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Water uptake by plant roots is an important component of the soil water balance. Predicting to what extent potential transpiration from the canopy, that is, transpiration demand, can be met by supply of water from the soil through the root system is crucial to simulate the actual transpiration and assess vegetation water stress. In models that simulate the dynamics of vertical soil water content profiles as a function of water fluxes and soil water potential gradients, the root water uptake (RWU) distribution is represented by macroscopic sink terms. We present RWU functions that calculate sink terms based on a mechanistic model of water flow in the soil–root system. Based on soil–root hydraulics, we define α‐supply functions representing the maximal uptake by the root system from a certain soil depth when the root collar water potential equals the wilting point, ω‐supply factors representing the maximal supply from the entire root system, and a critical ωc factor representing the potential transpiration demand. These functions and factors are subsequently used to calculate RWU distributions directly from potential transpiration or demand and the soil water potentials. Unlike currently used approaches, which define α‐stress functions and ω factors representing ratios of actual uptake to uptake demand, the supply‐based formulations can be derived directly from soil and root hydraulic properties and can represent processes like root hydraulic redistribution and hydraulic lift. Core Ideas: Functions to calculate root water uptake (RWU) from different soil depths were derived.RWU is calculated directly using soil water potentials and the potential transpiration rate.The functions are derived using soil and root hydraulic properties.Phenomena like RWU compensation, hydraulic redistribution, and hydraulic lift are reproduced.Similarities and differences with currently used uptake functions are discussed. [ABSTRACT FROM AUTHOR]

When estimating field‐scale average soil moisture from sensors measuring at fixed positions, spatial variability in soil moisture leads to "measurement errors" of the spatial mean, which may persist over time due to persistent soil moisture patterns resulting in autocorrelated measurement errors. The uncertainty of parameters that are derived from such measurements may be underestimated when they are assumed to be independent. Temporal autocorrelation models assume stationary random errors, but such error models are not necessarily applicable to soil moisture measurements. As an alternative, we propose a mechanistic error model that is based on the spatial variability of the water retention curve and assumes a uniform water potential. We tested whether spatial soil moisture variability and its temporal covariance could be predicted based on (1) mean soil moisture, (2) water retention variability, and (3) (co)variances of the van Genuchten parameters using a first‐order expansion of the retention curve. The proposed models were tested in a numerical and a field experiment. For the field experiment, in situ sensor measurements and water retention curves were obtained in a field plot. Both experiments showed that water retention variability under a uniform water potential is a good predictor for spatial soil moisture variability, and that soil moisture errors are strongly correlated in time and neglecting them would be an incorrect assumption. The temporal error covariance could be predicted as a function of the mean moisture contents at two observation times. Further research is required to assess the impact of these temporal correlations on soil moisture predictions. Core Ideas: Soil moisture is spatially variable, and spatial variations are correlated in time.Due to spatial variability, the estimated average soil moisture from a limited number of measurements is uncertain.The error of the spatial mean estimated from a limited number of sensors at fixed positions is correlated in time.A mechanistic error modeling approach is presented based on the spatial variability of the water retention curve.Such a model can predict measurement variability and error covariance in time as a function of mean soil moisture. [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: 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]

Many different equations have been proposed to describe quantitatively one‐dimensional soil water infiltration. The unknown coefficients of these equations characterize soil hydraulic properties and may be estimated from a n record, {t∼i,I∼i}i=1n$\{ {\tilde t_i},{\tilde I_i}\} _{i = 1}^n$, of cumulative infiltration measurements using curve fitting techniques. The two‐term infiltration equation, I(t)=St+cKst$I(t) = S\sqrt t + c{K_{\rm{s}}}t$, of Philip has been widely used to describe measured infiltration data. This function enjoys a solid mathematical–physical underpinning and admits a closed‐form solution for the soil sorptivity, S [L T−1/2], and multiple, c [−], of the saturated hydraulic conductivity, Ks [L T−1]. However, Philip's two‐term equation has a limited time validity, tvalid [T], and thus cumulative infiltration data, I∼(t∼)$\tilde I(\tilde t)$, beyond t=tvalid$t = {t_{{\rm{valid}}}}$ will corrupt the estimates of S and Ks. This paper introduces a novel method for estimating S, c, Ks, and tvalid of Philip's two‐term infiltration equation. This method, coined parasite inversion, use as vehicle Parlange's three‐parameter infiltration equation. As prerequisite to our method, we present as secondary contribution an exact, robust and efficient numerical solution of Parlange's infiltration equation. This solution admits Bayesian parameter estimation with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm and yields as byproduct the marginal distribution of Parlange's β parameter. We evaluate our method for 12 USDA soil types using synthetic infiltration data simulated with HYDRUS‐1D. An excellent match is observed between the inferred values of S and Ks and their "true" values known beforehand. Furthermore, our estimates of c and tvalid correlate well with soil texture, corroborate linearity of the c(β)$c({{\beta}})$ relationship for 0≤t≤tvalid$0 \le t \le {t_{{\rm{valid}}}}$, and fall within reported ranges. A cumulative vertical infiltration of about 2.5 cm may serve as guideline for the time‐validity of Philip's two‐term infiltration equation. Core Ideas: We describe a method that can determine the time validity of infiltration equations.This method infers as well the hydraulic properties of unsaturated soils.We present a robust and efficient numerical solution of Parlange's three‐parameter infiltration equation.Posterior distribution determines how well parameters are defined by calibration to data.Two and a half centimeters of cumulative infiltration is a good proxy for time validity Philip's two‐term equation. [ABSTRACT FROM AUTHOR]

Meaningful assessment of pesticide fate in soils and plants is based on fate models that represent all relevant processes. With mechanistic models, these processes can be simulated based on soil, substance, and plant properties. We present a mechanistic model that simulates pesticide uptake from soil and investigate how it is influenced, depending on the governing uptake process, by root and substance properties and by distributions of the substance and water in the soil profile. A new root solute uptake model based on a lumped version of the Trapp model (Trapp, 2000) was implemented in a coupled version of R-SWMS-ParTrace models for 3-D water flow and solute transport in soil and root systems. Solute uptake was modeled as two individual processes: advection with the transpiration stream and diffusion through the root membrane. We set up the model for a FOCUS scenario used in the European Union (EU) for pesticide registration. Considering a single vertical root and advective uptake only, the root hydraulic properties could be defined so that water and substance uptake and substance fate in soil showed a good agreement with the results of the 1D PEARL model, one of the reference models used in the EU for pesticide registration. Simulations with a complex root system and using root hydraulic parameters reported in the literature predicted larger water uptake from the upper root zone, leading to larger pesticide uptake when pesticides are concentrated in the upper root zone. Dilution of root water concentrations at the top root zone with water with low pesticide concentration taken up from the bottom of the root zone leads to larger uptake of solute when uptake was simulated as a diffusive process. This illustrates the importance of modeling uptake mechanistically and considering root and solute physical and chemical properties, especially when root-zone pesticide concentrations are non-uniform. [ABSTRACT FROM AUTHOR]

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

Soils with high stone content represent a challenge to root development, as each stone is an obstacle to root growth. A high stone content also affects soil properties such as temperature or water content, which in turn affects root growth. We investigated the effects of all soil properties combined on root development in the field using both experiments and modeling. Field experiments were carried out in rhizotron facilities during two consecutive growing seasons (wheat [Triticum aestivum L.] and maize [Zea mays L.]) in silty loam soils with high (>50%) and low (<4%) stone contents. We extended the CPlantBox root architecture model to explicitly consider the presence of stones and simulated root growth on the plot scale over the whole vegetation period. We found that a linear increase of stone content resulted in a linear decrease of rooting depth across all stone contents and developmental stages considered, whereas rooting depth was only sensitive to cracks below a certain crack density and at earlier growth stages. Moreover, the impact of precipitation‐influenced soil strength had a relatively stronger impact on simulated root arrival curves during the vegetation periods than soil temperature. Resulting differences between stony and non‐stony soil of otherwise the same crop and weather conditions show similar trends as the differences observed in the rhizotron facilities. The combined belowground effects resulted in differences in characteristic root system measures of up to 48%. In future work, comparison of absolute values will require including shoot effects—in particular, different carbon availabilities. Core Ideas: We present a dynamic root architecture model that considers macroscopic soil properties.Root elongation rate and preferred growth direction are influenced by stones.We simulate the effects of soil properties on root architecture development using field data.Only belowground effects are considered by the root architecture model.Similar trends in measured and simulated root growth are observed in two different soils. [ABSTRACT FROM AUTHOR]

Multiannual data (2016–2018) from 12 weighed lysimeters (four soil types with textures ranging from sandy loam to silt loam, three replicates) of the TERENO SOILCan network were used to evaluate if evaporation (E) rates could be predicted from weather data using the FAO Penman–Monteith (PM) method combined with soil water flow simulations using the Richards equation. Soil hydraulic properties (SHPs) were estimated either from soil texture using the ROSETTA pedotransfer functions, from in situ measured water retention curves, or from soil surface water contents using inverse modeling. In all years, E was water limited and the measured evaporation rates (Em) surprisingly did not vary significantly among the four different soil types. When SHPs derived from pedotransfer functions were used, simulated evaporation rates of the finer textured soils overestimated the measured ones considerably. Better agreement was obtained when simulations were based on in situ measured or inversely estimated SHPs. The SHPs estimated from pedotransfer functions represented unrealistically large characteristic lengths of evaporation (Lc), and Lc was found to be a useful characteristic to constrain estimates of SHPs. Also, when soil evaporation was water limited and Em rates were below Epot (PM evaporation scaled by an empirical coefficient), the diurnal dynamics of Em followed those of Epot. The Richards equation that considers only isothermal liquid water flow did not reproduce these dynamics caused by temperature dependent vapor transport in the soil. [ABSTRACT FROM AUTHOR]

Stomatal regulation and whole plant hydraulic signaling affect water fluxes and stress in plants. Land surface models and crop models use a coupled photosynthesis–stomatal conductance modeling approach. Those models estimate the effect of soil water stress on stomatal conductance directly from soil water content or soil hydraulic potential without explicit representation of hydraulic signals between the soil and stomata. In order to explicitly represent stomatal regulation by soil water status as a function of the hydraulic signal and its relation to the whole plant hydraulic conductance, we coupled the crop model LINTULCC2 and the root growth model SLIMROOT with Couvreur's root water uptake model (RWU) and the HILLFLOW soil water balance model. Since plant hydraulic conductance depends on the plant development, this model coupling represents a two-way coupling between growth and plant hydraulics. To evaluate the advantage of considering plant hydraulic conductance and hydraulic signaling, we compared the performance of this newly coupled model with another commonly used approach that relates root water uptake and plant stress directly to the root zone water hydraulic potential (HILLFLOW with Feddes' RWU model). Simulations were compared with gas flux measurements and crop growth data from a wheat crop grown under three water supply regimes (sheltered, rainfed, and irrigated) and two soil types (stony and silty) in western Germany in 2016. The two models showed a relatively similar performance in the simulation of dry matter, leaf area index (LAI), root growth, RWU, gross assimilation rate, and soil water content. The Feddes model predicts more stress and less growth in the silty soil than in the stony soil, which is opposite to the observed growth. The Couvreur model better represents the difference in growth between the two soils and the different treatments. The newly coupled model (HILLFLOW–Couvreur's RWU–SLIMROOT–LINTULCC2) was also able to simulate the dynamics and magnitude of whole plant hydraulic conductance over the growing season. This demonstrates the importance of two-way feedbacks between growth and root water uptake for predicting the crop response to different soil water conditions in different soils. Our results suggest that a better representation of the effects of soil characteristics on root growth is needed for reliable estimations of root hydraulic conductance and gas fluxes, particularly in heterogeneous fields. The newly coupled soil–plant model marks a promising approach but requires further testing for other scenarios regarding crops, soil, and climate. [ABSTRACT FROM AUTHOR]

To investigate transient dynamics of soil water redistribution during infiltration, we conducted horizontal borehole and surface ground penetrating radar measurements during a 4‐day infiltration experiment at the rhizontron facility in Selhausen, Germany. Zero‐offset ground penetrating radar profiling in horizontal boreholes was used to obtain soil water content information at specific depths (0.2, 0.4, 0.6, 0.8 and 1.2 m). However, horizontal borehole ground penetrating radar measurements do not provide accurate soil water content estimates of the top soil (0–0.1 m depth) because of interference between direct and critically refracted waves. Therefore, surface ground penetrating radar data were additionally acquired to estimate soil water content of the top soil. Due to the generation of electromagnetic waveguides in the top soil caused by infiltration, a strong dispersion in the ground penetrating radar data was observed in 500 MHz surface ground penetrating radar data. A dispersion inversion was thus performed with these surface ground penetrating radar data to obtain soil water content information for the top 0.1 m of the soil. By combining the complementary borehole and surface ground penetrating radar data, vertical soil water content profiles were obtained, which were used to investigate vertical soil water redistribution. Reasonable consistency was found between the ground penetrating radar results and independent soil water content data derived from time domain reflectometry measurements. Because of the improved spatial representativeness of the ground penetrating radar measurements, the soil water content profiles obtained by ground penetrating radar better matched the known water storage changes during the infiltration experiment. It was concluded that the combined use of borehole and surface ground penetrating radar data convincingly revealed spatiotemporal soil water content variation during infiltration. In addition, this setup allowed a better quantification of water storage, which is a prerequisite for future applications, where, for example, the soil hydraulic properties will be estimated from ground penetrating radar data. [ABSTRACT FROM AUTHOR]

Three-dimensional models of root growth, architecture and function are becoming important tools that aid the design of agricultural management schemes and the selection of beneficial root traits. However, while benchmarking is common in many disciplines that use numerical models, such as natural and engineering sciences, functional-structural root architecture models have never been systematically compared. The following reasons might induce disagreement between the simulation results of different models: different representation of root growth, sink term of root water and solute uptake and representation of the rhizosphere. Presently, the extent of discrepancies is unknown, and a framework for quantitatively comparing functional-structural root architecture models is required. We propose, in a first step, to define benchmarking scenarios that test individual components of complex models: root architecture, water flow in soil and water flow in roots. While the latter two will focus mainly on comparing numerical aspects, the root architectural models have to be compared at a conceptual level as they generally differ in process representation. Therefore, defining common inputs that allow recreating reference root systems in all models will be a key challenge. In a second step, benchmarking scenarios for the coupled problems are defined. We expect that the results of step 1 will enable us to better interpret differences found in step 2. This benchmarking will result in a better understanding of the different models and contribute toward improving them. Improved models will allow us to simulate various scenarios with greater confidence and avoid bugs, numerical errors or conceptual misunderstandings. This work will set a standard for future model development. [ABSTRACT FROM AUTHOR]

Future crop production will be affected by climatic changes. In several regions, the projected changes in total rainfall and seasonal rainfall patterns will lead to lower soil water storage (SWS), which in turn affects crop water uptake, crop yield, water use efficiency (WUE), grain quality and groundwater recharge. Effects of climate change on those variables depend on the soil properties and were often estimated based on model simulations. The objective of this study was to investigate the response of key variables in four different soils and for two different climates in Germany with a different aridity index (AI): 1.09 for the wetter (range: 0.82 to 1.29) and 1.57 for the drier (range: 1.19 to 1.77) climate. This is done by using high-precision weighable lysimeters. According to a "space-for-time" (SFT) concept, intact soil monoliths that were moved to sites with contrasting climatic conditions have been monitored from April 2011 until December 2017. Evapotranspiration (ET) was lower for the same soil under the relatively drier climate, whereas crop yield was significantly higher, without affecting grain quality. Especially "non-productive" water losses (evapotranspiration out of the main growing period) were lower, which led to a more efficient crop water use in the drier climate. A characteristic decrease of the SWS for soils with a finer texture was observed after a longer drought period under a drier climate. The reduced SWS after the drought remained until the end of the observation period which demonstrates carry-over of drought from one growing season to another and the overall long-term effects of single drought events. In the relatively drier climate, water flow at the soil profile bottom showed a small net upward flux over the entire monitoring period as compared to downward fluxes (groundwater recharge) or drainage in the relatively wetter climate and larger recharge rates in the coarser- as compared to finer-textured soils. The large variability of recharge from year to year and the long-lasting effects of drought periods on the SWS imply that long-term monitoring of soil water balance components is necessary to obtain representative estimates. Results confirmed a more efficient crop water use under less-plant-available soil moisture conditions. Long-term effects of changing climatic conditions on the SWS and ecosystem productivity should be considered when trying to develop adaptation strategies in the agricultural sector. [ABSTRACT FROM AUTHOR]

Understanding the effect of the top soil layer on surface evaporation and water distribution is critical to modeling hydrological systems. However, the dependency of near-surface soil moisture and fluxes on layering characteristics remains unclear. To address this uncertainty, we investigate how the arrangement of soil horizons affects the evaporation and soil moisture, specifically, the near-surface soil moisture, through the combination of numerical simulations and evaporation experiments. The characteristics of fluxes and moisture from different soil profiles are then used to understand the soil layering conditions. Results show that the top soil layer can significantly affect the evolution of soil moisture profiles and evaporation dynamics, the extent of which depends on the layering sequence, thickness, and properties of each layer. The soil systems consisting of a thick coarse (C) layer overlying a fine (F) layer, or a very thin F layer overlying a C layer exhibit near-surface moisture, temperature and fluxes nearly identical to that of a homogeneous C system; in these cases, a homogeneous C soil could be used to represent the above two layered systems. However, some soil profiles cannot be described by a single set of soil properties, nevertheless, they show distinct characteristics that can serve as indicators for soil layering conditions, e.g., "first slowly then rapidly" decreasing dynamics of near-surface soilmoisture. As some characteristics are not unique to layered soil, the combined information including the near-surface soil moisture defined at different depths and evaporation behavior of an entire drying cycle can be used to better characterize the layering conditions. [ABSTRACT FROM AUTHOR]

Weighable lysimeters were used to study the relation between soil water content (SWC) and the actual evapotranspiration (ETa) of grassland under two different climate regimes of Rollesbroich and Selhausen but for an identical soil from Rollesbroich. All components of the water balance were determined from 2012 until 2018. Budyko analysis was used to characterize the hydrological status of the studied sites. Wavelet analysis was also applied to study the power spectrum of ETa, vegetationheight- adjusted reference evapotranspiration (ETcrop), and water stress index (WSI) defined as ETa/ETcrop, as well as SWC at three different depths and the coherence between SWC and ETa and WSI. The Budyko analysis showed that 2018 resulted in a shift of both locations towards more water-limited conditions, although Rollesbroich remained an energy-limited system. Based on the power spectrum analysis, the annual timescale is the dominant scale for the temporal variability of ETa, ETcrop, and SWC. The results also showed that increasing dryness at the energy-limited site led to more temporal variability of SWC at all depths at the annual timescale. Wavelet coherence analysis showed a reduction of the phase shift between SWC and ETa at an annual scale caused by the increase in dryness during the measurement period. We found that phase shifts between SWC and ETa and SWC and WSI were stronger at the water-limited site than at the energy-limited site. The wavelet coherence analysis also showed that from 2014 to 2018, the control of ETa and WSI on SWC increased due to higher dryness of soil. [ABSTRACT FROM AUTHOR]

Soil water evaporation plays a critical role in mass and energy exchanges across the land–atmosphere interface. Although much is known about this process, there is no agreement on the best modeling approaches to determine soil water evaporation due to the complexity of the numerical modeling scenarios and lack of experimental data available to validate such models. Existing studies show numerical and experimental discrepancies in the evaporation behavior and soil water distribution in soils at various scales, driving us to revisit the key process representation in subsurface soil. Therefore, the goal of this work is to test different mathematical formulations used to estimate evaporation from bare soils to critically evaluate the model formulations, assumptions and surface boundary conditions. This comparison required the development of three numerical models at the REV scale that vary in their complexity in characterizing water flow and evaporation, using the same modeling platform. The performance of the models was evaluated by comparing with experimental data generated from a soil tank/boundary layer wind tunnel experimental apparatus equipped with a sensor network to continuously monitor water–temperature–humidity variables. A series of experiments were performed in which the soil tank was packed with different soil types. Results demonstrate that the approaches vary in their ability to capture different stages of evaporation and no one approach can be deemed most appropriate for every scenario. When a proper top boundary condition and space discretization are defined, the Richards equation-based models (Richards model and Richards vapor model) can generally capture the evaporation behaviors across the entire range of soil saturations, comparing well with the experimental data. The simulation results of the non-equilibrium two-component two-phase model which considers vapor transport as an independent process generally agree well with the observations in terms of evaporation behavior and soil water dynamics. Certain differences in simulation results can be observed between equilibrium and non-equilibrium approaches. Comparisons of the models and the boundary layer formulations highlight the need to revisit key assumptions that influence evaporation behavior, highlighting the need to further understand water and vapor transport processes in soil to improve model accuracy. [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: 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]

How much water can be taken up by roots and how this depends on the root and water distributions in the root zone are important questions that need to be answered to describe water fluxes in the soil-plant-atmosphere system. Physically based root water uptake (RWU) models that relate RWU to transpiration, root density, and water potential distributions have been developed but used or tested far less. This study aims at evaluating the simulated RWU of winter wheat using the empirical Feddes-Jarvis (FJ) model and the physically based Couvreur (C) model for different soil water conditions and soil textures compared to sap flow measurements. Soil water content (SWC), water potential, and root development were monitored noninvasively at six soil depths in two rhizotron facilities that were constructed in two soil textures: stony vs. silty, with each of three water treatments: sheltered, rainfed, and irrigated. Soil and root parameters of the two models were derived from inverse modeling and simulated RWU was compared with sap flow measurements for validation. The different soil types and water treatments resulted in different crop biomass, root densities, and root distributions with depth. The two models simulated the lowest RWU in the sheltered plot of the stony soil where RWU was also lower than the potential RWU. In the silty soil, simulated RWU was equal to the potential uptake for all treatments. The variation of simulated RWU among the different plots agreed well with measured sap flow but the C model predicted the ratios of the transpiration fluxes in the two soil types slightly better than the FJ model. The root hydraulic parameters of the C model could be constrained by the field data but not the water stress parameters of the FJ model. This was attributed to differences in root densities between the different soils and treatments which are accounted for by the C model, whereas the FJ model only considers normalized root densities. The impact of differences in root density on RWUcould be accounted for directly by the physically based RWUmodel but not by empirical models that use normalized root density functions. [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]

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]

Near-surface soil moisture profiles contain important information about the evaporation process from a bare soil. In this study, we demonstrated that such profiles could be monitored noninvasively and with high spatial resolution using Nuclear Magnetic Resonance (NMR). Soil moisture profiles were measured in a column exposed to evaporation for a period of 67 days using a stationary Magnetic Resonance Imaging (MRI) high field scanner and a unilateral NMR sensor. The column was packed with medium sand and initially saturated. Two distinct shapes of soil moisture profiles that are characteristic for stage I (evaporation rate is controlled by atmospheric demand) and stage II (evaporation rate is controlled by the porous medium) of the evaporation process were followed by both MRI and unilateral NMR. During stage I, an approximately uniform decrease of soil moisture over time was monitored, whereas during stage II, S-shaped moisture profiles developed which receded progressively into the soil column. These promising results and the specific design of the unilateral NMR system make it very well suited for determining soil moisture profiles in the field. [ABSTRACT FROM AUTHOR]

We investigated the effects of a drying front that emerges below an evaporating soil surface on the far-field ground-penetrating radar (GPR) data. First, we performed an analysis of the width of the drying front in soils with 12 different textures by using an analytical model. Then, we numerically simulated vertical soil moisture profiles that develop during evaporation for the soil textures. We performed the simulations using a Richards flow model that considers only liquid water flow and a model that considers coupled water, vapor, and heat flows. The GPR signals were then generated from the simulated soil water content profiles taking into account the frequency dependency of apparent electrical conductivity and dielectric permittivity. The analytical approach indicated that the width of the drying front at the end of Stage I of the evaporation was larger in silty soils than in other soil textures and smaller in sandy soils. We also demonstrated that the analytical estimate of the width of the drying front can be considered as a proxy for the impact that a drying front could have on far-field GPR data. The numerical simulations led to the conclusion that vapor transport in soil resulted in S-shaped soil moisture profiles, which clearly influenced the GPR data. As a result, vapor flow needs to be considered when GPR data are interpreted in a coupled inversion approach. Moreover, the impact of vapor flow on the GPR data was larger for silty than for sandy soils. These effects on the GPR data provide promising perspectives regarding the use of radars for evaporation monitoring. [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]

The spatiotemporal development of soil surface temperatures (SST) depends on water availability in the near-surface soil layer. Because the soil loses latent heat during evaporation and water available for evaporation depends on soil hydraulic properties (SHP), the temporal variability of SST should contain information about the near-surface SHP. The objective of this study was to investigate the uncertainties of SHP derived from SST. The HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate van Genuchten-Mualem parameters from infrared-measured SST and time domain reflectometry (TDR)-measured water contents. This approach was tested using synthetic and real data, collected during September 2008 from a harrowed silty loam field plot in Selhausen, Germany. The synthetic data illustrated that SHP can be derived from SST and that additional soil water content measurements reduce the uncertainty of the estimated SHP. Unlike for the synthetic experiment with a vertically homogeneous soil profile, a layered soil profile had to be assumed to derive SHP from the real data. Therefore, the uncertainty of SHP derived from real data was considerably larger. Water retention curves of undisturbed soil cores were similar to those estimated from SST and TDR data for the deeper undisturbed soil. The retention curves derived from SST and TDR data for the harrowed topsoil layer were typical for a coarse-textured soil and deviated considerably from the retention curves of soil cores, which were typical for a fine-textured soil and similar to those from the subsoil. [ABSTRACT FROM AUTHOR]

The microwave Forest Soil Moisture Experiment (FOSMEX) was performed at a deciduous forest site at the Research Centre Jülich (Germany). An L-and an X-band radiometer were mounted 100 m above ground and directed to the canopy. The measurements consist of dual- and single-polarized L- and X-band data and simultaneously recorded ground moisture, temperature, and meteorological data. The canopy L-band transmissivity was estimated from a subset of the FOSMEX data, where the ground was masked with a metalized foil. For the foliage-free canopy, the reflecting foil diminished the L-band brightness by ≈24 K, whereas brightness increased by ≈14 K when the foil was removed from below the foliated canopy. Depending on the assumption made on the scattering albedo of the canopy, the transmissivities were between 0.2 and 0.51. Furthermore, the contribution of the foliage was quantified. Although, the evaluation revealed the semitransparency of the canopy for L-band frequencies, the brightness sensitivity with respect to ground moisture was substantially reduced for all foliation states. The effect of ground surface moisture was explored in an irrigation experiment. The L-band measurements were only affected for a few hours until the water drained through the litter layer. This emphasizes the significance of the presence of litter for soil moisture retrieval from remotely sensed L-band brightness data. The FOSMEX database serves for further testing and improving radiative transfer models used for interpreting microwave data received from future spaceborne L-band radiometers flying over areas comprising a considerable fraction of deciduous forests. [ABSTRACT FROM AUTHOR]

This article discusses fluxes of dissolved organic carbon (DOC) and the relationship between dissolved organic carbon concentration and water flux in agricultural soils. The concentrations were unrelated to soil moisture content or average temperature. Fluxes among the automatic equilibrium tension plate lysimeters was positively related to leachate volume and not to average DOC concentrations. The authors suggest that water fluxes are the main determinants of spatial variability in DOC fluxes and that the maximal net DOC mobilization rate in the topsoil is limited. They emphasize that water flux and velocity are important parameters for DOC fluxes and concentrations.

Accurately measuring water fluxes and associated nutrient or contaminant concentrations through the vadose zone is difficult because an appropriate suction needs to be exerted on the soil to sample water under unsaturated conditions. Passive capillary wick sampling systems are cheap and reliable instruments resulting in acceptable measurements of water fluxes in the vadose zone; however, their success in measuring realistic fluxes depends on their compatibility with the soil and climatic conditions in which they are installed. This study was developed in the preplanning phase of a field experiment with its main objective the monitoring of dissolved organic matter and the associated transfer of Cu2+ and pesticides through the vadose zone. We studied a combination of two-dimensional and axisymmetrical three-dimensional numerical analyses using the HYDRUS-2D software to identify what sampler geometry, wick type, wick length, and number of wicks are most suitable for the soil conditions at the experimental site. An AM3/8HI wick with seasonally varying wick length (40 cm in winter and 100 cm in summer) was found to be most appropriate for the soil and climatic conditions of the experimental field. The numerical analysis indicated that well-designed wick samplers had a negligible effect on the soil moisture content close to the sampler. A double-ring wick sampler is proposed to minimize the effect of the area between the installation pit or trench and the sampler. This approach is easily applicable and transferable to other soil and wick types and climatic conditions. The study emphasizes the suitability of numerical modeling to optimize experimental design before installation. [ABSTRACT FROM AUTHOR]

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 spatiotemporal distribution of root water uptake (RWU) depends on the dynamics of the root distribution and compensatory uptake from wetter regions in the root zone. This work aimed to parameterize three RWU models with different representations of compensation: the Feddes-Jarvis model that uses an empirical function, the Feddes model without compensation, and the Couvreur model that is based on a physical description of water flow in the soil-root system. These models were implemented in HYDRUS-1D, and soil hydraulic parameters were optimized by inverse modeling using soil water content and potential measurements and observations of root distributions of winter wheat (Triticum aestivum L.) in horizontally installed rhizotubes. Soil moisture was equally well predicted by the three models, and the soil hydraulic parameters optimized by the models with compensation were comparable. The obtained RWU parameters of the Feddes-Jarvis model were consistent with data reported in the literature, although the pressure heads h$ and h^ for lower and higher transpirations rates, respectively, could not be uniquely identified. Response surfaces of the objective function showed that the root-related parameters of the Couvreur model could be identified using inverse modeling. Furthermore, these parameters were consistent with combined root architectural and hydraulic observations from the literature. The Feddes-Jarvis and Couvreur models simulated similar root-system-scale stress functions that link total RWU to the effective root zone water potential, suggesting that parameters may be transferable between the two models. Simulated RWU profiles differed due to different water redistribution by the root system, but the measurements were not sufficiently precise to observe this redistribution. [ABSTRACT FROM AUTHOR]

This special section of Vadose Zone Journal (VZJ) contains 15 contributions focusing on the physical, biological, and chemical aspects of water and solute transport into and through the soil root zone, including root water and solute uptake. The papers stem from presentations at the 2016 Kirkham Conference, "The Root Zone: Soil Physics and Beyond," which took place at the Sede Boqer campus of Ben-Gurion University of the Negev, Israel, during 10 to 14 April (https://www.soils.org/membership/divisions/soil-physics- and-hydrology/kirkham-conferences). Much consensus existed at the conference for a special VZJ section to reflect the importance of the soil root zone from many disciplinary perspectives (soil, environmental, agricultural, hydrologic, and atmospheric) and the complexity of the basic processes involved. The contributions deal with root zone processes at different scales and from different disciplinary viewpoints, while covering a broad range of topics from the very theoretical to important practical applications. Special emphasis is on novel measurement and modeling tools at various scales and the need for interdisciplinary research. [ABSTRACT FROM AUTHOR]

Minimally invasive monitoring of root development and soil states (soil moisture, temperature) in undisturbed soils during a crop growing cycle is a challenging task. Minirhizotron (MR) tubes offer the possibility to view root development in situ with time. Two MR facilities were constructed in two different soils, stony vs. silty, to monitor root growth, root zone processes, and their dependence on soil water availability. To obtain a representative image of the root distribution, 7-m-long tubes were installed horizontally at 10-, 20-, 40-, 60-, 80-, and 120-cm depths. A homemade system was developed to install MR tubes in the silty soil in horizontally drilled straight holes. For the stony soil, the soil rhizotubes were installed in an excavated and subsequently backfilled pit. In both facilities, three subplots were established with different water treatments: rain sheltered, rainfed, and irrigated. To monitor soil moisture, water potential, and soil temperature, time domain reflectometer probes, tensiometers, and matrix water potential sensors were installed. Soil water content profiles in space and time were obtained between two MR tubes using cross-hole ground-penetrating radar along the tubes at different depths. Results from the first growing season of winter wheat (Triticum aestivum L.) after installation demonstrate that differences in root development, soil water, and temperature dynamics can be observed among the different soil types and water treatments. When combined with additional measurements of crop development and transpiration, these data provide key information that is essential to validate and parameterize root development and water uptake models in soil–vegetation–atmosphere transfer models. [ABSTRACT FROM AUTHOR]

A dynamic tension-controlled bottom boundary of lysimeters allows observing water and matter fluxes in lysimeters that are close to natural field conditions, as pressure heads at the lysimeter bottom are adjusted to measured pressure heads at the same depth in the surrounding field. However lysimeters are often transferred from their sampling location for practical reasons or to study, for example, the effect of climate change on soil functions. This transfer can be accompanied by a change aboveground but also in subsurface conditions that are used to control the bottom boundary and that may affect the soil water balance of lysimeters. This issue is also relevant for lysimeter stations which use a tension-controlled bottom boundary and are not directly installed near the site of excavation. The potential impact of different bottom boundary conditions on the water balance of lysimeters that were transferred in a climate impact experiment (SOILCan) was investigated exemplarily by a numerical study. Results showed that by using nonappropriate pressure heads, which were measured in soil profiles with a different texture and water table depth than the profile where the lysimeter was taken from, had partially large impacts on soil water fluxes, especially when the water table was located within a specific critical range. Different climate conditions between sampling and installation site were buffered by the soil and did not show a strong influence on the bottom boundary control of lysimeters when the groundwater table depth was assumed to remain constant. Considering a change in groundwater table depths due to changing climate tempered the effects of climate change on the soil water balance terms. In general, results demonstrate the importance of a proper control of the lysimeters bottom boundary conditions in studies that investigate the influence of climate change on soil functions and ecosystem variables by transferring lysimeter along climate gradients. [ABSTRACT FROM AUTHOR]

A critical review of implicit assumptions behind typical one-dimensional root water uptake and stress models is performed. Plantscale mathematical expressions for stress and uptake functions obeying Darcy flow equations in three-dimensional systems are proposed. The process description of plant transpiration and soil water uptake in macroscopic root water uptake models is often based on simplifying assumptions that no longer reflect, or even contradict, the current status of knowledge in plant biology. The sink term in the Richards equation for root water uptake generally comprises four terms: (i) a root resistance function, (ii) a soil resistance function, (iii) a stress function, and (iv) a compensation function. Here we propose to use a detailed three-dimensional model, which integrates current knowledge of soil and root water flow equations, to deduct a one-dimensional effective behavior at the plant scale and to propose improvements for the four functions used in the macroscopic sink term. We show that (i) root hydraulic resistance may be well defined by the root length density but only for homogeneous lateral conductances and no limiting xylem conductance--in other cases a new function depending on the root hydraulic architecture should be used; (ii) soil resistance cannot be neglected, in particular in the rhizosphere where specific processes may occur that alter the soil hydraulic properties and therefore affect uptake; (iii) stress and compensation are two different processes, which should not be linked explicitly; (iv) there is a need for a clear definition of compensatory root water uptake independent of water stress; (v) stress functions should be defined as a maximal actual transpiration in function of an integrated root--soil interface water head rather than in terms of local bulk water heads; and (vi) nonlinearity in the stress function is expected to arise if root hydraulic resistances depend on soil matric head or when it is defined as a function of the bulk soil water head. [ABSTRACT FROM AUTHOR]

The coupling of soil and root water fluxes at the plant scale is a particularly challenging task. Numerical three-dimensional plant-scale models exist that consider these soil--root interactions. The influence of the hydraulic conductivity drop at the microscopic scale and especially the effect on root water uptake is not yet assessed in such models. In this study, an analytical approach describing the hydraulic conductivity drop from the bulk soil to the soil--root interface for a three-dimensional plant-scale model was derived and validated by numerical means. With these tools, quantification of the local hydraulic conductivity drop with time was possible. Furthermore, the effect of the hydraulic conductivity drop on the time occurrence of plant stress was evaluated. Root water uptake was assessed, with and without considering the hydraulic conductivity drop around single roots in a three-dimensional plant-scale model in terms of total water uptake at the root collar under different soil and root properties. It was shown that the total root water uptake was strongly affected, especially under conditions where the radial root hydraulic conductivity, which regulates root water uptake, was larger than the soil hydraulic conductivity, which regulates water flow in the soil. These findings were backed up by numerical validation of the model using mesh refinement. Incorporation of the hydraulic conductivity drop around individual roots in a three-dimensional plant-scale model can solve problems with greater accuracy for larger grid resolutions, and with smaller computational times, than not considering the hydraulic conductivity drop. [ABSTRACT FROM AUTHOR]

We studied water uptake variability at the plant scale using a three-dimensional detailed model. Specifically, we investigated the sensitivity of the R-SWMS model under different plant collar conditions by comparing computed water fluxes, flow variability, and soil water distributions for different case scenarios and different parameterizations. The relative radial root conductivity and soil hydraulic conductivity were shown to control the plant water extraction distribution. Highly conductive soils promote water uptake but at the same time decrease the variability of the soil water content. A large radial root conductivity increases the amount of water extracted by the root and generates very heterogeneous water extraction profiles. Increasing the xylem conductivity has less impact because the xylem is generally the most conductive part of the system. It was also determined that, due to the different magnitudes of soil and root conductivities, similar one-dimensional sink-term profiles can result in very different water content and flux distributions at the plant scale. Furthermore, an analysis based on soil texture showed that the ability of a soil to sustain high plant transpiration demand cannot be predicted a priori from the soil hydraulic properties only, as it depends on the evaporative demand and on the three-dimensional distributions of the soil/root conductivity ratio and soil capacity, which continuously evolve with time. Combining soil and root hydraulic properties led to very complex one-dimensional sink functions that are quite different from the simple reduction functions usually found in the literature. The R-SWMS model could be used to develop more realistic one-dimensional reduction functions. [ABSTRACT FROM AUTHOR]

Measuring leachate mobility in the vadose zone is necessary to understand the processes controlling groundwater and river contamination, and requires recording leachate volumes with time. Many field studies manually measure the volume of leachate with a daily, weekly, or even biweekly resolution; however, measurement of leachate at higher temporal resolution is needed for the calibration of solute transport models and is useful in identifying the contribution of preferential flow to solute transport. We designed a simple, robust, and low-cost drop counter for measuring leachate volumes at a high temporal resolution. Laboratory experiments showed a nearly perfect linear relationship between the applied flux and the number of drops per unit time, and indicate an average drop size of 35 µL. Due to manual manufacturing, variability between drop counters is not negligible and a one-point calibration is necessary. The drop counter consists of an upper (guiding) tube from which a drop forms and a lower (capillary) tube that "sucks" the drop down before it falls. The presence of the lower tube makes the counter less vulnerable to temperature and ionic strength effects of the leachate. Counting of the drops can be easily achieved using any type of datalogger capable of logging electrical pulses. [ABSTRACT FROM AUTHOR]

The one-dimensional convection-dispersion equation is often used to estimate the risk of nonpoint source groundwater contamination and the dispersivity in this equation is known to be a sensitive parameter for predicting the mass that leaches through the vadose zone to the groundwater. We derived a database of dispersivities from leaching studies in soils. Besides dispersivities, the database contains information about experimental parameters: transport distance, scale of the experiment, flow rate, boundary conditions, soil texture, pore water velocity, transport velocity, and measurement method. Dispersivities were found to increase with increasing transport distance and scale of the experiment. Considerably larger dispersivities were observed for saturated than for unsaturated flow conditions. No significant effect of soil texture on dispersivity was observed, but the interactive effects of soil texture, lateral scale of the experiment, and flow rate on dispersivity were significant. In coarse-textured soils, lateral water redistribution may take place across relatively larger distances, which explains the larger dependency of dispersivity on lateral scale of the experiment in coarse- than in fine-textured soils. The activation of large interaggregate pores may explain the increase in dispersivity with increasing flow rate in fine-textured soils, which was not observed in soils with a coarser texture. The distribution of dispersivities was positively skewed and better described with a lognormal than a normal distribution. Different experimental factors explained 25% of the total variability of loge-transformed dispersivities. The unexplained variance of the dispersivity was large and its coefficient of variation was 100%. [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]