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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]

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]

Abstract: Atrazine was banned in Germany in 1991 due to findings of atrazine concentrations in ground- and drinking waters exceeding threshold values. Monitoring of atrazine concentrations in the groundwater since then provides information about the resilience of the groundwater quality to changing agricultural practices. In this study, we present results of a monitoring campaign of atrazine concentrations in the Zwischenscholle aquifer. This phreatic aquifer is exposed to intensive agricultural land use and susceptible to contaminants due to a shallow water table. In total 60 observation wells (OWs) have been monitored since 1991, of which 15 are sampled monthly today. Descriptive statistics of monitoring data were derived using the “regression on order statistics” (ROS) data censoring approach, estimating values for nondetects. The monitoring data shows that even 20 years after the ban of atrazine, the groundwater concentrations of sampled OWs remain on a level close to the threshold value of 0.1 μg l−1 without any considerable decrease. The spatial distribution of atrazine concentrations is highly heterogeneous with OWs exhibiting permanently concentrations above the regulatory threshold on the one hand and OWs were concentrations are mostly below the limit of quantification (LOQ) on the other hand. A deethylatrazine-to-atrazine ratio (DAR) was used to distinguish between diffuse – and point-source contamination, with a global mean value of 0.84 indicating mainly diffuse contamination. Principle Component Analysis (PCA) of the monitoring dataset demonstrated relationships between the metabolite desisopropylatrazine, which was found to be exclusively associated with the parent compound simazine but not with atrazine, and between deethylatrazine, atrazine, nitrate, and the specific electrical conductivity. These parameters indicate agricultural impacts on groundwater quality. The findings presented in this study point at the difficulty to estimate mean concentrations of contamination for entire aquifers and to evaluate groundwater quality based on average parameters. However, analytical data of monthly sampled single observation wells provide adequate information to characterize local contamination and evolutionary trends of pollutant concentration. [Copyright &y& Elsevier]

Abstract: Water infiltration into heterogeneous, structured soil leads to hydraulic non-equilibrium across the infiltration front. That is, the water content and pressure head are not in equilibrium according to some static water retention curve. The water content increases more rapidly in more conductive regions followed by a slow relaxation towards an equilibrium state behind the front. An extreme case is preferential infiltration into macropores. Since flow paths adapt to the structural heterogeneity of the porous medium, there is a direct link between structure and non-equilibrium. The aim of our study is to develop an upscaled description of water dynamics which conserves the macroscopic effects of non-equilibrium and which can be directly linked to structural properties of the material. A critical question is how to define averaged state variables at the larger scale. We propose a novel approach based on flux-weighted averaging of pressure head, and compare its performance to alternative methods for averaging. Further, we suggest some meaningful indicators of hydraulic non-equilibrium that can be related to morphological characteristics of infiltration fronts in quantitative terms. These methods provide a sound basis to assess the impact of structural connectivity on hydraulic non-equilibrium. We demonstrate our approach using numerical case studies for infiltration into two-dimensional heterogeneous media using three different structure models with distinct differences in connectivity. Our results indicate that an increased isotropic, short-range connectivity reduces non-equilibrium, whereas anisotropic structures that are elongated in the direction of flow enforce it. We observe a good agreement between front morphology and effective hydraulic non-equilibrium. A detailed comparison of averaged state variables with results from an upscaled model that includes hydraulic non-equilibrium outlines potential improvements in the description of non-equilibrium dynamics including preferential flow in simplified, upscaled models based on Richards equation. [Copyright &y& Elsevier]

Examines the use of fluorescent tracers in identifying transport processes in soil cores. Interaction between solutes and solid soil phase; Spatial structure of the soil leaching process; Effects of lateral mixing and sorption on leaching.

Examines the fluorescent dye concentrations on soil surfaces. Correction of fluorescent signal for variable illumination light intensity; Optical properties of soil across exposed surfaces; Linear calibration relations related to corrected fluorescent image.

The local scale dispersion tensor, Dd, is a controlling parameter for the dilution of concentrations in a solute plume that is displaced by groundwater flow in a heterogeneous aquifer. In this paper, we estimate the local scale dispersion from time series or breakthrough curves, BTCs, of Br− concentrations that were measured at several points in a fluvial aquifer during a natural gradient tracer test at Krauthausen. Locally measured BTCs were characterized by equivalent convection dispersion parameters: equivalent velocity, veq(x) and expected equivalent dispersivity, 〈λeq(x)〉. A Lagrangian framework was used to approximately predict these equivalent parameters in terms of the spatial covariance of loge transformed conductivity and the local scale dispersion coefficient.The approximate Lagrangian theory illustrates that 〈λeq(x)〉 increases with increasing travel distance and is much larger than the local scale dispersivity, λd. A sensitivity analysis indicates that 〈λeq(x)〉 is predominantly determined by the transverse component of the local scale dispersion and by the correlation scale of the hydraulic conductivity in the transverse to flow direction whereas it is relatively insensitive to the longitudinal component of the local scale dispersion. By comparing predicted 〈λeq(x)〉 for a range of Dd values with 〈λeq(x)〉 obtained from locally measured BTCs, the transverse component of Dd, DdT, was estimated. The estimated transverse local scale dispersivity, λdT=DdT/U1 (U1=mean advection velocity) is in the order of 101–102 mm, which is relatively large but realistic for the fluvial gravel sediments at Krauthausen. [Copyright &y& Elsevier]

Future food production is expected to be affected by climate change, because it will alter the crop water balance components, such as water storage, evapotranspiration and drainage. Variations in weather conditions could explain more than 50% of the variability of wheat yield. Higher temperatures and lower rainfall amounts mainly limit the actual evapotranspiration and reduce soil water storage, which in turn affect crop yield and water use efficiency. To study these effects, soil monoliths were moved to sites with contrasting climatic conditions (space for time concept) and monitored.In this contribution, yield, evapotranspiration, and changes in soil water storage from lysimeters soils for a period from 2011 until 2017 were analyzed. Data were obtained from a German wide monitoring network of lysimeter stations (TERENO-SOILCan), which was established across a rainfall and temperature transect, and lysimeters were transferred between the stations to subject them to different climate regimes. A uniform crop management (crop type, fertilizer, growth regulator, tillage, and use of pesticides) and crop rotation allows investigating the response of soil water storage and cropping water use efficiency for different soil types to a change in climate conditions.Main results showed a characteristic decrease of water availability of soils with a finer texture and smaller pores under drier and warmer climate conditions. The drier and warmer climate significantly increase crop yield and reduce at the same time evapotranspiration. This result confirms a more efficient use of water by plants under less optimal water availability in the root zone. [ABSTRACT FROM AUTHOR]

The International Soil Modeling Consortium (ISMC) was established in 2016 with the aim to integrate and advance soil systems modeling, data collection, and observational capabilities. ISMC is a community effort. It follows a bottom-up approach, is based on scientific principles, voluntary contributions, and open to anybody who wants to become a member of the consortium (https://soil-modeling.org/). Its activities are organized into three science panels, organized around a broad workflow from data collection and observation (DO-LINK) to model development and intercomparison (Soil-MIP) to engagement with different scientific communities (CROSS-Connect). ISMC has an executive board and a scientific advisory board that guides ISMC in pursuing its objectives. The mission of the Soil-MIP science panel is to foster the further development of soil models that can predict soil functions and their changes due to soil use and land management, as well as climate change and pollution. A number of model intercomparison studies were recently initiated, focusing on specific processes like soil hydraulic properties, soil thermal properties and related soil heat fluxes, root growth and root water uptake, soil evaporation, soil freezing, infiltration and runoff processes, and coupling between preferential flow in soils and groundwater. From these comparisons, lessons can be learned about how process controls at small scales propagate to larger scales and how this leads to effective process representations at larger scales. The mission of DO-Link is to assist with the development of a global soil data meta-repository that is openly available for soil system research. Data and data requirements are as diverse as the various disciplines developing and applying soil models. The soil data meta-repository will be a resource to analyze past and recent model- and data requirements for continuous standardization and harmonization of soil data. The CROSS-connect science panel identifies soil related knowledge gaps between science communities, and shares this knowledge with other ISMC science panels to push forward development of new tools to better translate soil processes into functions for assessing sustainability and ecosystem services. CROSS-connect develops an exchange platform with other international partners like AgMip/MACSUR, GEWEX, ISCN (International Soil Carbon Network), GSBI (Global Soil Biodiversity initiative) and CSDMS (Community Surface Dynamics Modeling System). In this presentation, we will highlight the most recent developments and activities that are currently underway as well as future projects that are under preparation. [ABSTRACT FROM AUTHOR]

The rhizosphere refers to the soil area that is directly and actively influenced by root exudation and secretions. In terms of its spatio-temporal pattern, the rhizosphere is a not a fixed-size region, but consists of gradients in biological, chemical and physical properties that vary radially, longitudinally and temporally along the root. A better understanding of the rhizosphere in terms of root exudation and secretions dynamics and associated biogeochemical processes is critical for maintaining the health of plant growth and the composition of the organisms within the rhizosphere. Various types of organic substances are released by roots. Their crucial impact on rhizosphere properties and related functional processes depends on their spatio-temporal concentration distribution around roots. Further more, different plant species/genotypes have varying root architectures, and individual rhizodeposits have their own diffusion coefficients and decomposition rates. Their re- lease patterns, root growth dynamics and solute transport are jointly responsible for the distribution of the rhizodeposit in the soil. Here, we derive a mathematical model that simulates the spatio-temporal distribution of rhizodeposits. The model is based on convolutions of the analytical solution of the 3D convection diffusion equation coupled to a root growth model. In terms of the rhizodeposit distribution, we define the mathematical formulas to describe the rhizosphere and hotspot for each single root of the root system. The model simulations did involve two plant species differing in root architecture (Vicia faba and Zea mays) and two kinds of rhizodeposits (citrate and mucilage) were examined. The impact of the transport parameters (diffusion and sorption coefficients) and the root architecture on the spatio-temporal evolution of the rhizodeposit distribution was also evaluated. The spatio-temporal distribution of the rhizodeposits can be characterized by discriptors, such as the width of the rhizodeposit zone, reactor ratio. The following information about the rhizosphere was highlighted by the model simulation: (a) the dynamics of the root architecture development strongly affects the rhizodeposit distribution in the root zone; (b) each growing root develops a dynamic rhizosphere (i.e. the width of the rhizosphere is varying for a given position behind the root tip-it is increasing over a certain time interval and then decreasing). Its width depends on the value of the diffusion coefficient of the compound in soil. The overlap of individual rhizospheres is more likely to occur for citrate than for mucilage rhizodeposits. Our results improve our understanding of the impact of the spatial and temporal heterogeneity of rhizodeposits input on rhizosphere development for different root system types and substances and gain insight into the computation and interpretation of the development of the rhizosphere mathematically. [ABSTRACT FROM AUTHOR]

Aims: Demonstrating the potential of MRI as a 3D, non-invasive and continuous measurement technique to map Na+ concentration distributions in soil and around roots. Methods: Dissolved NaCl in soil and soil-plant systems was mapped by 3D 23Na-MRI. The lower limit of detectability in saturated and unsaturated porous media was evaluated, followed by evaporation experiments to test the quantification. Finally, Na+ enrichment around tomato roots, irrigated with saline solution under low/high transpiration rates (LT, HT), was imaged in parallel to the root system,. Results: A spin echo pulse sequence allowed the quantitative mapping of the volume concentration of NaCl in sandy porous medium. Evaporation experiments showed slight enrichment in the top surface layer, plus uniform temporal enrichment in the deeper layers. In the tomato experiments, enrichment was more distinct under HT than under LT. Concentration-distance correlation curves revealed thin enrichment zones ranging a few mm around the roots. Conclusions: MRI can map Na+ non-invasively in 3D at relevant concentrations for root activity. Visualizing water content, roots and Na+ on the same scale is possible, despite limitations of different scanning times and resolution. This opens a route for further quantitative investigations of salt enrichment processes in soil and soil-plant systems. [ABSTRACT FROM AUTHOR]

Aims: (1) Monitoring 'root-felt' salinity by using rhizoslides as a non-invasive method, (2) Studying how transpiration rate, salinity in irrigation water, and root water uptake affect sodium distribution around single roots, (3) Interpreting experimental results by using simulations with a 3-D root system architecture model coupled with water flow and solute transport models. Methods: Tomato plants were grown on rhizoslides under various salinity levels and two transpiration rates: high and low. Daily root images were processed with GIMP and incorporated into a 3-D numerical model. The experiments were simulated with R-SWMS, a 3-dimensional numerical model that simulates water flow and solute transport in soil, into the root and inside root systems. Results: Both experimental and simulation results displayed higher root-felt sodium concentrations compared with the bulk concentrations, and larger accumulation at higher transpiration rate. The simulations illustrated that the root-felt to bulk concentration ratio changed during the experiment depending both on the irrigation water salinity and transpiration rate. Conclusions: Changes in sodium concentrations with transpiration rates are most likely caused by root water uptake and ion exclusion. Simulation results indicate that root-scale process models are required to link root system architecture, environmental, and soil conditions with root-felt salinities. [ABSTRACT FROM AUTHOR]

Summary: The effect of root hairs on water uptake remains controversial. In particular, the key root hair and soil parameters that determine their importance have been elusive.We grew maize plants (Zea mays) in microcosms and scanned them using synchrotron‐based X‐ray computed microtomography. By means of image‐based modelling, we investigated the parameters determining the effectiveness of root hairs in root water uptake. We explicitly accounted for rhizosphere features (e.g. root–soil contact and pore structure) and took root hair shrinkage of dehydrated root hairs into consideration.Our model suggests that > 85% of the variance in root water uptake is explained by the hair‐induced increase in root–soil contact. In dry soil conditions, root hair shrinkage reduces the impact of hairs substantially.We conclude that the effectiveness of root hairs on root water uptake is determined by the hair‐induced increase in root–soil contact and root hair shrinkage. Although the latter clearly reduces the effect of hairs on water uptake, our model still indicated facilitation of water uptake by root hairs at soil matric potentials from −1 to −0.1 MPa. Our findings provide new avenues towards a mechanistic understanding of the role of root hairs on water uptake. See also the Commentary on this article by Boursiac & Bauget 240: 2173–2175. [ABSTRACT FROM AUTHOR]

Functional–structural root-system models simulate the relations between root-system architectural and hydraulic properties, and the spatio-temporal distributions of water and solutes in the root zone. Such models may help identify optimal plant properties for breeding and contribute to increased water-use efficiency. However, it must first be demonstrated that they accurately reproduce the processes they intend to describe. This is challenging because the flow and transport processes towards individual roots are hard to observe. In this study, we demonstrate how this problem can be addressed by combining co-registered root and tracer distributions obtained from magnetic resonance imaging with a root-system model in an inverse modeling scheme. The main features in the tracer distributions were well reproduced by the model using realistic root hydraulic parameters. By combining the functional–structural root-system model with 4D tracer observations, we were able to quantify the water uptake distribution of a growing root system. We determined that 76% of the transpiration was extracted through 3rd-order roots. The simulations also demonstrated that accurate water uptake distribution cannot be directly derived either from observations of tracer accumulation or from water depletion. However, detailed tracer experiments combined with process-based models help decipher mechanisms underlying root water uptake. [ABSTRACT FROM AUTHOR]

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (˜76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76% of the experimental sites with agricultural land use as the dominant type (˜40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it. [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]

In this manuscript, we propose a new method to calculate water flow and xylem water potential distribution in hydraulic architectures (such as root systems) of any complexity. It is based on the extension of the water flow equation analytical resolution of Landsberg and Fowkes for single roots. It consists in splitting the root systems in zones of homogeneous or homogeneously changing properties and deriving the xylem potential and water flow under any given boundary conditions (plant transpiration or collar potential, and potential at soil-root interfaces) without assuming a uniform xylem potential within each zone. The method combines analytical solutions of water flow within the segmented zones with the numerical solution of flow connectivity for the whole root system. We demonstrate that the proposed solution is the asymptote of the exclusively numerical solution for infinitesimal root segment lengths (and infinite segment number). As water uptake locations and magnitudes predicted by the latter solution for finite segmentation lengths deviate from the exact solution, and are computationally more intensive, we conclude that the new methodology should always be privileged for future applications. The proposed solution can be easily coupled to soil modules (as already done with existing solutions) and further implemented in functional-structural plant models to predict water flow in the soil-plant atmosphere continuum with a better accuracy than current models. Finally the new solution may be used to calculate more accurately plant scale macroscopic parameters for crop models. [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]

Meteoric 10 Be allows for the quantification of vertical and lateral soil fluxes over long time scales ( 10 3 – 10 5 yr ). However, the mobility of meteoric 10 Be in the soil system makes a translation of meteoric 10 Be inventories into erosion and deposition rates complex. Here, we present a spatially explicit 2D model simulating the behaviour of meteoric 10 Be on a hillslope. The model consists of two parts. The first component deals with advective and diffusive mobility of meteoric 10 Be within the soil profile, and the second component describes lateral soil and meteoric 10 Be fluxes over the hillslope. Soil depth is calculated dynamically, accounting for soil production through weathering as well as downslope fluxes of soil due to creep, water and tillage erosion. Synthetic model simulations show that meteoric 10 Be inventories can be related to erosion and deposition across a wide range of geomorphological and pedological settings. Our results also show that meteoric 10 Be can be used as a tracer to detect human impact on soil fluxes for soils with a high affinity for meteoric 10 Be. However, the quantification of vertical mobility is essential for a correct interpretation of the observed variations in meteoric 10 Be profiles and inventories. Application of the Be2D model to natural conditions using data sets from the Southern Piedmont ( Bacon et al., 2012 ) and Appalachian Mountains ( Jungers et al., 2009; West et al., 2013 ) allows to reliably constrain parameter values. Good agreement between simulated and observed meteoric 10 Be concentrations and inventories is obtained with realistic parameter values. Furthermore, our results provide detailed insights into the processes redistributing meteoric 10 Be at the soil-hillslope scale. [ABSTRACT FROM AUTHOR]

Background and aims: Impact of drought on crop growth depends on soil and root hydraulic properties that determine the access of plant roots to soil water. Root hairs may increase the accessible water pool but their effect depends on soil hydraulic properties and adaptions of root systems to drought. These adaptions are difficult to investigate in pot experiments that focus on juvenile plants. Methods: A wild-type and its root hairless mutant maize (Zea mays) were grown in the field in loam and sand substrates during two growing seasons with a large precipitation deficit. A comprehensive dataset of soil and plant properties and monitored variables were collected and interpreted using simulations with a mechanistic root water uptake model. Results: Total crop water use was similar in both soils and for both genotypes whereas shoot biomass was larger for the wild type than for the hairless mutant and did not differ between soils. Total final root length was larger in sand than in loam but did not differ between genotypes. Simulations showed that root systems of both genotypes and in both soils extracted all plant available soil water, which was similar for sand and loam, at a potential rate. Leaf water potentials were overestimated by the model, especially for the hairless mutant in sand substrate because the water potential drop in the rhizosphere was not considered. Conclusions: A direct effect of root hairs on water uptake was not observed but root hairs might influence leaf water potential dependent growth. [ABSTRACT FROM AUTHOR]

Aims: Root hairs are important for uptake, especially for nutrients with low mobility in soils with high sorption capacity. Mutants with defective root hairs are expected to have lower nutrient uptake, unless they compensate with more root growth. Since root hairs can also contribute to the plant's water uptake their importance could change over the course of a growing season. It was our objective to investigate the role of root hairs under field conditions. Methods: The root hair mutant rth3 of Zea mays and the corresponding wild-type were grown for two years under field conditions on sand and loam. Results: Shoot growth and P and K uptake of the plants were promoted by the presence of hairs at all growth stages. Differences between genotypes were greater on loam than on sand until tassel emergence, presumably as additional exploitation by hairs is more relevant in loam. Compensation for the absence of root hairs by increased root growth was not observed in absolute terms. The root to shoot ratio was higher for rth3 than for wild-type. Root traits showed high plasticity in response to texture, the most salient being a greater mean root diameter in sand, irrespective of genotype. The mechanism causing the increase in mean root diameter is still unknown. Root length density was higher in sand, which can be explained by a greater need for exploration than exploitation in this substrate. Conclusion: The role of hairs for nutrient uptake could be confirmed under field conditions. The large impact of texture on root growth and consequences for carbon balance require further investigations. [ABSTRACT FROM AUTHOR]

Bare soils are natural porous media where moisture and transport properties may change considerably. Under very dry conditions, it is predicted that capillary continuity from deeper soil layers to the surface ceases and evaporation decreases drastically because it is only sustained by vapor transport through an increasing dry surface layer (stage II). In this study, we firstly confirm this effect by investigating the drying of a lab-scale sand column using various MRI sequences as well as a unilateral NMR sensor (NMR-MOUSE). Proofing the convenience of the unilateral sensor, we take a step forward by monitoring moisture development of a natural soil under controlled ambient conditions. Finally, the experimental results clearly validate the prediction of a coupled water, vapor and heat flow model regarding the onset of stage II evaporation and the subsequent receding secondary evaporation front. [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]

Kinetic parameters of environmental fate processes are usually inferred by fitting appropriate kinetic models to the data using standard nonlinear least squares (NLS) approaches. Although NLS is appropriate to estimate the optimum parameter values, it implies restrictive assumptions on data variances when the confidence limits of the parameters must also be determined. Particularly in the case of degradation and metabolite formation, the assumption of equal error variance is often not realistic because the parent data usually show higher variances than those of the metabolites. Conventionally, such problems would be tackled by weighted NLS regression, which requires prior knowledge about the data errors. Instead of implicitly assuming equal error variances or giving arbitrary weights decided by the researcher, we use an iteratively reweighted least squares (IRLS) algorithm to obtain the maximum likelihood estimates of the model parameters and the error variances specific for the different species in a model. A study with simulated data shows that IRLS gives reliable results in the case of both unequal and equal error variances. We also compared results obtained by NLS and IRLS, with probability distributions of the parameters inferred with a Markov-Chain Monte-Carlo (MCMC) approach for data from aerobic transformation of different chemicals in soil. Confidence intervals obtained by IRLS and MCMC are consistent, whereas NLS leads to very different results when the error variances are distinctly different between different species. Because the MCMC results can be assumed to reflect the real parameter distribution imposed by the observed data, we conclude that IRLS generally yields more realistic estimates of confidence intervals for model parameters than NLS. Environ. Toxicol. Chem. 2011;30:2363-2371. © 2011 SETAC [ABSTRACT FROM AUTHOR]

Abstract: Spatially distributed soil hydraulic properties are required for distributed hydrological modelling. These soil hydraulic properties are known to vary significantly in space, and considering the non-linearity of runoff generation, the question arises how the spatial variation of soil hydraulic parameters affects the continuous runoff modelling for a micro-scale catchment. This was analysed by applying a three-dimensional hydrological model to the 28.6ha ‘Berrensiefen’ catchment, Germany, for a simulation period of one year. The model was based on an observed distribution of soil hydraulic properties, which were assumed to be layered in vertical and to vary continuously in horizontal direction, and validated for total runoff. Numerical experiments with five spatial distributions of soil hydraulic parameters derived from the observed spatial distribution, which was supposed to be the ‘true’ underlying spatial variation, were carried out. These five spatial concepts were: choropleth map, spatially homogeneous case, random distribution, stochastic simulation and conditional stochastic simulation. The comparative modelling revealed a significant sensitivity of runoff generation towards the spatial variation of soil hydraulic properties. The comparison of the hydrograph of surface and macropore runoff to the initial model runs exhibited the highest root mean square error with 1.3mmh−1 for the homogeneous case. Further we detected, that the frequency distribution of soil hydraulic properties played an important role for the reproduction of runoff amounts. But also the spatial topology (deterministic spatial variation) was relevant for an adequate description of runoff generation. Conditional stochastic simulation is seen as a promising approach, because it preserved both, the frequency distribution and the deterministic variation. [Copyright &y& Elsevier]

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]

Background and Aims Upland rice is often grown where water and phosphorus (P) are limited. To better understand the interaction between water and P availability, functional–structural models that mechanistically represent small-scale nutrient gradients and water dynamics in the rhizosphere are needed. Methods Rice was grown in large columns using a P-deficient soil at three P supplies in the topsoil (deficient, sub-optimal and non-limiting) in combination with two water regimes (field capacity vs. drying periods). Root system characteristics, such as nodal root number, lateral types, interbranch distance, root diameters and the distribution of biomass with depth, as well as water and P uptake, were measured. Based on the observed root data, 3-D root systems were reconstructed by calibrating the structural architecure model CRootBox for each scenario. Water flow and P transport in the soil to each of the individual root segments of the generated 3-D root architectures were simulated using a multiscale flow and transport model. Total water and P uptake were then computed by adding up the uptake by all the root segments. Key Results Measurements showed that root architecture was significantly affected by the treatments. The moist, high P scenario had 2.8 times the root mass, double the number of nodal roots and more S-type laterals than the dry, low P scenario. Likewise, measured plant P uptake increased >3-fold by increasing P and water supply. However, drying periods reduced P uptake at high but not at low P supply. Simulation results adequately predicted P uptake in all scenarios when the Michaelis–Menten constant (K m) was corrected for diffusion limitation. They showed that the key drivers for P uptake are the different types of laterals (i.e. S- and L-type) and growing root tips. The L-type laterals become more important for overall water and P uptake than the S-type laterals in the dry scenarios. This is true across all the P treatments, but the effect is more pronounced as the P availability decreases. Conclusions This functional–structural model can predict the function of specific rice roots in terms of P and water uptake under different P and water supplies, when the structure of the root system is known. A future challenge is to predict how the structure root systems responds to nutrient and water availability. [ABSTRACT FROM AUTHOR]

• A new expression of the groundwater − surface water conductance is derived. • It is function of the surface water network density and aquifer properties. • It is dependent on the vertical and horizontal model discretization sizes. • It is evaluated against 2D and 3D numerical experiments. • It accurately captures the scale dependency of the conductance. In regional hydrogeological models groundwater–surface water interaction is generally represented with a Cauchy boundary condition, in which a conductance parameter governs the exchange flux rate. In some models, the conductance is controlled by the streambed properties, since it has generally a lower hydraulic conductivity than the aquifer. However, depending on the specific system and the spatial discretization of the hydrogeological model, aquifer conductance can be a limiting factor for groundwater–surface water interactions. The present study introduces a new expression to represent the aquifer conductance as a function of aquifer properties, surface water network density and model discretization. This expression is based on the Dupuit-Forcheimer theory, the Ernst equation and vertical 2D numerical experiments at the field scale. The main assumptions used to derive our formulation are the presence of a no-flow boundary at the bottom of the hydrogeological model and the homogeneity of the aquifer. The expression is evaluated using simulations with 3D hydrogeological models at different spatial resolutions and compared against previously published parameterization approaches. The results show that the new expression outperforms the other approaches by capturing accurately both the grid-size and the surface water network density dependency of the conductance, which is caused by pressure head losses due to flow within the aquifer grid cell to the surface water, without any additional numerical calculation. Moreover, the proposed expression can be implemented directly in hydrogeological models thereby improving current approaches to represent groundwater–surface water interactions in regional hydrogeological models. [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]

Highlights • A novel RWU scheme based on the root hydraulic architecture is integrated in a LSM. • Root hydraulic properties control transpiration during prolonged dry conditions. • Soil parameterization uncertainty influences transpiration and soil water content. • Roots distribution induce larger variability in the hydraulic model response. Abstract 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 the soil characteristics. [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]

In recent years, many computational tools, such as image analysis, data management, process-based simulation, and upscaling tools, have been developed to help quantify and understand water flow in the soil–root system, at multiple scales (tissue, organ, plant, and population). Several of these tools work together or at least are compatible. However, for the uninformed researcher, they might seem disconnected, forming an unclear and disorganized succession of tools. In this article, we show how different studies can be further developed by connecting them to analyse soil–root water relations in a comprehensive and structured network. This 'explicit network of soil–root computational tools' informs readers about existing tools and helps them understand how their data (past and future) might fit within the network. We also demonstrate the novel possibilities of scale-consistent parameterizations made possible by the network with a set of case studies from the literature. Finally, we discuss existing gaps in the network and how we can move forward to fill them. [ABSTRACT FROM AUTHOR]

Background and Aims Root architecture development determines the sites in soil where roots provide input of carbon and take up water and solutes. However, root architecture is difficult to determine experimentally when grown in opaque soil. Thus, root architecture models have been widely used and been further developed into functional--structural models that simulate the fate of water and solutes in the soil--root system. The root architecture model CRootBox presented here is a flexible framework to model root architecture and its interactions with static and dynamic soil environments. Methods CRootBox is a C++-based root architecture model with Python binding, so that CRootBox can be included via a shared library into any Python code. Output formats include VTP, DGF, RSML and a plain text file containing coordinates of root nodes. Furthermore, a database of published root architecture parameters was created. The capabilities of CRootBox for the unconfined growth of single root systems, as well as the different parameter sets, are highlighted in a freely available web application. Key results The capabilities of CRootBox are demonstrated through five different cases: (1) free growth of individual root systems; (2) growth of root systems in containers as a way to mimic experimental setups; (3) fieldscale simulation; (4) root growth as affected by heterogeneous, static soil conditions; and (5) coupling CRootBox with code from the book Soil physics with Python to dynamically compute water flow in soil, root water uptake and water flow inside roots. Conclusions CRootBox is a fast and flexible functional--structural root model that is based on state-of-the-art computational science methods. Its aim is to facilitate modelling of root responses to environmental conditions as well as the impact of roots on soil. In the future, this approach will be extended to the above-ground part of the plant. [ABSTRACT FROM AUTHOR]

Quick, reliable and accurate estimates of soil water content (SWC) at intermediate (slope) to larger scale (catchment) are important for understanding hydrological processes and may be provided by electromagnetic induction (EMI). EMI measures the apparent electrical conductivity of the subsurface (EC app ) which represents a depth weighted average value of the bulk soil electrical conductivity (EC b ). The relation between EC b and SWC has generally been investigated in soil cores or using local measurements of SWC and EC b . Studies that investigated the relation between EC app measured with EMI and SWC in considerably larger and internally more heterogeneous support volumes are far scarcer and cover a limited range of environments with a limited range of factors contributing to EC app . This study developed a new calibration method to obtain quantitative estimates of SWC using EMI measured EC app data in a sub-tropical region in Southern Brazil at sites with different soil properties. SWC and EC b were measured in soil pits with Time Domain Reflectometry (TDR) probes. Collocated EC app was simultaneously measured with EMI using different coil separations and orientations to measure over increasing sensing volume. EMI measured EC app data were first calibrated against calculated EC app , which were derived from EC b profiles inserted in an exact EMI forward model. A depth averaged SWC (SWC avg ) was calculated and different calibrations that relate EC app to SWC avg were evaluated. EC app measurements of the deeper sensing coil configurations could predict best the variability of SWC avg using a non-linear relation. Spatio-temporal variations of pore water electrical conductivity (EC w ) were found to be an important cofounding factor. Temporal variations of EC w and the small temporal variability of SWC avg prevented the prediction of temporal variability of SWC avg using EC app measurements. Overall, the combination of both calibration steps resulted in the description of 83% of the spatial variability of SWC avg from EC app measurements. [ABSTRACT FROM AUTHOR]

Abstract: Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale. [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]

Background and aims: Hedgerow cropping decreases erosion in hillside agriculture but also competes for water and nutrients with crops. This study combined two methods for an improved understanding of water and nutrient competition at the crop-soil-hedge interface. Methods: δC isotopic discrimination in plants and soil electrical resistivity tomography (ERT) imaging were used in a field trial with maize monocropping (MM) vs. leucaena hedgerow intercropping with and without fertilizer (MHF and MHF) in Thailand. Results: Hedges significantly reduced maize grain yield and aboveground biomass in rows close to hedgerows. ERT revealed water depletion was stronger in MM than in MHF and MHF confirming time domain reflectometry and leaf area data. In MHF, water depletion was higher in maize rows close to the hedge compared to rows distant to hedges and maize grain δC was significantly less negative in rows close to hedges (-10.33‰) compared to distant ones (-10.64‰). Lack of N increased grain δC in MHF (-9.32‰, p ≤ 0.001). Both methods were correlated with each other (r = 0.66, p ≤ 0.001). Combining ERT with grain δC and %N allowed identifying that maize growth close to hedges was limited by N and not by water supply. Conclusion: Combining ERT imaging and C isotopic discrimination approaches improved the understanding of spatial-temporal patterns of competition at the hedge-soil-crop interface and allowed distinguishing between water and N competition in maize based hedgerow systems. [ABSTRACT FROM AUTHOR]

Summary Spatially highly resolved mapping of aquifer heterogeneities is critical for the accurate prediction of groundwater flow and contaminant transport. Here, we demonstrate the value of using full-waveform inversion of crosshole ground penetrating radar (GPR) data for aquifer characterization. We analyze field data from the Krauthausen test site, where crosshole GPR data were acquired along a transect of 20 m length and 10 m depth. Densely spaced cone penetration tests (CPT), located close to the GPR transect, were used to validate and interpret the tomographic images obtained from GPR. A strong correlation was observed between CPT porosity logs and porosity estimates derived from GPR using the Complex Refractive Index Model (CRIM). A less pronounced correlation was observed between electrical conductivity data derived from GPR and CPT. Cluster analysis of the GPR data defined three different subsurface facies, which were found to correspond to sediments with different grain size and porosity. In conclusion, our study suggests that full-waveform inversion of crosshole GPR data followed by cluster analysis is an applicable approach to identify hydrogeological facies in alluvial aquifers and to map their architecture and connectivity. Such facies maps provide valuable information about the subsurface heterogeneity and can be used to construct geologically realistic subsurface models for numerical flow and transport prediction. [ABSTRACT FROM AUTHOR]

Abstract: Dissolved organic carbon (DOC) is one of the most active and mobile carbon pools, and thus an important component of the global carbon cycle. Previous research on DOC transport in the soil and on factors controlling DOC export towards the river system focused mainly on forest and wetland areas, with only limited information available from agricultural soils. We carried out rainfall simulations on agricultural field sites to identify the effect of soil properties, field characteristics and hydrological conditions on DOC export by surface runoff from loamy agricultural soils. Furthermore, the temporal evolution of DOC concentrations and specific UV absorbance (SUVA) values in runoff water during a rainfall event was monitored. Additional rainfall simulations in the lab allowed to investigate the effects of drop impact, crop residue incorporation and drying–rewetting of the soil on DOC concentrations and SUVA values in both runoff and percolation water. DOC concentrations were the highest and SUVA values the lowest at the start of a rainfall event, both in runoff and percolation water. Afterwards, DOC concentrations diminished and SUVA values rose to steady values towards the end of the experiments. Overall, rainfall conditions prior to the experiment showed to be a major control on DOC concentrations and quality in runoff water from agricultural fields. Smaller rainfall depths before the experiment and lower initial soil moisture content led to high concentrations of low aromatic DOC in the runoff water. This drying–rewetting effect on DOC concentrations and quality was also observed in the lab for percolation water. For the range of considered soil types, only a limited effect of soil and field characteristics on DOC concentrations and quality in runoff was observed. The effect of reduced tillage on DOC concentrations in surface runoff was ambiguous, with effects differing between experimental field sites. [Copyright &y& Elsevier]

The transport and biochemical transformations of the iodinated X-ray contrast medium (ICM) iomeprol were studied at the stream/groundwater interface. During a one-month field experiment piezometric pressure heads, temperatures, and concentrations of redox-sensitive species, iomeprol and 15 of its transformation products (TPs) were collected in stream- and groundwater. The data set was analyzed and transformation processes and rates identified by comparing conservative and reactive transport simulations. ICM and TP transformations were simulated as a cometabolic process during organic carbon degradation. Using iomeprol/TPs ratios as calibration constrain mitigated the uncertainties associated with the high variability of the ICM wastewater discharge into the investigated stream. The study provides evidence that biodegradation of ICM occurs at the field-scale also for predominantly denitrifying conditions. Under these anaerobically dominated field conditions shortest simulated half-life (21 days) was in the same range as previously reported laboratory-determined half-lives for aerobic conditions. [ABSTRACT FROM AUTHOR]

Standardised exposure scenarios play an important role in European pesticide authorisation procedures (a scenario is a combination of climate, weather and crop data to be used in exposure models). The European Food Safety Authority developed such scenarios for the assessment of exposure of soil organisms to pesticides. Scenarios were needed for both the concentration in total soil and for the concentration in the liquid phase. The goal of the exposure assessment is the 90th percentile of the exposure concentration in the area of agricultural use of a pesticide in each of three regulatory European zones (North, Centre and South). A statistical approach was adopted to find scenarios that are consistent with this exposure goal. Scenario development began with the simulation of the concentration distribution in the entire area of use by means of a simple analytical model. In the subsequent two steps, procedures were applied to account for parameter uncertainty and scenario uncertainty (i.e. the likelihood that a scenario that is derived for one pesticide is not conservative enough for another pesticide). In the final step, the six scenarios were selected by defining their average air temperature, soil organic-matter content and their soil textural class. Organic matter of the selected scenarios decreased in the order North-Centre-South. Because organic matter has a different effect on the concentration in total soil than it has on the concentration in the liquid phase, the concentration in total soil decreased in the order North-Centre-South whereas the concentration in the liquid phase decreased in the opposite order. The concentration differences between the three regulatory zones appeared to be no more than a factor of two. These differences were comparatively small in view of the considerable differences in climate and soil properties between the three zones. [ABSTRACT FROM AUTHOR]

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite was launched in November 2009 and delivers now brightness temperature and soil moisture products over terrestrial areas on a regular three-day basis. In 2010, several airborne campaigns were conducted to validate the SMOS products with microwave emission radiometers at L-band (1.4 GHz). In this paper, we present results from measurements performed in the Rur and Erft catchments in May and June 2010. The measurement sites were situated in the very west of Germany close to the borders to Belgium and The Netherlands. We developed an approach to validate spatial and temporal SMOS brightness temperature products. An area-wide brightness temperature reference was generated by using an area-wide modeling of top soil moisture and soil temperature with the WaSiM-ETH model and radiative transfer calculation based on the L-band Microwave Emission of the Biosphere model. Measurements of the airborne L-band sensors EMIRAD and HUT-2D on-board a Skyvan aircraft as well as ground-based mobile measurements performed with the truck mounted JÜLBARA L-band radiometer were analyzed for calibration of the simulated brightness temperature reference. Radiative transfer parameters were estimated by a data assimilation approach. By this versatile reference data set, it is possible to validate the spaceborne brightness temperature and soil moisture data obtained from SMOS. However, comparisons with SMOS observations for the campaign period indicate severe differences between simulated and observed SMOS data. [ABSTRACT FROM PUBLISHER]

Abstract: Small amounts of organic compounds are often found at much larger depths than expected from their organic carbon normalized distribution coefficient (K oc). In this study the food dye Brilliant Blue (BB) was used to visualize the (preferential) transport pathways in undisturbed soil monoliths taken from an Orthic Luvisol and from a Eutric Cambisol. After spiking the monoliths with 1.0MBq of either 14C-labeled benazolin (leacher) or 14C-labeled benzo[a]pyrene (BaP, nonleacher), they were intermittently irrigated under free-draining conditions twice weekly with 4mm of rain water for 17weeks. BB (4gL−1) was added to the rain water during the last 4weeks. After irrigation, the monoliths were sliced and photographs were taken from horizontal cross-sections. Soil was dried and incinerated to measure total 14C-activity. The mean travel depth for benazolin (6–7cm) was larger than for BaP (2cm), which is in line with their K oc values, although BaP was much more mobile than expected from the K oc value. BB patterns, arbitrarily classified into five intensity classes, showed that large parts of the monolith were bypassed below the completely stained upper two to five centimeter. Furthermore, BB patterns indicated the locations of strongly sorbing compounds in the deeper soil layers and are therefore a helpful tool to selectively sample the soil for these compounds. A continuously stained root channel below the 20-cm depth contained substantial amounts of BaP, indicating that soil structure cannot be neglected to assess the fate of nonleachers in undisturbed soils. [Copyright &y& Elsevier]

Abstract: In arable farming systems, the term ‘subsoil’ refers to the soil beneath the tilled or formerly tilled soil horizon whereas the latter one is denoted as ‘topsoil’. To date, most agronomic and plant nutrition studies have widely neglected subsoil processes involved in nutrient acquisition by crop roots. Based on our current knowledge it can be assumed that subsoil properties such as comparatively high bulk density, low air permeability, and poverty of organic matter, nutrients and microbial biomass are obviously adverse for nutrient acquisition, and sometimes subsoils provide as little as less than 10% of annual nutrient uptake in fertilised arable fields. Nevertheless, there is also strong evidence indicating that subsoil can contribute to more than two-thirds of the plant nutrition of N, P and K, especially when the topsoil is dry or nutrient-depleted. Based on the existing literature, nutrient acquisition from arable subsoils may be conceptualised into three major process components: (I) mobilisation from the subsoil, (II) translocation to the shoot and long-term accumulation in the Ap horizon and (III) re-allocation to the subsoil. The quantitative estimation of nutrient acquisition from the subsoil requires the linking of field experiments with mathematical modelling approaches on different spatial scales including Process Based Models for the field scale and Functional–Structural Plant Models for the plant scale. Possibilities to modify subsoil properties by means of agronomic management are limited, but ‘subsoiling’ – i.e. deep mechanical loosening – as well as the promotion of biopore formation are two potential strategies for increasing access to subsoil resources for crop roots in arable soils. The quantitative role of biopores in the nutrient acquisition from the subsoil is still unclear, and more research is needed to determine the bioaccessibility of nutrients in subsoil horizons. [Copyright &y& Elsevier]

• Successful prediction of weathering indices with MIR spectroscopy. • Land use explains minor part of variations in soil thickness and weathering degree. • Soil thickness and weathering degree mainly determined by slope gradient. • Locally high erosion does not necessarily result in changes at landscape-scale. Land use and land cover changes (LUCC) can drastically alter various components of the critical zone, including soil thickness and soil chemical weathering processes. Often these studies, however, tend to focus on extreme cases, not representing what actually happens on average at larger, regional scales. Here, we evaluate the impact of LUCC on soil thickness and soil weathering degree at the regional scale, where we use soil spectroscopy to derive weathering indices. In a subtropical region in Southern Brazil, we collected calibration/validation soil samples (n = 49) from 4 different locations for which we measured the mid-infrared (MIR) spectral reflectance and 3 soil chemical weathering indices: chemical index of alteration (CIA), the total reserve in bases (TRB), and the iron ratio (Fe d /Fe t). We used partial least square regressions on this calibration/validation dataset to relate the MIR spectra of the soil samples to these weathering indices, resulting in good calibration relationships with R2 values of 0.97, 0.91 and 0.84 for CIA, TRB and Fe d /Fe t , respectively. Applying these relations to MIR spectra of regionally collected soil samples allowed us to calculate soil weathering degrees for a large number of soil samples (n = 229), without requiring costly and time-consuming chemical analyses. We collected these soil samples at 100 mid-slope positions: 50 under forest and 50 under agricultural land use. Land use explained only a minor part of the variation in soil thickness and weathering degree. Thus, while local water and tillage erosion rates might be considerable after deforestation, this has not led to significant reductions in average soil thickness and has not affected soil weathering degree. Slope gradient is the main factor influencing the spatial variability in soil thickness and weathering degree on mid-slope sections in our study area. Human activities over the last century did not fundamentally alter these patterns. [ABSTRACT FROM AUTHOR]