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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. [ABSTRACT FROM AUTHOR]

In most of the world, conditions conducive to wildfires are becoming more prevalent. Net carbon emissions from wildfires contribute to a positive climate feedback that needs to be monitored, quantified, and predicted. Here we use a causal inference approach to evaluate the influence of top-down weather and bottom-up fuel precursors on wildfires. The top-down dominance on wildfires is more widespread than bottom-up dominance, accounting for 73.3% and 26.7% of regions, respectively. The top-down precursors dominate in the tropical rainforests, mid-latitudes, and eastern Siberian boreal forests. The bottom-up precursors dominate in North American and European boreal forests, and African and Australian savannahs. Our study identifies areas where wildfires are governed by fuel conditions and hence where fuel management practices may be more effective. Moreover, our study also highlights that top-down and bottom-up precursors show complementary wildfire predictability across timescales. Seasonal or interannual predictions are feasible in regions where bottom-up precursors dominate. This paper shows that weather and fuel precursors show complementary predictability of wildfires extending across different timescales, which may be leveraged for seasonal or interannual wildfire prediction. [ABSTRACT FROM AUTHOR]

The production of crops secure the human food supply, but climate change is bringing new challenges. Dynamic plant growth and corresponding environmental data are required to uncover phenotypic crop responses to the changing environment. There are many datasets on above-ground organs of crops, but roots and the surrounding soil are rarely the subject of longer term studies. Here, we present what we believe to be the first comprehensive collection of root and soil data, obtained at two minirhizotron facilities located close together that have the same local climate but differ in soil type. Both facilities have 7m-long horizontal tubes at several depths that were used for crosshole ground-penetrating radar and minirhizotron camera systems. Soil sensors provide observations at a high temporal and spatial resolution. The ongoing measurements cover five years of maize and wheat trials, including drought stress treatments and crop mixtures. We make the processed data available for use in investigating the processes within the soil–plant continuum and the root images to develop and compare image analysis methods. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background and aims: Characterizing root system architectures of field-grown crops is challenging as root systems are hidden in the soil. We investigate the possibility of estimating root architecture model parameters from soil core data in a Bayesian framework. Methods: In a synthetic experiment, we simulated wheat root systems in a virtual field plot with the stochastic CRootBox model. We virtually sampled soil cores from this plot to create synthetic measurement data. We used the Markov chain Monte Carlo (MCMC) DREAM(ZS) sampler to estimate the most sensitive root system architecture parameters. To deal with the CRootBox model stochasticity and limited computational resources, we essentially added a stochastic component to the likelihood function, thereby turning the MCMC sampling into a form of approximate Bayesian computation (ABC). Results: A few zero-order root parameters: maximum length, elongation rate, insertion angles, and numbers of zero-order roots, with narrow posterior distributions centered around true parameter values were identifiable from soil core data. Yet other zero-order and higher-order root parameters were not identifiable showing a sizeable posterior uncertainty. Conclusions: Bayesian inference of root architecture parameters from root density profiles is an effective method to extract information about sensitive parameters hidden in these profiles. Equally important, this method also identifies which information about root architecture is lost when root architecture is aggregated in root density profiles. [ABSTRACT FROM AUTHOR]

Incorporation of crop residues into the soil has been widely recommended as an effective method to sustain soil fertility and improve soil carbon sequestration in arable lands. However, it may lead to an increase in the emission of nitrous oxide (N2O) and leaching of nitrate (NO3−) to groundwater due to higher nitrogen (N) availability after crop residue incorporation. Here, we conducted a meta-analysis based on 345 observations from 90 peer-reviewed studies to evaluate the effects of crop residue return on soil N2O emissions and NO3− leaching for different locations, climatic and soil conditions, and agricultural management strategies. On average, crop residue incorporation significantly stimulated N2O emissions by 29.7%, but decreased NO3− leaching by 14.4%. The increase in N2O emissions was negatively and significantly correlated with mean annual temperature and mean annual precipitation, and with the most significant changes occurring in the temperate climate zone. Crop residues stimulated N2O emission mainly in soils with pH ranging between 5.5 and 6.5, or above 7.5 in soils with low clay content. In addition, crop residue application decreased NO3− leaching significantly in soils with sandy loam, silty clay loam, and silt loam textures. Our analysis reveals that an appropriate crop residue management adapted to the site-specific soil and environmental conditions is critical for increasing soil organic carbon stocks and decreasing nitrogen losses. The most important novel finding is that residue return, despite stimulation of N2O emissions, is particularly effective in reducing NO3− leaching in soils with loamy texture, which are generally among the most productive arable soils. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1007/s13280-023-01930-4. B Publisher Correction to: Ambio b https://doi.org/10.1007/s13280-023-01930-4 In the original publication of article, a typo was introduced in the co-author name during the creation of the article proof. [Extracted from the article]

Purpose: Pesticide contamination of river waters is a global problem, and therefore, authorities regularly monitor the water quality status. Especially, flood events might transport large pesticide loads downstream and impact adjacent areas such as sensible floodplain environments by deposing particle bound pesticides or by contaminating the environments by dissolved substances directly. Unfortunately, only little attempts were made to quantify the pesticide pollution of such environments, as the monitoring of soil and sediment contamination is by far more time consuming and complicated compared to the analysis of water samples. Materials and methods: In the study presented, we therefore used a holistic approach starting with the reconstruction of the inundation characteristics of a floodplain located in the upper part of the river Elbe, Germany, by using nearby gauging data, screened databases for pesticide concentrations and calculated pesticide loads, and finally, sampled the floodplain soils along an elevation (inundation) gradient. Results: As expected, the reconstructed inundation characteristics showed that the low-lying areas of the backwater inflow of the floodplain were flooded more frequently compared to the areas at higher elevation, whereby even the highest elevations sampled were at least flooded during each decade. Furthermore, pesticide concentrations of the river waters and calculated pesticide loads revealed that 13 pesticides can be found regularly, whereby atrazine, terbuthylazine, metazachlor, metolachlor, isoproturon, and chlorotoluron are the main contaminants. Conclusion: Concluding, a spatial pattern in the contamination could be detected. High residues of simazine and ethofumesate were associated with areas of less and more frequent inundations, respectively. The transformation products of atrazine and terbuthylazine (2-hydroxy-atrazine and 2-hydroxy-terbuthylazine) were detected, whereby the quantity could be well explained by the inundation characteristics and pesticide loads of the river water. [ABSTRACT FROM AUTHOR]

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. The effect of soil structure is not included in most Earth System Models. The authors here introduce and evaluate the consequences at local and global scale of modifying hydraulic properties of soils in response to biological activity—a process significantly changing soil structure. [ABSTRACT FROM AUTHOR]

Background and aims: Although modelling of water and nutrient uptake by root systems has advanced considerably in recent years, steep local gradients of nutrient concentration near the root-soil interface in the rhizosphere are still a central challenge for accurate simulation of water and nutrient uptake at the root system scale. Conventionally, mesh refinement is used to resolve these gradients. However, it results in excessive computational costs. The object of the study is to present a multiscale approach which resolves the steep gradient of nutrient concentrations at rhizosphere scale and simulates nutrient and water fluxes within the entire root zone at macroscale scale in a computationally efficient way. Methods: We developed a 3D water and nutrient transport model of the root-soil system with explicit consideration of the 3D root architecture. To capture the nutrient gradients at root surfaces, 1D axisymmetric soil models at rhizosphere scale were constructed and coupled to the coarse 3D root-system-scale simulations using a mass conservative approach. The multiscale model was investigated under different scenarios for water and potassium (K+) uptake of a single root, multiple roots, and whole 3D architecture of a Zea mays L. root system in conditions of dynamic soil water and different soil buffer capacity of K+. Results: The steep gradients of K+ concentrations were efficiently resolved in the multiscale simulations thanks to the 1D model at the rhizosphere scale. In comparison with the refinement method, the multiscale model achieved a significant accuracy of K+ uptake prediction with a relative error below 5%. Meanwhile, the simulation at macroscale with coarse mesh could overestimate the K+ uptake in one order of magnitude. Moreover, the computational cost of multiscale simulations was decreased considerably by using coarse soil mesh. Conclusions: The newly developed model can describe the effect of the drying and nutrient transport in the root zone on nutrient uptake. It also allows to simulate processes in larger and complex root systems because of the considerable reduction in computational cost. [ABSTRACT FROM AUTHOR]

Aims: Traits of the plant root system architecture (RSA) play a key role in crop performance. Therefore, architectural root traits are becoming increasingly important in plant phenotyping. In this study, we use a mathematical model to investigate the sensitivity of characteristic root system measures, obtained from different classical field root sampling schemes, to RSA parameters. Methods: Root systems of wheat and maize were simulated and sampled virtually to mimic real field experiments using the root system architecture (RSA) model CRootBox. By means of a sensitivity analysis, we found RSA parameters that significantly influenced the virtual field sampling results. To identify correlations between sensitivities, we carried out a principal component analysis. Results: We found that the parameters of zero order roots are the most sensitive, and parameters of higher order roots are less sensitive. Moreover, different characteristic root system measures showed different sensitivity to RSA parameters. RSA parameters that could be derived independently from different types of field observations were identified. Conclusions: Selection of characteristic root system measures and parameters is essential to reduce the problem of parameter equifinality in inverse modeling with multi-parameter models and is an important step in the characterization of root traits from field observations. [ABSTRACT FROM AUTHOR]

Phosphorus (P) research still lacks techniques for rapid imaging of P use and allocation in different soil, sediment, and biological systems in a quantitative manner. In this study, we describe a time-saving and cost-efficient digital autoradiographic method for in situ quantitative imaging of 33P radioisotopes in plant materials. Our method combines autoradiography of the radiotracer applications with additions of commercially available 14C polymer references to obtain 33P activities in a quantitative manner up to 2000 Bq cm−2. Our data show that linear standard regressions for both radioisotopes are obtained, allowing the establishment of photostimulated luminescence equivalence between both radioisotopes with a factor of 9.73. Validating experiments revealed a good agreement between the calculated and applied 33P activity (R2 = 0.96). This finding was also valid for the co-exposure of 14C polymer references and 33P radioisotope specific activities in excised plant leaves for both maize (R2 = 0.99) and wheat (R2 = 0.99). The outlined autoradiographic quantification procedure retrieved 100% ± 12% of the 33P activity in the plant leaves, irrespective of plant tissue density. The simplicity of this methodology opens up new perspectives for fast quantitative imaging of 33P in biological systems and likely, thus, also for other environmental compartments. [ABSTRACT FROM AUTHOR]

In precision agriculture (PA), compact and lightweight electromagnetic induction (EMI) sensors have extensively been used to investigate the spatial variability of soil, to evaluate crop performance, and to identify management zones by mapping soil apparent electrical conductivity (ECa), a surrogate for primary and functional soil properties. As reported in the literature, differential global positioning systems (DGPS) with sub-metre to centimetre accuracy have been almost exclusively used to geo-reference these measurements. However, with the ongoing improvements in Global Navigation Satellite System (GNSS) technology, a single state-of-the-art DGPS receiver is likely to be more expensive than the geophysical sensor itself. In addition, survey costs quickly multiply if advanced real time kinematic correction or a base and rover configuration is used. However, the need for centimetre accuracy for surveys supporting PA is questionable as most PA applications are concerned with soil properties at scales above 1 m. The motivation for this study was to assess the position accuracy of a GNSS receiver especially designed for EMI surveys supporting PA applications. Results show that a robust, low-cost and single-frequency receiver is sufficient to geo-reference ECa measurements at the within-field scale. However, ECa data from a field characterized by a high spatial variability of subsurface properties compared to repeated ECa survey maps and remotely sensed leaf area index indicate that a lack of positioning accuracy can constrain the interpretability of such measurements. It is therefore demonstrated how relative and absolute positioning errors can be quantified and corrected. Finally, a summary of practical implications and considerations for the geo-referencing of ECa data using GNSS sensors are presented. [ABSTRACT FROM AUTHOR]

Background and aims: The main difficulty in the use of 3D root architecture models is correct parameterization. We evaluated distributions of the root traits inter-branch distance, branching angle and axial root trajectories from contrasting experimental systems to improve model parameterization.Methods: We analyzed 2D root images of different wheat varieties (Triticum aestivum) from three different sources using automatic root tracking. Model input parameters and common parameter patterns were identified from extracted root system coordinates. Simulation studies were used to (1) link observed axial root trajectories with model input parameters (2) evaluate errors due to the 2D (versus 3D) nature of image sources and (3) investigate the effect of model parameter distributions on root foraging performance.Results: Distributions of inter-branch distances were approximated with lognormal functions. Branching angles showed mean values <90°. Gravitropism and tortuosity parameters were quantified in relation to downwards reorientation and segment angles of root axes. Root system projection in 2D increased the variance of branching angles. Root foraging performance was very sensitive to parameter distribution and variance.Conclusions: 2D image analysis can systematically and efficiently analyze root system architectures and parameterize 3D root architecture models. Effects of root system projection (2D from 3D) and deflection (at rhizotron face) on size and distribution of particular parameters are potentially significant. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1007/s11104-019-03993-3 B Correction to: Plant Soil (2019) 438:101-126 b https://doi.org/10.1007/s11104-019-03993-3 The authors of this erratum regret that in the article entitled "Parameter sensitivity analysis of a root system architecture model based on virtual field sampling" (Morandage et al. [1]), which was published in Plant Soil (2019) 438:101-126, corrections to the lateral roots labels are necessary. Except for the number of zero-order roots NB, each parameter is a stochastic parameter with a mean and a standard deviation (values inside the brackets indicate the standard deviations of the parameters). [Extracted from the article]

Background and aims: The use of standard dynamic root architecture models to simulate root growth in soil containing macropores failed to reproduce experimentally observed root growth patterns. We thus developed a new, more mechanistic model approach for the simulation of root growth in structured soil. Methods: In our alternative modelling approach, we distinguish between, firstly, the driving force for root growth, which is determined by the orientation of the previous root segment and the influence of gravitropism and, secondly, soil mechanical resistance to root growth. The latter is expressed by its inverse, soil mechanical conductance, and treated similarly to hydraulic conductivity in Darcy's law. At the presence of macropores, soil mechanical conductance is anisotropic, which leads to a difference between the direction of the driving force and the direction of the root tip movement. Results: The model was tested using data from the literature, at pot scale, at macropore scale, and in a series of simulations where sensitivity to gravity and macropore orientation was evaluated. Conclusions: Qualitative and quantitative comparisons between simulated and experimentally observed root systems showed good agreement, suggesting that the drawn analogy between soil water flow and root growth is a useful one. [ABSTRACT FROM AUTHOR]

Nitrite (NO ) as an important intermediate of the biological nitrogen cycle is particularly reactive in acidic soils and acts as a source of NO and NO (NO and NO). However, abiotic and biotic pathways of NO -driven NO and NO production in forest soil and the role of soil organic matter (SOM) in these processes are still unclear. In this study, NO was applied to both unsterile and sterilized soil samples as well as to different SOM fractions from a Norway spruce forest. Biotic and abiotic NO emission was measured with an infrared absorption analyzer and gas chromatography, while NO emission was quantified with a chemiluminescence analyzer. Isotopic signatures of NO (δN, δO, and N-NO site preference) were analyzed with an isotope ratio mass spectrometer. After NO addition, a large amount of NO was emitted immediately, while NO emission occurred 15-60 min later and was much lower compared to NO. Sterilization of soil decreased NO emission significantly, but not NO emission. The N site preference of NO ranged from 7.98 to 11.58‰ for abiotic and 4.69-7.42‰ for biotic sources. The fulvic acid fraction contributed the most to abiotic NO emission, while the fastest NO and NO emission occurred after NO application to the humin fraction, followed by the humic acid fraction. These results are important for the future understanding of NO and NO sources, as well as the use of isotopic signatures for source-partitioning NO emission from soil. Graphical Abstract: [ABSTRACT FROM AUTHOR]

Mapping of soil water content (SWC) by electromagnetic induction (EMI) is an established method to obtain field-scale SWC information. However, the relationship between SWC and the apparent electrical conductivity (EC) measured with EMI is complex and affected by several confounding factors at the catchment scale such as variable porosity ( ϕ) and pore water electrical conductivity ( σ ). In this study, we investigated these confounding factors using a time-lapse EMI data set obtained in a forest ecosystem with soils of low EC and catchment-wide SWC data provided by a wireless soil moisture sensor network. To assess the impact of variable ϕ on the accuracy of SWC estimates, we compared three different models to relate SWC and EC: (i) a linear regression model and two nonlinear models based on Archie's equation with (ii) constant ϕ and (iii) variable ϕ. The linear model reached a prediction accuracy of RMSE = 5.83 vol%, while the Archie models increased the accuracy to RMSE = 4.55 vol% (constant ϕ) and RMSE = 4.20 vol% (variable ϕ). Although we found strong spatial similarities between SWC and EC maps, the temporal trends in SWC and EC were inconsistent. This was attributed to temporal variations in σ due to seasonal changes in ion concentrations of the soil pore water. To support this hypothesis, σ was calculated from the measured EC and the known soil saturation from SoilNet. The resulting σ maps showed highly structured and consistent patterns. We thus conclude that in addition to variation in SWC and ϕ, spatiotemporal variations of σ affected the EC measured with EMI. These potentially confounding factors in the interpretation of EMI measurements in terms of SWC have not been sufficiently recognized in the literature so far, and the results presented in this study indicate a range of limitations for the use of EMI to monitor spatiotemporal changes in SWC at test sites with low EC. [ABSTRACT FROM AUTHOR]

Irrigated agriculture is an important economic factor in the rural parts of the metropolitan area of Hamburg. It is commonly expected that climate change will reduce the groundwater quantities available for field irrigation. Against this background, the ratio of irrigation need and groundwater recharge (IGR-ratio) is suggested as an indicator to assess climate change impacts on the vulnerability of groundwater resources towards overexploitation by agricultural irrigation. The IGR-ratio has been assessed based on the distributed water balance model mGROWA, i.e. under consideration of the simulated groundwater recharge levels and the field crop-specific irrigation need of the commonly cultivated field crops. The spatial IGR-ratio distribution determined for the observed reference period 1971–2000 has shown that the delineated vulnerable areas coincide with the regions for which high irrigation quantities have been documented at present. Additionally, the IGR-ratio depicts the areas in which irrigation is currently still negligible, but in which the introduction of irrigation into agricultural practice would lead to an immediate overexploitation of the sustainably available groundwater budget. The possible impact of future climate on IGR-ratios was determined by using a model chain of mGROWA and the regional climate models REMO and WETTREG2010. The related ensemble simulations did not provide a uniform tendency of possible future IGR-ratio changes. Whereas the mGROWA–WETTREG2010 realisations projected a very high increase in the IGR-ratios, the mGROWA–REMO realisations did not show a pronounced trend of increasing IGR-ratios. Therefore, considerable uncertainties remain regarding the future bandwidth of IGR-ratio changes. [ABSTRACT FROM AUTHOR]

The addition of biochar or digestate as organic amendments to soils is currently controversially discussed with regard to its positive and negative effects on C mineralization. Organic amendments are generally applied to agricultural fields to improve soil quality and crop yield. In this study, we present results from short-term respiration experiments (90 days), where two different biochars (produced at 400 and 800 °C) as well as digestate from biogas production were added in different combinations to two soils (loamy sand and silt loam). Additionally, both amendments were mixed together into the soil to study interactions between biochar and digestate effects and investigate the interactions of both amendments with clay minerals resulting in a total of 13 mixtures (plus control soils) per soil type. The results indicate that the rate of CO evolution was not proportional to the amount of C added to the systems indicating a saturation effect in the C degradation mechanism. More than 40 % of the digestate C was released as CO and only 3 % for the biochar soil mixture; the recalcitrant nature of biochar and its suitability for short-term C stabilization in soils (incubation period of 90 days) were shown. Surprisingly, a much lower CO release (up to 11-fold) was observed in soil/digestate/biochar compared to soil/digestate mixtures without biochar. This effect was observed even when only 1 % ( w/ w) biochar was added to the digestate/soil mixtures, indicating that the biochar changed the physicochemical properties of the system. Additional dissolved organic C (DOC) sorption experiments revealed that large quantities of DOC can be sorbed by the biochar reducing the microbial accessible DOC in the liquid phase and as a consequence also the CO production. [ABSTRACT FROM AUTHOR]

Soils are highly complex and heterogeneous porous materials, and thus measuring water distribution non-invasively with high accuracy and adequate spatial resolution still remains challenging. The first few centimeters of a soil surface control the vapor flux to the atmosphere justifying the need for high spatial resolution measurements of moisture content. The objective of this study was to compare and assess the feasibility of various high-resolution magnetic resonance (MR) methods to characterize an unsaturated porous system. We employed (1) a spin-echo, (2) three types of single-point imaging and (3) a unilateral three-magnet array to monitor T and T relaxation time spectra and the effective moisture saturation (Θ) of a silt loam under progressing desaturation with focus on an emerging unsaturated surface layer, which is predicted by theory. During the first stage of drying where evaporation occurred at the soil surface, all methods showed homogeneously distributed moisture. A decreasing Θ and a shift in the T and T relaxation time spectra to shorter values indicated the commencement of stage 2 evaporation coincided with an increasing unsaturated layer. At low water contents, the most suitable method to determine the extent of a desaturated surface zone with high accuracy was found to be single--point ramped imaging with T enhancement. As a simple and low-cost device the unilateral three-magnet array was feasible to monitor the drying process until the dry surface layer developed. [ABSTRACT FROM AUTHOR]

Due to the recent system developments for the electromagnetic characterization of the subsurface, fast and easy acquisition is made feasible due to the fast measurement speed, easy coupling with GPS systems, and the availability of multi-channel electromagnetic induction (EMI) and ground penetrating radar (GPR) systems. Moreover, the increasing computer power enables the use of accurate forward modeling programs in advanced inversion algorithms where no approximations are used and the full information content of the measured data can be exploited. Here, recent developments of large-scale quantitative EMI inversion and full-waveform GPR inversion are discussed that yield higher resolution of quantitative medium properties compared to conventional approaches. In both cases a detailed forward model is used in the inversion procedure that is based on Maxwell's equations. The multi-channel EMI data that have different sensing depths for the different source-receiver offset are calibrated using a short electrical resistivity tomography (ERT) calibration line which makes it possible to invert for electrical conductivity changes with depth over large areas. The crosshole GPR full-waveform inversion yields significant higher resolution of the permittivity and conductivity images compared to ray-based inversion results. [ABSTRACT FROM AUTHOR]

Aims: Stomata can close to avoid cavitation under decreased soil water availability. This closure can be triggered by hydraulic ('H') and/or chemical signals ('C', 'H + C'). By combining plant hydraulic relations with a model for stomatal conductance, including chemical signalling, our aim was to derive direct relations that link soil water availability, expressed as fraction of roots in dry soil (f), to transpiration reduction. Methods: We used the mechanistic soil-root water flow model R-SWMS to verify this relation. Virtual split root experiments were simulated, comparing horizontal and vertical splits with varying f and different strengths of stomatal regulation by chemical and hydraulic signals. Results: Transpiration reduction predicted by the direct relations was in good agreement with numerical simulations. For small enough potential transpiration and large enough root hydraulic conductivity and stomatal sensitivity to chemical signalling isohydric plant behaviour originates from H + C control whereas anisohydric behaviour emerges from C control. For C control the relation between transpiration reduction and f becomes independent of transpiration rate whereas H + C control results in stronger reduction for higher transpiration rates. Conclusion: Direct relations that link effective soil water potential and leaf water potential can describe different stomatal control resulting in contrasting behaviour. [ABSTRACT FROM AUTHOR]

Recently we showed that during the degradation of sulfadiazine (SDZ) by Microbacterium lacus strain SDZm4 the principal metabolite 2-aminopyrimidine (2-AP) accumulated to the same molar amount in the culture as SDZ disappeared (Tappe et al. Appl Environ Microbiol 79:2572-2577, ). Although 2-AP is considered a recalcitrant agent, long-term lysimeter experiments with C-pyrimidine labeled SDZ ([C]SDZ) provided indications for substantial degradation of the pyrimidine moiety of the SDZ molecule. Therefore, we aimed to enrich 2-AP degrading bacteria and isolated a pure culture of a Terrabacter-like bacterium, denoted strain 2APm3. When provided with C-labeled SDZ, M. lacus strain SDZm4 degraded [C]SDZ to [C]2-AP. Resting cells of 2APm3 at a concentration of 5 × 10 cells ml degraded 62 µM [C]2-AP to below the detection limit (0.6 µM) within 5 days. Disappearance of 2-AP resulted in the production of at least two transformation products (M1 and M2) with M2 being identified as 2-amino-4-hydroxypyrimidine. After 36 days, the transformation products disappeared and 83 % of the applied [C]2-AP radioactivity was trapped as CO. From this we conclude that a consortium of two species should be able to almost completely degrade SDZ in soils. [ABSTRACT FROM AUTHOR]

Aims: A simulation model to demonstrate that soil water potential can regulate transpiration, by influencing leaf water potential and/or inducing root production of chemical signals that are transported to the leaves. Methods: Signalling impacts on the relationship between soil water potential and transpiration were simulated by coupling a 3D model for water flow in soil, into and through roots (Javaux et al. ) with a model for xylem transport of chemicals (produced as a function of local root water potential). Stomatal conductance was regulated by simulated leaf water potential (H) and/or foliar chemical signal concentrations (C; H + C). Split-root experiments were simulated by varying transpiration demands and irrigation placement. Results: While regulation of stomatal conductance by chemical transport was unstable and oscillatory, simulated transpiration over time and root water uptake from the two soil compartments were similar for both H and H + C regulation. Increased stomatal sensitivity more strongly decreased transpiration, and decreased threshold root water potential (below which a chemical signal is produced) delayed transpiration reduction. Conclusions: Although simulations with H + C regulation qualitatively reproduced transpiration of plants exposed to partial rootzone drying (PRD), long-term effects seemed negligible. Moreover, most transpiration responses to PRD could be explained by hydraulic signalling alone. [ABSTRACT FROM AUTHOR]

We applied three approaches to estimate the zero-plane displacement $$d$$ through the aerodynamic measurement height $$z$$ (with $$z = z_{m}- d$$ and $$z_{m}$$ being the measurement height above the surface), and the aerodynamic roughness length $$z_{0}$$ , from single-level eddy covariance data. Two approaches (one iterative and one regression-based) were based on the universal function in the logarithmic wind profile and yielded an inherently simultaneous estimation of both $$d$$ and $$z_{0}$$ . The third approach was based on flux-variance similarity, where estimation of $$d$$ and consecutive estimation of $$z_{0}$$ are independent steps. Each approach was further divided into two methods differing either with respect to the solution technique (profile approaches) or with respect to the variable (variance of vertical wind and temperature, respectively). All methods were applied to measurements above a large, growing wheat field where a uniform canopy height and its frequent monitoring provided plausibility limits for the resulting estimates of time-variant $$d$$ and $$z_{0}$$ . After applying, for each approach, a specific data filtering that accounted for the range of conditions (e.g. stability) for which it is valid, five of the six methods were able to describe the temporal changes of roughness parameters associated with crop growth and harvest, and four of them agreed on $$d$$ to within 0.3 m most of the time. Application of the same methods to measurements with a more heterogeneous footprint consisting of fully-grown sugarbeet and a varying contribution of adjacent harvested fields exhibited a plausible dependence of the roughness parameters on the sugarbeet fraction. It also revealed that the methods producing the largest outliers can differ between site conditions and stability. We therefore conclude that when determining $$d$$ for canopies with unknown properties from single-level measurements, as is increasingly done, it is important to compare the results of a number of methods rather than rely on a single one. An ensemble average or median of the results, possibly after elimination of methods that produce outliers, can help to yield more robust estimates. The estimates of $$z_{0}$$ were almost exclusively physically plausible, although $$d$$ was considered unknown and estimated simultaneously with the methods and results described above. [ABSTRACT FROM AUTHOR]

Aims: Soil salinity can cause salt plant stress by reducing plant transpiration and yield due to very low osmotic potentials in the soil. For predicting this reduction, we present a simulation study to (i) identify a suitable functional form of the transpiration reduction function and (ii) to explain the different shapes of empirically observed reduction functions. Methods: We used high resolution simulations with a model that couples 3D water flow and salt transport in the soil towards individual roots with flow in the root system. Results: The simulations demonstrated that the local total water potential at the soil-root interface, i.e. the sum of the matric and osmotic potentials, is for a given root system, uniquely and piecewise linearly related to the transpiration rate. Using bulk total water potentials, i.e. spatially and temporally averaged potentials in the soil around roots, sigmoid relations were obtained. Unlike for the local potentials, the sigmoid relations were non-unique functions of the total bulk potential but depended on the contribution of the bulk osmotic potential. Conclusions: To a large extent, Transpiration reduction is controlled by water potentials at the soil-root interface. Since spatial gradients in water potentials around roots are different for osmotic and matric potentials, depending on the root density and on soil hydraulic properties, transpiration reduction functions in terms of bulk water potentials cannot be transferred to other conditions, i.e. soil type, salt content, root density, beyond the conditions for which they were derived. Such a transfer could be achieved by downscaling to the soil-root interface using simulations with a high resolution process model. [ABSTRACT FROM AUTHOR]

Within the TERENO initiative, four terrestrial observatories, collecting huge amounts of environmental data, are being set up since 2008. To manage, describe, exchange and publish these data, the distributed Spatial Data Infrastructure TEODOOR () was created. Each institution responsible for an individual observatory sets up its own local data infrastructure, which may communicate with each other to exchange data and metadata internally or to the public by OGC compliant Web services. The TEODOOR data portal serves as a database node to provide scientists and decision makers with reliable and well-accessible data and data products. Various tools like hierarchical search or Web-GIS functions allow a deeper insight into the different observatories, test sites and sensor networks. Sensor data can be queried and selected for measured parameters, stations and/or time periods, and can be visualized and downloaded according to a shared TERENO data policy. Currently, TEODOOR provides free access to data from more than 500 monitoring stations. [ABSTRACT FROM AUTHOR]

The main goal of the project was to assess nitrogen pollution of surface waters and groundwater in the Federal State of North Rhine Westphalia (NRW), Germany. For this purpose the hydro(geo-)logical models GROWA-DENUZ/WEKU were coupled to the agro-economic model RAUMIS in order to assess the diffuse nitrogen loads and to approaches to determine the nitrogen loads from point sources. In this way the complex socio-economic interrelations and hydrological/hydrogeological interdependencies were simultaneously. The model network was applied consistently across the whole territory of NRW. At first the actual N inputs into groundwater and surface waters resulting from diffuse sources and point sources were assessed. For the relevant diffuse input pathways (groundwater runoff, drainage runoff and natural interflow) this was done in a spatial resolution of 100 m ∙ 100 m. In the case of point source inputs information from municipal waste water treatment plants, industrial effluents, rainwater sewers and combined sewer overflows has been considered. For NRW an actual total N input into surface waters of ca. 117.000 t ∙ a N has been quantified. As the inputs via natural interflow (ca. 30 %), groundwater runoff (ca. 26 %) and drainage systems (ca. 18 %) hold the largest portion, it is evident that measures to control nitrate pollution have to focus on the inputs from diffuse sources. For this purpose, initially the development of the agrarian sector according to the Common Agricultural Policy, CAP until 2015 including supplementary measures and other impact factors has been analysed. The impact of this so-called baseline scenario 2015 was predicted for both, the diffuse N surpluses and the N pollution of groundwater and surface waters. It could be shown that the baseline projections for the agricultural sector through 2015 may lead to decrease of the diffuse N inputs into groundwater by ca. 13.500 t ∙ a N and an overall decrease of the diffuse N inputs into surface waters by ca. 25.000 kg ∙ ha ∙ a N. Based on the baseline scenario 2015 the additional N reduction to guarantee nitrate concentrations in groundwater below the EU-threshold value of 50 mg ∙ l NO was determined by means of a backward model calculation. This was done using the predicted nitrate concentrations in the leachate 2015 for the individual 100 m ∙ 100 m grids as starting points. In this way for the whole territory of NRW an additional N reduction beyond the baseline scenario 2015 of ca. 12.000 t ∙ a N has been assessed. Model results indicate that additional N reduction measures don't have to be implemented area-covering in order to be efficient, but in certain subareas only. It is suggested that in these subareas the available financial resources for the implementation of N reduction measures shall be used for individual, i.e. regionally adapted nitrate reduction measures. [ABSTRACT FROM AUTHOR]

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Higher-order moments, minima and maxima of turbulent temperature and water vapour mixing ratio probability density functions measured with an eddy-covariance system near the ground were related to each other and to vertical boundary-layer profiles of the same scalars obtained through airborne soundings. The dependence of kurtosis on squared skewness showed a kurtosis intercept below the Gaussian expectation, suggesting a compression of the probability density function by the presence of natural boundaries. This hypothesis was corroborated by comparing actual minima and maxima of turbulent fluctuations to estimates obtained from the first four sample moments by fitting a four-parameter beta distribution. The most sharply defined boundaries were found for the minima of temperature datasets during the day, indicating that negative temperature fluctuations at the sensor are limited by the availability of lower temperatures in the boundary layer. By comparison to vertical profiles, it could be verified that the turbulent minimum of temperature near the ground is close to the minimum of potential temperature in the boundary layer. The turbulent minimum of water vapour mixing ratio was found to be equal to the mixing ratio at a height above the minimum of the temperature profile. This height roughly agrees with the top of the non-local unstable domain according to bulk Richardson number profiles. We conclude that turbulence statistics measured near the surface cannot be solely explained by local effects, but contain information about the whole boundary layer including the entrainment zone. [ABSTRACT FROM AUTHOR]

An area-differentiated model approach (MEPhos) for the quantification of mean annual P-inputs from point and diffuse sources is presented. The following pathways are considered: artificial drainage, wash-off, groundwater outflow, soil erosion, rainwater sewers, combined sewer overflows, municipal waste water treatment plants and industrial effluents. Two retention functions for rivers and reservoirs are included in order to model P-sinks within a river basin. This allows a complete record of P-loads in heterogeneous meso- and macroscale river basins and enables validation of modeling results with water quality data on a load basis. The model is applied to the River Ruhr basin (4,485 km2) in Germany, which includes contrasting natural conditions, land use patterns as well as population and industry densities. Based on validated modelling results sub-areas of high P-loads are localized and management options for the reduction of P-inputs to surface waters are proposed taking into account the site conditions of the sub-areas relevant for high P-inputs into surface waters. [ABSTRACT FROM AUTHOR]

The adsorption and degradation of chlorobenzene on partially modified organoclays and by the autochthonous microorganism Rhodococcus B528 were studied by means of the batch technique. Organoclays were prepared from Na-montmorillonite (MM) by using dodecyltrimethylammonium (C12) and dioctadecyldimethylammonium (2C18) bromides. The degree of modification was 35 (2C18-35-MM) and 89% (C12-89-MM) of the cation exchange capacity of MM. The adsorption experiments were carried out using headspace GC. The intercalation of chlorobenzene into the interlayers of organo-MM was detected by X-ray diffraction. The adsorption isotherms found were of the S1 type indicating a cooperative effect. Chlorobenzene showed a higher affinity for 2C18-35-MM than C12-89-MM, which could not only be explained by the organic carbon content. The comparison with 2,4-dichlorophenol adsorption has implied that for the studied systems the different adsorption mechanisms are primarily governed by the different molecular properties and not by the type of absorbent. The presence of 2C18-35-MM caused no negative effect on the investigated microorganisms and complete biodegradation of chlorobenzene was achieved without desorption limitation for growth, demonstrating the applicability of partially modified organoclays for bioremediation. [ABSTRACT FROM AUTHOR]

This paper demonstrates the possibilities of reactive transport modeling in predicting contaminant transport processes of laboratory and field scales. Basic approaches of reactive transport modeling are discussed, focusing on the incorporation of a thermodynamic description of chemical interactions into the convection-dispersion equation (CDE). Both equilibrium and kinetic approaches are presented. Chemical reaction parameters can be estimated from 1-D column experiments, by combining the CDE and the thermodynamic description of transport. A 2-D simulation with a heterogeneous flow field and ion exchange parameters obtained from column experiments is presented. The results of the 2-D model are in qualitative agreement with measured field breakthrough curves. Limitations of this approach are discussed, focusing on parameter heterogeneity and scaling effects. [ABSTRACT FROM AUTHOR]

The paper presents a study of the diffusive transport of passive solute plumes in a two-dimensional non-homogeneous depth stratified flow domain. All the properties of the process are expressed by depth dependent deterministic functions. The method of moments, combined with the method of Green functions are chosen to determine the relevant characteristics of the flow (mass, center of mass, variance, etc.) used to describe the behaviour of the transient motion. General relationships for the n-order concentration moments are proved. Further, it is derived that the transient motion defined by time-dependent parameters tends asymptotically at large time to a stable regime whose characteristics are determined. Consequently, under certain hypotheses, an equivalence between the mean original process and a Fickian diffusive transport at large time may be established. The time required by the process to reach its asymptotic behaviour is also calculated. [ABSTRACT FROM AUTHOR]

Copyright of Grundwasser is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)