ information. In addition, the uncertainty estimate is provided with the dataset, information that is particularly useful for remote sensing and modeling applications. This paper presents the current spatiotemporal coverage of CRNS stations in Europe and describes the protocols for data processing from raw measurements to consistent soil moisture products. The data of the presented COSMOS-Europe network open up a manifold of potential applications for environmental research, such as remote sensing data validation, trend analysis, or model assimilation. The dataset could be of particular importance for the analysis of extreme climatic events at the continental scale. Due its timely relevance in the scope of climate change in the recent years, we demonstrate this potential application with a brief analysis on the spatiotemporal soil moisture variability. The dataset, entitled “Dataset of COSMOS-Europe: A European network of Cosmic-Ray Neutron Soil Moisture Sensors”, is shared via Forschungszentrum Jülich: https://doi.org/10.34731/x9s3-kr48 (B

Climate change increases the occurrence and severity of droughts due to increasing temperatures, altered circulation patterns, and reduced snow occurrence. While Europe has suffered from drought events in the last decade unlike ever seen since the beginning of weather recordings, harmonized long-term datasets across the continent are needed to monitor change and support predictions. Here we present soil moisture data from 66 cosmic-ray neutron sensors (CRNSs) in Europe (COSMOS-Europe for short) covering recent drought events. The CRNS sites are distributed across Europe and cover all major land use types and climate zones in Europe. The raw neutron count data from the CRNS stations were provided by 24 research institutions and processed using state-of-the-art methods. The harmonized processing included correction of the raw neutron counts and a harmonized methodology for the conversion into soil moisture based on available in situ information. In addition, the uncertainty estimate is provided with the dataset, information that is particularly useful for remote sensing and modeling applications. This paper presents the current spatiotemporal coverage of CRNS stations in Europe and describes the protocols for data processing from raw measurements to consistent soil moisture products. The data of the presented COSMOS-Europe network open up a manifold of potential applications for environmental research, such as remote sensing data validation, trend analysis, or model assimilation. The dataset could be of particular importance for the analysis of extreme climatic events at the continental scale. Due its timely relevance in the scope of climate change in the recent years, we demonstrate this potential application with a brief analysis on the spatiotemporal soil moisture variability. The dataset, entitled "Dataset of COSMOS-Europe: A European network of Cosmic-Ray Neutron Soil Moisture Sensors", is shared via Forschungszentrum Jülich: 10.34731/x9s3-kr48 (Bogena and Ney, 2

MOSES (Modular Observation Solutions for Earth Systems) is a novel observation system that is specifically designed to unravel the impact of distinct, dynamic events on the long-term development of environmental systems. Hydro-meteorological extremes such as the recent European droughts or the floods of 2013 caused severe and lasting environmental damage. Modelling studies suggest that abrupt permafrost thaw events accelerate Arctic greenhouse gas emissions. Short-lived ocean eddies seem to comprise a significant share of the marine carbon uptake or release. Although there is increasing evidence that such dynamic events bear the potential for major environmental impacts, our knowledge on the processes they trigger is still very limited. MOSES aims at capturing such events, from their formation to their end, with high spatial and temporal resolution. As such, the observation system extends and complements existing national and international observation networks, which are mostly designed for long-term monitoring. Several German Helmholtz Association centers have developed this research facility as a mobile and modular “system of systems” to record energy, water, greenhouse gas and nutrient cycles on the land surface, in coastal regions, in the ocean, in polar regions, and in the atmosphere – but especially the interactions between the Earth compartments. During the implementation period (2017-2021), the measuring systems were put into operation and test campaigns were performed to establish event-driven campaign routines. With MOSES’ regular operation starting in 2022, the observation system will then be ready for cross-compartment and cross-discipline research on the environmental impacts of dynamic events.

Effects of climate change on the ecosystem productivity and water fluxes have been studied in various types of experiments. However, it is still largely unknown whether and how the experimental approach itself affects the results of such studies. We employed two contrasting experimental approaches, using high-precision weighable monolithic lysimeters, over a period of 4 years to identify and compare the responses of water fluxes and aboveground biomass to climate change in permanent grassland. The first, manipulative, approach is based on controlled increases of atmospheric CO2 concentration and surface temperature. The second, observational, approach uses data from a space-for-time substitution along a gradient of climatic conditions. The Budyko framework was used to identify if the soil ecosystem is energy limited or water limited. Elevated temperature reduced the amount of non-rainfall water, particularly during the growing season in both approaches. In energy-limited grassland ecosystems, elevated temperature increased the actual evapotranspiration and decreased aboveground biomass. As a consequence, elevated temperature led to decreasing seepage rates in energy-limited systems. Under water-limited conditions in dry periods, elevated temperature aggravated water stress and, thus, resulted in reduced actual evapotranspiration. The already small seepage rates of the drier soils remained almost unaffected under these conditions compared to soils under wetter conditions. Elevated atmospheric CO2 reduced both actual evapotranspiration and aboveground biomass in the manipulative experiment and, therefore, led to a clear increase and change in seasonality of seepage. As expected, the aboveground biomass productivity and ecosystem efficiency indicators of the water-limited ecosystems were negatively correlated with an increase in aridity, while the trend was unclear for the energy-limited ecosystems. In both experimental approaches, the responses of soil water fluxes an, Version of record

New knowledge on soil structure highlights its importance for hydrology and soil organic matter (SOM) stabilization, which however remains neglected in many wide used models. We present here a new model, KEYLINK, in which soil structure is integrated with the existing concepts on SOM pools, and elements from food web models, that is, those from direct trophic interactions among soil organisms. KEYLINK is, therefore, an attempt to integrate soil functional diversity and food webs in predictions of soil carbon (C) and soil water balances. We present a selection of equations that can be used for most models as well as basic parameter intervals, for example, key pools, functional groups’ biomasses and growth rates. Parameter distributions can be determined with Bayesian calibration, and here an example is presented for food web growth rate parameters for a pine forest in Belgium. We show how these added equations can improve the functioning of the model in describing known phenomena. For this, five test cases are given as simulation examples: changing the input litter quality (recalcitrance and carbon to nitrogen ratio), excluding predators, increasing pH and changing initial soil porosity. These results overall show how KEYLINK is able to simulate the known effects of these parameters and can simulate the linked effects of biopore formation, hydrology and aggregation on soil functioning. Furthermore, the results show an important trophic cascade effect of predation on the complete C cycle with repercussions on the soil structure as ecosystem engineers are predated, and on SOM turnover when predation on fungivore and bacterivore populations are reduced. In summary

With the upcoming L-band Synthetic Aperture Radar (SAR) satellite mission Radar Observing System for Europe L-band SAR (ROSE-L) and its integration into existing C-band satellite missions such as Sentinel-1, multi-frequency SAR observations with high temporal and spatial resolution will become available. The SARSense campaign was conducted between June and August 2019 to investigate the potential for estimating soil and plant parameters at the agricultural test site in Selhausen (Germany). It included C- and L-band air- and space-borne observations accompanied by extensive in situ soil and plant sampling as well as unmanned aerial system (UAS) based multispectral and thermal infrared measurements. In this regard, we introduce a new publicly available SAR data set and present the first analysis of C- and L-band co- and cross-polarized backscattering signals regarding their sensitivity to soil and plant parameters. Results indicate that a multi-frequency approach is relevant to disentangle soil and plant contributions to the SAR signal and to identify specific scattering mechanisms associated with the characteristics of different crop type, especially for root crops and cereals.

Plant water uptake from soil is an important component of terrestrial water cycle with strong links to the carbon cycle and the land surface energy budget. To simulate the relation between soil water content, root distribution, and root water uptake, models should represent the hydraulics of the soil-root system and describe the flow from the soil towards root segments and within the 3D root system architecture according to hydraulic principles. We have recently demonstrated how macroscopic relations that describe the lumped water uptake by all root segments in a certain soil volume, e.g. in a thin horizontal soil layer in which soil water potentials are uniform, can be derived from the hydraulic properties of the 3D root architecture. The flow equations within the root system can be scaled up exactly and the total root water uptake from a soil volume depends on only two macroscopic characteristics of the root system: the root system conductance, Krs, and the uptake distribution from the soil when soil water potentials in the soil are uniform, SUF. When a simple root hydraulic architecture was assumed, these two characteristics were sufficient to describe root water uptake from profiles with a non-uniform water distribution.

With the upcoming L-band Synthetic Aperture Radar (SAR) satellite mission Radar Observing System for Europe at L-band (ROSE-L) and its combination with existing C-band satellite missions such as Sentinel-1, multi-frequency SAR observations with high temporal and spatial resolution will become available. To investigate the potential for estimating soil and plant parameters, the SARSense campaign was conducted between June and August 2019 at the agricultural test site Selhausen in Germany. In this regard, we introduce a new publicly available, extensive SAR dataset and present a first analysis of C- and L-band co- and cross-polarized backscattering signals regarding their sensitivity to soil and plant parameters. The analysis includes C- and L-band airborne recordings as well as Senitnel-1 and ALOS-2 acquisitions, accompanied by in-situ soil moisture measurements and plant samplings. In addition, soil moisture was measured using cosmic-ray neutron sensing as well as unmanned aerial system (UAS) based multispectral and temperature measurements were taken during the campaign period. First analysis of the dataset revealed, that due to misalignments of corner reflectors during the SAR acquisition, temporal consistency of airborne SAR data is not given. In this regard, a scene-based, spatial analysis of backscatter behaviour from airborne SAR data was conducted, while the spaceborne SAR data enabled the analysis of temporal changes in backscatter behaviour. Focusing on root crops with radial canopy structure (sugar beet and potato) and cereal crops with elongated canopy structure (wheat, barley), the lowest correlations can be observed between backscattering signal and soil moisture, with R² values ranging below 0.35 at C-band and below 0.36 at L-band. Higher correlations can be observed focusing on vegetation water content, with R² values ranging between 0.12 and 0.64 at C-band and 0.06 and 0.64 at L-band. Regarding plant height, at C-band higher correlations with R² up t

Root water uptake is an important process in the terrestrial water cycle. How this process depends on soil water content, root distributions, and root properties is a soil–root hydraulic problem. We compare different approaches to implement root hydraulics in macroscopic soil water flow and land surface models. By upscaling a three-dimensional hydraulic root architecture model, we derived an exact macroscopic root hydraulic model. The macroscopic model uses the following three characteristics: the root system conductance, Krs, the standard uptake fraction, SUF, which represents the uptake from a soil profile with a uniform hydraulic head, and a compensatory matrix that describes the redistribution of water uptake in a non-uniform hydraulic head profile. The two characteristics, Krs and SUF, are sufficient to describe the total uptake as a function of the collar and soil water potential, and water uptake redistribution does not depend on the total uptake or collar water potential. We compared the exact model with two hydraulic root models that make a priori simplifications of the hydraulic root architecture, i.e., the parallel and big root model. The parallel root model uses only two characteristics, Krs and SUF, which can be calculated directly following a bottom-up approach from the 3D hydraulic root architecture. The big root model uses more parameters than the parallel root model, but these parameters cannot be obtained straightforwardly with a bottom-up approach. The big root model was parameterized using a top-down approach, i.e., directly from root segment hydraulic properties, assuming a priori a single big root architecture. This simplification of the hydraulic root architecture led to less accurate descriptions of root water uptake than by the parallel root model. To compute root water uptake in macroscopic soil water flow and land surface models, we recommend the use of the parallel root model with Krs and SUF computed in a bottom-up approach from a known

Water fulfils key roles in maintaining a plant’s biological activity. Water shortage induces stomatal closure, causing a reduction in photosynthesis and transpiration rates. Sun-induced chlorophyll fluorescence (SIF) emission is sensitive to subtle, stress-induced variations in non-photochemical quenching and in photosynthetic electron transport, caused by e.g., a fluctuation in the water availability. Based on this sensitivity, a framework for calibrating a water stress function in a crop growth model using ground-based SIF observations is proposed. SIF time series are simulated by coupling the AgroC crop growth model to the Soil Canopy Observations Photosynthesis Energy (SCOPE) model. This allowed parametrizing the water stress function in the AgroC crop growth model, resulting in improved estimates of actual evapotranspiration and net ecosystem exchange over a sugar beet stand during stressed periods. The improvement in the estimation of the water and carbon fluxes by AgroC during the summer months highlights the ability of canopyscale SIF observations to serve as a remote sensing metric to indicate the intensity of a stress condition. We argue that our framework, linking SIF emission to stress functions, can be used to extract information concerning drought stress from the Fluorescence Explorer (FLEX) satellite, scheduled for launch in 2024.

MOSES (Modular Observation Solutions for Earth Systems) is a novel observation system that is specifically designed to unravel the impact of distinct, dynamic events on the long-term development of environmental systems. Hydro-meteorological extremes such as the recent European droughts or the floods of 2013 caused severe and lasting environmental damage. Modelling studies suggest that abrupt permafrost thaw events accelerate Arctic greenhouse gas emissions. Short-lived ocean eddies seem to comprise a significant share of the marine carbon uptake or release. Although there is increasing evidence that such dynamic events bear the potential for major environmental impacts, our knowledge on the processes they trigger is still very limited. MOSES aims at capturing such events, from their formation to their end, with high spatial and temporal resolution. As such, the observation system extends and complements existing national and international observation networks, which are mostly designed for long-term monitoring. Several German Helmholtz Association centers have developed this research facility as a mobile and modular “system of systems” to record energy, water, greenhouse gas and nutrient cycles on the land surface, in coastal regions, in the ocean, in polar regions, and in the atmosphere – but especially the interactions between the Earth compartments. During the implementation period (2017-2021), the measuring systems were put into operation and test campaigns were performed to establish event-driven campaign routines. With MOSES’ regular operation starting in 2022, the observation system will then be ready for cross-compartment and cross-discipline research on the environmental impacts of dynamic events.

Coupled numerical models, which simulate water and energy fluxes in the subsurface-land-surface-atmosphere system in a physically consistent way, are a prerequisite for the analysis and a better understanding of heat and matter exchange fluxes at compartmental boundaries and interdependencies of states across these boundaries. Complete state evolutions generated by such models may be regarded as a proxy of the real world, provided they are run at sufficiently high resolution and incorporate the most important processes. Such a simulated reality can be used to test hypotheses on the functioning of the coupled terrestrial system. Coupled simulation systems, however, face severe problems caused by the vastly different scales of the processes acting in and between the compartments of the terrestrial system, which also hinders comprehensive tests of their realism. We used the Terrestrial Systems Modeling Platform (TerrSysMP), which couples the meteorological Consortium for Small-scale Modeling (COSMO) model, the land-surface Community Land Model (CLM), and the subsurface ParFlow model, to generate a simulated catchment for a regional terrestrial system mimicking the Neckar catchment in southwest Germany, the virtual Neckar catchment. Simulations for this catchment are made for the period 2007-2015 and at a spatial resolution of 400m for the land surface and subsurface and 1.1km for the atmosphere. Among a discussion of modeling challenges, the model performance is evaluated based on observations covering several variables of the water cycle. We find that the simulated catchment behaves in many aspects quite close to observations of the real Neckar catchment, e.g., concerning atmospheric boundary-layer height, precipitation, and runoff. But also discrepancies become apparent, both in the ability of the model to correctly simulate some processes which still need improvement, such as overland flow, and in the realism of some observation operators like the satellite-based so

Effects of climate change on the ecosystem productivity and water fluxes have been studied in various types of experiments. However, it is still largely unknown whether and how the experimental approach itself affects the results of such studies. We employed two contrasting experimental approaches, using high-precision weighable monolithic lysimeters, over a period of 4 years to identify and compare the responses of water fluxes and aboveground biomass to climate change in permanent grassland. The first, manipulative, approach is based on controlled increases of atmospheric CO2 concentration and surface temperature. The second, observational, approach uses data from a space-for-time substitution along a gradient of climatic conditions. The Budyko framework was used to identify if the soil ecosystem is energy limited or water limited. Elevated temperature reduced the amount of non-rainfall water, particularly during the growing season in both approaches. In energy-limited grassland ecosystems, elevated temperature increased the actual evapotranspiration and decreased aboveground biomass. As a consequence, elevated temperature led to decreasing seepage rates in energy-limited systems. Under water-limited conditions in dry periods, elevated temperature aggravated water stress and, thus, resulted in reduced actual evapotranspiration. The already small seepage rates of the drier soils remained almost unaffected under these conditions compared to soils under wetter conditions. Elevated atmospheric CO2 reduced both actual evapotranspiration and aboveground biomass in the manipulative experiment and, therefore, led to a clear increase and change in seasonality of seepage. As expected, the aboveground biomass productivity and ecosystem efficiency indicators of the water-limited ecosystems were negatively correlated with an increase in aridity, while the trend was unclear for the energy-limited ecosystems. In both experimental approaches, the responses of soil water fluxes an, Version of record

New knowledge on soil structure highlights its importance for hydrology and soil organic matter (SOM) stabilization, which however remains neglected in many wide used models. We present here a new model, KEYLINK, in which soil structure is integrated with the existing concepts on SOM pools, and elements from food web models, that is, those from direct trophic interactions among soil organisms. KEYLINK is, therefore, an attempt to integrate soil functional diversity and food webs in predictions of soil carbon (C) and soil water balances. We present a selection of equations that can be used for most models as well as basic parameter intervals, for example, key pools, functional groups’ biomasses and growth rates. Parameter distributions can be determined with Bayesian calibration, and here an example is presented for food web growth rate parameters for a pine forest in Belgium. We show how these added equations can improve the functioning of the model in describing known phenomena. For this, five test cases are given as simulation examples: changing the input litter quality (recalcitrance and carbon to nitrogen ratio), excluding predators, increasing pH and changing initial soil porosity. These results overall show how KEYLINK is able to simulate the known effects of these parameters and can simulate the linked effects of biopore formation, hydrology and aggregation on soil functioning. Furthermore, the results show an important trophic cascade effect of predation on the complete C cycle with repercussions on the soil structure as ecosystem engineers are predated, and on SOM turnover when predation on fungivore and bacterivore populations are reduced. In summary, KEYLINK shows how soil functional diversity and trophic organization and their role in C and water cycling in soils should be considered in order to improve our predictions on C sequestration and C emissions from soils.

Most soil hydraulic information used in Earth System Models (ESMs) is derived from pedo-transfer functions that use easy-to-measure soil attributes to estimate hydraulic parameters. This parameterization relies heavily on soil texture, but overlooks the critical role of soil structure originated by soil biophysical activity. Soil structure omission is pervasive also in sampling and measurement methods used to train pedotransfer functions. Here we show how systematic inclusion of salient soil structural features of biophysical origin affect local and global hydrologic and climatic responses. Locally, including soil structure in models significantly alters infiltration-runoff partitioning and recharge in wet and vegetated regions. Globally, the coarse spatial resolution of ESMs and their inability to simulate intense and short rainfall events mask effects of soil structure on surface fluxes and climate. Results suggest that although soil structure affects local hydrologic response, its implications on global-scale climate remains elusive in current ESMs.

Root water uptake is a key ecohydrological process for which a physically-based understanding has been developed in the past decades. However, due to methodological constraints, knowledge gaps remain about the plastic response of whole plant root systems to a rapidly changing environment. - We designed a laboratory system for non-destructive monitoring of stable isotopic composition in plant transpiration of an herbaceous species (Centaurea jacea) and of soil water across depths, taking advantage of newly developed in-situ methods. Daily root water uptake profiles were obtained using a statistical Bayesian multi-source mixing model. - Fast shifts in the isotopic composition of both soil and transpiration water could be observed with the setup and translated into dynamic and pronounced shifts of the root water uptake profile, even in well-watered conditions. - The incorporation of plant physiological and soil physical information into statistical modelling improved the model output. A simple exercise of water balance closure underlined the non-unique relationship between root water uptake profile on the one hand, and water content and root distribution profiles on the other, illustrating the continuous adaption of the plant water uptake as a function of its root hydraulic architecture and soil water availability during the experiment

Climate change and especially hydro-meteorological extremes, such as droughts, are affecting the land surface of the Earth and socioeconomic well-being. Current analyses and projections indicate that the frequency of extremes will increase in the next decades, and that drought events like the years 2003, 2015 and 2018 in Europe will occur more regularly and might be more disruptive as terrestrial ecosystems will have no time to recover. Heat waves in combination with longer drought periods caused a loss in agricultural productivity but also impacted the availability of water resources (e.g. low water levels in rivers) and led to a decrease of the storage capacity of grass- and agricultural lands for carbon storage (e.g., Ciais et al., 2005). In addition, we observed a worldwide increase in risk of forest fires and pest outbreaks. At present, we face the challenge of quantifying and predicting the resilience and adaptiveness of our terrestrial ecosystems, both natural and managed, in view of the expected increase in extreme events. In Central Europe, the 2018 extreme drought affected agricultural production and forests leading to damages on the order of billions of Euro. Similar losses occurred during the drought 2003.The consequences of these damages motivated the EU to upgrade its civil defense mechanism by launching a risk data hub to enhance EU resilience.

In summer 2019 the SARSense campaign was held in Jülich, Germany, to provide insights into the potentials and specifications of the ESA Copernicus candidate mission ROSE-L (Radar Observation System for Europe). ROSE-L will consist of two satellites that carry a polarimetric L-band SAR. Since the L-band signal can penetrate through many natural materials such as vegetation, dry snow and ice, the mission will provide additional information that cannot be gathered by the Copernicus Sentinel-1 C-band SAR mission. The overall objective of the SARSense 2019 campaign is to analyze the mission design concerning its potential for agricultural monitoring services including target applications such as soil moisture monitoring, irrigation management, crop type discrimination, food security and precision farming. The SARSense in situ measurements of soil moisture, soil temperature, vegetation properties, UAS-based multispectral and thermal mapping, as well as the airborne SAR observations are presented as well as strategies for soil moisture retrieval and first analysis.

Most soil hydraulic information used in Earth System Models (ESMs) is derived from pedo-transfer functions that use easy-to-measure soil attributes to estimate hydraulic parameters. This parameterization relies heavily on soil texture, but overlooks the critical role of soil structure originated by soil biophysical activity. Soil structure omission is pervasive also in sampling and measurement methods used to train pedotransfer functions. Here we show how systematic inclusion of salient soil structural features of biophysical origin affect local and global hydrologic and climatic responses. Locally, including soil structure in models significantly alters infiltration-runoff partitioning and recharge in wet and vegetated regions. Globally, the coarse spatial resolution of ESMs and their inability to simulate intense and short rainfall events mask effects of soil structure on surface fluxes and climate. Results suggest that although soil structure affects local hydrologic response, its implications on global-scale climate remains elusive in current ESMs.

Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO(2)exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004-2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO(2)uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Many different equations ranging from simple empirical to semi‐analytical solutions of the Richards equation have been proposed for quantitative description of water infiltration into variably saturated soils. The sorptivity, S, and the saturated hydraulic conductivity, Ks, in these equations are typically unknown and have to be estimated from measured data. In this paper, we use so‐called characteristic time (tchar) to design a new method, referred to as the characteristic time method (CTM) that estimates S, and Ks, from one‐dimensional (1D) cumulative infiltration data. We demonstrate the usefulness and power of the CTM by comparing it with a suite of existing methods using synthetic cumulative infiltration data simulated by HYDRUS‐1D for 12 synthetic soils reflecting different USDA textural classes, as well as experimental data selected from the Soil Water Infiltration Global (SWIG) database. Results demonstrate that the inferred values of S and Ks are in excellent agreement with their theoretical values used in the synthetically simulated infiltration experiments with Nash–Sutcliffe criterion close to unity and RMSE values of 0.04 cm h−1/2 and 0.05 cm h−1, respectively. The CTM also showed very high accuracy when applied on synthetic data with added measurement noise, as well as robustness when applied to experimental data. Unlike previously published methods, the CTM does not require knowledge of the time validity of the applied semi‐analytical solution for infiltration and, therefore, is applicable to infiltrations with durations from 5 min to several days. A script written in Python of the CTM method is provided in the supplemental material.

Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO2 exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004-2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO2 uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Terrestrial evapotranspiration (ET) is the second largest water flux in the global water cycle. It can be measured with different techniques; weighable lysimeters can provide very accurate measurements, and some very long-term time series exist. However, these lysimeter time series are affected by data gaps that must be filled to estimate actual ET totals and long-term trends. In this paper, we explore four different gap-filling methods: the potential ET-method, the ratio method, the FAO-based water balance method, and HYDRUS modeling. These gap-filling methods were evaluated for three time series of actual ET measured by lysimeters and meteorological data of three European sites. Separate evaluations were made for the five driest and five wettest April–October periods to investigate whether the performance of the gap-filling methods was affected by hydrological conditions. Series of random gaps were artificially created for the three time series, including gaps of four different lengths. Actual ET was estimated for these gaps with the gap-filling methods, which were evaluated based on RMSE and mean bias error. The results show that the ratio method outperformed other methods for gap filling of lysimeter data for Basel (Switzerland), whereas the HYDRUS method outperformed other methods for Rheindahlen (Germany). For Rietholzbach (Switzerland), the different methods performed very similarly, except that the FAO method gives slightly larger RMSEs. The gap-filling methods do not perform very differently for dry and wet conditions. The ratio method is recommended for filling smaller gaps, and the HYDRUS method is recommended for longer gaps of 30 d.

Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO2 exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004-2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO2 uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

[EN] Irrigation is essential for maintaining food production in water-scarce regions. The irrigation need depends on the water content of the soil, which we measured with the novel technique of cosmic-ray neutron sensing (CRNS). The potential of the CRNS technique for drip irrigation scheduling was explored in this study for the Picassent site near Valencia, Spain. To support the experimental evidence, the neutron transport simulation URANOS was used to simulate the effect of drip irrigation on the neutron counts. The overall soil water content (SWC) in the CRNS footprint was characterized with a root mean square error <0.03 cm3/cm3, but the experimental dataset indicated methodological limitations to detect drip water input. Both experimental data and simulation results suggest that the large¿area neutron response to drip irrigation is insignificant in our specific case using a standard CRNS probe. Because of the small area of irrigated patches and short irrigation time, the limited SWC changes due to drip irrigation were not visible from the measured neutron intensity changes. Our study shows that CRNS modeling can be used to assess the suitability of the CRNS technique for certain applications. While the standard CRNS probe was not able to detect small¿scale drip irrigation patterns, the method might be applicable for larger irrigated areas, in drier regions, and for longer and more intense irrigation periods. Since statistical noise is the main limitation of the CRNS measurement, the capability of the instrument could be improved in future studies by larger and more efficient neutron detectors.

Multi-walled carbon nanotubes (MWCNTs) are increasing used in commercial applications and may be released into the environment with anionic surfactants, such as sodium dodecylbenzenesulfonate (SDBS), in sewer discharge. Little research has examined the transport, retention, and remobilization of MWCNTs in the presence or absence of SDBS in porous media with controlled chemical heterogeneity, and batch and column scale studies were therefore undertaken to address this gap in knowledge. The adsorption isotherms of SDBS on quartz sand (QS), goethite coated quartz sand (GQS), and MWCNTs were determined. Adsorption of SDBS (MWCNTs » GQS > QS) decreased zeta potentials for these materials, and produced a charge reversal for goethite. Transport of MWCNTs (5 mg L-1) dramatically decreased with an increase in the fraction of GQS from 0 to 0.1 in the absence of SDBS. Conversely, co-injection of SDBS (10 and 50 mg L-1) and MWCNTs radically increased the transport of MWCNTs when the GQS fraction was 0, 0.1, and 0.3, especially at a higher SDBS concentration, and altered the shape of retention profile. Mathematical modeling revealed that competitive blocking was not the dominant mechanism for the SDBS enhancement of MWCNT transport. Rather, SDBS sorption increased MWCNT transport by increasing electrostatic and/or steric interactions, or creating reversible interactions on rough surfaces. Sequential injection of pulses of MWCNTs and SDBS in sand (0.1 GQS fraction) indicated that SDBS could mobilize some of retained MWCNTs from the top to deeper sand layers, but only a small amount of released MWCNTs were recovered in the effluent. SDBS therefore had a much smaller influence on MWCNT transport in sequential injection than in co-injection, presumably because of a greater energy barrier to MWCNT release than retention. This research sheds novel insight on the roles of competitive blocking, chemical heterogeneity and nanoscale roughness, and injection sequence on MWCNT retention

[EN] Irrigation is essential for maintaining food production in water-scarce regions. The irrigation need depends on the water content of the soil, which we measured with the novel technique of cosmic-ray neutron sensing (CRNS). The potential of the CRNS technique for drip irrigation scheduling was explored in this study for the Picassent site near Valencia, Spain. To support the experimental evidence, the neutron transport simulation URANOS was used to simulate the effect of drip irrigation on the neutron counts. The overall soil water content (SWC) in the CRNS footprint was characterized with a root mean square error <0.03 cm3/cm3, but the experimental dataset indicated methodological limitations to detect drip water input. Both experimental data and simulation results suggest that the large¿area neutron response to drip irrigation is insignificant in our specific case using a standard CRNS probe. Because of the small area of irrigated patches and short irrigation time, the limited SWC changes due to drip irrigation were not visible from the measured neutron intensity changes. Our study shows that CRNS modeling can be used to assess the suitability of the CRNS technique for certain applications. While the standard CRNS probe was not able to detect small¿scale drip irrigation patterns, the method might be applicable for larger irrigated areas, in drier regions, and for longer and more intense irrigation periods. Since statistical noise is the main limitation of the CRNS measurement, the capability of the instrument could be improved in future studies by larger and more efficient neutron detectors.

A detailed representation of plant hydraulic traits and stomatal closure in land surface models (LSMs) is a prerequisite for improved predictions of ecosystem drought response. This work presents the integration of a macroscopic root water uptake (RWU) model based on the hydraulic architecture approach in the LSM of the Terrestrial Systems Modeling Platform. The novel RWU approach is based on three parameters derived from first principles that describe the root system equivalent conductance, the compensatory RWU conductance, and the leaf water potential at stomatal closure, which defines the water stress condition for the plants. The developed RWU model intrinsically accounts for changes in the root density as well as for the simulation of the hydraulic lift process. The standard and the new RWU approach are compared by performing point-scale simulations for cropland over a sheltered minirhizotron facility in Selhausen, Germany, and validated against transpiration fluxes estimated from sap flow and soil water content measurements at different depths. Numerical sensitivity experiments are carried out using different soil textures and root distributions in order to evaluate the interplay between soil hydrodynamics and plant characteristics, and the impact of assuming time-constant plant physiological properties. Results show a good agreement between simulated and observed transpiration fluxes for both RWU models, with a more distinct response under water stress conditions and with uncertainty in the soil parameterization prevailing to the differences due to changes in the model formulation. The hydraulic RWU model exhibits also a lower sensitivity to the root distributions when simulating the onset of the water stress period. Finally, an analysis of variability across the soil and root scenarios indicates that differences in soil water content are mainly influenced by the root distribution, while the transpiration flux in both RWU models is additionally determined by